sl a s h - a n d - bu r n ag r i c u lt u re
Slash-and-Burn Agriculture
th e s e a rc h f o r a lt e r n at i ve s
Edited by Cheryl A. Palm, Stephen A. Vosti,
Pedro A. Sanchez, and Polly J. Ericksen
A Collaborative Publication by the Alternatives to Slash and Burn Consortium,
the World Agroforestry Centre, The Earth Institute at Columbia University,
and the University of California, Davis
columbia university press
new york
Columbia University Press
Publishers Since 1893
New York
Chichester, West Sussex
Copyright © 2005 Columbia University Press
All rights reserved
Part opening art: Part 1, Yurimaguas, Peru. (Photo by Pedro Sanchez.) Part 2, Nkolbisson, Cameroon.
(Photo by Pedro Sanchez.) Part 3, Krui Sumatra, Indonesia. (Photo by Pedro Sanchez.) Part 4, Manaus,
Brazil. (Photo by Erick Fernandes.) Part 5, New slash-and-burn field in Pedro Peixoto, Acre, Brazil.
(Photo by Pedro Sanchez.)
Library of Congress Cataloging-in-Publication Data
Slash-and-burn agriculture : the search for alternatives / edited by Cheryl A. Palm … [et al.].
p. cm.
A collaborative publication by the Alternatives to Slash and Burn consortium, and others.
Includes bibliographical references (p.
) and index.
ISBN 0–231–13450–9 (cloth : alk. paper) — ISBN 0–231–13451–7 (pbk. : alk. paper)
1. Alternatives to Slash-and-Burn (Programme)—Congresses. 2. Shifting cultivation—Tropics—
Congresses. 3. Shifting cultivation—Environmental aspects—Tropics—Congresses. 4. Deforestation—Control—Tropics—Congresses. I. Palm, C. A. (Cheryl Ann) II. Alternatives to Slash-and-Burn
(Programme)
S602.87.S63 2005
631.5'818—dc22
A
Columbia University Press books are printed on permanent and durable acid-free paper.
Printed in the United States of America
c 10 9 8 7 6 5 4 3 2 1
p 10 9 8 7 6 5 4 3 2 1
Contents
Foreword ix
Preface xi
Contributors xv
Acronyms and Abbreviations
xxi
I
The Problem and Approach
1
Alternatives to Slash and Burn: Challenge and Approaches of an
International Consortium
Pedro A. Sanchez, Cheryl A. Palm, Stephen A. Vosti, Thomas P. Tomich,
and Joyce Kasyoki 3
II
Thematic Research
2
Carbon Losses and Sequestration After Land Use Change in the
Humid Tropics
Cheryl A. Palm, Meine van Noordwijk, Paul L. Woomer, Julio C. Alegre,
Luis Arévalo, Carlos E. Castilla, Divonzil G. Cordeiro, Kurniatun Hairiah,
Jean Kotto-Same, Appolinaire Moukam, William J. Parton, Auberto Ricse,
Vanda Rodrigues, and Syukur M. Sitompul 41
3
Greenhouse Gas Fluxes in Slash and Burn and Alternative Land Use
Practices in Sumatra, Indonesia
Daniel Murdiyarso, Haruo Tsuruta, Shigehiro Ishizuka, Kurniatun Hairiah,
and Cheryl A. Palm 64
4
The Potential Role of Above-Ground Biodiversity Indicators in
Assessing Best-Bet Alternatives to Slash and Burn
Andrew N. Gillison
83
vi Contents
5
Below-Ground Biodiversity Assessment: Developing a Key Functional
Group Approach in Best-Bet Alternatives to Slash and Burn
David E. Bignell, Jerome Tondoh, Luc Dibog, Shiou Pin Huang,
Fátima Moreira, Dieudonné Nwaga, Beto Pashanasi,
Eliane Guimarães Pereira, Francis-Xavier Susilo, and Michael J. Swift
6
Sustainability of Tropical Land Use Systems After Forest Conversion
Kurniatun Hairiah, Meine van Noordwijk, and Stephan Weise
7
119
143
The Forest for the Trees: The Effects of Macroeconomic Factors on
Deforestation in Brazil and Indonesia
Andrea Cattaneo and Nu Nu San
170
III
Site-Specific Alternatives to Slash-and-Burn Agriculture
8
Sustainable Forest Management for Smallholder Farmers in the
Brazilian Amazon
Marcus V. N. d’Oliveira, Michael D. Swaine, David F. R. P. Burslem,
Evaldo M. Bráz, and Henrique J. B. de Araújo 199
9
Permanent Smallholder Rubber Agroforestry Systems in Sumatra,
Indonesia
Gede Wibawa, Sinung Hendratno, and Meine van Noordwijk
10
Coffee, Pastures, and Deforestation in the Western Brazilian Amazon:
A Farm-Level Bioeconomic Model
Chantal L. Carpentier, Stephen A. Vosti, and Julie Witcover
11
222
233
Smallholder Options for Reclaiming and Using Imperata cylindrica
L. (Alang-Alang) Grasslands in Indonesia
Pratiknyo Purnomosidhi, Kurniatun Hairiah, Subekti Rahayu,
and Meine van Noordwijk 248
IV
National Perspectives
12
The Western Brazilian Amazon
Judson F. Valentim and Stephen A. Vosti
13
265
The Forest Margins of Sumatra, Indonesia
Soetjipto Partohardjono, Djuber Pasaribu, and Achmad M. Fagi
291
Contents vii
14
The Forest Margins of Cameroon
James Gockowski, Jean Tonyé, Chimere Diaw, Stefan Hauser, Jean Kotto-Same,
Rosaline Njomgang, Appolinaire Moukam, Dieudonné Nwaga,
Téophile Tiki-Manga, Jerome Tondoh, Zac Tschondeau, Stephan Weise,
and Louis Zapfack 305
15
The Peruvian Amazon: Development Imperatives and Challenges
Douglas White, Manuel Arca, Julio Alegre, David Yanggen, Ricardo Labarta,
John C. Weber, Carmen Sotelo-Montes, and Héctor Vidaurre 332
16
Northern Thailand: Changing Smallholder Land Use Patterns
Plodprasop Suraswadi, David E. Thomas, Komon Pragtong,
Pornchai Preechapanya, and Horst Weyerhaeuser 355
V
Cross-Site Comparisons and Conclusions
17
Land Use Systems at the Margins of Tropical Moist Forest: Addressing
Smallholder Concerns in Cameroon, Indonesia, and Brazil
Stephen A. Vosti, James Gockowski, and Thomas P. Tomich
18
387
Balancing Agricultural Development and Environmental Objectives:
Assessing Tradeoffs in the Humid Tropics
Thomas P. Tomich, Andrea Cattaneo, Simon Chater, Helmut J. Geist,
James Gockowski, David Kaimowitz, Eric F. Lambin, Jessa Lewis, Ousseynou
Ndoye, Cheryl A. Palm, Fred Stolle, William D. Sunderlin, Judson F. Valentim,
Meine van Noordwijk, and Stephen A. Vosti 415
Index
441
Foreword
T
his remarkable volume addresses the sustainable management of tropical
forests with unstinting sophistication, moving the analysis beyond clichés to the true complexities of the challenge. The world’s tropical forests, in
Latin America, Africa, and Asia, are being cut down, at enormous costs to local
and global biodiversity and ecosystem services. The carbon released by tropical
deforestation is a significant factor in the overall increase in atmospheric greenhouse gases. Yet the “best bets” to deal with the challenge of tropical deforestation remain far from obvious. The studies collected here offer new conceptual
tools and a rich compendium of empirical analyses that will be needed to formulate a set of viable responses to this major global challenge.
The traditional interpretation of tropical deforestation has usually proceeded in something like the following way. A rising population of smallholder
farmers at the forest margin—the boundary between farm and forest—leads
to deforestation as forests are cut to make room for new farms. At the same
time, existing farmland is abandoned because of land degradation, soil erosion,
and soil nutrient depletion. The loss of existing farmland is exacerbated by the
pressure of shortened fallows, caused by the rise of population densities. In this
traditional view, the best way to slow or stop deforestation would be to raise
productivity on existing farms in a sustainable manner—for example, through
the systematic replenishment of soil nutrients, so that pressures to expand into
new lands can be eased.
There are of course important aspects of truth in this conventional view,
but as the studies in this volume make clear, the situation is far more complex.
Natural population growth on the forest margin is not the only, or even the
key, driver of deforestation. Population growth often results from in-migration
of settlers, rather than from the natural population increase among existing
residents. Ironically, in such circumstances, intensification of agricultural techniques, even in a sustainable manner, can increase rather than decrease the rate
of deforestation, by raising the profitability of farming and thereby inducing
the in-migration of settlers to the forest margin. There may be a strong case for
improving the productivity of agricultural practices, but that step alone may
not solve the problem of deforestation.
x Foreword
Moreover, population increases of smallholders, whether by natural population
increase or by in-migration, are just part of the overall story. Land clearing results not
only from the expansion of land for crop production, but also from cattle ranching,
commercial logging, and other extractive activities. Since deforestation for such purposes is often highly profitable for private actors, even if it is socially costly (e.g., due
to the loss of biodiversity, or the increase of carbon emissions), deforestation will not
be stopped merely through the introduction of sustainable agronomic practices. Policies will be needed that explicitly aim to tilt the incentives toward forest conservation.
It may be advisable, for example, to compensate landowners for the conservation of
nonmarketed ecosystem services such as conserved habitats and sequestered carbon.
Some economists stop at that point, saying that all that is needed is to “get the
prices right,” by putting market prices on ecosystem services. This book explains why
that insight, valuable as it might be, only touches the surface of the practical issues.
Lurking beneath the idea of setting prices for ecosystem services are measurement
and conceptual problems of enormous scientific complexity. Identifying and valuing
nonmarket ecosystem services require the very best of ecological, soil, and farming
sciences, indeed just what the essays in this volume provide.
How much carbon, for example, is actually sequestered by various land use systems? How does the soil carbon change over time under particular agronomic practices, and how can the soil carbon best be measured and monitored? How can we
measure “biodiversity” and “habitat” in a practical manner, in order to promote the
conservation of biodiversity in a managed ecosystem? What indicators should be used
reliably to link observed land use patterns to economic incentives such as payments
for carbon or habitat preservation?
The ASB studies in this volume offer a uniquely informed and up-to-date treatment of these challenging issues, and many more issues as well. The essays combine
rigorous science, new conceptual and empirical tools, and thoughtful policy analysis.
Moreover, the studies describe these issues in a remarkable range of settings, in all
three affected continents and for a wide variety of land use systems. The introduction
and concluding essays are masterful in setting out the issues, as well as identifying the
practical and policy uncertainties not yet solved by the ASB project. In short, this
book is a landmark on the path to sustainable development.
Jeffrey D. Sachs
Jeffrey D. Sachs is Director of the Earth Institute at Columbia University and Special Advisor to
U.N. Secretary General Kofi Annan.
Preface
A
t the start of the twenty-first century an area of humid tropical forest
about the size of Nicaragua, New York State, or Greece (130,000 km2) is
destroyed every year. Tropical deforestation remains a major worldwide concern because it threatens the high plant and animal biodiversity these forests
contain, the large carbon stocks stored in them, and the many ecosystem services they provide. Small-scale farmers practicing slash-and-burn agriculture
clear forests to produce food and make a living for their families. To escape
poverty, these families often have few options other than to continue clearing
tropical forests. Striking an equitable balance between the legitimate interests of these rural households and the equally legitimate global concerns over
the environmental consequences of tropical deforestation is one of the major
challenges of the coming decades.
The Alternatives to Slash and Burn (asb) consortium was established
in 1992 by a group of concerned national and international research institutions and nongovernment organizations in response to recommendations
in the Rio Earth Summit’s Agenda 21 to halt destructive forms of shifting
cultivation by addressing the underlying social and ecological causes and to
reduce damage to forests by promoting sustainable management at the forest
margins. At that time, there was much understanding of how slash-and-burn
agriculture was performed, but knowledge of its global environmental consequences was sketchy, and what was known about the socioeconomic factors
driving slash-and-burn agriculture was not particularly useful to policymakers seeking to reduce deforestation and improve human welfare. Moreover,
there were few cross-country studies and almost no cross-disciplinary research
efforts involving agricultural scientists, environmental scientists, and social
scientists to draw on for scientific or policy guidance.
The asb consortium—eventually comprising more than forty organizations spread across the humid tropical belt—met this challenge by identifying more sustainable land use practices and enabling policies that help conserve environmental functions of the tropical forest margins while increasing
household income and food security for millions of poor people. After initial
xii Preface
support from the Global Environment Facility, asb became a systemwide program of
the Consultative Group on International Agricultural Research in 1994 and has since
been supported by its members and by the participating national research institutions in Brazil, Cameroon, Indonesia, Peru, Philippines, and Thailand. The asb consortium changed the way scientists and policymakers work together to tackle major
global challenges.
This book is a synthesis of the first decade of asb’s work, written by a team
of seventy-nine soil scientists, economists, ecologists, anthropologists, and foresters encompassing twenty-six nationalities. Forty-one of them are national scientists
affiliated with government research institutes, universities, and nongovernment organizations of eight tropical countries, and twenty-six others are affiliated with international agricultural research centers. This synthesis is organized in five sections. The
first chapter introduces slash-and-burn activities and the overall research framework
used by asb, including its tradeoff matrix. The second section focuses on the different environmental, agronomic, and socioeconomic dimensions of deforestation
and tropical agriculture, including chapters on carbon dynamics, greenhouse gas
emissions, above-ground and below-ground biodiversity, agronomic sustainability,
and the effects of macroeconomic policy on land and forest use. The third section
focuses on specific best-bet alternatives to slash-and-burn, including community forest management, jungle rubber, shade coffee, and reclamation of degraded grasslands
and pastures. The fourth section describes the perspectives of the main countries
involved—Brazil, Indonesia, Cameroon, Peru, and Thailand—regarding the environmental, economic, and social importance of slash-and-burn agriculture at the
local, regional, and national levels and the contribution of asb to addressing key
research and capacity-strengthening issues. The final section compares the different
sites and assesses the tradeoffs between the environmental, agronomic, and economic
costs and benefits of alternative uses of forests and cleared land and identifies the
roles of science and policy action in effecting known tradeoffs today and improving
the terms of these tradeoffs in the future.
The editors held asb leadership positions while working at the Tropical Soil
Biology and Fertility Programme (Palm), the World Agroforestry Centre (Sanchez and Ericksen), and the International Food Policy Research Institute and the
University of California, Davis (Vosti), in the past decade. All editors want to
acknowledge the vision of Nyle Brady, who brought the idea to reality; the assistance of the asb global coordination office at the World Agroforestry Centre in
Nairobi, particularly Joyce Kasyoki for her hard work and institutional memory;
the copyediting work of Sherri Mickelson; and the formatting by Rafael Flor. The
editors also thank Anthony Juo of Texas a&m University for his review of the early
versions of several chapters. We would also like to thank the Australian Centre
for International Agricultural Research for funding that supported the production
of this book and the symposium that launched the chapters for this book at the
American Society of Agronomy meetings in Salt Lake City and the United States
Preface
xiii
Agency for International Development for funds that assisted in the editing of this
book.
Cheryl A. Palm, Pedro A. Sanchez, Polly J. Ericksen
The Earth Institute at Columbia University
Stephen A. Vosti
University of California, Davis
January 2004
Contributors
Julio Alegre Senior Soil Scientist, World Agroforestry Centre–Peru; Centro
Internacional de la Papa, Apartado 5969, Lima, Peru; e-mail: j.alegre@cgiar.org
Henrique J. B. de Araújo Forest Engineer, Research Scientist at the Agroforestry
Research Center of Acre; Caixa Postal 392, Rio Branco–AC, Brazil, CEP
6990080; e-mail: henrique@cpafac.embrapa.br
Manuel Arca Research Director, inia; Av. La Universidad s/no; La Molina, Lima
12, Apartado 2791, Peru; e-mail: marcab@fenix.inia.gob.pe
Luis Arévalo Research Officer, World Agroforestry Centre–Peru; Km. 4.2 Carretera
Federico Basadre, Pucallpa–Ucayali, Peru; e-mail: l.arevalo@cgiar.org
David E. Bignell Professor of Zoology, School of Biological Science; Queen
Mary, University of London, Mile End Road, London, UK, E1 4NS; e-mail:
D.Bignell@qmul.ac.uk
Evaldo M. Bráz Forest Engineer, Research Scientist at the National Forest Research
Center-Embrapa Floresta, Curitiba–PR, Brazil; e-mail: evaldo@cnpf.embrapa.br
David F. R. P. Burslem Senior Lecturer, University of Aberdeen, School of
Biological Sciences; Cruickshank Building, St. Machar Drive, Aberdeen AB24
3UU, Scotland, UK; e-mail: d.burslem@abdn.ac.uk
Chantal L. Carpentier Program Manager, Environment, Economy, and
Trade, North American Commission for Environmental Cooperation; 393
St-Jacques O., Suite 200, Montreal, Quebec, Canada H2Y 2A7; e-mail:
clcarpentier@ccemtl.org
Carlos E. Castilla Soil and Water Management Program, cenipalma; Calle 21,
no. 42C-47, Bogota, Colombia; e-mail: cecastilla@unipacifico.edu.co
Andrea Cattaneo Economist, Resource Economics Division, Economic Research
Service, usda; 1800 M Street, NW, Washington, DC 20036; e-mail:
cattaneo@ers.usda.gov
Simon Chater Director, Green Ink Publishing Services Ltd.; Hawson Farm,
Buckfastleigh, Devon, UK; e-mail: s.chater@cgnet.com
Divonzil G. Cordeiro Soil Scientist, Embrapa–Acre; BR-364, KM 14, Caixa Postal
381, CEP: 69 908–970, Rio Branco, Acre, Brazil; e-mail: matell@mdnet.com.br
Chimere Diaw Scientist, cifor, iita Humid Forest Ecoregional Centre; B.P. 2008
(Messa), Yaoundé, Cameroon; e-mail: c.diaw@cgiar.org
Luc Dibog Soil Macrobiologist (Termites), Institute of Agricultural Research
for Development, irad; P.O. Box 2067, Yaoundé, Cameroon; e-mail:
lucdibog@yahoo.com, luc.dibog@caramail.com
xvi
The Problem and Approach
Contributors xvi
Polly J. Ericksen Research Fellow, International Research Institute for Climate Prediction,
The Earth Institute at Columbia University; 61 Route 9W, P.O. Box 1000, Palisades,
NY 10960, USA; e-mail: ericksen@iri.columbia.edu, p.ericksen@cgiar.org
Achmad M. Fagi ASB National Facilitator, Indonesian Center for Food Crops Research
and Development (icford); Jl. Merdeka No. 147, Bogor 16111, Indonesia; e-mail:
crifc@indo.net.id
Helmut J. Geist Executive Director, Land-Use & Cover Change Project, lucc
International Project Office (ipo); University of Louvain, 3 Place Louis Pasteur, B-1348
Louvain-la-Neuve, Belgium; e-mail: geist@geog.ucl.ac.be
Andrew N. Gillison Director, Center for Biodiversity Management; P.O. Box 120,
Yungaburra, Queensland 4872, Australia; e-mail: andy.gillison@austarnet.com.au
James Gockowski Agricultural Economist, iita–Humid Forest Station; B.P. 2008,
Yaoundé, Cameroon; e-mail: j.gockowski@cgiar.org
Kurniatun Hairiah Professor of Soil Biology and Root Ecology, Brawijaya University; Jl.
Veteran, Malang 65145, Indonesia; e-mail: soilub@malang.wasantara.net.id
Stefan Hauser Soil Physicist/Agronomist iita Humid Forest Station; B.P. 2008, Yaoundé,
Cameroon; e-mail: s.hauser@cgiar.org
Sinung Hendratno Socioeconomic Researcher, Pusat Penelitian Karet Sembawa, Balai
Penelitian Sembawa; Jl. Raya Palembang-Sekayu Km 29, Kotak Pos 1127, Palembang,
Sumatra, Selatan 300031, Indonesia; e-mail: irri-sbw@mdp.co.id
Shiou Pin Huang Professor, Departamento de Filopatalogia, Universidade de Brasilia; cepp
7099–970, Brasilia, DF, Brazil; e-mail: huang@guarany.cpd.unb.br
Shigehiro Ishizuka Senior Scientist, Forest and Forest Product Research Institute (ffpri); 7
Hitsujigaoka, Toyohira-ku, Sapporo, Hokkaido 062-8516, Japan; e-mail: ishiz03@ffpri.
affrc.go.jp
David Kaimowitz Director General, Center for International Forestry Research (cifor),
Jalan cifor; P.O. Box 6596, JKPWB, Jakarta 10065, Indonesia
Joyce Kasyoki Programme Administrator, asb; World Agroforestry Centre, UN Avenue,
Gigiri, P.O. Box 30677, 00100 GPO, Nairobi, Kenya; e-mail: j.kasyoki@cgiar.org
Jean Kotto-Same Soil Scientist, Institut de la Recherche Agricole pour le Développement
(irad); B.P. 2067, Yaoundé, Cameroon; e-mail: jkottosame@yahoo.fr
Ricardo Labarta Research Assistant Economist, World Agroforestry Centre–Peru; Km. 4.2
Carretera Federico Basadre, Pucallpa–Ucayali, Peru; e-mail: r.labarta@cgiar.org
Eric F. Lambin Professor, Department of Geography, University of Louvain; 3 Place
Pasteur, B-1348 Louvain-la-Neuve, Belgium; e-mail: lambin@geog.ucl.ac.be
Jessa Lewis Consultant; 8268 Sugarman Drive, La Jolla, CA 92037, USA; e-mail: jessa.
lewis@stanfordalumni.org
Fátima Moreira Soil Microbiologist, Dep. de Ciencia do Solo, Universidade Federal de
Lavras; cep 37200–000, Lavras, Minas Gerais, Brazil; e-mail: fmoreira@esal.ufla.br
Appolinaire Moukam Deceased; Soil Scientist, Institut de la Recherche Agricole pour le
Développement, irad, Yaoundé, Cameroon
Daniel Murdiyarso Professor, Department of Geophysics and Meteorology, Bogor
Agricultural University; Jl. Raya Pajajaran, Bogor, 16143, Indonesia; e-mail:
d.murdiyarso@icsea.org
Ousseynou Ndoye Regional Coordinator; Center for International Forestry Research
(cifor), Regional Office for Central and West Africa; c/o iita-hfc, B.P. 2008,
Yaoundé, Cameroon; e-mail: o.ndoye@cgiar.org
xvii
Contributors
Alternatives to Slash and Burn
xvii
Rosaline Njomgang Soil Chemist, Institut de la Recherche Agricole pour le
Développement (irad); B.P. 2067, Yaoundé, Cameroon; e-mail: j.tonye@camnet.cm
Dieudonné Nwaga Soil Microbiologist, University of Yaoundé, Plant Biology Department;
P.O. Box 812, Yaoundé, Cameroon; e-mail: j.tonye@camnet.cm
Marcus V. N. d’Oliveira Forestry Scientist, Embrapa Acre; BR-364 km 14, cep 69.901–
180, Caixa Postal 321, Rio Branco, Acre, Brazil; e-mail: mvno@cpafac.embrapa.br
Cheryl A. Palm Senior Research Scientist, The Earth Institute at Columbia University; 167
Monell, Lamont–Doherty Earth Observatory, 61 Route 9W, P.O. Box 1000, Palisades,
NY 10960, USA; e-mail: cpalm@iri.columbia.edu
Soetjipto Partohardjono Principal Researcher, Indonesian Center for Food Crops Research
and Development (icford); Jl. Merdeka No. 147, Bogor 16111, Indonesia; e-mail:
crifc@indo.net.id
William J. Parton Senior Research Scientist, Natural Resource Ecology Laboratory,
Colorado State University; Fort Collins, CO 80523, USA; e-mail: billp@nrel.colostate.
edu
Djuber Pasaribu Researcher, Indonesian Center for Food Crops Research and Development
(icford); Jl. Merdeka 147, Bogor 16111, Indonesia; e-mail: crifc1@indo.net.id,
crifc3@indo.net.id
Beto Pashanasi Lecturer, Universidad Nacional de la Amazonia Peruana, Yurimaguas, Peru;
e-mail: l.arevalo@cgiar.org
Eliane Guimarães Pereira Environmental Engineer, Soil and Plant Nutrition, Universidade
Federal de Itajubá, Av. BPS, 1303, Pinheirinho, Itajubá, Minas Gerais, 37500-903,
Brazil; e-mail: elianegp@unifei.edu.br
Komon Pragtong Division of Silvicultural Research and Botany, National Park, Wildlife
and Plant Conservation Department, Ministry of Natural Resources and Environment;
Paholyothin Rd., Jatujak, Bangkok, 10900, Thailand
Pornchai Preechapanya Division of Watershed Conservation and Management, National
Park, Wildlife and Plant Conservation Department, Ministry of Natural Resources and
Environment Station; 130/1 M4 Don Keaw, Mae Rim, Chiang Mai 50180, Thailand;
e-mail: pcpc@loxinfo.co.th, pornchaiP@icraf-cm.org
Pratiknyo Purnomosidhi Associate Research Officer, World Agroforestry Centre–
Kotabumi; P.O. Box 167, Kotabumi 34500, Lampung, Indonesia; e-mail:
icrafktb@lampung.wasantara.net.id
Subekti Rahayu Data Technician, World Agroforestry Centre–Indonesia; Jl. Cifor, Situ
Gede, Sindang Barang, Bogor, Indonesia; e-mail: S.Rahayu@cgiar.org
Auberto Ricse Forestry Scientist, inia, Agrarian Systems for Mountains Programme; Km.
4 Carretera Federico Basadre, Pucallpa–Ucayali, Peru; e-mail: eepuc@terra.com.pe
Vanda Rodrigues Soil Scientist, Embrapa–Rondônia; BR-364km, 5, 5, Caixa Postal 406,
cep 78900, Porto Velho, Rondônia, Brazil; e-mail: vanda@ronet.com.br
Nu Nu San Postdoctoral Researcher, University of West Virginia; 450 Medical Center Dr.,
Apt. B302, Morgantown, WV 26505, USA
Pedro A. Sanchez Director of Tropical Agriculture, The Earth Institute at Columbia
University; 2G Lamont Hall, Lamont–Doherty Earth Observatory, 61 Route 9W, P.O.
Box 1000, Palisades, NY 10964, USA; e-mail: sanchez@iri.columbia.edu
Syukur M. Sitompul Professor, Agronomy Department, Faculty of Agriculture, Brawijaya
University; Jl. Veteran Malang, Jawa Timur 65145, Indonesia; e-mail: smtom@malang.
wasantara.net.id
xviii
The Problem and Approach
Contributors xviii
Carmen Sotelo-Montes Forester, World Agroforestry Centre–Peru; Av. La Molina 1895, La
Molina, Lima 12, Peru; e-mail: c.sotelo@cgiar.org
Fred Stolle Lab de Télédetection, Université Catholique Louvain (ucl); Place Louis
Pasteur 3, B 1348 Louvain-la-Neuve, Belgium; e-mail: stolle@geog.ucl.ac.be
William D. Sunderlin Program Leader Forest, Society, and Policy Program, Center for
International Forestry Research (cifor); Situ Gede, Sindangbarang, Bogor Barat
16680, Indonesia; e-mail: w.sunderli@cgiar.org
Plodprasop Suraswadi Director General, Royal Forestry Department; 61 Paholythin Road,
Chatujak, Bangkok 10900, Thailand; e-mail: chahut@forest.go.th
Francis-Xavier Susilo Lecturer, Department of Plant Protection, Faculty of Agriculture,
Universitas Lampung; Gedung Bioteknologi Pertanian, Lantai 2 Universitas Lampung,
Jalan Sumantri Brojonegoro No. 1, Bandar Lampung, 35145, Indonesia; e-mail:
fxsusilo@telkom.net fxsusilo2000@yahoo.com
Michael D. Swaine Senior Lecturer, Department of Plant and Soil Science, Aberdeen
University; Aberdeen AB24, United Kingdom; e-mail: m.swaine@abdn.ac.uk
Michael J. Swift Consultant, ird Centre de Montpellier; 911 Avenue Agropolis, B.P.
64501, 34394 Montpellier Cedex 5, France; e-mail: swift@mpl.ird.fr, swiftmj@yahoo.
co.uk
David E. Thomas Senior Policy Analyst, World Agroforestry Centre–Chiang Mai; P.O. Box
267 cmu Post Office, Chiang Mai 50202, Thailand; e-mail: Thomas2@loxinfo.co.th
Téophile Tiki-Manga Agronomist, Institut de la Recherche Agricole pour le
Développement (irad); B.P. 2067, Yaoundé, Cameroon; e-mail: j.tonye@camnet.cm
Thomas P. Tomich Principal Economist and Global Coordinator asb Programme; World
Agroforestry Centre, UN Avenue, Gigiri, P.O. Box 30677, 00100 gpo, Nairobi, Kenya;
e-mail: t.tomich@cgiar.org
Jerome Tondoh Soil Microbiologist, Laboratoire d’Ecologie des Sols Tropicaux; 32 Avenue
Varagnat, 93 143 Bondy Cedex, France; e-mail: yazi@bondy.orstom.fr
Jean Tonyé ASB National Coordinator and Director, Farming Systems, irad; P.O. Box
2067, Yaoundé, Cameroon; e-mail: j.tonye@camnet.cm
Zac Tschondeau Senior Scientist, World Agroforestry Centre, Cameroon; B.P. 2067,
Yaoundé, Cameroon; e-mail: Z.Tchoundjeu@cgiar.org
Haruo Tsuruta Senior Scientist, National Institute of Agro-Environmental Sciences (niaes);
3-1-1 Kan-Nondai, Tsukuba, Ibaraki 305, Japan; e-mail: tsuruta@niaes.affrc.go.jp
Judson F. Valentim Pasture Researcher, Embrapa–Acre; KM-14, BR-364, Caixa Postal 392,
69.801–180 Rio Branco–Acre, Brazil; e-mail: judson@cpafac.embrapa.br
Meine van Noordwijk Regional Coordinator for Southeast Asia, World Agroforestry
Centre, Indonesia; P.O. Box 161, Bogor 16001, Indonesia; e-mail: m.vannoordwijk@cgiar.org
Héctor Vidaurre Forester, World Agroforestry Centre–Peru; Centro Internacional de la
Papa, Apartado 5969, Lima, Peru
Stephen A. Vosti Adjunct Assistant Professor, Department of Agricultural and Resource
Economics; Center for Natural Resources Policy Analysis, University of California–
Davis, Davis, CA 95616, USA; e-mail: vosti@primal.ucdavis.edu
John C. Weber Senior Forest Geneticist, World Agroforestry Centre, Peru; 2224 NW 11th
Street, Corvallis, OR 97330, USA; e-mail: JohnCRWeber@aol.com
Stephan Weise Vegetation Management Team Leader and asb Regional Coordinator, iita
Humid Forest Station; B.P. 2008, Yaoundé, Cameroon; e-mail: s.weise@cgiar.org
xix Contributors
Alternatives to Slash and Burn
xix
Horst Weyerhaeuser Senior Natural Resource Management Researcher, World Agroforestry
Centre/Chiang Mai; P.O. Box 267 cmu Post Office, Chiang Mai 50202, Thailand; email: horst@loxinfo.co.th
Douglas White Senior Research Fellow, Agricultural and Environmental Economist,
Centro Internacional de Agricultura Tropical (ciat), Centro Eco-Regional–inia; A.P.
558, Pucallpa, Peru; e-mail: d.white@cgiar.org
Gede Wibawa Head of Research Bureau, Research Institute for Estate Crops gapkindo;
Jl. Salak 1, Bogor 16151, Indonesia; e-mail: G.Wibawa@cgiar.org
Julie Witcover Graduate Student, University of California–Davis; 1429 H St. #1, Davis,
CA 95616, USA; e-mail: witcover@primal.ucdavis.edu
Paul L. Woomer Visiting Scientist, Sacred Africa; P.O. Box 79, Village Market, Nairobi,
Kenya; e-mail: plwoomer@africaonline.co.ke, format@nbnet.co.ke, plwoomer@nbnet.
co.ke
David Yanggen Agricultural and Natural Resource Economist, Centro Internacional de la
Papa; Apartado 1558, Lima 12, Peru; e-mail: d.yanggen@cgiar.org
Louis Zapfack Botanist, Senior Lecturer, University of Yaoundé I, Faculty of Sciences,
Department of Plant Biology; P.O. Box 812, Yaoundé, Cameroon; e-mail:
lzapfack@uycdc.uninet.cm
Acronyms and Abbreviations
AARD
AC
ACIAR
AGBD
AMF
AMR
ANOVA
ANU
ASB
ASC
BAPPENAS
BASA
BC
BD
BGBD
BPS
CABI
CAP_PRD
CATIE
CBD
CDM
CEB
CENFOR
CGE
CGIAR
CIAT
CIFOR
CIRAD
CMU
CODESU
CPAF
CPAF/AC
CPATU
Agency for Agricultural Research and Development
Acre State, Brazil
Australian Centre for International Agricultural Research
above-ground biodiversity
arbuscular mycorrhizal fungi
mean annual mortality
analysis of variance
Australian National University
Alternatives to Slash and Burn Agriculture
active soil carbon
Badan Perencanaan Pembangunan Nasional
Banco da Amazônia S.A.
benefit:cost ratios
bulk density
below-ground biodiversity
Biro Pusat Statistik
CAB International
improved productivity of capital
Centro Agronómico Tropical de Investigación y Enseñanza
Convention on Biological Diversity
Clean Development Mechanism
Casa do Estudante do Brasil
Center for Forestry Research
computable general equilibrium
Consultative Group on International Agricultural Research
Centro Internacional de Agricultura Tropical
Center for International Forestry Research
Centre de Cooperation Internationale en Recherche
Agronomique pour le Développement
Chiang Mai University
Consorcio para el Desarrollo Sostenible de Ucayali
Centro de Pesquisa Agroflorestal
Centro de Pesquisa Agroflorestal do Acre
Centro de Pesquisa Agroflorestal da Amazônia Oriental
xxii Acronyms and Abbreviations
CRFC
CSIRO
DANIDA
DF
DGE
Ditjenbun
EMATER
Embrapa
EPTD
ESALQ
FAEALQ
FaleBEM
FAO
FCCC
fcfa
FFTC
FGV
FNMA
FUNTAC
GDP
GEF
GHG
GIS
GMS
GPS
GTCE
HDI
HMSO
HTI
IBAMA
IBGE
IBMA
IBSRAM
ICFORD
ICRAF
IDB
IDESP
IFAD
IFDC
IFPRI
IGES
IIAP
IICA
IIED
IITA
Center for Research on Food Crops
Commonwealth Scientific and Industrial Research Organization
Danish Agency for Development Assistance
Distrito Federal
Directorate General of Estate
Direktorat Jenderal Perkebunan
Empresa de Assistência Técnica e Extensão Rural
Empresa Brasileira de Pesquisa Agropecuária
Environment and Production Technology Division
Escola Superior de Agricultura “Luiza de Queiroz”
Fundação de Estudos Agrários Luiz de Aueiroz
Farm Level Bioeconomic Model
Food and Agriculture Organization
Framework Convention on Climate Change
Central African franc
Food and Fertilizer Technology Center
Fundação Getulio Vargas
National Environmental Fund
State Technological Foundation of Acre
gross domestic product
Global Environment Facility
greenhouse gas
geographic information system
Greater Mekong Subregion
global positioning system
Global Change in Terrestrial Ecosystems
Human Development Index
Her Majesty’s Stationery Office
hutan tanaman industri (industrial timber estate)
Brazilian Institute for the Environment and Natural Resources
Instituto Brasileiro de Geografia e Estatística
Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais
Renováveis
International Board for Soil Research and Management
Indonesian Center for Food Crops Research and Development
World Agroforestry Centre
InterAmerican Development Bank
Instituto de Estudos Econômicos, Sociais e Políticos
International Fund for Agricultural Development
International Fertilizer Development Center
International Food Policy Research Institute
Institute for Global Environmental Strategies
Institutio de Investigación de la Amazonía Peruana
Instituto Interamericano de Cooperación para la Agricultura
International Institute for Environment and Development
International Institute for Tropical Agriculture
Acronyms and Abbreviations
IMAC
INCRA
INEI
INIA
INIFAP
INPE
INRM
IPCC
IPEA
IRAD
IRD
IRR
ITTO
IUCN
IUFRO
JICA
JIRCAS
KDTI
LAB_PRD
LANDSAV
LF
LN
LP
LUS
LUT
MAB
m a.s.l.
MDS
MMSEA
MPN
MPS
NDTR
NGO
NIES
NNE
NPV
NRC
NTFP
OM
PAM
PAR
PC
PCARRD
PESACRE
xxiii
Instituto de Meio Ambiente do Acre
Instituto Nacional de Colonização e Reforma Agrária
Instituto Nacional de Esatadística e Informática
Instituto Nacional de Investigación Agraria
Instituto Nacional de Investigación Agrícola, Pecuaria y Forestal
Instituto Nacional de Pesquisas Espaciais
integrated natural resource management
Intergovernmental Panel on Climate Change
Instituto de Pesquisa Econômica Aplicada
Institut de Recherche Agricole pour le Développement
Institut de Recherche pour le Développement
internal rates of return
International Tropical Timber Organization
International Union for the Conservation of Nature and Natural Resources
International Union of Forest Research Organizations
Japanese International Cooperation Agency
Japan International Research Center for Agricultural Sciences
Dawasan Dengan Tijuana Istimewa (Zone with Distinct Purpose)
improved productivity of labor
improvements in labor and capital productivity that increases the
overall productivity of land
long fallow
natural logarithm
linear programming
land use system
land use type
Man and the Biosphere
meters above sea level
multidimensional scaling
mountainous mainland Southeast Asia
most probable number per unit of soil volume
mean particle size
nutrient depletion time range
nongovernment organization
National Institute for Environmental Studies
net nutrient export
net present value
National Research Council
nontimber forest product
soil organic matter content
Policy Analysis Matrix
photosynthetically active radiation
colonization project
Philippine Council for Agriculture, Forestry, and Natural Resources
Research
Grupo de Pesquisa e Extensão em Sistemas Agroflorestais do Acre
xxiv Acronyms and Abbreviations
PFA
PFC
PFT
PLP
PPP
PROCITROPICOS
PROSEFOR
PSP
QFRI
RAP
RBA
RFD
RNRV
RO
SAM
SAREC
SC
SE
SECTMA
SF
SIF
SIFRECA
SOBER
SOM
SPI
SUDAM
SUFRAMA
TAC
TDRI
TFP
TSBF
UCA
UCA/SAREC
UEPAE
UNDP
UNEP
USAID
USDA-ARS
USGS
WFPS
WRI
WWF
ZEE
plant functional attribute
plant functional complexity
plant functional type
participatory land use planning
purchasing power parity
Programa Cooperativo de Investigación y Transferencia de Tecnología
para los Trópicos Suramericanos
Proyecto de Semillas Forestales
permanent sample plot
Queensland Forestry Research Institute
Rapid Assessment Program
rapid biodiversity assessment
Royal Forestry Department
relative nutrient replacement value
Rondônia
social accounting matrix
Sciences d’Anticipation Reconnaissance Evaluation Contrôle
shifting cultivation
soil exposure
Secretaria de Ciência, Tecnologia e Meio Ambiente do Acre
short fallow
Sociedade de Investigações Florestais
Sistema de Informações de Fretes para Cargas Agrícolas
Sociedade Brasileira de Economia Rural
soil organic matter
Servico de Produção de Informação
Superintendência de Desenvolvimento da Amazônia
Superintendência da Zona Franca de Manaus
Technical Advisory Committee
Thailand Development Research Institute
total factor productivity
Tropical Soil Biology and Fertility Programme
Universidad Centro Americana
Universidad Centro Americana/Science d’Anticipation
Reconnaissance Evaluation Contrôle
Unidade de Execução de Pesquisa de Ámbito Estadual
United Nations Development Program
United Nations Environment Programme
United States Agency for International Development
United States Department of Agriculture, Agricultural Research
Service
United States Geological Survey
water-filled pore space
World Resources Institute
World Wildlife Fund
Zoneamento Ecológico Econômico
i. t h e p ro b l e m a n d a p p roac h
1
Alternatives to Slash and Burn
challenge and app roac h e s o f
an international co n s o rt i u m
Pedro A. Sanchez and Cheryl A. Palm
The Earth Institute at Columbia University New York, New York
Stephen A. Vosti
University of California and Center of Natural Resource Policy
Analysis Davis, California
Thomas P. Tomich and Joyce Kasyoki
World Agroforestry Centre Nairobi, Kenya
T H E CHALLENGE
The world has lost about half of its forests to agriculture and other uses, and
78 percent of what remains is heavily altered, bearing little resemblance to
the original forests (Bryant et al. 1997). About 72 percent of the original
1450 million ha of tropical forests have been converted to other uses (Myers
1991; fao 1997). Deforestation rates for the humid tropics were estimated
to be 6.9 million ha/yr at the end of the 1970s (Lanly 1982) and doubled to
14.8 million ha/yr by 1991 (Myers 1993). More recent studies indicate that
deforestation rates decreased by about 10 percent in the 1990s (Durst 2000).
These values are fraught with methodological problems. Achard et al. (2002)
asserted that previous methods overestimated tropical deforestation rates by as
much as 25 percent. Brazil, the country with the largest area of tropical forests,
reports that deforestation rates in the Brazilian Amazon increased by as much
as 40 percent from 2001 to 2002 (inpe 2003). Despite these limitations, it
is obvious that tropical deforestation and subsequent ecosystem degradation
continue at alarming rates. They remain a major worldwide concern because
of the high levels of plant and animal biodiversity these forests contain, the
large carbon (C) stocks stored in them, and the many other ecosystem services
tropical forests provide (Myers 1993; Laurance et al. 1997).
Small-scale farmers often are viewed as the primary agents of deforestation (Hauck 1974), accounting for as much as 96 percent of forest losses
(Amelung and Diehl 1992). Myers (1994) reported that the aggregate actions
4
The Problem and Approach
of small-scale farmers resulted in greater deforestation than the activities of large-scale
operations and accounted for about 70 percent of the deforestation in Africa, 50 percent in Asia, and 30 percent in Latin America. Although the predominant role played
by small-scale farmers has come into question (Geist and Lambin 2002; chapter 18,
this volume), they are often part of the deforestation process.
Small-scale farmers practicing slash-and-burn agriculture clear forests to produce
food and make a living for their families. They often have few options other than
to continue clearing tropical forests because of the benefits and profits derived from
deforestation. In many cases, these farmers are marginalized from society and government support programs, and often they are migrants escaping from poverty and
inequities elsewhere in the country. Any efforts to arrest deforestation must consider
this group; in the absence of alternatives they will continue to clear forest to meet their
needs for food and income.
Early approaches to conserve tropical forests were done at the exclusion of smallscale farmers that depend on the forest for their livelihoods (fao Staff, 1957). These
“fence off the forest” approaches often increased conflicts between conservation and
development efforts and ignored the causes of deforestation. The importance of agricultural development for reducing poverty of the small-scale farmers and the economic
development of developing countries is increasingly recognized. Therefore the development and promotion of agricultural systems that reduce poverty must be integrated
with strategies to conserve tropical forests and the biodiversity and carbon they house
(McNeely and Scherr 2003). The challenges are to identify alternative systems that
meet farmers’ needs and that can reduce pressure to clear more forest or minimize the
impacts on biodiversity and other global environmental resources. The Alternatives to
Slash and Burn (asb) consortium was created to address this challenge.
This chapter introduces the asb Program, an international consortium of researchers and extension groups that was established specifically to investigate the causes and
consequences of deforestation by small-scale farmers and to identify land use systems that enhance both local livelihoods and the environment and the policies and
other changes needed to support them. It begins with a description and distinction
of shifting cultivation and slash-and-burn practices and continues with a summary
of land use intensification pathways in the tropics. This is followed by the objectives,
benchmark site locations, broad methods, and activities of the asb consortium. The
subsequent chapters of the book describe in detail the methods and results of the past
10 years of this interdisciplinary, multi-institutional effort and include suggestions for
implementation of the findings.
L A N D U SE AT THE TROPICAL FOREST MARGINS
Almost all tropical forests are cleared by similar methods that start with slashing the
forest with chainsaws, axes, and machetes and burning the felled vegetation after it
has dried. In this sense, slash-and-burn is simply a land-clearing technique. The sub-
Alternatives to Slash and Burn
5
sequent land use pathway that follows land clearing differs depending on the different
groups of people involved—indigenous forest dwellers, small-scale farmers, and largescale private operators—and the intended use of the land, including the various types
of shifting cultivation, agroforestry, logging, cattle ranching, and commercial tree
plantations. There is much confusion in the literature regarding the use of the terms
shifting cultivation and slash-and-burn agriculture; the following sections distinguish
between the different land use pathways that follow the clearing of tropical forests.
S h i f t i n g Cultivation or Sl ash-and-Burn Agriculture?
Shifting cultivation is probably the oldest farming system (Nye and Greenland 1960)
and is remarkably similar throughout the humid tropics. Farmers slash and burn a
hectare or so of primary or tall secondary forest, grow food crops in polyculture for
1 to 3 years, and abandon the land to secondary forest fallow regrowth for 20 to
40 years, then repeat the cycle. This traditional shifting cultivation with short cropping periods and long secondary forest fallow periods is now rare, practiced primarily
by indigenous communities disconnected from the national economy. It is socially
and environmentally sustainable (Thrupp et al. 1997), albeit at low levels of agricultural productivity and human population densities of less than thirty people per
square kilometer (Boserup 1965). Shifting cultivation is known by a variety of terms,
referring mostly to cleared fields: swidden (Old English), rai (Sweden), milpa, conuco,
roza (Latin America), shamba, chitemene (Africa), jhum (India), kaingin (Philippines),
ladang (Indonesia and Malaysia), and many others. Fallows are commonly called bush
fallow and jachere in Africa; barbecho, capoeira, and purma in Latin America; and
belukar and other terms in Indonesia. The concept of fallows in the tropics differs
from that used in the temperate zone, where the term fallow normally means leaving
the soil bare (Sanchez 1999). The vegetative fallow phase restores carbon and nutrient
stocks in the biomass, improves soil physical properties, and suppresses weeds (Nye
and Greenland 1960; Sanchez 1976; Szott and Palm 1986).
When human population pressures exceed a critical density that varies with agroecological zones and inherent soil fertility, traditional shifting cultivation is replaced
by a variety of other agricultural practices that still involve clearing by slash-andburn methods. We suggest that the loosely used terminology be specified as follows:
shifting cultivation refers to the traditional long-fallow rotational system, and slashand-burn agriculture refers to other farming systems characterized by slash-and-burn
clearing, short-term fallows, or no fallows at all. These systems include the shortened
fallow–food crop systems and the establishment of tree-based systems such as complex
agroforests, simple agroforests, or monoculture tree crop plantations such as oil palm
(Elaeis guineensis Jacquin), coffee (Coffea spp.), rubber (Hevea brasiliensis [Willd. ex A.
Juss.] Muell.-Arg.), or pulp and timber species. Slash-and-burn is also the means of
establishing pastures that are found throughout the humid forest zone of Latin America. These slash-and-burn systems differ from shifting agriculture in that the crops are
6
The Problem and Approach
interplanted with pastures or tree seedlings, or in some cases the cropping period is
omitted. Many of the systems are still rotational to some degree, with occasional slashand-burn clearing when the productivity of the system declines.
L a n d U s e Intensification Pathways
The pathway of agricultural intensification depends to some extent on the biophysical
environment but is modified by the demographic composition and pressures, production technologies, and natural resource management practices, infrastructure, institutions, and policy environment present at the time. The usual pathway begins with
the reduction of the fallow period to less than 10 years and more commonly less than
5 years. These short fallows are incapable of accumulating sufficient nutrient stocks
in the biomass and suppressing weeds by shading. Unlike shifting cultivation, where
soil erosion is seldom a problem, slash-and-burn systems have less vegetative cover
and often exposed, compacted soils that increase water runoff and soil erosion rates
(Lal et al. 1986). This change in vegetation and soil structure may lead to changes
in the hydrologic cycle, with negative consequences downstream (Bruijnzeel 1990;
Tinker et al., 1996). The combined effects of shortened fallows result in systems with
declining productivity, depending more and more on less and less fallow biomass. In
some cases, the systems reach a point at which the trees are replaced by other, highly
degraded systems such as Imperata cylindrica (L.) Beauv grasslands in Southeast Asia
and West Africa (Garrity 1997) and degraded pastures in Latin America (Serrão and
Homma 1993). This pathway of land use intensification, land degradation, and the
resulting losses of carbon stocks, nutrients, and biodiversity is depicted in the lefthand, declining curve in figure 1.1, line a. It is important to remember that those and
other ecosystem services have been traded for private benefits, including food, feed,
fiber, and cash.
With further increases in population density come increased access to markets
and decreased access to forest products. A point may be reached when land degradation begins to be reversed with changes in land tenure institutions that facilitate
investments in improved land management. This process was recognized by Boserup
(1965) and is sometimes called induced institutional innovation (Hayami and Ruttan
1985). Land rehabilitation usually is accomplished by replenishing lost plant nutrients; using improved crop germplasm, agronomic practices, and soil conservation
methods; introducing livestock; and planting more trees.
Farmers will invest in improved land management and care for the environment
when they have reasonably secure land or tree tenure and if it is profitable compared
with other investment options within the context of household constraints and individual time preferences and attitudes toward risk. Examples of soil and land rehabilitation with increasing population pressure are well documented as “more people, less
erosion” (Tiffen et al. 1996) and “more people, more trees” (Sanchez et al. 1998).
They are accompanied by increasing productivity and profitability. Ecosystem stocks
Alternatives to Slash and Burn
7
Figure 1.1 Land use intensification pathways and changes in stocks of natural capital such as carbon and
nutrient stocks, biodiversity, and other ecosystem services, with time and increasing population density
in the tropics (Sanchez et al. 1998). Line a represents the usual pattern of land degradation and eventual
rehabilitation when the proper policies and institutions are in place, line b represents the continued state
of degradation that can occur in the absence of appropriate policies and institutions, and line c represents
the desired course where there is little degradation of the resource base yet improved livelihoods are
achieved.
of carbon and nutrients increase and other ecosystems services also return, the level of
which depends on the previous state of degradation and on the type of land use system
that is established. Livelihoods may continue to improve as more and more valuable
economic products are obtained from the system. The tradeoffs between the environmental services and profitability are lower than those in the degraded state. This is the
right-hand side of figure 1.1, line a. In some cases, the policy environment does not
provide incentives to rehabilitate these degrading lands (line b in figure 1.1), and the
challenge is to find policy tools that will provide those incentives.
Alternative land use intensification pathways that do not first involve severe land
degradation (line c in figure 1.1) do exist in the form of the complex agroforests that
have been developed by indigenous communities (Padoch and de Jong, 1987; Michon
and de Foresta 1996; Duguma et al., 2001). The challenge is, first, to identify and
understand barriers to adoption of other systems by smallholders when such systems
are superior alternatives in terms of their environmental impacts and sustainability as
well as their profitability, food security, riskiness, and other measures of acceptability
to smallholders. When such superior win–win alternatives exist, the next challenge is
8
The Problem and Approach
to identify means to reduce barriers to adoption by smallholders before land degradation occurs to such an extent that ecosystems services are lost. More often, however,
there is no single “best bet,” but instead there is a range of tradeoffs across land use
alternatives regarding environmental and agricultural development objectives.
Wh o A re the Small-Scale Sl ash-and-Burn Farmers?
The number of people who depend on shifting cultivation for their livelihoods has
for decades been estimated at about 250 to 300 million (Hauck 1974; Myers, 1994).
Recent georeferenced population and farming system data suggest that the numbers
are an order of magnitude lower. Dixon et al. (2001) report that 37 million people, or
2 percent of the agricultural population of the tropics, practice some form of shifting
cultivation in about 1 billion ha or 22 percent of the tropical land area. This is the
area of influence, but only a small fraction of that is under actual cropping or fallows.
These numbers do not include people practicing more intense systems in the humid
tropics that were originally established by slash-and-burn practices. The number of
people involved in these other crop-based, tree-based, or pasture-based slash-and-burn
systems is several times that of shifting cultivators (Dixon et al. 2001).
Deforestation by slash-and-burn farmers is a response to underlying root causes.
Population growth is naturally viewed as a main driver of deforestation, and economic
growth often is viewed in the same vein. But no direct relationship between deforestation and population growth or economic growth has been found. Myers (1991)
noted that whereas the population of forested tropical countries increased by 15 to 35
percent in the 1980s, deforestation expanded by 90 percent during the same period.
The recent analysis by Geist and Lambin (2002) shows that in-migration to the forest margins is a much larger factor in deforestation than high internal population
growth. Brown and Pearce (1994) obtained inconclusive results when attempting
to relate gross domestic product (gdp) growth rates, foreign debt, and population
growth with deforestation in tropical countries. Rudel and Roper (1997) found that
in tropical countries with large forested areas, deforestation increases with increasing
gdp, whereas in countries with mainly forest fragments, increasing gdp decreases
deforestation.
Whereas traditional, indigenous people practice shifting cultivation, many (in
some cases most) of the people practicing slash-and-burn agriculture are migrants
from other parts of their country who seek a better life at the forest margins. In some
countries, large numbers of migrants to the forest margins come as part of government-sponsored colonization programs aimed at transmigrating poor people from
densely populated areas to the forest frontier, particularly in Brazil and Indonesia
(Hecht and Cockburn 1989; Kartasubrata 1991). Others are spontaneous migrants
who, acting independently with little or no government support, follow the opening
of roads and logging trails. Planned and spontaneous migrations of poor people from
crowded regions such as Java, the Andes, and northeastern and southern Brazil have
Alternatives to Slash and Burn
9
undeniably contributed to deforestation. Opening of roads into primary forests such
as the Belém-Brasília, Transamazônica, and São Paulo–Rio Branco in Brazil, the Carretera Marginal de la Selva and the Federico Basadre in Peru, and the Trans-Sumatra
and Trans-Gabon highways have provided access to forests to both small-scale farmers
and commercial interests.
Many of these migrants are unfamiliar with the humid tropics, are largely unaware
of the knowledge-intensive practices of indigenous shifting cultivators, and attempt to
establish cropping systems that work where they came from (Moran 1981). People in
these situations usually lack alternative employment opportunities; have limited access
to markets, credit, and information; and often are politically marginalized. These people are a major focus of the asb consortium.
T H E A S B CONSORTIUM
The asb consortium is an international group of researchers, extension workers, and
nongovernment organizations (ngos) established in February 1992 to investigate
the causes and consequences of deforestation by small-scale farmers and to identify
land use systems that enhance local livelihoods and the environment and the policies
and other changes needed to support them. The asb focuses on areas with high rates
of deforestation where rapid increases in population density caused primarily by inmigration result in conversion of natural forests and where the environment–livelihood
tradeoffs are large. The asb does not focus on shifting cultivation, but in some locations where it did occur, it was included in the comparative analysis. Similarly, largerscale slash-and-burn operations also were included in some of the comparisons.
S tat e o f Knowledge
A literature review undertaken in 1992 showed much process-based understanding
of agricultural practices, empirical understanding of global environmental processes
and social processes, some policy research, and almost no multidisciplinary research
(Sanchez and Bandy 1992; Bandy et al. 1993; Sanchez and Hailu 1996). The biophysical processes of shifting cultivation and slash-and-burn systems have been well
understood through decades of long-term, place-based research (Nye and Greenland
1960; Jurion and Henry 1969; Sanchez 1976; Juo and Lal 1977; Seubert et al. 1977;
Serrão et al. 1979; MacIntosh et al. 1981; Toky and Ramakrishnan 1981; Sanchez
et al. 1983, 1987; Ramakrishnan 1984, 1987; Smyth and Bastos 1984; Von Uexkull
1984; Alegre and Cassel 1986, 1996; Sanchez and Benites 1987; Wade et al. 1988;
Kang et al. 1990; Cerri et al. 1991; Palm and Sanchez 1991; Smyth and Cassel 1995;
Juo and Manu 1996; Palm et al. 1996).
The environmental consequences of slash-and-burn and tropical deforestation on
greenhouse gas emissions have been modeled or estimated with limited data on the
10
The Problem and Approach
rates of deforestation, the carbon stored in the forests, and subsequent land use systems (Houghton et al. 2000). Much data have been gathered on the effects of tropical
deforestation on above-ground biodiversity (Whitmore and Sayer 1992; Heywood
1995) and watershed hydrology (Bruijnzeel 1990; Tinker et al. 1996), but with limited specificity to slash-and-burn agriculture. There were only a few studies on belowground biodiversity (Lavelle and Pashanasi 1989).
The anthropological aspects of shifting cultivation have been described extensively
(Conklin 1954, 1963; Cowgill 1962; Padoch and de Jong 1987; Thrupp et al. 1997),
with more recent studies focusing on migrants practicing slash-and-burn agriculture
(Moran 1981; Colfer et al. 1988; Rhoades and Bidegaray 1987; Fujisaka et al. 1991).
There have been several studies about the economics and policies of deforestation and
slash-and-burn practices, focused primarily on Brazil (Mahar 1988; Binswanger 1991;
Brown and Pearce 1994; Mahar and Schneider 1994).
What this incomplete literature review showed was an almost total absence of
multidisciplinary work. Social and biophysical scientists have seldom worked together
on slash-and-burn issues. There was no tradition of joint research and collaboration
between economic groups and the environmental community dealing with this issue
(Repetto and Gillis 1988), or between the agricultural, economic, and environmental
communities. The asb consortium was established to link the diverse research disciplines and the development community to address jointly the problems of deforestation, unsustainable land use, and rural poverty at the humid forest margins.
I n c e p t i on
A United Nations Development Programme (undp)–sponsored workshop was held
in Porto Velho, Rondônia, Brazil, on February 16–21, 1992, attended by twenty-six
environmental policymakers and research leaders from eight tropical countries, five
ngos, six international agricultural research centers, three regional research organizations, and six donor agencies (asb 1992). Participants concluded that a global effort
was needed because the problem and impacts were global and that cross-site comparisons of causes and solutions could provide insights not possible from isolated studies.
The participants created the asb consortium, set the broad basis for collaboration,
selected three initial benchmark sites, and formed a governing body to guide the intricate linkages and processes.
Two key recommendations of the Rio Earth Summit that was held later in 1992
provided international legitimacy to the asb consortium. They appear in chapter 11,
“Combating Deforestation,” of Agenda 21, as follows (Keating 1993):
Limit and aim to halt destructive shifting cultivation by addressing the underlying social and ecological causes.
Reduce damage to forests by promoting sustainable management of areas adjacent to the forests.
Alternatives to Slash and Burn
11
G oa l , H y pothesis, and Objectives
The overall goals of the asb consortium are to help reduce the rate of deforestation
caused by slash-and-burn agriculture, rehabilitate degraded lands created by slashand-burn, and improve the well-being of slash-and-burn farmers by providing economically and ecologically viable alternative land use practices.
The underlying hypothesis at the inception of asb was that intensification of
agricultural systems on already cleared lands and rehabilitation of degraded lands at
the humid forest margins would reduce deforestation. Although this hypothesis has
since been shown to be too simplistic because the underlying behavioral assumptions
were wrong (Angelsen and Kaimowitz 2001), it provided a framework around which
the program focused its initial research objectives and activities:
• Site characterization. Assess the principal socioeconomic and biophysical processes leading to deforestation, including government policy and decisionmaking patterns of farmers practicing slash-and-burn.
• Environmental and agronomic sustainability studies. Quantify the contribution of slash-and-burn agriculture and alternative land use practices to
global, regional, and local environmental changes such as climate change,
biodiversity loss, and land degradation.
• Socioeconomic studies and tradeoff analysis. Integrated assessment of land
use alternatives to identify appropriate technologies and develop improved
production systems that are economically feasible, socially acceptable, and
environmentally sound alternatives to current slash-and-burn systems or to
understand tradeoffs between land use alternatives.
• Policy research and implementation. Identify policy options and institutional
reforms that can facilitate the adoption of the improved systems and the
balancing of tradeoffs to attain a more desirable mix of outcomes and discourage further deforestation.
Succinctly stated, are there alternative land use systems to slash-and-burn that
reduce deforestation, poverty, and global environmental changes such as greenhouse
gas emissions and biodiversity loss? What are the type and magnitude of the environmental and livelihood tradeoffs for these different systems? And, based on that tradeoff analysis, how can the systems be influenced to attain better outcomes for a range
of stakeholders, including farmers?
The slash-and-burn topic is complex, involving multiple agents, land use objectives, and driving forces (Tomich et al. 1998b). In addition, slash-and-burn is carried
out in a diverse array of biophysical, socioeconomic, and policy environments. To
address the objectives of the asb consortium requires an understanding of the influence of these multiple factors and environments on the economic viability, sustainability, and environmental impacts of the alternatives. From the outset asb deter-
12
The Problem and Approach
mined four key features to assist in this complex task: a cross-disciplinary approach
combining biophysical and behavioral sciences, the participation of diverse kinds of
institutions, work based at benchmark sites, and common methods to be used at all
sites. The benchmark sites and standard protocols are introduced in this chapter, and
the details of the methods, their application, and results are presented in subsequent
chapters in the book.
C ro s s - D isciplinary Research and
D eve lo p ment F ramework
The asb developed a conceptual framework in which the land use system adopted by
farmers depends on farm households’ objectives; their natural, human, social, technical, and financial resources; and the biophysical, social, economic, and political constraints to the use of these resources. The effects of these land use systems for alleviating poverty, conserving resources, and reducing deforestation were then assessed along
with the impacts of current and alternative policies (Palm et al. 1995; asb 1996). An
integrated natural resource management (inrm) research framework that was later
developed by the international agricultural research centers (figure 1.2; cifor 2000;
Izac and Sanchez 2001) was based largely on the asb experience. The various steps
Figure 1.2 The research and development framework used by asb (modified from asb 1996; cifor
2000; Izac and Sanchez 2001).
Alternatives to Slash and Burn
13
in the research process of problem identification, assessment of food and income services, assessment of ecosystem services, tradeoff analysis, policy research and implementation, and impact analysis are discussed in the following sections.
D i ve r s e Institutions
In 2001 the asb consortium was composed of seven national agricultural research
systems, four other national agencies, seven international agricultural research centers,
twenty universities and advanced research institutions, and five local and national
ngos, many of them represented in this volume. The asb researchers have organized
themselves in an evolving collection of multidisciplinary thematic working groups,
including site characterization, biodiversity (above- and below-ground), climate
change, agronomic sustainability, sustainable land use mosaics, farmer concerns, policy and institutional issues, synthesis and linkages, and training and capacity building.
A Global Steering Group provides governance to the consortium. It meets yearly and
sets overall policy, funding strategy, and reporting. A global coordinator with a small
global team of two to three staff facilitates operations (Swift and Bandy 1995).
B e n c h m a rk Sites
A network of benchmark sites was identified to represent large, active areas of deforestation caused by slash-and-burn practices. The sites that were selected provide a range
of biophysical and socioeconomic conditions under which slash-and-burn occurs and
include a land use intensity gradient from traditional shifting cultivation to intensive
continuous cropping and degraded lands. Benchmark sites were also selected based
on sufficient infrastructure to conduct the research and development activities. Each
benchmark site covers a large area and has a national research station as its physical
base, but the bulk of the work is done locally with researchers, ngos, extension services, farmers, and policymakers.
Latin America
Two areas were selected in the Amazon Basin; they represent areas that have experienced rapid deforestation as a result of government colonization programs (western
Amazon Brazilian benchmark site) and other areas of lower population density and
poor infrastructure where population densities are increasing through spontaneous
migration from the overcrowded urban and Andean areas (Peruvian benchmark site).
The site in the western Brazilian Amazon encompasses two colonization projects,
Pedro Peixoto, Acre and Theobroma, Rondônia, and areas along the BR-362 highway
(see details and map in chapter 12 this volume). Settlements are all under government
14
The Problem and Approach
sponsorship, with migrants assigned 50- to 100-ha plots, and currently undergoing
rapid development. The site headquarters is the Empresa Brasileira de Pesquisa Agropecuária (Embrapa)–Acre research center, near Rio Branco. The Peruvian benchmark
area focuses on Pucallpa and Yurimaguas in the Ucayali and Loreto regions of the
Selva Baja (see details in chapter 15, this volume). The site is managed from the Center for Forestry Research (cenfor) of the Instituto Nacional de Investigación Agraria
(inia), working in close cooperation with Consorcio para el Desarrollo Sostenible de
Ucayali (codesu), a group of ngos, the Ucayali Regional Government, the Instituto
de Investigación de la Amazonía Peruana (iiap), and inia’s Yurimaguas Experiment
Station.
A third area in Latin America represents the humid and subhumid forests of the
Atlantic Coast of Central America and Mexico where encroaching urban areas and
slash-and-burn has reduced the extent of the northernmost extension of tropical forests. The benchmark area in the Yucatan in southeast Mexico was managed by Instituto Nacional de Investigación Agrícola, Pecuaria y Forestal (inifap).
Africa
A site in Cameroon represents the equatorial Congo Basin rainforest of Congo–
Kinshasa, Congo–Brazzaville, Equatorial Guinea, Gabon, Central African Republic, and Cameroon, where there is low but increasing population density and largely
indigenous slash-and-burn agriculture. The site includes a north–south gradient, from
rapid, spontaneous colonization around Yaoundé at the north, though an intermediate situation at M’Balmayo, to very low population density at Ebolowa in the southern end, close to the Gabon–Equatorial Guinea border (see details and map in chapter
14, this volume). Site headquarters are at the Institut de Recherche Agricole pour le
Développement (irad) at Nkolbisson, near Yaoundé, with strong support from the
iita Humid Forest Centre.
Southeast Asia
Sites in Southeast Asia represent three quite different forest ecosystems. The Sumatran
benchmark area in Indonesia represents the equatorial rainforests of the Indonesian
and Malaysian archipelago. Located in Jambi and Lampung provinces, it covers a
broad gradient from primary forests in the Jambi area to degraded Imperata grasslands
in Lampung Province, including both indigenous farmers and colonization projects as
well as large-scale plantations and logging companies (see details and maps in chapter
13, this volume). The site is managed from the Central Research Institute for Food
Crops (crifc) of the Agency for Agricultural Research and Development (aard) in
Bogor, Java. A benchmark area in the Philippines represents the monsoonal forests,
where only forest remnants exist on steep mountain slopes and degraded grasslands
Alternatives to Slash and Burn
15
dominate the landscape. The sites in Claveria and Lantapan in Northern Mindanao,
Philippines, are operated by the Philippine Council for Agriculture, Forestry, and
Natural Resources Research (pcarrd) together with a number of other organizations. A benchmark area in the Ma Chaem watershed near Chiang Mai, Thailand,
represents the extensive area of subtropical hill forests of mainland mountain Southeast Asia found in Thailand, Myanmar, Laos, Vietnam, and southern China. The site
was chosen to extend asb research into higher-elevation areas with broad ranges of
slope conditions where issues of land use management often overlap with issues of
watershed management. Chapter 16 provides additional details. The benchmark site
is managed by Thailand’s Royal Forest Department in close collaboration with Chiang
Mai University.
All benchmark sites fall within the tropical and subtropical moist broadleaf forest
biome (wwf 2001). To indicate how much the benchmark sites represent other areas
in the tropics, regional similarity classes were developed from a set of key physical,
environmental determinants of plant growth. The domain potential mapping procedure developed by Carpenter et al. (1993) was used to generate the map shown in
figure 1.3 of matching climate surface values for each of 108 sample locations in asb’s
benchmark sites in Brazil, Indonesia, and Cameroon. The various similarity classes
indicate the degree to which the asb sites can be extrapolated over a global surface
using the same climate variables.
Initial asb research was concentrated in the Brazil, Cameroon, and Indonesian benchmark sites, and these three thus serve as the focus for much of this book,
although much progress has also been made in Thailand and Peru, the results of which
are presented in chapters 15 and 16.
Figure 1.3 Map indicating the location and global environmental representativeness of the asb sites in
western Amazon, Indonesia, Thailand, Philippines, and Cameroon. The domain similarity values are
based on elevation, potential evapotranspiration, total annual precipitation, precipitation in the driest
month, precipitation range, minimum average monthly temperature, and maximum average monthly
temperature (Gillison 2000).
16
The Problem and Approach
R E S E A RCH THEMES AND M ETHODS
The asb integrates a range of geographic sites, spatial and temporal scales, disciplines,
and partner institutions. To implement the various steps of the interdisciplinary inrm
research framework at the various sites demanded a minimum, common research
approach for making cross-site comparisons. Standardized methods were developed
for identifying problems and characterizing sites (figure 1.2, step 1), quantifying the
environmental, agronomic, and socioeconomic parameters of the different land use
alternatives (steps 2 and 3), assessing the economic and environmental tradeoffs (step
4), and researching and implementing policies (step 5). The various methods are
described in detail in this section.
C h a r ac t erizing Sites
The first phase of asb research involved characterizing the benchmark sites. The
purpose of the characterization was to describe the biophysical, socioeconomic, and
policy settings of the sites, define the extent and process of slash-and-burn agriculture
in forming land use patterns, investigate the driving forces for slash-and-burn, develop
typologies of slash-and-burn land use systems that exist across the asb sites, establish a
baseline of information for future impact assessments, and provide regional and global
extrapolation domains for research results. The results were used to identify research
priorities and develop research protocols for the subsequent steps.
Guidelines were developed for characterizing the rates of forest conversion; dominant land use systems; and the biophysical, socioeconomic, and policy environments
in which they are found at the regional, benchmark, community, and farm and household scales (Palm et al. 1995). Within each benchmark site there are numerous communities that represent a range of demographic conditions and land use histories that
result in different local land use patterns. The characterization process also included
detailed interviews to establish the problems, opportunities, constraints, and resources
at the community and farm or household scales, the responses to which were important for identifying factors that affect decision making and driving forces of land use
and for establishing research agendas for finding sustainable alternatives to slash-andburn. Remote sensing and geographic information system (gis) techniques were used
to assess rates of deforestation and land use patterns at the sites.
Site characterization results for the first three benchmark sites are documented
by Ávila (1994) for Brazil, Ambassa-Kiki and Tiki Manga (1997) for Cameroon, and
Gintings et al. (1995) and van Noordwijk et al. (1995) for Indonesia. Information
is also presented in benchmark site reports (Tomich et al. 1998a; Kotto-Same et al.
2000; Lewis et al., 2002). A comparison of some of the key biophysical and socioeconomic conditions shows the broad range encompassed by benchmark sites (table 1.1).
4–200
5–30
1.21
Tropical moist forest;
semideciduous forest
Paleudults, hapludox
3–5
15–250a
6.25
Dominant original vegetation
b
a
Indicates small-scale farms as initially defined for Brazil.
Wage rates are from 1996–1997.
c
For women and men, respectively.
Source: Modified from Tomich et al. (1998b).
Predominant soils
(U.S. Soil Taxonomy)
Population density (people/km2)
Farm size (ha/household)
Agricultural wage ( $/d)b
1400–1900
2–4N
July–August;
October–February
Tropical moist forest;
semideciduous forest
Kandiudults
1700–2400
7–12S
June–September
Rainfall (mm/yr)
Latitude
Months dry season (100 mm)
Southern Cameroon
Western Amazon,
Brazil
Characterization Parameter
Table 1.1 Selected Site Characterization Parameters for the Benchmark Areas
Hapludox, kandiudox,
kandiudults, dystrudepts
2–175
2–10
1.67
Tropical moist forest
2500–3000
0–6S
June–August
Sumatran Lowlands,
Indonesia
1–9
2–50
2.5
Paleudults, paleaqualfs
Tropical moist forest
1500–2200
6–12S
June–August
Selva Baja of Peru
20
2.4–16
1.45, 1.75c
Tropical semideciduous
montane forest
Haplustults, dystrustepts
1200–1500
20N
November–April
Ma Chaem,
North Thailand
18
The Problem and Approach
Comparable activities and approaches for Mexico and the Philippines are presented in
Haggar et al. (2001) and Mercado et al. (2001), respectively.
Meta–Land Use Systems
A set of meta–land use systems was identified from the site characterization process that
aggregates the broad range of specific land use systems found in the diverse benchmark
sites (asb 1996). Such systems were initially identified as “best-bet” and “worst-bet”
alternative systems for specific benchmark sites (Tomich et al. 1998b). Meta–land use
systems include forests, complex agroforests, simple agroforests, crop–fallow rotations,
continuous food crops, and pastures and grasslands (table 1.2). This array of land uses
covers a gradient often used by biophysical scientists to describe varying levels of disturbance of forest for agriculture (Ruthenberg 1980; nrc 1993). General descriptions
of these meta–land use systems and some specific examples are given here.
Forests
Undisturbed or so-called primary forests are rare in and around the benchmark sites.
Disturbed forests, with some degree of logging, are dominant, with the intensity of
logging low in Cameroon, where a few trees are harvested per hectare, intermediate in
Brazil and Peru, and high in Indonesia and Thailand. Extractive reserves, where nontimber forest products are harvested, are perhaps best known in the Amazon, where
Brazil nuts or castanha (Bertholletia excelsa Humb. & Bonpl.) and rubber are harvested
from naturally occurring trees, but at all sites some amount of nontimber forest products is harvested from forests of the different categories. The concept of sustainably
managed community-based forests is being developed at the Brazil benchmark site by
Embrapa (chapter 8, this volume). Community-protected secondary forests are found
in the Thailand site (chapter 16, this volume) and in Sumatra, Indonesia.
Complex Agroforests
Complex agroforests contain a wide variety of economic plant species and usually
have a rotation time greater than 20 years. The complex agroforests of Indonesia are
indigenous systems established over generations by local peoples living at the margins of tropical rainforests in Sumatra, Borneo, and other islands (Torquebiau 1984;
Foresta and Michon 1994). Primary or old secondary forests are slashed and burned,
food crops, citrus, and robusta coffee (Coffea canephora Pierre ex Froehner) are planted
along with several trees species, and natural regeneration of forest species is allowed.
The trees eventually shade out the crops, occupy different strata, and produce highvalue products such as fruits, resins, medicines, and commercially valuable timber.
Main economic tree species include damar (Shorea javanica Koord. & Valeton), durian (Durio zibethinus Murray), duku (Lansium domesticum Corr.), and rubber. In the
case of rubber, production declines after 20 or 30 years, and the slash-and-burn cycle
typically begins again; some of the other tree species, notably damar, can have much
Continuous food crops
Pasture and grasslands
Food crop–fallow systems
Simple agroforests and
intensive tree crops
None
Degraded
pasturesImproved pastures
Coffee monoculture
Annual food crop, 3-yr
fallowAnnual food crop, 2yr legume fallow
Multistrata agroforests
(cupuaçú pupunha
castanha)
Coffee rubber
Coffee fast-growing
timber
Natural forests
Logged forests
Extractive reserves
Community-managed
forests
None
Forests
Complex agroforests
Brazil
Meta–Land
Use System
Melon and mixed food
crop, 15-yr fallow
Mixed food crop, 4-yr
bush fallow
Mixed food crop, 4-yr
Chromolaena fallow
None
None
Cocoa agroforests (jungle
cocoa)
Oil palm plantations
Natural forests
Logged forests
Community-managed
forests
Cameroon
Upland rice, 10-yr bush
fallow
Mixed food crops, 5-yr
bush fallow
Cassava, 2-yr Imperata
fallow
Cassava
Imperata grasslands
Rubber agroforests (jungle
rubber)
Oil palm plantations
Rubber monoculture
plantations
Pulpwood plantations
Natural forests
Logged forests
Community-managed
forests
Indonesia
Degraded
pasturesImproved
pastures
Upland rice,
cassava, short
fallows
Peach palm
Bolaina
Capirona
Bora system
Natural forests
Logged forests
Extractive reserves
Peru
Table 1.2 Meta–Land Use Systems and Candidate Best-Bet Alternative Systems (with Some Worst Bets) at Each Benchmark Site
Cabbages
Imperata grasslands
Upland rice, barley,
ginger, short fallows
Tea agroforests
(jungle tea)
Fruit orchards
Natural forests
Logged forests
Communityprotected forests
Thailand
20
The Problem and Approach
longer cycles. Alternatively, agroforests can be managed with gap replanting that eliminates the need for subsequent slash-and-burn cycles. In either case, such agroforests,
composed of hundreds of small plots managed by individual families, occupy large
contiguous areas in Sumatra and can be mistaken for forests to the untrained eye.
Biophysical scientists have documented the high productivity and ecosystem services
provided by these agroforests (Michon and de Foresta 1996; Michon 1997). Plant
diversity in the mature complex agroforests is on the order of 300 species/ha, which
approximates that of adjacent undisturbed forests (420 plant species/ha). The richness
of bird species in mature agroforests is approximately 50 percent that of the original
rainforest, and almost all mammal species are present in the agroforest (Foresta and
Michon 1994). The villagers in Krui, Lampung Province, who make a living from
these complex agroforests, have an obviously higher standard of living than those
neighbors who grow only food crops (Bouamrane 1996).
Complex agroforests based on cacao (Theobroma cacao [Linn.]) as the major cash
crop have been developed in humid forest margins of West Africa over the past century (Duguma et al. 2001; chapter 14, this volume). Jungle tea (Camellia sinensis [L.]
Kuntze) complex agroforests occur in North Thailand, where the naturally occurring
tea trees are left when the forest is cleared and fruit trees are interplanted (chapter 16,
this volume). Jungle rubber is a complex agroforest occupying 3 million ha where
most of the rubber is produced in Indonesia (chapter 9, this volume). Indigenous Bora
communities of the Peruvian Amazon establish complex agroforests by interplanting
trees in upland rice and cassava crops (Padoch and de Jong 1987). Economic trees
include peach palm (Bactris gasipaes Kunth) for fruits and heart of palm, Inga spp.
for fruits and firewood, arazá (Eugenia stipitata McVaugh) for fruit, and timber trees
such as mahogany (Swietenia macrophylla King) and tornillo (Cedrelinga cataeniformis
Ducke).
Simple Agroforestry Systems and Intensive Tree Crop Systems
Simple agroforestry systems usually contain fewer than five economic plant species,
whereas tree crop plantations include only one. Both systems may include a leguminous crop cover. These systems are common in many parts of the humid tropics, particularly where infrastructure is well developed. Nevertheless, most of these start with
slash-and-burn, in some cases followed by food crops interplanted with tree seedlings.
Intensive tree crop systems include the classic monoculture plantations such as oil
palm and rubber, timber plantations such as pine (Pinus spp.), Eucalyptus spp., and
cypress (Cupressus spp.), and fast-growing pulpwood plantations such as Acacia mangium and albizia (Paraserianthes falcataria [L.] I. Nielsen). These systems can be vast
and run by corporations or run by individual smallholder farmers.
Simple agroforestry systems have less plant diversity than complex agroforests,
higher levels of management are needed, and the regeneration of forest species is
restricted. Included in this category are shade coffee, cacao, and coconut plantations
found throughout the humid tropics and the peach palm–based systems in Latin
America. A slightly more diverse system based on peach palm, Brazil nut (Bertholletia
Alternatives to Slash and Burn
21
excelsa), and cupuaçú (Theobroma grandiflorum [Willd. ex Spreng.] Schum) has been
developed at the western Brazilian Amazon site (chapter 12, this volume).
Food Crop–Fallow Rotations
Traditional shifting cultivation with long-term fallows was only found in the southern
reaches of the Cameroon benchmark site and is absent in or disappearing from the
other sites. Fallows of 10 years or less are more common at the other sites and include
either natural secondary forest fallows or managed fallows (Sanchez 1999). In the
northern parts of the Cameroon benchmark site, shortening of the fallow period has
resulted in the invasion and dominance of the bush Chromolaena odorata (L.) R.M.
King and H. Robinson, a member of the Asteraceae family.
Improved or managed fallows, where trees are planted into the fallow, are now being
tried in some of the benchmark sites. The planted trees often are nitrogen-fixing legumes
that restore soil fertility more rapidly and include Inga edulis Mart. in Brazil and Peru
or Calliandra calothyrsus Meissner in Cameroon. Deliberately planted fallows of Tithonia diversifolia (Hemsl.) Gray, another Asteraceae, are commonly found in the uplands
of Southeast Asia, practiced by indigenous communities (Cairns and Garrity 1999).
Improved fallows using leguminous cover crops kept in the field for less than 2 years
occur in Peru and include kudzu (Pueraria phaseoloides [Roxb.] Benth) (Sanchez and
Benites 1987), Mucuna spp., and Centrosema macrocarpum Benth. (Palm et al. 2002a).
Continuous Food Crop Production
Continuous cropping is found in valley bottoms as irrigated paddy rice (Oryza sativa
L.) in Indonesia, Peru, and Thailand, but because it is so well established and is rarely
associated with slash-and-burn and deforestation it was not included in the analysis
by asb (except in Thailand). In Cameroon and Thailand, intensive horticulture with
high rates of use of mineral fertilizers and pesticides forms an important option near
the large urban centers of Yaoundé and Chiang Mai. Cassava is grown continuously
in the Lampung area of the Indonesian benchmark site, particularly on transmigration
settlement sites, and often eventually degrades through invasion by Imperata cylindrica
into landscape patches or large grasslands.
Pastures and Grassland Systems
Pastures for beef production dominate the deforested landscape in the Brazilian and
Peruvian benchmark sites. These include traditional, extensive pasture systems that
degrade within a decade or so, as well as more intensive grazing systems with improved
grass species (Brachiaria humidicola [Rendle] Schweick; B. brizantha [Hochst.] Stapf )
often mixed with pasture legumes such as Pueraria phaseoloides, Desmodium ovalifolium Wall, Arachis pintoi Krap. & Greg., and others (Serrão et al. 1979; Serrão and
Toledo, 1990). The pasture species are tolerant to aluminum toxicity and are normally
planted into a preceding crop of upland rice or maize (Zea mays L.). In parts of Brazil,
these pastures are rejuvenated by burning, plowing, and fertilizing a maize crop to
which pastures are replanted.
22
The Problem and Approach
Extensive areas of Imperata cylindrica grasslands occur throughout Southeast
Asia and parts of West Africa. This species is known as alang-alang in Indonesia and cogon in the Philippines. These grasslands are dominant in the Lampung
area of the Indonesian benchmark site (Garrity 1997; chapter 11, this volume).
This coarse, unpalatable grass invades areas where the fallow cycle has been
shortened and is basically a degraded system. It is difficult to eradicate and is maintained by frequent fires. Fortunately Imperata cylindrica grasslands do not occur
in Latin America, where less invasive Imperata species exist and pose no major
problems.
These meta–land use categories were used to set up land use intensity transects
or chronosequences (see chapter 2, this volume) at several locations in each benchmark site where environmental, agronomic, and socioeconomic factors were evaluated
by standard protocols. Whenever and wherever possible the different measurements
were all taken from the same plot, farm, or location in the landscape. Natural forest
was considered the point of departure for all land uses, and grasslands, short-fallow
cultivation systems, and pastures were included as the other endpoint, representing
degraded conditions. The specific environmental, agronomic, and socioeconomic
measurements are described in the sections that follow.
Q ua n t i f ying Environmental, Agronomic,
a n d S o c ioeconomic Parameters
Climate Change
Tropical deforestation and land use change contribute as much as 25 percent of the
annual flux of carbon dioxide (CO2) to the atmosphere (ipcc 2001), yet there is
still much debate on this issue because of uncertainties in biomass estimates, rates of
deforestation, and land use change sequences (chapter 2, this volume). Changes in
carbon stocks and the associated sources or sinks of atmospheric CO2 and fluxes of
nitrous oxide (N2O) and methane (CH4), the three most important greenhouse gases,
were measured in the different land use systems at the Brazil, Cameroon, Indonesia,
and Peru benchmark sites. Whereas most previous studies have focused on measurements in the forest and grassland or continuous cropping systems—in other words,
the extremes—the dataset from asb, described in chapter 2, included measurements
from many of the tree-based systems that often dominate the landscape in the humid
tropics (Wood et al. 2000).
Carbon stocks in the above- and below-ground vegetation and in the top 20 cm of
the soil were estimated by a combination of allometric equations (for converting tree
diameters into biomass) and destructive harvest. The concept of the average amount
of carbon stored in each of the land use systems during the time course of the rotations, or time-averaged carbon, was used for comparing land use systems with different rotations times. The standardized methods for sampling are presented in Woomer
et al. (2000) and Woomer and Palm (1998), and those for calculating time-averaged
Alternatives to Slash and Burn
23
carbon are presented in chapter 2. Results are presented in Woomer et al. (2000),
Palm et al. (2002b), and chapter 2.
Estimating N2O and CH4 fluxes entails intensive, long-term sampling. This was
not possible at most of the asb sites. To obtain some estimates for annual fluxes and
seasonal patterns for the different land use systems, N2O and CH4 fluxes were measured monthly over the course of 2 years in the Indonesia and Peruvian benchmark
sites using static chamber techniques. The sampling protocol and results are detailed
in chapter 3 and in Ishizuka et al. (2002) and Palm et al. (2002a).
Biodiversity
Tropical forests contain two-thirds of the estimated 250,000 world’s terrestrial plant
species, 90 percent of world’s insects, and many bird species (Osborne 2000), making tropical deforestation a primary cause of global biodiversity loss (Heywood 1995;
Stork 1997). The extent of biodiversity loss associated with different land use systems
has seldom been considered, although many traditional land management strategies
have supported biodiversity maintenance (McNeely et al. 1995; McNeely and Scherr
2003). Diversity of the above-ground vegetation and below-ground biota were measured in the range of land use systems at the benchmark sites to address these issues.
Above-ground plant diversity was measured as the number of plant species occurring in transects in each land use type but also according to plant functional types
(pfts) (Gillison and Carpenter 1997). Assessing plant diversity in the tropics is timeconsuming and difficult, necessitating expertise in tropical plant identification and
classification. The functional analysis uses a combination of adaptive morphologic
or functional features (leaf size class, leaf inclination class, leaf form and type) and
enables rapid characterization by people with minimal training. It includes measures
of site physical features, vegetation structure, species composition, and pfts (Gillison
2001, 2002). Results from the benchmark sites are found in Gillison (2000) and in
chapter 4.
Assessing diversity of below-ground biota is even more complex than aboveground vegetation, partly because many of the species have never been identified but
also because sampling strategies that capture the spatial heterogeneity of the different
types of biota have not been developed. The asb below-ground biodiversity group
designed a prototype sampling strategy and focused on assessing the biodiversity of
certain functional groups of soil biota including macrofauna (earthworms, ants, and
termites), nematodes, arbuscular mycorrhizal fungi, and rhizobial microsymbionts.
Methods and results are presented in Swift and Bignell (2001) and in chapter 5.
Agronomic Sustainability
The majority of soils in the humid tropics are acid and have low native fertility (Sanchez 1976). Crops planted after slash-and-burn benefit from the nutrients in the ash,
24
The Problem and Approach
but rapid nutrient depletion takes place with successive nutrient removal in crop
harvests, nutrient leaching, runoff and erosion promoted by high rainfall, and rapid decomposition of soil organic matter after burning. Soil physical properties also
degrade with exposure caused by removal of the protective vegetation, and weeds
invade fields, both of which contribute to declining crop yields (Sanchez et al. 1987;
Juo and Manu, 1996). The long vegetative fallow characteristic of traditional shifting
cultivation restores soil physical properties, accumulates carbon and nutrients in the
fallow biomass, and eradicates weed populations. But as fallows shorten, their ability to perform these functions diminishes. The sustainability of the different land
use systems depends on the ability to maintain these vital ecosystem functions. A set
of measurements that could indicate the sustainability of the systems was developed
and includes soil structure and biological activity, nutrient balances and replacement
costs, and weeds, pests, and diseases. These criteria were assessed for the different land
use systems and then, based on expert judgment, translated into scales indicating the
relative degree of difficulty farmers would face in solving the problem (chapter 6, this
volume).
Household Economic and Social Concerns
Regardless of the global environmental benefits or agronomic sustainability of a land
use system, farmers cannot be expected to adopt it unless it contributes more to meeting household objectives, does not entail excessive risks, and is compatible with the
social and cultural norms of the community. The promotion of systems with greater
environmental benefits must specifically consider the profitability, labor needs, food
security, and equity issues associated with them, as well as the institutions needed.
Methods to assess these objectives, their social and institutional needs, and the
ability of farm households and communities to meet these needs were developed by
the asb consortium (Tomich et al. 1998a; Vosti et al. 2000) and used to assess the
alternative land uses within and across sites. Key parameters included profitability
(measured in terms of economic returns to land and labor), labor and capital needs
for establishing and maintaining land use systems, the potential contribution of given
land use systems to meet household food security needs, and market and nonmarket
institutional needs of specific land use systems. Detailed results of these studies for
Brazil, Cameroon, and Indonesia are found in Vosti et al. (2001), Gockowski et al.
(2001), and Tomich et al. (2001) and are summarized in chapter 17.
A n a ly z i ng Tradeoffs: The ASB Matrix
Land use at the humid forest margins is perceived by three general sets of beneficiaries. The global community is interested in saving tropical forests, increasing carbon
sequestration, reducing greenhouse gas emissions, and preserving plant and animal
Alternatives to Slash and Burn
25
biodiversity. Small-scale farmers are interested in household food security, property
rights, the profitability of their farms, and the institutions that support their goals.
National policymakers occupy intermediate positions and can be the key actors. In
1996, asb researchers developed a framework known as the asb matrix to help evaluate the local, national, and global impacts of the alternative land use systems and guide
their decisions (table 1.3; Tomich et al. 1998b).
The evaluation criteria include the environmental, agronomic, and socioeconomic impacts, previously described, for each of the land use options. The matrix puts
together the food and income functions with ecological functions (production, human
welfare, and environmental impacts) of each system, indicating the potential tradeoffs
between the perspectives and interests of different stakeholders. This framework is
intended for use in selecting from among the land use alternatives. The challenge is
for the multiple stakeholders to weigh tradeoffs between their varied objectives. The
notion of best-bet alternatives was introduced to indicate the systems that provide
the combination of environmental services, poverty level, and economic growth that
is most acceptable to society in the production (private) and environmental (global)
functions. Some advantages and limitations of the matrix are discussed in Vosti et al.
(2000) and Tomich et al. (1998b). The filled-in tradeoff matrices from the Brazil,
Cameroon, and Indonesia benchmark sites are reported in chapter 18.
The analysis of the resulting tradeoff matrix must be done with full participation
of the various stakeholders and is crucial for achieving a common understanding of
the different viewpoints, vested interests, and potential conflicts associated with the
different choices. An example of the types of tradeoffs is that between the carbon
stored in different land use systems and the private profitability realized from them.
This tradeoff at the Cameroon benchmark site is shown in chapter 18. There is no
win–win alternative system that combines maximum carbon stocks with maximum
farmer profitability. There is a lose–lose or worst-bet alternative: food crops followed
by short fallows. But there are two medium-carbon systems that have high levels of
farmer profitability: cacao–fruit tree complex agroforests and small-scale oil palm
plantations. These are the best-bet alternatives for minimizing the tradeoffs between
carbon sequestration and farmer profitability, and one can envision how policies or
programs could be established to promote these systems to replace the other systems
with low carbon and low profits (chapters 14 and 18, this volume).
R e s e a rc hing and Implementing Policies
Once the diverse stakeholders have decided which land use systems provide the desired
combination of production, human welfare, and environmental services, such as the
example just described, it is necessary to search for policy instruments that can balance
these tradeoffs and that will lead to a broad-based adoption of those desired systems.
Typically, there are few (if any) proven policy or institutional mechanisms to address
these environment–development tradeoffs. ASB has been involved with various part-
Carbon
Sequestration
(above-ground
time-averaged;
Mt/ha)
Biodiversity
(above-ground
plant species per
plot)
Global Environmental Concerns
Source: Modified from (1996).
Forests
Complex agroforests
Simple agroforests;
intensive tree crops
Crop–fallow rotations
Continuous annual crops
Grasslands, pastures
Meta–Land Use
Systems
Plot-Level
Production
Sustainability
(overall rating)
Agronomic
Sustainability
Potential
Profitability
(returns to land,
$/ha)
Employment
(average labor
input; d/ha/yr)
Smallholders’ Socioeconomic Concerns
Table 1.3 Matrix Comparing the Environmental, Agronomic, Socioeconomic, and Policy Aspects of the Alternative Land Use Systems
Production
Incentives at
Private Prices
(returns to labor;
$/d)
Policy and
Institutional Issues
Alternatives to Slash and Burn
27
ners in policy research at different levels, some of which are described in chapter 7 for
national and international policy arenas and chapters 10, 17, and 18 and the various
country chapters in part IV for the national and local policy levels.
A s s e s s i n g Impact and Providing F eedback
The last step in the asb research and development framework is the assessment of
the impacts of the options thus devised (figure 1.2). Although implementation of the
various land use alternatives that have been identified as best bets is still in progress, in
its first decade of existence the asb consortium has had impacts on scientific methods
and improved datasets, national research institutions, global forums concerned with
poverty, the environment, and deforestation in the tropics, and policymakers. At the
national scale, impacts are described for the benchmark sites in their respective chapters in this publication (chapter 12 for Brazil, chapter 13 for Indonesia, chapter 14 for
Cameroon, chapter 15 for Peru, and chapter 16 for Thailand) and globally in chapter
18. A summary follows.
Impact on Science
Perhaps the greatest impact on science has been the research process and framework
designed and implemented by asb. The research framework established the basis for
integrated natural resource management research of the cgiar centers (cifor 2000).
The asb matrix and tradeoff analysis provides a way to tackle complex problems and
reconcile the interests of different stakeholders. ASB has also shown how the disciplinary strengths in climate change, biodiversity, agronomy, policy reform, and adoption
can be used in a balanced and positive way, with combined, mutually accepted standard methods.
Other scientific contributions relate to improved methods of data collection and
analysis and include improved equations for estimating carbon in young and regrowing trees, where the original equations overestimated carbon by as much as 100 percent (Ketterings et al. 2001; chapter 2, this volume); refinement of the concept of
time-averaged carbon for comparing carbon stored in land use systems with different
rotation times (van Noordwijk et al. 1998); validation of the use of plant functional
attributes for above-ground biodiversity assessment (chapter 4, this volume); methods
for assessing below-ground soil biodiversity by the use of functional groups (Swift and
Bignell 2001); and the identification of agronomic sustainability indicators (chapter
6, this volume) which is a major advance in the concept of soil quality.
The asb has enriched the scientific literature substantially, particularly with articles written by national colleagues in international journals, with almost 450 publications by the end of 2003.
28
The Problem and Approach
Impact on National Institutions
The country chapters in part IV of this volume identify many of the effects of the
asb consortium on the collaborating national institutes including implementing the
cross-disciplinary research approach, moving much of the work away from experiment stations to farmer fields and communities, and developing meaningful dialogues
with policymakers. In addition, the “south–south” exchange between scientists and
policymakers visiting the asb sites has spurred the imagination of many, resulting
in the direct transfer of knowledge generated at one site to another. Such visits and
workshops, along with the publication efforts, have “internationalized” many national
partners, but this is an area in which a great deal of potential for impact remains to
be tapped.
Impact on Policymakers
Substantive and long-term interactions have developed between asb researchers and
national policymakers, based on the solid scientific foundation asb brings to the discussions. Chapter 18 and the country chapters in part IV describe much of this policy
research.
At the national level, work with the Indonesian Ministry of Forestry resulted in
a presidential decree that recognized the property rights of the people managing the
complex agroforests on government lands in Sumatra (Fay et al. 1998). ASB has also
worked with the Indonesian government to address the devastating forest fires associated with El Niño events. Suggestions include selective restrictions on burning during
El Niño events, monitoring and penalizing large companies that misuse fire to clear
land, recognizing long-standing land claims to help minimize conflicts over land allocation, reducing or eliminating policies that depress timber prices, and encouraging
people who clear land to sell excess wood rather than burn it. At the regional level asb
scientists have promoted enabling policies to support community-based forest management plots with the government of the State of Acre in Brazil and to provide credits
for on-farm reforestation with the Ucayali regional government in Peru.
Impacts on Global Organizations and Forums
ASB is now a systemwide program of the cgiar and an ngo accredited by the Global
Environment Facility. The asb network of well-characterized benchmark sites in the
world’s tropical moist forests has attracted the attention of other groups concerned
with the issues of poverty, the environment, and deforestation at the forest margins.
This includes the World Bank, the Asian Development Bank, the International Fund
for Agricultural Development (ifad), many bilateral donors, the Intergovernmental
Panel on Climate Change (ipcc), the Millennium Ecosystem Assessment, the Rain-
Alternatives to Slash and Burn
29
forest Challenge Partnership, and many others. Many of the approaches and results
are being mainstreamed as new projects emerge. The methods for assessing carbon
stocks and the improved estimates from the asb assessment have been recognized and
used by the ipcc (Paustian et al. 1997; ipcc 2001).
External Reviews
The asb consortium has been periodically evaluated by external teams (Eswaran
1995; Hansen et al. 1997; Technical Advisory Committee [tac] 2000). The review
by the Scientific and Technical Advisory Panel of the Global Environment Facility
considered asb “exceptional and pioneering in its design, coverage, methodology,
organization and scope for transferability and replicability” (Hansen et al. 1997:1).
According to tac (2000:xxi), “the Alternatives to Slash and Burn Programme has
gone further than others in relating its research sites to the whole area over which the
problem occurs, and in scaling up to the global level in its findings on tradeoffs. This
is very helpful for the global debate on sustainability issues.” These positive reviews
should be balanced with the real limitations of the asb consortium, including recurring funding shortfalls and the communication challenge of keeping culturally diverse
partners informed across the tropical belt.
The Way Forward
The first decade of the consortium was evaluated in 1999 at a conference in Chiang Mai on environmental services and land use change. Details of the findings and
recommendations are found in van Noordwijk et al. (2001b), Tomich et al. (2004),
and chapter 18, this volume. Two of the major gaps that were identified included the
assessment of hydrologic, ecological, and other environmental services at the watershed or community scale and methods for the various stakeholders to develop workable responses and monitor the impacts of ongoing change.
A range of flexible tools will be identified and developed for communities, local
government agencies, ngo activists, research managers, policymakers, and other
officials. Diverse stakeholders can then better explore their options to influence the
individual choices that really determine the rate and pattern of land use change (van
Noordwijk et al. 2001b).
C O N C LU SION
The asb consortium has contributed scientifically and from a policy perspective
to addressing the issues of poverty and deforestation in the humid tropics and has
complied with the two Agenda 21 recommendations that formed the reason for its
existence: “Limit and aim to halt destructive shifting cultivation by addressing the
30
The Problem and Approach
underlying social and ecological causes” and “Reduce damage to forests by promoting sustainable management of areas adjacent to the forests.” But tropical deforestation remains at alarming levels, and so do the poverty and harsh living conditions of
most forest margins dwellers. The challenge has been partially met, and the response
requires continuous hard work across the research–development continuum throughout the humid tropics. Latin American, African, and Asian scientists have learned how
to work together and have experienced first hand the benefits of cross-disciplinary and
interinstitutional collaboration, working with international scientists, farming communities, government policymakers, and leaders of international institutions, and are
equipped with the methods and partners to meet this continuing challenge.
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ii. t h e m at i c re s e a rc h
2
Carbon Losses and Sequestration with
Land Use Change in the Humid Tropics
Cheryl A. Palm
The Earth Institute at Columbia University Palisades, New York
Meine van Noordwijk
World Agroforestry Centre, Indonesia Bogor, Indonesia
Paul L. Woomer
Sacred Africa Nairobi, Kenya
Julio C. Alegre
World Agroforestry Centre, Peru Pucallpa, Peru
Luis Arévalo
World Agroforestry Centre, Peru Pucallpa, Peru
Carlos E. Castilla
Cenipalma, Bogatá, Colombia
Divonzil G. Cordeiro
Embrapa, Acre Rio Branco, Acre, Brazil
Kurniatun Hairiah
Brawijaya University Malang, Indonesia
Jean Kotto-Same
Institut de Recherche Agricole pour le Développement Yaoundé, Cameroon
Appolinaire Moukam
Deceased
William J. Parton
Colorado State University Fort Collins, Colorado
Auberto Ricse
Instituto Nacional de Investigacion Agraria Pucallpa, Peru
Vanda Rodrigues
Embrapa, Rondonia Porto Velho
Syukur M. Sitompul
Brawijaya University Malang, Indonesia
T
he role of tropical forests in the global carbon (C) cycle has been debated over
the past 20 years, as several estimates of the flux of carbon dioxide (CO2) from
42
Thematic Research
tropical deforestation have been proposed (Houghton et al. 1987; Detwiler and Hall
1988; Brown et al. 1993). Current estimates indicate that land use change in the tropics released 1.7 (0.6–2.5) Gt C/yr, compared with 5.4 ± 0.3 Gt C/yr from fossil fuel
emissions (ipcc 2001). This flux has been attributed primarily to deforestation in
the tropical zone, with Asia and Latin America accounting for more than 80 percent
of the flux (Houghton 1997). However, a recent analysis of the net carbon flux from
the Brazilian Amazon suggests that carbon sources created by deforestation are offset by carbon sinks from the undisturbed forest and regrowing secondary vegetation
(Houghton et al. 2000). As noted by DeFries et al. (1999), reducing the uncertainty
of estimates of CO2 emissions caused by land use change is key to balancing the global
carbon budget. Much of the uncertainty in the values of CO2 flux from the tropics is a
result of inadequate estimates for rates of different land use transitions, the biomass of
the vegetation that is cleared, the rates of regrowth, and levels of biomass recovery of
the subsequent land use systems. In particular there is little information on the carbon
stored and the potential to sequester carbon in many of the land use systems of the
humid tropics other than for continuous cropping and pasture systems, both of which
have low carbon storage potential. However, there is significant tree cover on deforested, agricultural, and abandoned land in the rainfed, or humid, tropics (Fearnside
and Guimaraes 1996; Houghton et al. 2000; Silver et al. 2000; Wood et al. 2000) that
could provide a potentially large sink for carbon.
One of the primary objectives of the Alternatives to Slash and Burn (asb) program
was to improve information on the carbon stored in the biomass of the vegetation and
soils during the various stages of the land use systems established after deforestation
in the humid tropics. Changes in carbon stocks associated with the different land use
systems combined with details on the time course of these changes during the land
use rotation are necessary to estimate the net carbon losses and sequestration potential
associated with these different land use conversions.
M E T H O DS
F i e l d Sa mpling
Above-ground (live trees and understory, dead vegetation, litter layer) and belowground (roots and soil to 20-cm depth) carbon stocks were measured in forests or
other land uses established after slash-and-burn clearing in the benchmark sites in Brazil (Pedro Peixoto and Theobroma), Cameroon (Yaoundé, M’Balmayo, and Ebolowa),
and Indonesia (Lampung and Jambi). The land uses sampled at each site together
made up a time course, or chronosequence, of land use change. In this type of sampling, called type II studies by Sanchez et al. (1985), the time courses of changes in
carbon stocks for different land use scenarios are reconstructed by sampling areas of
known but different ages. The preferred sampling method, a type I study, in which
the changes in carbon stocks are followed in a single plot through time, is impractical
Carbon Losses and Sequestration After Land Use Change 43
because of the long-term nature of these studies. In type II studies, in which space
substitutes for time, care must be taken to sample areas in a chronosequence that have
similar soil texture; if not, then differences in carbon stocks that are attributed to land
use change might actually be a result of differences in site characteristics that affect
carbon storage (Sanchez et al. 1985).
At each location in the benchmark sites, one or two land use chronosequences
were sampled. Each chronosequence included the meta–land use systems (chapter 1,
this volume) appropriate for each benchmark site. Natural or selectively logged forests
served as reference points for baseline data on initial carbon stocks for each chronosequence. The land use sequence was then represented by areas that had recently
been slashed, burned, and cropped combined with areas that included various stages
of the crop and fallow cycles; various ages of lands subsequently planted to pastures,
agroforests, or tree plantations; or stages of cropland and pasture degradation. The
management practices, age, and time course, including rotation time of each land
use system sampled, were obtained by interviewing the farmers. The land use systems
that were evaluated for carbon stocks in each of the benchmark sites are summarized
in table 2.1.
Above-ground and below-ground carbon stocks were measured for each land use
within the chronosequences according to standardized methods described in Woomer
and Palm (1998) and Woomer et al. (2000). Briefly, tree biomass was determined by
measuring diameter at breast height (dbh) for all trees with dbh greater than 2.5 cm in
five 4- by 25-m quadrats. Diameter was converted to tree biomass by use of the allometric equations for tropical moist forest trees in Brown et al. (1989) or fao (1997).
Understory biomass was determined by destructively harvesting and drying all
vegetation less than 2.5 cm dbh within two 1-m2 quadrats placed in each tree quadrat.
The biomass of the litter layer was determined by removing all surface litter from a
0.5- by 0.5-m quadrat placed in each understory plot. Roots were excavated and soil
carbon assessed in a minimum of four 0.2- by 0.2-m quadrats, for the 0- to 0.2-m
and 0.2- to 0.5-m soil depths, for each land use per chronosequence. Vegetation, root,
and litter biomass were all converted to carbon multiplying by a factor of 0.45. As
discussed later, root data were ignored because of their variability.
C a lc u l at ing Time-Averaged Above-Ground C arbon
S to c k s a nd Net C arbon Loss or Sequestration
The carbon stocks of the different land use systems at the asb sites are presented
in Kotto-Same et al. (1997), Fujisaka et al. (1998), and Tomich et al. (1998) and
summarized in Woomer et al. (2000). In this chapter, that information was used to
calculate the above-ground time-averaged carbon for the different land use systems.
The carbon loss or sequestration potential of a land use system is determined not by
the maximum carbon stock of the system or the stocks at any one point in time but,
rather, by the average carbon stored in that land use system during its rotation time
Table 2.1 Details of the Major Components and Management of the Different Land Use
Systems Evaluated for Above-Ground Time-Averaged Carbon for the Different Benchmark
Areas
Brazil
Pastures: both extensive and intensive (grass–legume mixtures)
Simple agroforests (single tree crop systems): monoculture coffee plantations (1000 plants/ha),
assuming a 7-yr establishment phase plus 5 more years of production for a total rotation time of 12 yr
Simple agroforestry systems (includes three systems: coffee [Coffea canephora Pierre ex Froehner]
rubber [Hevea brasiliensis (Willd. ex A. Juss.) Muell.-Arg.], coffee bandarra (Schizolobium
amazonicum Huber ex Ducke); and cupuaçú [Theobroma grandiflorum (Willd. ex Spreng.) Schum]
pupunha (Bactris gasipaes Kunth) castanha [Bertholletia excelsa Humb. & Bonpl.]), with an
establishment phase of 12 yr and rotation time of 20 yr
Crop–short fallow systems: annual crop–fallow cycles with 3 yr of cropping and 5 yr of natural bush
fallow
Crop–short improved fallow systems: annual crop–improved tree fallow with inga (Inga edulis Mart.) or
senna (Senna reticulata [Willd.] H. Irwin and Barneby) cycles with 3 yr of cropping and 5 yr of fallow
Cameroon
Crop–Chromolaena fallow systems: 2 yr of annual cropping followed by 4 yr of Chromolaena odorata
(L.) R.M. King and H. Robinson fallow
Crop–short fallow system: 2 yr of cropping followed by 9 yr of secondary forest fallow
Crop–long fallow system: 2 yr of cropping followed by 23 yr of secondary forest fallow
Complex agroforests: 2 yr of cropping followed by establishment of Theobroma cacao (jungle cacao)
with a 25-yr establishment phase and 40-yr rotation
Complex agroforests: a permanent, nonrotational cacao system established through gap and understory
plantings of cacao
Simple agroforests (single tree crop system): 1 yr of cropping followed by establishment of an oil palm
plantation with 146 trees/ha with a 7-yr establishment phase and a 25-yr rotation
Indonesia
Complex agroforests: 2 yr of annual cropping followed by establishment of a rubber plantation (jungle
rubber) with a 25-yr establishment phase and 30-yr rotation time
Complex agroforests: a nonrotational, permanent rubber agroforestry system established through
understory and gap plantings
Simple agroforests (intensive tree crop systems): establishment of an industrial oil palm plantation with
120 trees/ha and an establishment phase of 7 yr and rotation time of 25 yr
Simple agroforests (single tree crop system): establishment of an industrial timber plantation of a single
fast-growing tree (Paraserianthes falcataria, Eucalyptus sp., Acacia mangium) with a rotation time of
8 yr
Crop–fallow rotation: 7 yr of cassava followed by 3 yr of Imperata cylindrica (L.) Beauv grassland
Carbon Losses and Sequestration After Land Use Change 45
(icraf 1996). This quantity is referred to here as the time-averaged carbon stock and
is similar to the average carbon storage method described in the Intergovernmental
Panel on Climate Change (ipcc) Special Report on Land Use, Land-Use Change
and Forestry (Watson et al. 2000). The time-averaged carbon takes into account the
dynamics of systems that include tree regrowth and harvesting and allows the comparison of land use systems that have different tree growth and harvesting rotation
times and patterns.
The time-averaged carbon stock depends on the carbon accumulation rates, the
maximum and minimum carbon stored in the system during a full rotation, the time
it takes to reach maximum carbon, and the rotation time of the system (figure 2.1).
Carbon accumulation rates (Ic), in tons of carbon per hectare per year, for aboveground vegetation regrowth were calculated as the carbon stock value of the sampled
vegetation (Cs) divided by the age (Ts) of the vegetation (icraf 1996). Average carbon accumulation rates were obtained for each land use system in each country from
the individual rates for the replicate chronosequences. It is assumed that the carbon
increase rates (Ic) are linear throughout the time period of vegetation regrowth after
clearing (Tf). This appears to hold at least for the first 20 years (Brown and Lugo 1990;
Fearnside and Guimaraes 1996). The maximum carbon stored in fallows (Cm) at the
time of clearing (Tf) is calculated as Cm = Ic × Tf. The time-averaged carbon stock for
a crop–fallow system that has negligible carbon stored in a short cropping phase is
essentially the carbon stored in the fallow vegetation at the time of reclearing (Cm)
divided by 2, or the carbon accumulation rate (Ic) times the years of fallow (Tf) divided
by 2 (figure 2.1a). For tree crop plantations or some agroforestry systems, however,
the maximum carbon stock (Cmax) may be reached at a time (Tmax) before the end of
the rotation (Tr). As an example, a coffee (Coffea spp.) plantation may reach the maximum carbon stock in 7 years (establishment phase), but production continues for an
additional 5 years (production phase), giving a rotation time (Tr) of 12 years, at which
time the plantation is cut and reestablished. The time-averaged carbon stock for such
land use systems is determined as the weighted average of the time-averaged carbon
stocks for the different phases of the rotation (figure 2.1b).
Details of the sites sampled, including location, land use categories, and age
since clearing and the above-ground and soil carbon stocks used for calculating timeaveraged carbon can be found in Palm et al. (2002).
Differences in above-ground carbon stocks between the forest and the aboveground time-averaged carbon of the different land use systems were used to calculate
the loss of carbon with the alternative slash-and-burn systems. Likewise the potential
for different land use systems to sequester carbon relative to other systems was determined by pairwise comparisons of their time-averaged carbon.
B e low - G round C arbon
The time-averaged comparison just described was calculated only for the above-ground
carbon stocks because the root and soil data were extremely variable and consistent
Figure 2.1 Schematic of the changes in carbon stocks and means for calculating time-averaged carbon
stocks after forest clearing and establishment of (a) crop–fallow systems and (b) tree plantations.
Carbon Losses and Sequestration After Land Use Change 47
time trends did not emerge that are needed for such calculations. The root data in
particular were not useful in making comparisons between land use systems because
few significant differences emerged between land use systems.
The soil data were also variable within chronosequences, partially because of
textural differences in the soils of the chronosequence sampled at each site, despite
attempts to sample similar soils. To account for the variability caused by differences
in soil texture within a site, the soil carbon data were normalized using equation 2.1,
developed by van Noordwijk et al. (1997) for estimating the soil carbon equilibrium
values:
Calculated forest soil C = Cref = exp(1.333 + 0.00994 × % clay + 0.00699 × %
2.1
silt – 0.156 × pHKCl).
The equation was derived with soil carbon data from Sumatra to estimate equilibrium topsoil carbon values for undisturbed forest systems. This Cref value referred to
the carbon content of the topsoil as identified in the soil survey data, with a variable
depth but generally between 0–5 and 0–10 cm. Another equation developed by van
Noordwijk et al. (2000) provides a means for standardizing soil carbon according to
variable sampling depths. Equation 2.2, developed from soil data from Jambi Province, Indonesia, shows a relationship between soil carbon content and soil depth in
the top 100 cm:
%C = 8.38 Z–0.58(R2 = 0.86),
2.2
where Z is the midpoint of the soil-sampling depth.
By integrating this equation over the sampling depth, we obtain a correction factor:
Cref(Z2) = Cref(Z1) × (Z2/Z1)–0.58,
2.3
where Z2 and Z1 are the midpoint of the sampling depth of a specific sample and
the sampling depth, 7 cm, that was used to establish the initial Cref equation, respectively.
The calculated Cref values, corrected for texture and sampling depth, for each land
use per site were then compared with the actual carbon measured (Cact) to give a relative carbon value (Crel) = Cact/Cref. The Crel values indicated the soil carbon in the land
use system relative to that expected from a forest system on a similar soil type. The
Crel of a forest soil should be 1 if the equation is appropriate for that location and the
sampling depth is similar to that used in deriving the equation. The Crel of soils from
the different land use systems was then used to estimate the gain or loss of soil carbon
relative to that of the forest, with a Crel less than 1 indicating a loss of soil carbon.
An approximation of a time-averaged carbon for the soil over the rotation could
then be calculated in a manner similar to that for above-ground carbon. The time-
Complex
agroforests
Cacao
Rubber
Cameroon
Indonesia
Brazil
Bush fallow, 9.5 yr
Chromolaena
fallow, 4 yr
Short fallow, 5 yr
Improved fallow,
5 yr
fallow
Shifting
cultivation, 23-yr
5
4
7
Cameroon
Indonesia
Cameroon
Crop–fallow
rotations
4
Brazil
Managed and
logged forests
4
5
3
5
6
2
Indonesia
Undisturbed
forest
89.2 (39.8)
88.7 (31.6)
15.4 (9.43)
13.7 (2.51)
64.1(18.8)
5.78 (2.76)
228 (27)
93.2 (41.3)
131 (37)
148 (19)
306 (99)
C/ha (SD)
of Sample
Plots, in t
Replicates Average
Carbon Stock
Country and Specific
Land Use
Meta–Land
Use Systems
NA
NA
4 (4.0)
2 (0)
9.6 (0.9)
2
?
?
18.5 (4.2)
?
100
in yr (SD)
NA
NA
3.91 (1.66)
6.86 (1.26)
6.68 (1.76)
2.89 (1.38)
NA
NA
7.26 (2.02)
NA
NA
Rate, 100 t
C/ha/yr (SD)
Average Age of Carbon
Sample Plots, Accumulation
NA
NA
5
5
9
4
NA
NA
25
NA
NA
Carbon
(yr)
Age at
Maximum
NA
NA
8
8
11
6
NA
NA
25
NA
NA
(yr)
Rotation
Time of
Land Use
System
89.2 (49.4–129)
88.7 (57.2–120)
19.6 (1.2–28.4)
34.3 (28.0–40.6)
56.2 (44.3–76.0)
11.6 (6.04–17.1)
228 (221–255)
93.2 (51.9–134)
167 (120–213)
148 (129–149)
306 (207–405)
89.2 (49.4–129)
88.7 (57.2–120)
6.86 (4.27–9.61)
11.5 (9.50–13.4)
28.1 (22.1–38.1)
4.52 (2.6–6.38)
228 (221–255)
93.2 (51.9–134)
77.0 (60.2–107)
148 (129–149)
306 (207–405)
(t C/ha)b
Maximum Carbon Time-Averaged
Stock
Above-Ground
(t C/ha)a
Carbon of Land
Use System
Table 2.2 Average Above-Ground Carbon Stocks (standard deviation) and Age of the Land Use Systems Sampled at the Benchmark Areas and the
Calculated Carbon Accumulation Rates, Maximum Carbon Stock, and Land Use System Time-Averaged Carbon Stock
3
1
2
4
3
11
Multistrata system
Oil palm
Pulp trees
Extensive pastures
Intensive pastures
Cassava–Imperata
Brazil
Cameroon
Indonesia
Brazil
Indonesia
3
4
5
4
Coffee
monoculture
Rubber
Cacao
Rubber
Indonesia
Cameroon
Indonesia
5
3
5
6
7
Brazil
Cacao
Bush fallow, 9.5 yr
Chromolaena
fallow, 4 yr
Short fallow, 5 yr
Improved fallow,
5 yr
fallow
Shifting
cultivation, 23-yr
Cameroon
Brazil
Cameroon
6.04 (1.91)
2.05 (0.98)
70.5 (24.3)
42.2
22.0 (1.91)
5.70 (3.43)
15.0 (2.66)
89.2 (39.8)
88.7 (31.6)
89.2 (39.8)
88.7 (31.6)
15.4 (9.43)
13.7 (2.51)
64.1(18.8)
5.78 (2.76)
131 (37)
10 (3.6)
—
10 (5.2)
15
2.5 (2.1)
11 (1.0)
8 (2.31)
NA
25 (0)
30
NA
4 (4.0)
2 (0)
9.6 (0.9)
2
18.5 (4.2)
—
—
7.26 (1.63)
6.03
9.29 (3.39)
—
2.14 (0.38)
NA
3.55 (1.26)
3.57 (1.59)
NA
3.91 (1.66)
6.86 (1.26)
6.68 (1.76)
2.89 (1.38)
7.26 (2.02)
—
—
12
7
8
—
7
NA
25
25
NA
5
5
9
4
25
8
10
20
25
8
8
12
NA
40
30
NA
8
8
11
6
25
b
a
The range is given in parentheses and was determined by multiplying the age at maximum carbon by 1 SD of the carbon accumulation rate.
The range was obtained by inserting the range in values for the maximum carbon into the equations for calculating Cta.
Grasslands and
crops
Simple
agroforests and
intensive tree
crops
Complex
agroforests
Crop–fallow
rotations
—
1.97
87.1 (67.6–106.7)
42.2
74.3 (47.2–101)
—
15.0
89.2 (49.4–129)
88.7 (57.2–120)
89.2 (49.4–129)
88.7 (57.2–120)
19.6 (1.2–28.4)
34.3 (28.0–40.6)
56.2 (44.3–76.0)
11.6 (6.04–17.1)
167 (120–213)
3.06
2
61.2 (47.5–74.7)
36.4
37.2 (23.6–50.7)
2.85
11.0 (8.73–12.5)
89.2 (49.4–129)
61 (40–83)
46.2 (28.9–75.2)
88.7 (57.2–120)
6.86 (4.27–9.61)
11.5 (9.50–13.4)
28.1 (22.1–38.1)
4.52 (2.6–6.38)
77.0 (60.2–107)
50
Thematic Research
averaged calculations for soil carbon are complicated by the pattern of carbon loss and
recovery for soil, which shows a time lag relative to that of the recovery of vegetation.
There is typically a loss of 10 to 40 percent of the topsoil carbon the first 2 to 5 years
after clearing of forests or fallows, with the percentage loss depending on several factors that influence the amount of organic materials returned to the soil. After the loss
phase, there is recovery of soil carbon to a level depending on the land use management and rotation times (Szott and Palm 1986; Sommer et al. 2000). For purposes
of this study, because there was insufficient detail of the pattern and time course of
soil carbon for the different land use systems, the time-averaged topsoil carbon was
assumed to simply be that at the end of the rotation indicated in table 2.2. These estimates do not include the temporary loss of soil carbon after fallow clearing and thus
would be slight overestimates.
M o d e l i ng C arbon D ynamics with Land Use Change
Obtaining more accurate values of carbon stocks, rates of carbon accumulation, and
the time course of changes in carbon stocks in tropical land use systems is essential for
improving our understanding of the role of tropical land use in the global carbon budget. Yet obtaining this information is extremely time consuming and costly. Once sufficient data have been collected, they can be used to parameterize and validate models
that simulate changes in carbon with land use change. Version 4.0 of the century
model is well suited for the purposes of simulating carbon changes with land use in
the asb program because it includes the growth of trees and crops and the complex
management practices used in tropical agroecosystems (Metherell et al. 1993). The
century model is a generic plant–soil ecosystem model that has been used to simulate carbon, nitrogen, and phosphorus dynamics of natural and managed ecosystems.
Once tested and validated for the different soils, climates, crops and trees of the asb
benchmark sites, the century model can be used to explore the productivity and
carbon losses and sequestration potential of land use alternatives beyond the time
frame possible from direct field experimentation and for additional land use systems.
Soil, climate, and land use management data, including clearing and burning,
crop type, and sequencing, were used to simulate the pulpwood plantations and
cassava–Imperata land uses in Indonesia (Sitompul et al. 1996) and conversion from
traditional slash-and-burn to tree-based systems in Cameroon (Woomer et al. 2000).
R E S U LTS AND DISCUSSION
Ti m e - Averaged Above-Groun d C arbon
The above-ground carbon stocks in the forest systems differed between sites; the highest, with more than 300 t C/ha, was reported for the natural or undisturbed forests
Carbon Losses and Sequestration After Land Use Change 51
of Indonesia (table 2.2). There were no measurements of natural undisturbed forests
at the other sites because they were not found near the study areas. The decreasing
above-ground carbon in the managed or logged forests, from a high of 228 t C/ha in
Cameroon to a low of 93 t C/ha in Indonesia, reflected varying extraction intensities
from a few boles per hectare by the local farmers in Cameroon and Brazil to large-scale
extraction by commercial loggers in Indonesia. The values for above-ground carbon
in selectively logged forests in Indonesia and Brazil are similar to values reported by
fao (1997). The average value for Brazilian forests fell into the lower estimates used
by Houghton et al. (2000) for calculating net CO2 fluxes from the area. The values for
the logged forest of Cameroon and the undisturbed forest of Indonesia were higher
than the few values reported by fao (1997). Increasing the fao values by 20 to 30
percent to account for understory vegetation, trees with dbh less than 10 cm, and the
litter layer (Sandra Brown, pers. comm. 1998) may account for the tendency of higher
biomass values obtained with the asb method.
Slash-and-burn clearing generally is from logged or secondary forests and not
undisturbed forests (Fujisaka et al. 1998), so the current carbon losses from slash-andburn would be lower than if undisturbed forests were cleared. The carbon of logged
forests therefore was used as reference point with which other systems were compared.
The least intensive of the land use systems, the permanent cacao or rubber agroforests
of Cameroon and Indonesia, had maximum and time-averaged carbon stocks of 90
t C/ha, or 40 to 100 percent of the logged forests, respectively. There was a further
drop to about 50 t C/ha time-averaged carbon for the rotational, complex cacao and
rubber agroforests of Cameroon and Indonesia, representing 22 and 54 percent of
the carbon of the logged forests, respectively. The time-averaged carbon of the other
rotational, more intensively managed tree-based systems depends on a variety of factors, including planting densities, rotation time, and management factors. The values
ranged from a high of 60 t C/ha for the multistrata fruit tree complex agroforests in
Brazil to a low of 11 t C/ha in monoculture coffee plantations. The time-averaged carbon of an oil palm plantation in Cameroon was about half that of the cacao complex
agroforestry system.
The more intensively managed tree plantation systems do not necessarily have
lower time-averaged carbon stocks than the simple agroforestry systems such as the
coffee- and oil palm–based ones. As an example, the Acacia mangium Willd. or Paraserianthes falcataria (L.) I. Nielsen (now called Falcataria moluccana [Miq.] Barneby and
Grimes) pulp plantations in Indonesia attained a lower maximum carbon stock (74 t
C/ha) than complex rubber agroforests (90 t C/ha), but the faster carbon accumulation rates of almost 9 t C/ha/yr compared with 3.5 t C/ha/yr result in similar timeaveraged carbon stocks of 40 t C/ha. This emphasizes the importance of regrowth
rates and rotation times in time-averaged carbon stocks.
The time-averaged carbon stock of the traditional, long-fallow shifting cultivation
still practiced in parts of Cameroon was almost 80 t C/ha. Intensifying the cropping
system by shortening the fallow period in Cameroon reduced time-averaged carbon
stocks to 28 and 5 t C/ha for systems with 9- and 4-year fallows, respectively. In Brazil,
52
Thematic Research
the time-averaged carbon stock of the 5-year natural fallow was 7 t C/ha (5 percent
of the forest); the value increased to only 12 t C/ha for improved fallows planted with
Inga or Senna trees but with similar rotation times.
Eventual conversion of deforested land to pastures or continuous cropping systems reduced time-averaged carbon stocks to only about 3 t C/ha, 2 percent that of
the logged forest. The average rotation time of a pasture is 8 to 10 years before reestablishment. Intensifying pastures through management or introduction of legumes
increased the above-ground carbon by less than 1 C/ha above the traditional pasture
systems. Similarly, the cassava–Imperata systems in Indonesia had time-averaged carbon stocks of only 2 t C/ha.
Above-ground carbon accumulation rates differed between the meta–land use system categories (table 2.2). Rates were highest, up to 9.3 t C/ha/yr, in the intensive tree
crop systems and simple agroforests. The exception to this was coffee monocultures,
which had a low accumulation rate of 2.1 t C/ha/yr, a result of the low planting density
and intensive pruning. Crop–fallow successions had lower carbon accumulation rates,
averaging 3 t C/ha/yr and 7 t C/ha/yr for the short- and long-term natural secondary
fallows, respectively. The improved tree fallows in Brazil had a higher carbon accumulation rate of 7 t C/ha/yr, compared with 4 t C/ha/yr for the natural tree fallow of the
same rotation time. The chromolaena (Chromolaena odorata [L.] R.M. King and H.
Robinson) fallow in Cameroon had the lowest accumulation rate, probably because
of arrested succession caused by the aggressive cover of the low-biomass chromolaena
plants. The complex cacao and rubber agroforestry systems had carbon accumulation
rates about half that of the natural fallows, probably from selective slashing and thinning of understory vegetation to reduce competition with the tree cash crops.
There are few data with which to compare the asb carbon stock and regrowth
rates of the fallows, tree crop plantations, and agroforestry systems. Houghton et al.
(1993) reported time-averaged carbon values of 50 to 100 t C/ha for agroforestry
systems and plantations. These values, in general, are higher than those measured in
the asb systems.
The regrowth rates of the natural fallows estimated for the asb systems are in the
upper range reported in other studies (Uhl et al. 1988; Szott et al. 1994; Fearnside and
Guimaraes 1996; Houghton et al. 2000; Silver et al. 2000). The lower regrowth rates
are generally found after pasture, rather than crop, abandonment (Uhl et al. 1988;
Fearnside and Guimaraes 1996); most of the asb fallow systems followed cropping,
which could partly explain the high regrowth rates.
The asb dataset allows comparisons of carbon stocks and time-averaged carbon
values between meta–land use systems and between sites. Some caution must be taken
regarding the precision and accuracy of these estimates. There are several steps in
which errors can affect the estimates, including the plot size used for estimating biomass of large trees (Brown et al. 1995), the allometric equations used for estimating
tree biomass (Ketterings et al. 2001), an insufficient number of replicates for some
of the land use systems, and inaccurate ages of plots and rotation times. The carbon
estimates for some of the tree plantations and agroforestry systems were obtained from
Carbon Losses and Sequestration After Land Use Change 53
only two replicates, and the ages at which maximum biomass is attained and rotation
times for some of the land use systems were sometimes informed guesses. Further
sampling and time course delineation may improve estimates of carbon stocks and
time-averaged carbon in some of these tree-based systems.
One of the factors that could introduce the largest errors in carbon stock estimates
is the choice of allometric equations used for estimating tree biomass. The equation
used for estimating tree biomass for the asb sites was developed primarily from old
age forest stands and for trees with diameters greater than 10 or even 25 cm (Brown
et al. 1989). Most of the nonforest, tree-based systems in the asb site were younger
than 20 years, and the majority of trees had diameters less than 25 cm. New allometric equations have since been developed from young secondary forests and fallows in
Indonesia (Ketterings et al. 2001) that result in biomass estimates half those obtained
from the equation of Brown et al. (1989). The main factors influencing the tree biomass were the height of the trees and the wood density. Several other recent studies
have shown a wide range in allometric equations for both primary and secondary
forests in the humid tropics of Brazil (Alves et al. 1997; Araújo et al. 1999; Nelson
et al. 1999). Such a wide range in carbon estimates for trees stresses the difficulty in
assessing vegetation biomass. It does, at least, set an upper (Brown et al. 1989) and
lower limit (Ketterings et al. 2001) to these estimates. Further testing and application
of the new allometric equations will assist in reducing the uncertainty in carbon stocks
and fluxes particularly for the younger fallow and tree-based systems.
B e low - G round C arbon
As mentioned previously, the root biomass data were extremely variable and did not
indicate differences between the land use systems. Apparently the excavation method
used did not adequately sample large roots, so the values for roots in forests and other
tree-based systems were underestimates. These data are not included in the results
and will not be discussed. A means for estimating roots through the time course of
regrowth of tree-based systems could be to use the root-to-shoot ratios of 0.42 for
5-year regrowth and 0.20 for 20-year secondary regrowth obtained by Fearnside and
Guimaraes (1996). Basically this would show that including roots from tree-based
systems would magnify the differences in carbon stocks between the land use systems
already reported for above-ground vegetation. The case of pasture systems may be
quite different, as discussed later in this chapter.
The baseline topsoil (0–20 cm) carbon stocks in the forest systems ranged from
45 to 50 t C/ha in Indonesia and Cameroon and were 35 t C/ha in the Brazil forest
sites (table 2.3). Values for the logged forests in Indonesia did not differ from those of
the undisturbed forest sites. The baseline values for the asb sites are on the low end
compared with the range of 46 to 69 t C/ha reported by Detwiler (1986), assuming
that 45 percent of the carbon in a 1-m profile reported in his study is located in the
top 20 cm (Moraes et al. 1995). The values for the soils sampled at the benchmark
54
Thematic Research
sites in Brazil are exceptionally low when compared with the range reported by Moraes
et al. (1995) for undisturbed forests in the Amazon.
The soil carbon stocks for the other land use systems did not reflect the expected
trends, with some land use systems having higher topsoil carbon than the forest systems (table 2.3). Generally, land use systems on soils with higher clay content had
higher soil carbon, indicating that attempts at selecting land use systems on soils of
similar texture within a chronosequence were unsuccessful. The wide range in soil carbon losses results from variation in the length of time since clearing, the type of land
use, the soil type, and topsoil erosion. To correct for the differences in soil texture, the
Crel values of the different land use systems were used to indicate relative changes in
soil carbon (table 2.3).
Table 2.3 Actual Soil Carbon Values and Values Corrected According to Soil Texture (equation
1, van Noordwijk et al. 1997a) and Soil Sampling Depth (van Noordwijk et al. 2000) and the
Soil Carbon Stocks Measured for the Forest Systems and Corrected for the Land Use Systems
Sampled at Sites
Country and Land Use
(sampling depth, cm)
Cactual
(g/kg)
Cland use/Cforest
(uncorrected)
Creference
(g/kg)
Crelative
Cactual/Creference
Average Soil Carbon
Stock,a,b t C/ha
(SD)
1.78
1.52
0.96
1.12
1.70
1.00
0.85
0.54
0.63
0.96
1.82
1.91
1.52
1.54
1.95
0.98
0.80
0.63
0.73
0.87
35 (1.3)
28c
22c
26c
30c
1.56
1.47
1.72
1.49
1.62
1.00
0.94
1.10
0.96
1.04
1.62
1.43
1.65
2.30
1.53
0.97
1.03
1.04
0.65
1.06
45 (8.5)
46c
47c
39c
48c
1.01
1.21
1.91
1.12
1.54
1.09
0.76
1.00
1.20
1.89
1.11
1.52
1.08
0.75
1.00
1.09
1.59
1.11
1.90
1.64
1.59
1.01
1.11
1.20
1.01
0.81
0.66
0.48
48 (7.6)
49 (3.8)
54c
49c
39c
32c
23c
Brazil (0–20)
Forest
Agroforestry
Fallow
Pasture
Crop
Cameroon (0–20)
Forest
Jungle cacao
Fallow (8 yr)
Fallow (2 yr)
Crop
Indonesia (0–5)
Forest
Logged forest
Jungle rubber
Pulpwood plantation
Rubber plantation
Cassava
Imperata
Values for the forest systems are the measured values of soil carbon stocks of forest systems at the different
sites.
b
Calculated as the forest soil carbon stock Creference.
c
Indicates estimated time-averaged carbon for the topsoil.
a
Carbon Losses and Sequestration After Land Use Change 55
The Crel values for the forest systems in Brazil, Cameroon, and Indonesia were
remarkably close to 1.0 (table 2.3), indicating that the equation for normalizing soil
carbon for texture and sampling depth that was developed from soils in Indonesia
applies well to other humid tropical forest sites. The Crel index shows there was little
or no change in soil carbon for most the land use systems considered in Cameroon,
except for the 2-year fallows, which had 35 percent less soil carbon (table 2.3). This
drop is indicative of the changes that occur the first 2 to 5 years after forest or fallow
clearing, followed by a recovery of soil carbon as the fallow period increases. The lack
of change in topsoil carbon in the other systems is consistent with the low land use
intensity of this benchmark area. In contrast to Cameroon, topsoil carbon losses of 11
to 53 percent were found in the more intensive pastures and croplands in Brazil and
degraded grasslands and continuous cropping in Indonesia. In general, the tree-based
plantations and agroforestry systems lost less than 20 percent of the topsoil carbon,
and the complex rubber and cacao agroforests had levels of soil carbon similar to the
forests.
The relative soil carbon losses as calculated for the different land use systems are
similar to those reported by Detwiler (1986) in a review of soil carbon changes with
land use change in the humid tropics. Improved pasture management from the asb
sites in Brazil did not show an increase in the topsoil carbon compared with the traditional or degraded pastures, at least to levels that would be significant for carbon
sequestration. Fisher et al. (1994) found substantial amounts of carbon in the roots
and subsoil of improved pastures in the drier, subhumid savanna areas of Brazil. Subsoil carbon and roots were not measured in the asb plots, so there may actually be
some storage through improved pastures, although Nepstad et al. (1994) and Trumbore et al. (1995) found dramatic decreases in occurrence of deep roots on conversion
of forest to pasture in the seasonal zone of the eastern Brazilian Amazon. Sommer et al.
(2000) found that the biomass of deep roots and root patterns with depth were similar
under forests and young secondary vegetation but substantially less under intensive
plantations. These differences in root profiles were accompanied by decreases of 25 to
50 percent carbon in the topsoil in the plantations and a reduction in carbon throughout the profile. These findings indicate that there are also large losses of soil carbon
at depth with the conversion of forest to other systems without deep rooting. More
root and subsoil carbon measurements are needed on a variety of land use systems in
different soil and climate regimes in the tropics to verify these findings.
M o d e l i n g Changes in C arbon Stocks with Changes
i n L a n d Use
CENTURY model simulations of the Paraserianthes pulpwood plantations and
cassava–Imperata systems in Indonesia agreed with the vegetation carbon stocks measured in the field for the tree plantation and the cassava–Imperata systems (figure
2.2) (Sitompul et al. 1996). However, the biomass carbon simulated for the primary
Figure 2.2 CENTURY model simulations and measured values of (a) biomass and (b) soil carbon changes on conversion of forest to Paraserianthes tree plantations or cassava–Imperata systems. Note the different y-axes for estimating carbon values in Paraserianthes and Imperata systems (Sitompul et al. 1996).
Carbon Losses and Sequestration After Land Use Change 57
forest is high by about 25 percent, indicating there may be a need for further model
parameterization and validation for the Indonesia site. The simulated topsoil soil carbon (figure 2.2) shows that the tree plantation maintains a steady-state level similar to
that of the forest; the blips are a result of the slash that is added and decomposes after
tree harvest. Field measurements also indicate little or no drop in soil carbon in the
plantations (table 2.3). However, the cassava–Imperata simulation shows a dramatic
and continuing decline in soil carbon, declining by 40 percent in 20 years, similar to
that from field measurements.
The simulations reported for Cameroon of the current traditional slash-and-burn
agriculture with a declining fallow phase and two alternative systems indicated a slight
overestimation of total system carbon (Woomer et al. 2000). The model simulated
350 t C/ha in the undisturbed forest, compared with a measured total system carbon
of 280 t C/ha for logged forests and 270 t/ha system carbon for a 20-year fallow compared with 210 t C/ha measured in those systems. Use of the model to simulate traditional slash-and-burn agriculture and an alternative land use that included soil conservation and retention of some of the larger trees showed increases in carbon stocks
compared with that of the traditional system, but the system carbon still declined
with decreasing fallow length but at a slower rate. These comparisons of measured
and simulated changes in carbon stocks with several land use systems found in the
humid tropics show that, with some minor adjustments, century Version 4.0 will
be useful for extrapolating and predicting carbon changes for a variety of alternative
land use systems.
C O N C LU SION
Carbon losses and potential carbon sequestration associated with the various land use
transitions can be estimated by combining information on the above-ground timeaveraged carbon and the relative soil carbon values for the different land use systems
(table 2.4, figure 2.3). In table 2.4 a net loss of carbon from the vegetation is considered a flux to the atmosphere and is indicated by a positive sign (+) with the values in
the table. Likewise, a net sink of carbon into the vegetation is indicated by a negative
sign (–).
The carbon losses from converting the natural forests to logged forests ranges
from a low of 80, in the case of Cameroon, to a high of 200 t C/ha for Indonesia,
assuming the carbon stock of the natural forests in all countries are similar to that of
Indonesia. There is little if any carbon loss from the topsoil (table 2.3). Further losses
from conversion of logged forests to other tree-based systems range from 40 to 190 t
C/ha above ground and 6 to 12 t C/ha from the soil. Eventual conversion of logged
forest to continuous cropping or pasture systems results in a net loss of 90 to 200 t
C/ha from the vegetation and 12 to 27 t C/ha from the topsoil. It is important to note
that these losses would be larger if roots were included in the calculations.
Primary
Forest
306
213
217
260
252
269
304
Logged
Forest
228
NA
151
139
167
192
190
222
Indonesia
Time-averaged C (t C/ha1)
Logged forest
Jungle rubber (permanent)
Jungle rubber (rotation)
Oil palm
Pulp plantation
Crop–Imperata
Cameroon
Time-averaged C (t C/ha1)
Forest
Shifting cultivation
Jungle cacao (permanent)
Jungle cacao (rotational)
Oil palm
Crop–bush fallow
Crop–Chromolaena
–151
NA
–12
16
41
39
71
77
Shifting
Cultivation
(long fallow)
4
47
39
56
91
NA
93
Logged Forest
–139
12
NA
28
53
51
83
89
Jungle Cacao
(permanent)
–4
NA
–43
–35
–52
–87
89
Jungle Rubber
(permanent)
–167
–16
–28
NA
25
23
55
61
Jungle Cacao
(rotational)
–47
–43
NA
–8
9
44
46
Jungle Rubber
(rotational)
–192
–41
–53
–25
NA
–2
30
36
Oil Palm
–39
–35
8
NA
17
52
54
Oil Palm
–190
–39
–51
–23
2
NA
32
38
Crop–Bush
Fallow
–56
–52
–9
–17
NA
35
37
Pulpwood
Plantation
–222
–71
–83
–55
–30
–32
NA
6
Crop–Chromalaena
Fallow
–91
–87
–44
–52
–35
NA
2
Crop–Imperata
Table 2.4 Carbon Sequestered (–t C/ha) or Lost () from Above-Ground Vegetation by Converting from One Land Use System (column) to Another Land
Use System (row)
NA
151
139
167
192
190
222
Logged
Forest
148
NA
87
137
137
141
145
Forest
Shifting cultivation
Jungle cacao (permanent)
Jungle cacao (rotational)
Oil palm
Crop–bush fallow
Crop–Chromolaena
Brazil
Time-averaged C (t C/ha1)
Forest
Multistrata agroforestry
Coffee
Crop–improved fallow
Crop–fallow
Pasture
–87
NA
50
50
54
58
61
Multistrata
Agroforest
–151
NA
–12
16
41
39
71
77
Cultivation
(long fallow)
–137
–50
NA
0
0
8
–137
–50
0
NA
NA
8
11
Crop–Improved
Fallow
Coffee
Plantation
11
–167
–16
–28
NA
25
23
55
61
(rotational)
–139
12
NA
28
53
51
83
89
(permanent)
–141
–54
–4
–4
NA
4
7
Crop–Natural
Fallow
–192
–41
–53
–25
NA
–2
30
36
–145
–58
–8
–4
–8
NA
3
Pasture
–190
–39
–51
–23
2
NA
32
38
Fallow
–222
–71
–83
–55
–30
–32
NA
6
Fallow
Values are determined by subtracting the time-averaged carbon value for the system in the row from that of the time-averaged value of the system in the column (e.g., Indonesia,
primary forest (306) to oil palm (54) 306 – 54 252 t C lost to atmosphere).
228
Time-averaged C (t C/ha1)
Forest
60
Thematic Research
Figure 2.3 Above-ground time-averaged and topsoil (0–20 cm) carbon of the meta–land use systems for
the three benchmark sites.
If croplands and pastures were taken as the endpoint, in terms of carbon stocks
resulting from the conversion of tropical forests, then rehabilitation through conversion to tree-based systems would result in carbon sequestration. The amount of
carbon that could be sequestered above ground would range from 5 t C/ha for coffee
plantations to 60 t C/ha for more complex agroforestry systems over a 20- to 25-year
period (table 2.4); 5 to 25 t C/ha could be sequestered in the topsoil (table 2.4). Silver
et al. (2000) reported soil carbon sequestration rates of 1.3 t C/ha/yr for the first 20
years after reforestation or abandonment of agricultural lands or pastures in the tropics. Such rates would result in soil carbon sequestration values at the upper end of
those estimated here for conversion of croplands to complex agroforestry systems over
a 20-year time span. Overall our results indicate that the potential for carbon sequestration in the humid tropics is much greater above ground than in the topsoil, as was
also shown by Sommer et al. (2000).
The total carbon sequestered through the establishment of tree-based systems
depends on the areas of degraded grasslands, pastures, or croplands available for conversion. Estimates of such areas in the humid tropics range from 300 million to 1
billion ha (Grainger 1988; Houghton et al. 1993). In addition to the major environmental benefits that could be gained from converting degraded lands to tree-based
systems, many of these systems also provide net profit to the individual farmers (see
chapter 17, this volume). Yet these conversions are not occurring on a broad scale.
Reason for farmers not choosing to rehabilitate these degraded lands systems could be
lack of planting materials, lack of funds to purchase inputs, and the long lag between
establishing the trees and realizing profits. Other obstacles include policy issues, such
Carbon Losses and Sequestration After Land Use Change 61
as land tenure and tree rights, and lack of infrastructure for input and output markets.
The Clean Development Mechanism (cdm) of the Kyoto Protocol (unfccc 1997)
may eventually provide a means of overcoming some of these obstacles. If land use
change and forestry are eventually included under the cdm, this would allow industrialized nations to meet some of their greenhouse gas reductions via carbon offset
projects that provide farmers with the inputs or policy changes needed to establish
these profitable, tree-based systems that sequester carbon.
AC K N OWLEDGMENTS
The work reported here was made possible through grants to the Alternatives to Slash
and Burn Program of the Consultative Group on International Agricultural Research
from the Global Environment Facility and the Danish International Development
Agency. In addition, each of the collaborating institutions contributed substantially in
terms of staff, facilities, operations, and enthusiasm.
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3
Greenhouse Gas Fluxes in Slash and Burn
and Alternative Land Use Practices in
Sumatra, Indonesia
Daniel Murdiyarso
Bogor Agricultural University Bogor, Indonesia
Haruo Tsuruta
National Institute of Agro-environmental Sciences Tsukuba, Japan
Shigehiro Ishizuka
Forestry and Forest Products Research Institute Sapporo, Japan
Kurniatun Hairiah
Brawijaya University Malang, Indonesia
Cheryl A. Palm
The Earth Institute at Columbia University Palisades, New York
T
ropical deforestation and land use change occur rapidly and on a large
scale in the Alternatives to Slash and Burn (asb) program benchmark
sites because natural resource–based development has traditionally been the
main pathway to establish new arable land and to gain revenues. When this
land use change occurs on a large scale, it results in significant environmental consequences, including changes in biogeochemical cycles. Sources and
sinks of carbon and other nutrients are altered with the changing land cover
and land use practices. In some cases the land use change is promoted by
government policies, often for the expansion of agricultural lands to meet
the needs for food, fiber, and settlement. A better understanding of the environmental consequences of land use changes from natural forests to managed
ecosystems is needed to support successful policy interventions that involve
tradeoffs between global climate change, which is associated with greenhouse
gas (ghg) emissions and the sustainability of the systems to support the local
needs (Sanchez et al. 1994).
Globally, land use, land use change, and forestry activities in the last
decade have annually contributed around 1.7 Gt, or 25 percent of the total
carbon dioxide (CO2) emissions of 8.0 Gt, and a resulting net emission of
2.9 Gt (ipcc 2001). Meanwhile, the global net methane (CH4) emission is
only 0.022 Gt (ipcc 2001). However, CH4 has a radiative forcing or heat
Greenhouse Gas Fluxes in Sumatra
65
trapping capacity twenty-one times as large as that of CO2. Tropical deforestation has
been well documented to substantially contribute in the global net increase in nitrous
oxide (N2O) concentration. The current annual global N2O emission is 0.004 Gt, 25
percent of which comes from land use–related activities, mainly in the tropics (ipcc
2001). Such a small emission has become significant because the radiative forcing of
N2O is 310 times larger than that of CO2 (Watson et al. 2000).
The effect of land use change on ghg fluxes from soils is associated with the changes in biophysical and chemical properties of the soils caused by changes in land cover
and management. Soil water content controls CH4 uptake through porosity-dependent parameters that affect gas transport mechanisms, namely air permeability and
gas diffusivity. Low permeability, which is related to soil structure, prevents methanecontaining air from being consumed by microorganisms near and below the soil surface (Ball et al. 1997). Long-term measurements in temperate soils carried out by
Castro et al. (1995) indicated that when water-filled pore space (wfps) increased to
a range of 60 to 100, CH4 uptake decreased significantly. Forest soils absorbed CH4,
whereas pasture soils, which had poor drainage, generally produced CH4 (Lessard et al.
1993). Rates of CH4 uptake substantially increased from 5–15 µg/m2/hr to 100–150
µg/m2/hr after land use was changed from arable agriculture to woodland in northern
Europe (Prieme et al. 1997). In the humid tropics conversion of tropical forest soils
to agriculture, in general, reduces the consumption of CH4 (Keller et al. 1990; Mosier
and Delgado 1997), and pasture systems can become a net source of CH4 (Keller and
Reiners 1994; Steudler et al. 1996).
Soil microbiological activities are also affected by soil moisture and bulk density
because the activity of CH4-consuming bacteria is less in anaerobic and compacted
soils. Soil compaction experimentally reduced CH4 uptake by at least half (Hansen et
al. 1993). As concluded by Dobbie and Smith (1996), CH4 uptake is controlled partly
by diffusion and partly by biological processes. Data from a variety of temperate and
tropical native and managed ecosystems confirm that the activity of soil microbial
processes responsible for CH4 production and consumption can be roughly predicted
from soil wfps (Del Grosso et al. 2000).
Land management can also change soil chemical properties that affect trace gas
fluxes. Many studies show that CH4 uptake can be suppressed in systems that receive
high nitrogen inputs (Steudler et al. 1989; Keller et al. 1990; Hansen et al. 1993;
Hutsch et al. 1993, 1994; Hutsch 1996; Mosier and Delgado 1997). In compacted
soils, nitrogen fertilization could reduce CH4 uptake up to 78 percent (Hansen et al.
1993).
There is a substantial amount of information regarding N2O emissions from tropical soils, mainly from Latin America (Keller 1986; Luizao et al. 1989; Vitousek et al.
1989; Piccolo et al. 1994; Neill et al. 1995; Veldkamp and Keller 1997). Tropical soils
are believed to be the major natural source of N2O. Deforestation results in a large flux
of N2O from soils that may be as much as three times that of an intact forest ecosystem
(Luizao et al. 1989). The increased gaseous release is associated with rapid nitrogen
mineralization and nitrification as a result of the deforestation process. This occurs at a
66
Thematic Research
time when there is low plant demand for nitrogen, and excess mineral nitrogen builds
up in the soil and is susceptible to loss (Vitousek and Reiners 1975). This large flux of
N2O apparently is temporary and can last from a few months to a few years. Otherwise natural systems generally have higher fluxes than converted, unfertilized systems.
Fertilized cropping systems in the humid and subhumid tropics can have N2O fluxes
as much as ten times that of the natural systems depending on the rates and timing of
application of nitrogenous fertilizers (Davidson et al. 1996; Erickson and Keller 1997;
Veldkamp and Keller 1997; Matson et al. 1998).
Nitrous oxides are formed via nitrification and denitrification, the former being
an aerobic and the later an anaerobic process. Fluxes in the humid tropics are positively correlated with some measure of nitrogen availability and with wfps (Verchot et al.
1999; Davidson et al. 2000). Nitrification is the primary source of nitrogen gas below
60 percent wfps, the dominant form of gas being NO rather than N2O; above 60
percent wfps denitrification dominates and N2O becomes the dominant form of gas,
and N2 dominates at even higher wfps (Davidson et al. 2000). Although flooded rice
(Oryza sativa L.) cultivation is not considered an important source of N2O because
of the complete reduction to N2 under more complete anaerobic conditions, N2O
formation may be significant in flooded rice cultivation with alternate irrigation and
drainage cycles (Granli and Bøkman 1994; Cai et al. 1997; Tsuruta et al. 1997; Xu et
al. 1997; Suratno et al. 1998).
Most studies on trace gas emissions from the humid tropics have been from natural forests and pasture systems, and much of that has been done in Latin America. One
objective of the global asb Program has been to quantify the consequences of land
use change on emissions of trace gases, primarily CH4 and N2O, at the benchmark
sites across the humid tropics. These benchmark sites encompass a broad range of
land use systems and can therefore greatly expand information for the humid tropics. A protocol for measurements was developed and used for comparisons of regions
and land use systems. This chapter summarizes the analysis of CH4 and N2O flux
measurements from soils under alternative land use practices in Sumatra, Indonesia,
and compares the results obtained in another study at the asb benchmark site in
Yurimaguas, Peru (Palm et al. 2002). By comparing the two benchmark sites we hope
to better understand and document the effects of land use intensification in the tropics on ghg emissions.
M AT E R I ALS AND METHODS
S t u dy S i te
In asb’s Sumatran sites, Jambi and Lampung Provinces, landscapes are dominated
by tree-based agriculture. Changes in natural vegetation are associated with the conversion of tropical forests to provide land for settlement, agriculture, and large-scale
plantations. Many smallholder farmers (mainly local inhabitants) practice tree-based
Greenhouse Gas Fluxes in Sumatra
67
agriculture, using annual crops while new plantations are becoming established or old
trees are regenerating. Very often they use fire, which is considered the cheapest and
easiest way to clear.
A general survey of trace gas emissions was carried out in three districts in Jambi
Province, and intensive monthly samplings were set up at the area of Pasir Mayang
Research Station in the lowland of Jambi Province. The detailed biophysical characteristics of the area were described by Murdiyarso and Wasrin (1995). The average
monthly rainfall during the experimental period in the wet season (October–March)
was 250 mm, or twice as much as the average monthly rainfall of the dry season
(April–September). Ultisols were the major soil type of the sampling sites; general soil
properties are shown in table 3.1.
Sa m p l i n g Protocol
A standard gas sampling protocol was used in the field throughout the study. The
same protocol was also used in Peru. A closed sampling chamber with a diameter of
30 cm and height of around 12 cm was used. Gas samples were collected from the
chamber by means of a syringe and then transferred to evacuated glass vials. Sampling
intervals from the closed chamber of 0, 10, 20, and 40 minutes were adopted to
determine the flux rates. Gas chromatography techniques were used to determine the
concentration of the gases.
Table 3.1 Properties of Soils Under Each Land Use Type at Pasir Mayang, Sumatra
Land-Use
Type
Depth
(cm)
pH
(H2O)
Total C
(mg/g)
Total N
(mg/g)
C/N
Bulk
Density
(Mg/m3)
Microbial
Biomass
(g C/g)
P1
0–10
10–20
20–30
0–10
10–20
20–30
0–10
10–20
20–30
0–10
10–15
0–10
10–20
20–30
4.2
4.7
4.9
4.8
4.3
4.4
4.0
4.1
4.4
4.0
4.3
4.7
4.6
4.5
30
19
19
35
25
23
45
23
10
36
36
16
11
9
1.9
1.6
1.6
2.4
2.0
1.9
6.5
1.7
0.8
3.0
3.0
1.2
0.9
0.8
16.2
11.5
11.5
14.5
12.5
12.2
6.9
13.3
11.5
12.0
12.0
13.0
13.4
13.4
1.12
1.22
1.16
0.81
1.26
1.35
0.88
1.19
1.17
1.20
1.17
0.98
1.03
1.06
554
262
199
471
316
274
449
512
85
374
278
322
255
153
L1
L2
Op
R
P1, primary forest; L1 and L2, logged-over forest; Op, open land; R, rubber agroforest.
Source: Ishizuka et al. (2002).
68
Thematic Research
C o m p o n ents of Study
Trace gas emissions were evaluated first through a sampling survey of trace gases along
a land use intensity gradient in Jambi. That study was followed by more intensive
monthly sampling in one area of Jambi to investigate seasonality of gas fluxes in a few
selected land use types. An additional study compared fluxes from cores incubated
in the laboratory with the average annual fluxes measured in the field and with those
obtained in the field the same day the core was sampled.
General Survey
To explore the spatial variability of CH4 and N2O fluxes, a general survey was carried
out covering fifteen sites and representing five land uses across a land use intensity
gradient in the lowlands of Jambi Province in July–August 1996, the dry season. The
five land use types, representing a land use intensity gradient, included primary forest, logged-over forest, rubber agroforests, field crops of cassava (Manihot esculenta
Crantz), and degraded Imperata cylindrica (L.) Beauv grasslands. The intensity of land
management depends on the land productivity and availability of labor and is usually
highest in areas of high population density. The samples were collected only one time,
with three replicates for each land use type. The results were then used to select land
use types for the intensive study that followed. The fluxes were also compared with
those measured in another land use intensity gradient in Yurimaguas, Peru (Palm et
al. 2002).
Intensive Study
To monitor seasonal variation of CH4, N2O, and CO2 fluxes, monthly samplings were
carried out beginning in September 1997 for 1 year. The samples were taken from
fixed points in each of the selected land use types. The monthly sampling was carried
out around the same dates and at the same time of the day for each land use. Three
replicates were collected for each land use.
Four land use types were monitored: a primary forest, logged-over forest, newly
open or deforested area, and a rubber plantation. The primary forest (P1 and P2,
1°05.164´S, 102°05.702´E) was a 200-ha old-growth forest that had not been affected by human activities for more than 50 years. P1 was located on a 15° slope, whereas
P2 was on a flat top of the hill. Two plots of logged-over forests had been selectively
logged in 1977 and consisted of tall trees with evenly distributed diameters. The first
logged-over forest (L1, 1°3.810´S, 102°9.754´E) was slashed in September 1997. The
slashed material less than 50 cm in diameter was dried on site and burned in March
Greenhouse Gas Fluxes in Sumatra
69
1998, before a rubber plantation was established by a large-scale operator. The second
logged-over forest (L2, 1°5.235´S, 102°6.586´E) was located near the primary forest and was not disturbed by human activities during this experimental period. The
deforested site (Op, 1°3.660´S, 102°9.681´E) was clear-cut and burned in August
1996, followed by the establishment of a plantation of Gmelina arborea Roxb. (India),
a fast-growing tree species. The height of planted trees was about 4 m in October
1997. The rubber agroforest site (R, 1°5.648´S, 102°7.207´E) was a 5-year-old rubber
plantation managed by a smallholder and was occasionally intercropped with annual
crops, a practice commonly observed in Sumatra. Neither fertilizer nor herbicides
were applied to control the commonly found weed, alang-alang grass (Imperata).
Soil samples were collected from each land use type at three depths of 0–10, 10–
20, and 20–30 cm to determine their physical and chemical properties. The sampling
was carried out once in the wet and once in the dry season.
Incubation Experiment
A laboratory incubation of soil cores was established to evaluate the potential of assessing ghg emissions from the soils through laboratory methods (Ishizuka et al. 2000).
Soil core samples were collected at P1, L1, L2, Op, and R in September 1997 using
core sampler with a diameter and height of 5 cm from the depth of 0–5 cm, 10–15
cm, and 20–25 cm. Triplicate samples were collected from each depth. The incubations were set up within 14 days of soil core collection. For each sample, an intact
soil core was set into an incubation jar with a volume of 0.5 10–3m3. The jars were
equipped with a butyl rubber stopper for gas sampling. The soils were incubated at
25°C, and soil moisture was maintained at the levels similar to those of the different
soils on the day they were collected from the field.
Gas fluxes were determined from sampling of the headspace of the incubation jars
over a 24-hour period. The gas concentrations of CO2 and N2O increased linearly,
and the emission rates were calculated by linear regression. The CH4 concentration
decreased according to first-order kinetics, and the following equation was used for
calculating emission rates:
Ct = C0e–kt,
where Ct (m3/m3) is the CH4 concentration at time t (hours), C0 (m3/m3) is the CH4
concentration of the headspace at the beginning, and k is the reaction rate coefficient.
The uptake potential rate was defined by kC0 (namely, C0 was approximately 1.8
µg/m3/m3).
The ghg uptake and release from the core samples were compared with the average of seasonal fluxes from the field and fluxes obtained from field measurement taken
on the same day the cores were taken.
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Thematic Research
Soil Gas Concentration Profile
Soil gas profiles were developed by collecting gas samples at 5- or 10-cm depth intervals, up to a depth of 50 cm, where possible. Samples were collected by inserting stainless steel tubes (outer diameter of 3 mm and inner diameter of 1 mm) into the soil.
Samples were taken with a syringe and stored in evacuated vials and later analyzed by
gas chromatography. The samples were collected in January 1997 at P1, L1, and Op
and in October 1998 at L1 after slashing and burning.
R E S U LTS AND DISCUSSION
G e n e r a l Survey of Fluxes from Alternative Land Uses
The one-time measurements of CH4 fluxes from the land use survey in Jambi showed
that land use intensification reduced the soil sink strength (figure 3.1). The CH4 consumption ranged from a high of 30 and 36 µg CH4•C/m2/hr in the primary and
Figure 3.1 Mean methane (CH4) fluxes from alternative land uses in (a) Jambi, Indonesia, and
(b) Yurimaguas, Peru (adapted from Palm et al. 2002).
Greenhouse Gas Fluxes in Sumatra
71
logged forests, respectively, to a low of 7.3 µg CH4•C/m2/hr in the degraded grassland. These fluxes are within the range reported elsewhere in the humid tropics. In
Yurimaguas, the range of CH4 uptake ranged from a high of 30 µg CH4•C/m2/hr in
the shifting cultivation forest fallow to a net CH4 release in the high-input cropping
system of 15.2 µg CH4•C/m2/hr (Palm et al. 2002). The CH4 consumption rates of
the soil in the tree-based systems and low-input cropping system in Yurimaguas were
slightly lower than those of the forest fallow and were similar to the fluxes in Jambi.
The decrease in CH4 uptake or sink strength at both sites indicates that soil properties that determine CH4 uptake were affected. In Yurimaguas the CH4 sink strength
decreased with increasing bulk density and wfps. Also, the net efflux of CH4 from
the high-input cropping system in Yurimaguas is similar to previous findings that
nitrogen fertilization can suppress CH4 uptake (Keller et al. 1990; Keller and Reiners
1994; Steudler et al. 1996; Mosier and Delgado 1997). Although in this case the net
efflux probably is more related to soil compaction and high wfps, leading to anaerobic conditions that favor CH4 production (Palm et al. 2002), others have reported net
CH4 production in pastures in the humid tropics during the rainy season (Keller and
Reiners 1994; Steudler et al. 1996).
The N2O flux in Jambi ranged between 2 and 12 µg N2O•N/m2/hr. The flux
from the Imperata grassland was the lowest, and the highest was found in the rubber
agroforest (figure 3.2). Therefore the fluxes were not directly related to land use intensity, with the managed systems having fluxes both higher and lower than those in the
primary and logged forests. Fluxes in Yurimaguas were similar to those in Jambi and
ranged from 6 to 14 µg N2O•N/m2/hr in the unfertilized systems but almost doubled
to 27 µg N2O•N/m2/hr in the nitrogen-fertilized high-input cropping system (Palm et
al. 2002). Others have noted that managed but unfertilized systems had lower fluxes
than forest systems; this follows a brief increase in flux after deforestation (Davidson
et al. 2000).
L a n d U s e Intensit y and Seasonal Fluxes in Jambi
The average CH4 uptake shown in figure 3.3a followed a similar pattern with respect
to land use intensity to that observed in the general survey (figure 3.1), the CH4 sink
strength was substantially lower under managed systems. The highest uptake level was
in the primary forest (P1), followed by the undisturbed logged forest (L2) and the 5year-old rubber agroforest (R), then the site that had been slashed and burned 1 year
previously (Op), and finally the logged forest that had been slashed in 1997, when the
measurements began (L1). The low uptake in both the Op and L1 sites probably was
caused by compaction from the slashing. Also, when L1 was logged in 1994, heavy
equipment was used to drag the logs. The bulk density of L1 below the surface (10–30
cm) ranged between 1.3 and 1.4 Mg/m3 and was higher than in the other land uses;
diffusion would be less, causing less CH4 to be absorbed. Methane consumption rates
were slightly higher when the land was replanted (Op and R).
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Thematic Research
Figure 3.2 Mean nitrous oxide (N2O) fluxes from alternative land uses in (a) Jambi, Indonesia, and
(b) Yurimaguas, Peru (adapted from Palm et al. 2002).
In general, differences in CH4 flux seasonally were not large (figure 3.4a). Other
studies have reported that CH4 consumption rates during the dry season were twice
those during the wet season (Keller and Reiners 1994; Steudler et al. 1996). Only in
the primary forest in Jambi does there appear to be higher CH4 consumption during
the dry season, when gas diffusion would be at a maximum.
The average N2O fluxes were highest, 15 µg N2O/m2/hr, in the logged forest
(L1) that had been slashed in September 1997 (figure 3.3b). The site that had been
deforested the previous year (Op) had fluxes only slightly higher than those of the
forest and rubber agroforests. These trends are consistent with others that have found
temporary increases in N2O fluxes after deforestation (Keller et al. 1993, 1997; Davidson et al. 2001). This increase often is associated with higher soil temperatures and
increased decomposition rates.
There was also a further temporary increase in N2O flux from L1 to around 40
µg N2O/m2/hr in March 1998 (figure 3.4b). This increase corresponded with the
rainy season and also followed the burn in March 1998. Fluxes in the other systems
Figure 3.3 Average fluxes of (a) methane (CH4), (b) nitrous oxide (N2O), and (c) carbon dioxide (CO2)
from different land uses: primary forest (P1 and P2), logged-over forest (L1 and L2), newly planted open
land (Op), and rubber agroforest (R). The data were an average of the first 6 months of measurements
before clear-felling of the logged-over forest (L1).
Figure 3.4 Seasonal variation of (a) methane (CH4), (b) nitrous oxide (N2O), and (c) carbon dioxide
(CO2) fluxes from primary forest, logged-over forest, newly planted open land, and rubber agroforest in
Jambi.
Greenhouse Gas Fluxes in Sumatra
75
remained low (less than 5 µg N2O/m2/hr) and did not show such marked increases
with the rains. The N2O fluxes often are 50 to 80 percent higher during the rainy
season (Keller and Reiners 1994; Verchot et al. 1999). The higher N2O fluxes in the
recently deforested lands (L1 and Op) are correlated with higher nitrification rates in
the soil surface (0–10 cm) (table 3.2; R = .746). However, this conclusion needs further clarification because nitrification data are not available from all systems in both
the dry and wet seasons. The overall low N2O emission rates in this study were related
to the low levels of nitrate and low rates of nitrification that are often associated with
infertile and acidic soil properties. Similarly low levels of nitrate and nitrification were
measured in the systems in Yurimaguas, and N2O fluxes were significantly correlated
to nitrification rates and wfps (Palm et al. 2002).
The average fluxes of CO2 from soils show a slight variation between land use
types (figure 3.3c) compared with seasonal variation (figure 3.4c), except for the lower
flux from the deforested system (Op); this lower flux probably was caused by the
absence of surface litter and hence lower decomposition rates compared with the other
areas. With such a low variation, a rate of 300 mg CO2/m2/hr may be taken as an average across land use types.
Table 3.2 Soil Inorganic Nitrogen Content and Rate of Nitrogen Mineralization in the
Different Land Use Systems During the Dry and Wet Seasons
Land Use Type
Depth
(cm)
NH4
(g/g)
NO3
(g/g)
Nitrification
(g/g/d)
Nitrogen Mineralization
(g/g/d)
0–10
10–20
20–30
0–10
10–20
20–30
0–10
10–20
20–30
17.9
ND
ND
15.0
7.6
6.4
4.3
4.8
5.0
4.9
ND
ND
12.7
8.3
4.6
2.8
3.0
2.7
0.03
ND
ND
0.07
0.13
0.09
0.14
0.24
0.17
0.80
ND
ND
0.76
0.69
0.56
0.39
0.35
0.28
0–10
10–20
20–30
0–10
10–20
20–30
0–10
10–15
8.6
5.0
4.7
5.5
3.2
3.5
4.2
5.5
6.6
0.8
1.3
9.4
2.0
2.4
13.6
10.9
0.15
0.04
0.04
0.45
0.11
0.19
0.35
0.32
0.94
0.47
0.52
0.83
0.48
0.43
0.55
0.28
Dry Season (September 1997)
P1
L2
R
Wet Season (January 1998)
P1
L1
Op
P1, primary forest; ND, not determined; L1 and L2, logged-over forest; R, rubber agroforest; Op, open land.
Source: Ishizuka et al. (2002).
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Thematic Research
In contrast to methane and nitrous oxide, there was seasonal variation in CO2
emissions from all land use types (figure 3.4c). High rates of around 450 mg CO2/
m2/hr usually were reached in the wet season (December 1997–February 1998).
In general the lowest rates, closer to 100 mg CO2/m2/hr, were measured in the dry
season (June or July), with the lowest in Op at around 50 mg CO2/m2/hr (July
1998).
I n c u b at ion Experiments
Methane flux rates from core samples incubated in the laboratory were plotted against
the seasonal average fluxes obtained from the monthly field measurements in September 1997 to August 1998 (figure 3.5a, top) and against the flux rates from the field
measurements taken on the same day the core samples were collected (figure 3.5a,
bottom). These data indicate that results obtained from the core incubations explained
60 percent of the variation obtained from both the average of the monthly field measurements and the field samples collected during core sampling. For CH4 there is no
difference in using either monthly average data or one-time sample data. However, the
40 percent unexplained variation suggests a need for more soil core samples collected
in more locations and seasons to incorporate more spatial and temporal variations.
A higher correlation was obtained for N2O fluxes between the laboratory incubations and same-day field samples (R2 = .73, figure 3.5b, bottom). The correlation with
the monthly average, however, was quite poor (R2 = .39). The outlier that explains the
low correlation is from L1, which for the average includes measurements from both
before and after the burn, whereas the core sample was collected before the burn. As
shown in figure 3.4b, N2O fluxes were affected by the burn in March 1998, but there
was less effect on the other gases.
High coefficients of determination were obtained when CO2 fluxes from the laboratory incubation experiments were related with both averaged monthly data (R2 = .97)
and the one-time field sample (R2 = .78). Again, the outlier is L1, which was more than
600 µg CO2/m2/hr from field data during core sampling (figure 3.5c, bottom) but less
than 400 µg CO2/m2/hr from the monthly average (figure 3.5c, top). This difference
may be explained by the fact that organic inputs, and hence decomposition, were still
high before L1 was burned.
Overall it could be concluded that laboratory incubation of soil cores can explain
much of the spatial and temporal variability of gas fluxes when there is no change in
system management during the sampling period. More core samples would be needed
to incorporate temporal variations caused by changes in land management.
G H G C oncentration in Soil Profile
In general, the concentration of CH4 decreased with depth in the soil profile, whereas
N2O and CO2 concentrations increased with depth (figure 3.6). The profiles reflect
Figure 3.5 Comparisons of (a) methane (CH4), (b) nitrous oxide (N2O), and (c) carbon dioxide (CO2) fluxes obtained from laboratory incubations of soil cores with (top)
the average monthly flux from field measurements and (bottom) fluxes obtained from field measurement taken on the same day the cores were taken. L1 and L2, logged-over
forest; Op, newly planted open land; P1, primary forest; R, rubber agroforest.
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Thematic Research
Figure 3.6 Soil depth profile of methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) concentrations under logged-over forest (L1), newly opened area (Op), and primary forest (P1). L1 was slashed
in September 1997 and burned in March 1998 (Ishizuka et al. 2002).
the biological processes of production and consumption of the different gases. They
also suggest that the gas diffusion occurred throughout the profile. The CO2 and N2O
are produced throughout the profile but only diffuse from the soil surface. On the
other hand, CH4 shows net consumption in the profile: As it enters from the atmosphere it is consumed, and concentrations decrease. From an applied perspective, to
maintain the CH4 sink strength of the soil it would be necessary to allow gas diffusion
at the soil surface.
Concentration of N2O in the soil before burning did not markedly change with
depth. After the burn of L1, however, there was a significant increase in N2O concentrations at all depths in the soil, and the concentrations increased more with depth.
These higher N2O concentrations in the soil after the burn in L1 were matched by
higher fluxes of N2O from L1 (figure 3.4b).
Greenhouse Gas Fluxes in Sumatra
79
C O N C LU SION
GHG fluxes from soils in Jambi, Sumatra, and Yurimaguas, Peru, are associated with
land management. Tropical deforestation has caused the weakening of the CH4 sink
strength of tropical soils and an increase of N2O fluxes in some of the systems in
Sumatra. The trend for decreased methane sink strength was confirmed in the Peruvian Amazon, although decreasing N2O fluxes with increasing land use intensity were
found there, as long as nitrogen fertilizers were not applied.
Globally, the current CH4 emission is around 600 Tg/yr, and only 30 Tg is
absorbed by soil (ipcc 2001). This means that the role of land use change accounts
for only 5 percent of the total CH4 uptake. Forest soils in Europe are estimated to
oxidize 0.6 Tg CH4/yr and the corresponding agricultural land 0.23 Tg CH4/yr (Dobbie and Smith 1996). Tropical forest soils could play important roles in sequestering
CH4 through proper land management while addressing the tradeoffs that meet the
national and local objectives.
When the net global warming potentials of the combined CO2, CH4, and N2O
fluxes from deforestation and land use change are considered together, the trace gas
fluxes of CH4 and N2O are basically irrelevant when compared with the CO2 fluxes
resulting from deforestation (Tomich et al. 1998; Palm et al. 2004). The amount of
carbon released from the soil is also far smaller than that emitted from the removal of
above- and below-ground biomass during deforestation or land use changes. In the
landscape of Jambi Province, for example, we estimate that as much as 8 t C/ha/yr was
released through land use and land cover change over a 25-year period; at the same
time only 0.8 t C/ha/yr was released from the soil. Therefore the deforestation process
itself provides the largest source of ghgs to the atmosphere, primarily as CO2 from
the burn, the amount depending on the land use system established (see chapter 2,
this volume). The subsequent losses of carbon from the soil have minor impacts in
terms of global consequences but can be of local significance in terms of soil fertility
and sustainability (see chapter 6, this volume).
AC K N OWLEDGMENTS
D. Murdiyarso, K. Hairiah, and C. Palm would like to thank the asb Program, which
has channeled the Global Environment Facility and United Nations Development
Program funding, and the Australian Centre for International Agricultural Research
for financial support. The involvement of Haruo Tsuruta and Shigehiro Ishizuka was
made possible by the support of the Japan Environmental Agency.
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4
The Potential Role of Above-Ground
Biodiversity Indicators in Assessing
Best-Bet Alternatives to Slash and Burn
Andrew N. Gillison
Center for Biodiversity Management Yungaburra, Queensland, Australia
I
mprovements in agricultural productivity usually are counterproductive to
maintaining or enhancing indigenous biodiversity. Habitat loss, the main
factor associated with biodiversity decline, increases with intensive, permanent, large-area cropping systems. Biodiversity continues to be reduced globally, partly because it is consistently undervalued and partly because of the lack
of sufficient incentives for its retention and maintenance (unep/cbd 2002).
Major contributing factors are the extraordinarily high biotic complexity in
tropical forested lands and difficulties in devising and implementing costefficient methods for biodiversity survey and evaluation. Few published data
demonstrate significant links between biodiversity and ecosystem dynamics
in a way that can be used to attach a meaningful value to biodiversity or to
provide related landscape-based indicators of profitability.
Against this background Alternatives to Slash and Burn (asb) has
sought readily observable field indicators that can be used to assess the status
of nutrient dynamics and help forecast the impact of a specified land use
on biodiversity and net primary productivity. To be acceptable to management, methods of biodiversity assessment must be cost-effective and easy
to implement. Although a truly generic means of rapid biodiversity assessment remains elusive, surveys using newly developed protocols along comparable, putative land use intensity gradients in different global ecoregions
have generated improved baseline datasets that provide new insights into
response couplings between biodiversity and land use condition (Gillison
and Liswanti 1999; Gillison 2000a). This is a significant point of entry into
exploring the next important step: the biodiversity–profitability dynamic.
Apart from local and regional needs, a global challenge for developing generic assessment methods is to facilitate the comparison of vegetation response
to environmental change between different continents where environment
and plant adaptation may be similar but where species differ. In this way
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Thematic Research
lessons learned in one region may be translated to another, thereby improving the
information feedback loop to farmers and enhancing international dialogue on alternatives to slash-and-burn. For management and planning to be effective, assessment
techniques should be readily transferable and should deliver interpretable results with
tangible, practical outcomes.
The asb ecoregional studies to date conclude that managers and planners should
be better empowered to assess their existing resources to improve management practices. This strategy should provide a more acceptable, rational, and scientific basis
for adapting management to meet unpredicted changes in the physical environment
caused by events such as El Niño extremes, war, change in governments, or price
shocks in global and regional markets. This chapter discusses the need to improve
the efficiency of existing vegetation survey and classification methods and the ways
in which these methods can be integrated with multitaxon surveys to identify, calibrate, and test appropriate biodiversity indicators. Finally, case studies from tropical,
lowland rainforest environments illustrate ways in which policymakers and managers
can use the outcomes from these procedures in selecting more attractive alternatives
to slash-and-burn.
The need to conserve biodiversity is reflected in the mission of the international
Convention on Biological Diversity (cbd), which highlights a demand for improved
methods of assessing biodiversity and an understanding of the nexus between biodiversity and socioeconomic incentives (unep/cbd 2002). Despite the clear need to
develop a science-based, practical framework for biodiversity conservation, there is
as yet no operational definition for biodiversity. As Weitzman (1995:21) points out,
the implementation of any plan to preserve biodiversity is hampered by the lack of an
operational framework: “We need a more-or-less consistent and useable measure of
the value of biodiversity that can tell us how to trade off one form of diversity against
another.” Miller and Lanou (1995) maintain that the issue of attaching a value to
biodiversity is governed largely by the interaction between human society and biodiversity. This implies that there should be a demonstrable, dynamic link between
biodiversity and productivity for human needs (unep/cbd 2002). And although the
World Bank (1995) has made a case for integrating biodiversity concerns into national
decision making, the mechanisms for achieving this remain elusive. In Indonesia, as
in many other developing countries, the government recognizes that a lack of scientific and management expertise is a serious impediment to biodiversity conservation
(Government of Indonesia 1993). This constraint is further aggravated by the current
policies of property rights on public lands and waters and the failure to use much of
the financial returns from the use of the country’s natural living resources (e.g., via
logging) to support biodiversity conservation (Barber et al. 1995; see also chapter 13,
this volume). These concerns highlight the need not only for a working definition of
biodiversity but also for a cost-efficient, generic, science-based tool for its assessment.
Both should aim to provide practical outcomes for government and corporate policy
planners and managers involved in natural resource management.
Above-Ground Biodiversity Indicators
85
B I O D I V E RSIT Y INDICATORS
Th e N e e d
One of the tenets of rapid biodiversity assessment (rba) is that for practical purposes
there should be readily observable indicators or surrogates of more complex plant and
animal assemblages. Whether this is a pious hope or a genuine possibility is a continuing source of debate (Cranston and Hillman 1992; Reid et al. 1993; Pearson 1995;
Howard et al. 1996; Lawton et al. 1998). For example, there may be questionable
theoretical support for targeting so-called keystone or flagship species (Tanner et al.
1994; Williams 2002). It can be argued that without a clear understanding of multidimensional, causal relationships or trophic webs, simple, linear correlations between
singular, ecosystem variables such as woody plant basal area and primates may lead
to incorrect forecasts of land use impact. On the other hand, comparative estimates
of ecosystem variables such as soil nutrients, soil structure, plant species richness, and
richness of plant and animal functional types can provide important insights into ecosystem behavior and biodiversity when examined along key environmental gradients
(Gillison 1981; Gillison and Brewer 1985; Wessels et al. 1998).
An in-depth study of biodiversity conservation in Ugandan forests led Howard et
al. (1996, 1997) to conclude that although the value of indicators and their ability to
provide an accurate assessment of biodiversity within a particular site remain debatable, practical factors compel their use. Thus much importance is placed on selecting
appropriate indicator groups for which selection criteria involve ease of sampling and
availability of resources (Howard et al. 1996, 1997). In similar vein, Miller et al.
(1995) argue for reduced, manageable attribute sets that can be used to convey more
complex information such as the status of key pollinators and seed dispersers that may
not be available at the time of survey. In the absence of experimental data, an inescapable outcome is that demonstrating indicator efficiency entails, at the very least, calibration from intensive baseline studies of taxa and functional types at a comprehensive
range of spatial, temporal, and environmental scales. But because traditional survey
methods attract high logistic costs, such studies are almost nonexistent in complex
tropical environments. And depending on environmental context and the variables
used, surveys may demonstrate conflicting, correlative trends between biotic and abiotic variables. For example, a multitaxon baseline study of Sumatran rainforests (Gillison et al. 1996), showed that whereas plant biodiversity increased with elevation from
500 to 900 m above sea level, the converse was true for insects and birds. Although
such confounding effects can be accommodated in part by appropriate regression
models and site stratification, predictive models of biodiversity based on environmental correlates such as elevation must be evaluated carefully before being adopted
by managers. It follows that environmental context and scale are critical in designing
field studies of biodiversity and interpreting the results (see also He et al. 1994). This
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Thematic Research
chapter briefly discusses the relative merits of certain forms of biodiversity indicators
in a specific environmental context. These include Linnean species, functional types,
diversity indexes, and measurable elements of vegetation structure.
S pe c i e s
Despite recent advances in the use of alternative indicators, the species remains the
most widely used currency for biodiversity assessment. Other species-based approaches may use higher taxa such as families or genera (Prance 1995) or a measure of phylogenetic distance that includes taxic richness or genealogical relationships embodied
in taxonomic classifications, typically by weighting the relative number of species per
genus, genera per family, and so on (Vane-Wright et al. 1991; Williams et al. 1992;
Faith 1995). In complex, tropical lowland forests, however, species identification can
be difficult, costly, and time-consuming. For this and other ecological reasons there
is growing concern that as long as the species remains the preferred indicator, there
will be little progress in biodiversity assessment (cf. Wulff 1943; Heywood and Baste
1995). When used in isolation from other, more dynamic descriptors of organism
behavior and performance, species richness and abundance can seriously misinform
and distort biodiversity assessment. Parity in richness alone between sites does not
guarantee equivalence in either genetic composition or genetically determined, adaptive response to environment. Yet from a conservation management perspective,
response characterization of individuals to environmental impact should form an
important benchmark for assessing biodiversity and the degree to which biodiversity
is affected by external factors such as disturbance and habitat modification. Therefore
there is a clear need for other biotic descriptors that offer a reasonable alternative or
complement to the use of species in biodiversity assessment.
F u n c t i o nal Types
Partly through increasing dissatisfaction with species as sole indicators, an emerging
school of thought now holds that biodiversity or other forms of ecological assessment
should include functional aspects of individuals as well as species (Box 1981; Gillison
1981, 1988; Nix and Gillison 1985; Cowling et al. 1994a, 1994b; Huston 1994;
Collins and Benning 1996; Martinez 1996; Woodward et al. 1996). Diaz (1998:18)
regards functional types (fts) as “sets of organisms showing similar responses to environmental conditions and having similar effects on the dominant ecosystem processes”
(see also Cramer et al. 1999). This is an extension of an earlier definition by Shugart
(1997:20), who used plant functional types (pfts) “ to connote species or groups of
species that have similar responses to a suite of environmental conditions.” Varying
definitions of fts are most commonly associated with guilds (organisms that share
the same resources) (Gillison 1981; Bahr 1982; Huston 1994; Gillison and Carpenter
Above-Ground Biodiversity Indicators
87
1997; Gitay and Noble 1997; Mooney 1997; Shugart 1997; Smith 1997; Smith et
al. 1997). But as Martinez (1996:115–116) asserts, “The functional aspects of biodiversity are a broad and vague concept that needs substantial added specification in
order to become scientifically more useful.” According to Cramer (1997), the task of
screening all the world’s species for fts is impossible, and for a global model, a breakdown of the world’s vegetation can be achieved only based on major physiognomic or
otherwise recognizable features. Such views are rapidly changing; Cramer et al. (1999)
now argue that pfts may be considered a necessary and appropriate simplification
of species diversity, with the added advantage that ecosystem types often correspond
naturally with pft assemblages.
Gillison (1981) devised a method of assembling plant functional attributes (pfas)
into a functional modus or pft and demonstrated correlations between pfts or modi
and landscape disturbance patterns. A formal, generic approach for characterizing vascular plants as pfts from combinations of a basic set of thirty-five pfas was developed
by Gillison and Carpenter (1997:Appendix). Whereas species identification, especially in complex tropical forests, demands botanical expertise that is often unavailable,
pfts can be applied by observers with limited botanical and ecological experience.
P l a n t F u nctional Types
As described by Gillison and Carpenter (1997), pfts or functional modi are combinations of essentially adaptive morphologic or functional attributes (e.g., leaf size class,
leaf inclination class, leaf form and type [distribution of chlorophyll tissue]) coupled
with a modified Raunkiaerean life form and the type of above-ground rooting system.
The pfts are derived according to a specific grammar or rule set from a minimum
set of thirty-five functional attributes. An individual with microphyll-sized, vertically
inclined, dorsiventral leaves supported by a phanerophyte life form would be a pft
expressed as mi-ve-do-ph. Although they tend to be indicative for a species, they are
independent of species in that more than one species can occur in one pft and more
than one pft in a species. The pfts allow the recording of genetically determined,
adaptive responses of plant individuals that can reveal intraspecific as well as interspecific response to environment (e.g., land use) in a way that is not usually contained
in a species name. Because they are generic, they have a singular advantage in that
they can be used to record and compare datasets derived from geographically remote
regions where, for example, adaptive responses and environments may be similar but
where species differ.
Functional characteristics can be used to compare adaptive properties between
individuals and sets of individuals independently of species, for example, where taxa
may be geographically disjunct but where individuals possess similar adaptations to
environment. In a comparative study of methods of characterizing site productivity and growth patterns in North Queensland rainforests (Vanclay et al. 1996), the
pft-based approach was more efficient in estimating site productivity potential for
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Thematic Research
commercial tree species than traditional methods of site characterization based on species and vegetation structure. Consistently high correlations have been demonstrated
between total numbers of species and total numbers of unique pft plots across a wide
range of environments (Gillison et al. 1996; see also Baskin 1994). The implications
from these studies are that for surveys where taxonomic expertise is lacking, pfts
can be used to predict species richness with a high degree of confidence should this
be needed. This may also benefit rapid assessment of plant biodiversity and improve
correlations between plant and animal biodiversity (cf. Gillison et al. 1996). A field
technique (the VegClass procedure, Gillison 2001, 2002) embodying this approach
and designed specifically for rapid survey is now available for use by observers with
minimal training. This technique enables rapid characterization of site physical features, vegetation structure, species composition, and pfts and is supported by a training manual and a software package that facilitates data compilation and analysis (Gillison 2002).
D i ve r s i t y Measures and Indexes
Plant species richness (the number of species per unit area) can be a useful descriptor
of animal habitat but does not in itself reflect evenness or dominance of species, as
do the frequently used diversity indexes of Shannon-Wiener and Simpson (Magurran
1988). Despite the widespread application of these complex indexes, ecologists rarely
agree about their interpretive value. For this reason, species richness is still the most
commonly applied diversity index in biodiversity studies, although the search for more
ecologically meaningful indexes continues (Cousins 1991; Majer and Beeston 1996).
Most diversity indexes are based on species abundance (number of individuals per species) and at best are usually regarded as a species-based stand attribute with potentially
low ecological information. Generating such indexes entails time-consuming counts
of individuals, which is rarely cost-effective, especially in rapid surveys of complex,
tropical forested landscapes. To circumvent this problem, Gillison et al. (1999; see
also Gillison 2000a) developed a method for calculating Shannon-Wiener, Simpson’s,
and Fisher’s alpha diversity indexes based primarily on pft data. Unlike several other
approaches (e.g., Martinez 1996), this has the advantage that in rapid survey it is the
number of species per pft rather than numbers of individuals (abundance) per species that is counted in each plot. Using pfts alone, a measure of plant functional complexity (pfc) developed by the same authors can be computed as a functional numeric
distance between pft assemblages derived from a table of weighted transformation
values between specific pfas (Gillison and Carpenter 1997; Gillison 2000a). The pfc
value can be used to discriminate between two plots where species and pft richness
are similar but where pft composition varies. Such discrimination is potentially useful in discriminating between successional sequences in forest types or between widely
differing vegetation types such as mediterranean heaths and tropical forests with similar pft and species richness. Under such circumstances measures such as pfc can add
useful information to biodiversity assessment.
Above-Ground Biodiversity Indicators
89
Ve g e tat i on Structure
Vegetation classification and survey methods typically combine broad structural variables with seasonality (e.g., evergreenness, deciduousness) and a list of dominant species or higher taxa, as in “Very tall evergreen Dipterocarp forest.” Although this may
be relevant for geographic purposes, it is inappropriate for management at a 1:50,000
mapping scale. In addition, structurally similar interregional vegetation types rarely
contain the same plant species. Although vegetation structure may be used to predict
animal habitat within a region, sites with similar vegetation structure in widely separated ecoregions are not necessarily ecologically equivalent. Where enhanced sensitivity is
needed to discriminate between biodiversity patterns within and between regions, additional attributes such as pfts can provide the necessary value-added discriminants.
T H E L A N DSCAPE AS A SAMPLING FRAMEWORK
F O R B I O DIVERSIT Y INDICATORS
Given that plant and animal taxa and fts tend to be distributed throughout a variety
of land use mosaics, the landscape matrix seems to be a logical framework for studying biodiversity (cf. Forman and Godron 1986; Franklin 1993). This is the underlying concept for survey design and data collection across all the asb ecoregional
benchmark sites. Because landscape disturbance is a critical determinant of biodiversity (Petraitis et al. 1989; van der Maarel 1993; Phillips et al., 1994), factors such
as agriculture, shifting cultivation, and forest fragmentation should be considered in
survey design (Grime 1979; Bierregard et al. 1992; Sayer and Wegge 1992; Margules
and Gaston 1994; Brooker and Margules 1996; Margules and Pressey 2000). For
this reason asb ecoregional sites are located as far as possible along representative,
successional gradients of land use and vegetation types, from pristine rainforest and
logged-over forest to plantations and degraded grasslands. These successional or socalled land use intensity transects have been generally called chronosequences in asb
(chapter 2, this volume).
Within landscapes, the issue of plot size selection continues to be argued among
plant ecologists. Although plot size may vary typically from 1 to 50 ha (Dallmeier
1992; Condit 1995), some studies show that for characterizing plant diversity, useful
information can be recorded from complex, humid tropical forest plots as small as 50
by 2 m (Parker and Bailey 1991; Parker and Carr 1992; Parker et al. 1993) or 40 by
5 m (Gillison et al. 1996). At landscape mosaic scale, efficiency in biodiversity survey
usually is improved through the application of many small plots rather than a few
large plots (cf. Keel et al. 1992). Whereas large (e.g., 50-ha plots) tend to focus only
on tree species and mask important fine-scale habitat variability, a 40- by 5-m plot, or
multiples of them, can be used to record all vascular plant species and positioned to
target organisms with restricted or specific environmental ranges (e.g., streambanks,
ridge crests, and forest margins). Environmental variability at this typically complex
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Thematic Research
scale demands cost-effective survey techniques (cf. Margules and Haila 1996) where
cost efficiency is governed by the nature of the variables being recorded as well as
management scale and purpose. In selecting best-bet options for sustainably managing biodiversity and productivity, a manager or planner needs access to a variety
of management procedures with forecastable outcomes across a variety of landscape
facets. For this reason, the largely stochastic nature of landscape biodiversity dynamics
requires that samples should include the widest possible environmental range of taxa
and functional types. This may include a variety of land use types (luts) ranging from
largely unaltered to highly modified forests, home gardens, and intensive agricultural
plots to degraded grasslands. Within a region or subregion other factors such as climate (temperature, light, moisture), drainage, and soil gradients also play a significant
role in survey design.
M E T H O DS
F i e l d S t udies
Ecoregional land use intensity gradients were investigated in Brazil, Cameroon, and
Indonesia. These contained luts, also called meta–land use systems in asb, and
lowland, forested landscape mosaics that are common in many tropical developing
countries. The study was implemented at two levels: The first compared broad-scale,
plant-based biodiversity patterns across similar luts in the three ecoregions using a
standardized survey protocol. At a second and much more detailed level, the Indonesian ecoregion was subjected to an intensive biophysical, multitaxon (plant and animal) biodiversity baseline study. Sites in the three benchmark areas included sixteen
in Jambi Province, Central Sumatra, mainly on ultisols but ranging across intact and
logged-over rainforests, rubber plantations, jungle rubber, softwood timber plantations, agricultural subsistence gardens, and farmed Imperata grassland (cassava and
other crops) to degraded Imperata grassland (table 4.1). In Brazil, twenty-five sites
were located along a similarly putative but more widely distributed land use intensity
gradient mainly in the western Amazon Basin (Rondônia–Acre). These ranged from
logged-over rainforest on acid soils of moderate to poor fertility (ultisols) through coffee (Coffea canephora Pierre ex. Fröhner L.), cacao (Theobroma cacao L.), and rubber
plantations in various combinations with other agricultural and agroforestry crops, to
newly established subsistence gardens. To include a more comprehensive gradient of
soil features, other sites were added to include short-stature, closed forests (campinharana) on leached sands (spodosols) north of Manaus and shrubby heaths on lithosolic
sandstone soils (psamments), an oil palm plantation on a latosol (oxisol), and a semiclosed woodland savanna (cerradão) on an oxisol near Brasília (table 4.2). In Cameroon in humid tropical West Africa, twenty-one sites were located primarily along
a regional, rainfall seasonality gradient from rainforest in the south at Awae, Akok,
and Mbalmayo, extending north through Yaoundé to include sub-Sahelian savanna
Pasir Mayang
Pasir Mayang
Pasir Mayang
Pasir Mayang
Pasir Mayang
Pasir Mayang
BS02
BS03
BS04
BS05
BS06
BS07
01-03-09 S 102-08-10 E 55
01-04-59 S 102-06-43 E 65
01-04-56 S 102-06-05 E 75
01-04-53 S 102-06-09 E 60
01-04-43 S 102-05-55 E 85
01-04-45 S 102-05-53 E 60
01-04-47 S 102-06-02 E 76
Pasir Mayang
Intact rainforest (outside
permanent plot)
Intact rainforest (
permanent plot)
Logged over 1984 (old log
ramp secondary forest)
Logged over 1979–1980
(secondary forest)
Logged over 1983
(secondary forest)
Paraserianthes falcataria
plantation 1993–1994
Paraserianthes falcataria
Elevation Land Use Type
(m)
BS01
Longitude
(DMS)
Latitude
(DMS)
Site
Location
Number
Table 4.1 Site Physical Environment and Vegetation Features in Jambi Province, Indonesia
16
30
40
70
28
6
80
35
65
75
24
10
20
21
8.00
6.00
27.33
32.67
13.33
32.67
27.33
33
28
38
39
24
35
35
46
43
111
108
50
101
102
1.39
1.54
2.92
2.77
2.08
2.89
2.91
Crown Mean Basal Area, PFTs Plant
Mean
Species
Canopy
Cover All Woody Plants
Species per
Height (m) (%)
(m2/ha)
PFT
Pasir Mayang
Pancuran Gading
Pancuran Gading
Kuamang Kuning
Kuamang Kuning
Kuamang Kuning
Kuamang Kuning
Pancuran Gading
BS09
BS10
BS11
BS12
BS13
BS14
BS15
BS16
102-06-50 E
102-06-46 E
102-21-11 E
102-21-12 E
102-21-22 E
102-21-21 E
102-06-58 E
30
30
40
40
48
48
30
Rubber monoculture
plantation (8 yr)
Rubber monoculture
plantation (8 yr)
Jungle rubber (15–38 yr)
Jungle rubber (15–38 yr)
Tall Imperata grassland
Short Imperata grassland
Cassava plantation
Cassava plantation
Chromolaena, Clibadium 4yr fallow
50
50
90
90
50
40
95
70
12
14
14
1
1
1.8
1.8
2
65
11
18.00
20.67
0.01
0.01
0.10
0.10
0.10
15.33
14.67
47
41
10
5
12
13
32
30
37
112
97
11
7
15
19
43
54
66
2.38
2.37
1.10
1.40
1.25
1.46
1.34
1.80
1.78
Crown Mean Basal Area, PFTs Plant
Mean
Species
Canopy
Cover All Woody Plants
Species per
Height (m) (%)
(m2/ha)
PFT
DMS, degrees, minutes, and seconds; PFT, plant functional type; BS, Bina Samaktha plots now referred to as SUM (Sumatra) sites; BIOTROP, Southeast Asian Regional Centre
for Tropical Biology.
01-10-12 S
01-10-13 S
01-35-58 S
01-35-56 S
01-36-05 S
01-36-00 S
01-10-13 S
01-05-27 S 102-06-56 E 53
01-05-25 S 102-07-05 E 53
Pasir Mayang
Elevation Land Use Type
(m)
BS08
Longitude
(DMS)
Latitude
(DMS)
Site
Location
Number
Table 4.1 (Continued)
Ji Parana, Rondônia
Ji Parana, Rondônia
Ji Parana, Rondônia
Ji Parana, Rondônia
Ji Parana, Rondônia
BRA02
BRA03
BRA04
BRA05
BRA06
10-58-30 S 62-00-58 W 265
10-58-30 S 62-00-58 W 265
10-55-14 S 61-58-27 W 225
10-55-14 S 61-58-27 W 225
10-55-23 S 61-57-25 W 230
10-55-23 S 61-57-25 W 230
Ji Parana, Rondônia
Agroforestry plot, rubber
and coffee, 12 yr old
Agroforestry plot, rubber
and coffee, 12 yr old
Brachyaria pasture,
natural forest cleared 20
yr ago
Brachyaria pasture,
natural forest cleared 20
yr ago
Schizolobium (bandarra)
& Coffea robusta
plantation
Schizolobium (bandarra)
and Coffea robusta
plantation
Elevation Land Use Type
(m)
BRA01
Longitude
(DMS)
Latitude
(DMS)
Site
Location
Number
Table 4.2 Site Physical Environment and Vegetation Features in Brazil
30
40
22
21
95
95
0.8
0.8
45
45
8
8
7.33
7.33
0.03
0.03
8.00
8.67
19
19
9
10
13
13
27
27
14
12
15
16
1.42
1.42
1.56
1.20
1.15
1.23
Crown Mean Basal Area, PFTs Plant
Mean
Species
Canopy
Cover All Woody Plants
Species per
Height (m) (%)
(m2/ha)
PFT
Theobroma, Rondônia 10-06-40 S 62-11-58 W 242
Theobroma, Rondônia 10-06-40 S 62-11-58 W 240
Theobroma, Rondônia 10-13-03 S 62-23-49 W 252
Reca, Rondônia
09-46-48 S 66-37-44 W 287
Reca, Rondônia
Reca, Rondônia
Reca, Rondônia
Pedro Peixoto, Acre
BRA10
BRA11
BRA12
BRA13
BRA14
BRA15
BRA16
BRA17
10-01-13 S 67-09-39 W 270
09-46-48 S 66-37-43 W 232
09-46-48 S 66-37-43 W 232
09-46-48 S 66-37-44 W 287
Theobroma, Rondônia 10-06-12 S 62-11-40 W 230
Theobroma, Rondônia 10-06-12 S 62-11-40 W 230
Capoéira–cassava
plantation (after slashand-burn)
Inga edulis plantation
Capoéira–Cassia siamea
plantation
Rubber and coffee
plantation with mixed
fruit trees
Rubber and coffee
plantation with mixed
fruit trees
Secondary rainforest
Mixed agroforestry
plantation: cupuaçú,
Bactris, and Brazil nut
Mixed agroforestry
plantation: cupuaçú,
Bactris, and Brazil nut
New subsistence garden,
slash-and-burn, Bactris
New subsistence garden,
slash-and-burn, Bactris
Moderately disturbed
rainforest, grazed
Elevation Land Use Type
(m)
BRA08
BRA09
Longitude
(DMS)
Theobroma, Rondônia 10-06-18 S 62-11-40 W 230
Latitude
(DMS)
BRA07
Site
Location
Number
Table 4.2 (Continued)
26
0.4
0.4
12
90
10
10
40
85
40
10
15
8
22
12
8
90
95
15
5
4.5
2.2
22.33
1.00
0.01
11.33
18.00
13.33
3.33
5.00
8.67
7.00
0.50
44
20
20
33
39
33
15
15
21
17
29
80
23
26
47
79
50
16
17
32
21
34
1.82
1.15
1.30
1.42
2.03
1.52
1.07
1.13
1.52
1.24
1.17
Crown Mean Basal Area, PFTs Plant
Mean
Species
Canopy
Cover All Woody Plants
Species per
Height (m) (%)
(m2/ha)
PFT
Pedro Peixoto, Acre
Pedro Peixoto, Acre
Pedro Peixoto, Acre
Jardin do Botanica
Presidente Figueiredo
Igarape do lajes
Reserva Biologica
de Campina
Embrapa Acre
BRA19
BRA20
BRA21
BRA22
BRA23
—
100
02-53-34 S 59-58-21 W 120
02-35-21 S 60-01-55 W 120
01-59-39 S 60-01-34 W 130
—
10-01-03 S 67-09-27 W 316
10-01-03 S 67-09-27 W 316
10-01-13 S 67-09-39 W 295
10-01-13 S 67-09-39 W 295
DMS, degrees, minutes, and seconds; PFT, plant functional type; BRA, Brazil.
BRA25
BRA24
Pedro Peixoto, Acre
BRA18
Secondary forest:
capoéira (3–4 yr after
maize garden)
Secondary forest:
capoéira (3–4 yr after
maize garden)
10-yr-old Brachiaria
brizantha pasture
10-yr-old Brachiaria
brizantha pasture
Low, semievergreen vine
thicket, woodland, some
bromeliads
Shrubby heath,
moderately disturbed
Campinharana (intact
forest on white sand)
15- to 18-yr oil palm
(Elaeis guineensis)
plantation
80
35
0
7.50
80
70
4.50
2.50
95
95
95
95
0.2
0.2
12
12
20.00
18.67
2.67
13.33
0.10
0.01
11.67
16.00
21
25
28
36
10
12
43
32
24
44
36
90
14
18
82
63
1.14
1.76
1.29
2.50
1.40
1.50
1.91
1.97
45-yr-old jungle Cacao
2-yr Chromolaena fallow
03-36-05 N 11-36-15 E 657
03-55-31 N 11-35-49 E 696
03-55-31 N 11-35-49 E 696
03-55-41 N 11-35-49 E 696
02-34-37 N 11-01-29 E 576
02-42-19 N 11-16-09 E 554
CAM04 Awae
CAM05 Nkol-fulu
CAM06 Nkol-fulu Mefou and
Afamba Department
CAM07 Nkol-fulu Mefou and
Afamba Department
CAM08 Mengomo (Ebolowa
Station)
CAM09 Mengomo (Ebolowa
Station)
CAM10 Mengomo (Ebolowa
Station)
CAM11 Akok (Ebolowa
02-34-37 N 11-01-29 E 576
02-34-45 N 07-02-05 E 554
New cultivation, egusi
melon
Secondary forest, heavily
disturbed
2-yr Chromolaena fallow
03-36-05 N 11-36-15 E 657
03-36-05 N 11-36-15 E 657
Elevation Land Use Type
(m)
CAM02 Awae
CAM03 Awae
Longitude
(DMS)
Secondary forest, heavily
disturbed
2-yr Chromolaena fallow
New garden with
groundnut and cassava
8- to 10-yr Chromolaena
fallow
Secondary forest, heavily
disturbed
4-yr Chromolaena fallow
Latitude
(DMS)
03-36-05 N 11-36-15 E 657
Location
CAM01 Awae Village
Site
no.
Table 4.3 Site Physical Environment and Vegetation Features in Cameroon
2.30
12.00
2.50
18.00
0.40
2.60
12.00
3.50
2.50
0.40
20.00
95
75
95
70
30
95
95
95
95
5
70
1.50
17.33
0.50
20.67
4.67
2.17
7.33
4.67
2.00
0.50
18.00
50
47
47
42
12
22
33
35
37
19
43
71
80
76
93
14
30
50
54
61
20
103
1.42
1.70
1.62
2.21
1.17
1.36
1.52
1.54
1.65
1.05
2.40
Crown Mean Basal Area, PFTs Plant
Mean
Species
Canopy
Cover All Woody Plants
Species per
Height (m) (%)
(m2/ha)
PFT
New cultivation, egusi
melon
Secondary forest, heavily
disturbed
2-yr Chromolaena fallow
45-yr-old jungle Cacao
2-yr Chromolaena fallow
1-yr garden
4-yr Chromolaena fallow
2-yr Chromolaena fallow
30-yr Cacao plantation
1-yr cassava field
Humid savanna
1-yr Chromolaena fallow
Shrub savanna
Raffia palm swamp
Old secondary forest
03-55-41 N 11-35-49 E 696
02-34-37 N 11-01-29 E 576
02-42-19 N 11-16-09 E 554
02-42-27 N 11-16-30 E 554
02-43-08 N 11-17-05 E 585
02-43-12 N 11-16-58 E 585
02-42-45 N 11-16-42 E 559
04-48-58 N 11-10-27 E 560
05-02-40 N
04-04-51 N
04-48-56 N
03-28-21 N
02-42-45 N
10-42-04 E
11-33-17 E
11-10-25 E
11-29-25 E
11-16-45 E
977
596
640
600
550
02-34-37 N 11-01-29 E 576
02-34-45 N 07-02-05 E 554
4-yr Chromolaena fallow
03-55-31 N 11-35-49 E 696
DMS, degrees, minutes, and seconds; PFT, plant functional type; CAM, Cameroon.
CAM06 Nkol-fulu Mefou and
Afamba Department
CAM07 Nkol-fulu Mefou and
Afamba Department
CAM08 Mengomo (Ebolowa
Station)
CAM09 Mengomo (Ebolowa
Station)
CAM10 Mengomo (Ebolowa
Station)
CAM11 Akok (Ebolowa
Station)
CAM12 Akok
CAM13 Akok (Ebolowa
Station)
CAM14 Akok
CAM15 Akok (Ebolowa
Station)
CAM16 Bafia (20 km after
Bafia)
CAM17 Makam III–Batoum II
CAM18 Nkometou II
CAM19 Near Bafia
CAM20 Nkolitam
CAM21 Akok “Enuzam”
3.00
1.80
4.00
18.00
20.00
2.50
2.50
18.00
2.00
3.50
2.30
12.00
2.50
18.00
0.40
2.60
70
98
8
90
85
50
95
75
90
95
95
75
95
70
30
95
2.00
0.20
0.67
14.00
26.00
2.00
1.00
20.00
1.00
1.00
1.50
17.33
0.50
20.67
4.67
2.17
41
29
18
29
41
37
44
43
55
66
50
47
47
42
12
22
47
45
25
57
57
51
61
63
78
100
71
80
76
93
14
30
1.15
1.55
1.39
1.97
1.39
1.38
1.39
1.47
1.42
1.52
1.42
1.70
1.62
2.21
1.17
1.36
98
Thematic Research
sites (Makham III), with the soils in the southern zone being primarily ultisols. Along
this gradient luts ranged from closed, logged, and community-managed rainforest,
through cacao plantations and agricultural subsistence gardens with varying fallow
systems, to cassava and maize in farmed savanna, to nonagricultural woodland savanna (table 4.3).
Within each ecoregional gradient, sites were located according to the gradientbased or gradient-oriented transect (gradsect) method of Gillison and Brewer (1985).
With gradsects, sites are located according to a hierarchical nesting of presumed key
physical environmental determinants such as climate, elevation, parent rock type,
soil, vegetation type, and land use. Because the distribution of plants and animals is
determined mainly by environmental gradients, the gradsect approach offers a means
of sampling such variation. In most cases where the intent is to maximize information about environmental variability and species distribution in the area, the method
is logistically much more efficient than surveys based on purely random or purely
systematic grid designs (Gillison and Brewer, 1985) and is finding increasing application in regional surveys (Austin and Heyligers 1989, 1991; Sorrells and Glenn 1991;
Green and Gunarwadena 1993; usgs 2001; fao 2002). In addition, the sampling of
environmental gradients rather than discrete, non–gradient-oriented samples tends to
enhance efficiency of extrapolative spatial models by ensuring a more comprehensive
coverage of environmental range. Although the method was originally designed and
evaluated for vegetation survey, more recent, comparative assessments indicate that
the gradsect approach also performs more efficiently for fauna than many other survey
procedures (Wessels et al. 1998).
At each location, a standardized vegetation survey method (modified from Gillison 1988 and updated in part by Gillison and Carpenter 1997; Gillison 2002) was
used to record a minimum set of biophysical characteristics (table 4.4) and determine
the species and pft for each plant (see appendix). In each case, the data were recorded
along a 40- by 5-m strip transect located along the prevailing topographic contour. In
the Sumatran site an intensive, multitaxon baseline study was undertaken across all
land use types by a group of animal and plant specialists. Above- and below-ground
biodiversity was assessed (large and small mammals, birds, insects, soil macrofauna,
and vascular plants) in addition to soil physicochemical variables and above-ground
carbon. The vegetation transect was the focal point for all other specialist studies
(details of methods are available in Gillison 2000a).
Data A n alysis
Data were compiled using a laptop computer and a recently developed software package, VegClass (Gillison 2001), that facilitates compilation of pfts according to the
rule set of Gillison and Carpenter (1997). The Windows-based software provides a
means of recording all field data according to a standardized format. These include
all site physical and vegetational features listed in table 4.4. In addition, the VegClass
Table 4.4 List of Data Variables Recorded for Each 40- by 5-m Plot
Site Feature
Descriptor
Data Type
Location reference
Location
Date (dd-mm-yr)
Plot number (unique)
Country
Observer(s) by name
Latitude (deg.min.sec., GPS)
Longitude (deg.min.sec., GPS)
Elevation (m a.s.l., aneroid and GPS)
Aspect (compass degrees, perpendicular to
plot)
Slope percentage (perpendicular to plot)
Soil depth (cm)
Soil type (U.S. soil taxonomy)
Parent rock type
Litter depth (cm)
Terrain position
General description and land use or landscape
context
Vegetation type
Mean canopy height (m)
Crown cover percentage (total)
Crown cover percentage (woody)
Crown cover percentage (nonwoody)
Cover abundance (Domin) of bryophytes
Cover abundance of woody plants 1.5 m tall
Basal area (mean of 3, m2/ha)
Furcation index (mean and coefficient of
variation % of 20)
Profile sketch of 40- by 5-m plot (scannable)
Family
Genus
Species
Botanical authority
If exotic (binary, presence–absence)b
Plant functional elements combined according
to published rule set
Unique taxa and PFTs per quadrat (for each
of 8 [5- by 5-m] quadrats)b
Hard copy and digital imageb
Alphanumeric
Alphanumeric
Alphanumeric
Text
Text
Alphanumeric
Alphanumeric
Numeric
Numeric
Observer(s)
Physical
Site history
Vegetation structure
Plant taxa
PFT
Quadrat listing
Photograph
GPS, global positioning system; PFT, plant functional type.
a
Summary of presence–absence by site for numerical analyses.
b
Not available for all sites.
Numeric
Numeric
Text
Text
Numeric
Text
Text
Text
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
Digital image
Text a
Text a
Text a
Text a
Numeric
Text a
Numeric
Digital and hard copy image
100
Thematic Research
software facilitates on-demand data summaries and graphs of desired combinations of
variables within and between plots that can be exported to industry-standard spreadsheet and relational database software. For data recorded for each contiguous 5- by 5m quadrat within the 40- by 5-m transect, graphs of cumulative species and pft totals
per unit area can be generated to allow the subjective inspection of asymptotic curves
as an indicator of sample efficiency for a specific vegetation type or lut (Gillison
2002). If needed, the sampling procedure can be used to discriminate between successional stages of vegetation independently of species. And because it contains adaptive morphological (pft) as well as taxonomic attributes, VegClass exhibits a higher
sensitivity to changes in environment than more traditional classification methods.
The same software was used to calculate pft-based, Shannon-Wiener, Simpson’s, and
Fisher’s alpha indexes as well as pfc.
The most efficient vegetation correlates of animal distribution acquired from an
intensive multitaxon survey in Central Sumatra were obtained by linear regression
(Pearson product moment) between all attribute values using the Minitab (version
13.32) software package. The most efficient plant-based predictors of animal taxa
overall were plant species richness, pft richness, species richness:pft richness ratio,
mean canopy height, and basal area of all woody plants. Using a method of multidimensional scaling (mds) of these variables (Belbin 1992) based on a Gower metric
similarity measure, the two best eigenvector solutions were extracted for each ecoregional dataset. These vectors were then plotted as a two-dimensional display of relative
site distribution. With this procedure, the raw data variables can be back-correlated
against each vector axis to determine their relative contribution to overall pattern
should this be needed. The data from all ecoregional sites were then pooled and the
mds procedure repeated to display the relative distribution for the entire dataset.
As an additional exploratory measure, for each ecoregional dataset, the same mds
procedure was used to extract the best single eigenvector. The single eigenvalues thus
acquired were standardized and ranked on a 1–10 scale for each site in order to identify any biodiversity-related trend according to an intuitive ranking of land use intensity gradients. For Brazil this was restricted to twenty-one sites in the Rondônia–Acre
region of the western Amazon Basin to focus on a more constrained pattern of land
use. These ranked values were used as an integrated vegetation index (V-index) (Gillison 2000a). The V-index is used here as an additional, potentially useful predictor
for biodiversity; high values indicate more complex vegetation structure and richness
in species and pfts. For this reason V-index values were included in the correlative
analyses of the Sumatran multitaxon baseline study.
R E S U LTS AND DISCUSSION
In the Sumatran sites, richness in both plant species and pfts, mean canopy height,
basal area, and cover abundance of understory woody plants were the most efficient
predictors of fauna (table 4.5). Among the better indicators there is a clear tendency
Plant
Species
Hymenoptera
Hemiptera
Formicidae, total
Formicidae
Diptera
Collembola
Coleoptera
Blattodea
Acari
Canopy Arthropods
Termite species
Termite abundance
0.190
0.576
0.124
0.716
0.312
0.350
0.643
0.033
0.038
0.912
0.274
0.415
0.371
0.538
0.098
0.774
0.302
0.367
0.844
0.017
0.849
0.016
Ground-Dwelling Arthropods
Faunal Groups
–0.232
0.493
–0.014
0.966
0.458
0.156
0.089
0.795
0.404
0.217
0.370
0.262
0.572
0.313
0.229
0.499
0.446
0.169
0.732
0.061
0.705
0.077
PFT
0.443
0.172
0.204
0.548
0.127
0.709
0.882
0.000
–0.197
0.562
0.142
0.676
–0.052
0.933
–0.026
0.920
0.129
0.705
0.944
0.001
0.976
0.000
Species
per
PFT
–0.465
0.150
–0.061
0.858
0.481
0.134
–0.130
0.703
0.350
0.291
0.426
0.191
0.829
0.021
0.254
0.454
0.426
0.192
0.654
0.111
0.564
0.187
PFC
0.328
0.325
0.086
0.801
0.166
0.625
0.776
0.005
–0.035
0.918
0.121
0.723
0.069
0.912
0.005
0.988
0.169
0.619
0.810
0.096
0.811
0.096
V-Index
–0.662
0.027
–0.452
0.162
0.075
0.826
–0.374
0.258
0.279
0.406
0.082
0.810
0.713
0.072
0.073
0.832
0.068
0.843
0.687
0.088
0.650
0.114
Shannon
0.624
0.040
0.563
0.071
0.231
0.494
0.402
0.221
0.002
0.995
0.145
0.671
–0.724
0.066
–0.032
0.925
0.194
0.567
–0.643
0.119
–0.630
0.122
Simpson
–0.648
0.031
–0.456
0.158
–0.093
0.785
–0.720
0.013
0.261
0.438
–0.054
0.875
–0.045
0.924
0.161
0.637
–0.063
0.854
–0.656
0.109
0.564
0.187
F-Alpha
0.356
0.283
–0.010
0.977
0.016
0.963
0.799
0.003
–0.066
0.847
–0.040
0.906
–0.177
0.776
–0.039
0.910
0.061
0.858
0.832
0.080
0.900
0.038
Mean
Canopy
Height (m)
0.427
0.190
0.075
0.827
0.111
0.746
0.768
0.006
0.077
0.821
0.030
0.929
–0.158
0.799
–0.061
0.858
–0.075
0.827
0.872
0.054
0.869
0.056
Basal Area
(m2/ha)
0.154
0.651
–0.287
0.392
–0.026
0.940
0.567
0.069
0.179
0.597
–0.235
0.487
–0.391
0.524
–0.495
0.121
–0.105
0.759
0.384
0.524
0.481
0.412
Crown
Cover
(%)
0.622
0.041
0.554
0.077
0.453
0.162
0.729
0.011
–0.158
0.644
0.576
0.064
0.005
0.993
0.507
0.111
0.560
0.074
0.748
0.053
0.773
0.041
WPlts
Table 4.5 Linear Correlationsa Between Richness of Plant Species, s and Their Ratios, and Various Animal Taxa and Above-Ground Plant Carbon
–0.704
0.016
–0.060
0.861
0.416
0.203
–0.739
0.009
0.453
0.161
0.234
0.489
0.522
0.366
–0.245
0.469
0.207
0.541
–0.767
0.130
–0.813
0.094
FI
0.417
0.203
–0.038
0.911
0.545
0.083
0.398
0.225
0.186
0.584
0.470
0.144
0.593
0.055
0.771
0.005
0.599
0.040
0.796
0.000
Plant
Species
0.140
0.681
–0.267
0.428
0.378
0.252
0.148
0.664
0.307
0.359
0.756
0.007
0.487
0.129
0.418
0.201
0.347
0.269
0.558
0.025
PFT
0.496
0.121
0.172
0.613
0.528
0.095
0.457
0.157
0.050
0.884
0.138
0.685
0.526
0.096
0.839
0.001
0.704
0.011
0.909
0.000
Species
per
PFT
0.192
0.571
–0.323
0.333
0.395
0.229
0.019
0.956
0.298
0.374
0.693
0.018
0.529
0.094
0.439
0.177
0.306
0.334
0.484
0.057
PFC
0.519
0.102
0.161
0.636
0.467
0.147
0.451
0.164
0.097
0.776
0.244
0.470
0.515
0.105
0.820
0.002
0.661
0.019
0.771
0.005
V-Index
–0.134
0.695
–0.509
0.110
–0.223
0.509
–0.457
0.158
–0.066
0.847
0.426
0.191
0.002
0.995
–0.101
0.768
0.157
0.627
0.383
0.143
Shannon
0.132
0.698
0.527
0.096
0.432
0.185
0.019
0.956
0.307
0.358
–0.099
0.772
0.261
0.438
0.294
0.380
–0.157
0.627
–0.295
0.268
Simpson
–0.308
0.337
–0.443
0.172
–0.531
0.093
–0.562
0.072
–0.042
0.903
0.061
0.859
–0.287
0.392
–0.483
0.133
–0.370
0.237
–0.380
0.147
F-Alpha
0.652
0.030
0.279
0.406
0.380
0.249
0.458
0.157
0.011
0.973
0.066
0.847
0.395
0.229
0.773
0.005
0.726
0.008
0.792
0.004
Mean
Canopy
Height (m)
0.444
0.171
0.271
0.419
0.345
0.298
0.471
0.144
0.074
0.829
0.124
0.717
0.422
0.196
0.774
0.005
0.625
0.024
0.730
0.011
Basal Area
(m2/ha)
0.289
0.389
0.464
0.151
–0.025
0.942
0.353
0.287
–0.162
0.635
0.020
0.954
0.078
0.819
0.429
0.188
0.291
0.447
0.626
0.039
Crown
Cover
(%)
0.076
0.824
–0.313
0.349
0.709
0.014
0.535
0.090
0.484
0.131
0.416
0.203
0.667
0.025
0.545
0.083
0.442
0.150
0.382
0.145
WPlts
–0.409
0.212
–0.212
0.532
–0.154
0.651
–0.019
0.956
0.184
0.588
0.352
0.289
–0.036
0.916
–0.406
0.216
–0.244
0.445
–0.535
0.090
FI
PFT, plant functional type; PFC, plant functional complexity; V-index, vegetation index; Shannon, Shannon-Wiener diversity index for PFTs; Simpson, Simpson’s diversity index
for PFTs; F-Alpha, Fisher’s alpha diversity index for PFTs; WPlts, cover abundance of woody plants 1.5 m tall; FI, mean furcation index canopy trees.
a
Correlation r value on first line of each cell. Probability value on second line.
b
Above-ground carbon data from Hairiah and van Noordwijk (2000).
Above-ground carbonb
Bird spp., total
Insects, unidentified
Insects, total
Thysanoptera
Spiders
Psocoptera
Orthoptera
Neuroptera
Isoptera (canopy)
Canopy Arthropods
Faunal Groups
Table 4.5 (Continued)
Above-Ground Biodiversity Indicators
103
for the species:pft ratio rather than species or pft richness alone to improve prediction for above-ground carbon and for certain animal groups such as birds, collembolans, and termites. There is no clear ecological reason as to why this ratio should be a
better predictor. However, one can speculate that higher ratios in the later and more
complex successional stages of forest development reflect less available above-ground
ecological niche space for larger (more readily measurable) organisms where more species are represented by fewer pfts.
When the general pattern of plant and animal taxonomic distribution along the
luts is examined, it is evident that the highest biodiversity richness occurs in certain
pristine forest types and in the more disturbed jungle rubber. This may be explained
partly by the nature of the available ecological niches in both. The jungle rubber
plots have both higher species and pft richness than the older growth forests but a
lower species:pft ratio. Whereas the former has allowed the development of cryptic terrestrial and arboreal habitats over a longer time frame, the younger and more
dynamic jungle rubber displays a much wider variety of ecological niches and canopy
gap openings where the fragmentary nature of the stand is maintained mainly by frequent disturbance from humans and to a much lesser extent by large mammals such as
elephants and tapirs. This is consistent with the intermediate disturbance hypothesis,
which states that highest species richness will occur in zones of intermediate disturbance rather than in old growth.
Although the high correlations for many variables do not in themselves provide a
valid argument for identifying cause and effect, in this study the traditional hypothesis that richness begets richness is consistent with forest successional trends and the
coevolution of increasingly complex food webs and abundance of autotrophs and heterotrophs including detritivores. The distribution of plant cellulose, as represented by
mean canopy height, basal area, and above-ground carbon, along a land use intensity
gradient corresponds closely with species and abundance of ground-dwelling termites,
and this may be explained in part by termite feeding habits (see also Bignell et al.
2000; Jones et al. 2002).
In surveys of tropical forested landscapes, meaningful correlates between plants
and birds can be difficult to achieve (Jepson and Djarwadi 2000; Beehler et al. 2001),
and in temperate regions investigations using plant functional groups to predict bird
distribution can be inconclusive (cf. Abernethy et al. 1996). This study may be the
first of its kind to reveal the potential of a newer suite of plant-based variables to predict bird species richness across a range of luts in tropical, forested landscapes. Table
4.5 reveals highly significant correlations between bird species richness, plant species
richness, species:pft richness ratio, mean canopy height, basal area, and V-index.
When bird species richness is correlated with the ratio of mean canopy height to
furcation index (fi) of canopy woody plants (indicative of branching density) the correlation r value increases to 0.792 (p = .006), indicating that bird species richness may
be a function of both canopy height and “branchiness.” A regression of bird species
richness against combined mean canopy height and fi gave a significant R2 of 53.2
V–index
Species per PFT
Total plant species
PFT
FI
Cover abundance of bryophytes
WPlts
Crown cover (%)
Basal area (m2/ha)
Mean canopy height
–0.719
0.002
–0.684
0.004
0.215
0.424
–0.285
0.284
–0.593
0.016
0.172
0.525
–0.402
0.123
–0.550
0.027
–0.683
0.004
0.664
pH–H2O
–0.828
0.000
–0.780
0.000
0.125
0.644
–0.206
0.445
–0.777
0.000
0.293
0.270
–0.471
0.066
–0.653
0.006
–0.745
0.001
0.755
pH–KCl
0.486
0.056
0.503
0.047
0.092
0.737
0.502
0.048
0.459
0.074
–0.144
0.594
0.878
0.000
0.716
0.002
0.405
0.120
–0.611
Organic C (%)
K
0.005
0.984
0.048
0.859
–0.063
0.818
0.475
0.063
0.097
0.720
0.093
0.732
0.609
0.012
0.329
0.214
–0.012
0.966
–0.174
N_tot, %
0.386
0.140
0.395
0.130
0.095
0.728
0.376
0.151
0.526
0.037
–0.026
0.925
0.742
0.001
0.550
0.027
0.278
0.298
–0.477
Table 4.6 Plant-Based Linear Correlatesa with Soil Physicochemical Attributesb
–0.205
0.446
–0.198
0.462
0.076
0.779
0.381
0.146
–0.164
0.545
0.175
0.516
0.393
0.132
0.104
0.700
–0.196
0.466
0.056
Na
–0.370
0.159
–0.347
0.188
0.278
0.298
0.300
0.259
–0.300
0.260
0.180
0.504
0.097
0.720
–0.225
0.403
–0.463
0.071
0.291
Mg
0.632
0.009
0.684
0.003
–0.057
0.833
0.296
0.265
0.697
0.003
–0.123
0.651
0.643
0.007
0.687
0.003
0.616
0.011
–0.688
Al
0.441
0.087
0.491
0.053
–0.107
0.694
0.512
0.043
0.584
0.018
–0.094
0.728
0.880
0.000
0.650
0.006
0.353
0.180
–0.575
ECEC
0.558
0.025
0.595
0.015
–0.089
0.743
0.137
0.614
0.527
0.036
–0.074
0.786
0.279
0.295
0.484
0.058
0.602
0.014
–0.544
Al_sat
–0.770
0.000
–0.784
0.000
–0.120
0.659
–0.627
0.009
–0.743
0.001
0.291
0.274
–0.890
0.000
–0.868
0.000
–0.742
0.001
0.852
Bulk Density
–0.593
0.016
0.172
0.525
–0.402
0.123
–0.550
0.027
–0.683
0.004
0.664
0.005
–0.283
0.288
0.352
0.181
–0.367
0.162
0.488
0.055
–0.777
0.000
0.293
0.270
–0.471
0.066
–0.653
0.006
–0.745
0.001
0.755
0.001
–0.387
0.162
0.231
0.390
–0.309
0.244
0.542
0.030
0.459
0.074
–0.144
0.594
0.878
0.000
0.716
0.002
0.405
0.120
–0.611
0.012
0.855
0.000
–0.507
0.045
0.722
0.002
0.240
0.370
0.526
0.037
–0.026
0.925
0.742
0.001
0.550
0.027
0.278
0.298
–0.477
0.061
0.722
0.002
–0.496
0.051
0.661
0.005
0.174
0.519
0.097
0.720
0.093
0.732
0.609
0.012
0.329
0.214
–0.012
0.966
–0.174
0.520
0.714
0.002
–0.545
0.029
0.647
0.007
0.585
0.017
–0.164
0.545
0.175
0.516
0.393
0.132
0.104
0.700
–0.196
0.466
0.056
0.838
0.503
0.047
–0.327
0.217
0.445
0.084
0.633
0.009
–0.300
0.260
0.180
0.504
0.097
0.720
–0.225
0.403
–0.463
0.071
0.291
0.274
0.084
0.757
–0.348
0.186
0.327
0.216
0.876
0.000
0.697
0.003
–0.123
0.651
0.643
0.007
0.687
0.003
0.616
0.011
–0.688
0.003
0.589
0.016
–0.366
0.163
0.479
0.060
–0.348
0.187
0.584
0.018
–0.094
0.728
0.880
0.000
0.650
0.006
0.353
0.180
–0.575
0.020
0.865
0.000
–0.732
0.001
0.866
0.000
0.290
0.276
0.527
0.036
–0.074
0.786
0.279
0.295
0.484
0.058
0.602
0.014
–0.544
0.029
0.208
0.444
–0.049
0.858
0.100
0.712
–0.651
0.006
–0.743
0.001
0.291
0.274
–0.890
0.000
–0.868
0.000
–0.742
0.001
0.852
0.000
–0.843
0.000
0.615
0.011
–0.767
0.001
–0.018
0.946
N_tot, total nitrogen; ECEC, effective cation exchange capacity; Al_sat, aluminum saturation; WPlts, cover abundance of woody plants 1.5 m tall; Bryo, cover abundance of
bryophytes; FI, mean furcation index of canopy trees; PFT, plant functional types; V-index, vegetation index; PFC, plant functional complexity; Shannon, Shannon-Wiener diversity
index for PFTs; Simpson, Simpson’s diversity index for PFTs; F-alpha, Fisher’s alpha diversity index for PFTs.
a
Linear correlation r value on first line of each cell, probability value on second line.
b
Soil analytical data from Hairiah and van Noordwijk (2000).
F-alpha
Simpson
Shannon
PFC
V–index
Species per PFT
Total plant species
PFT
FI
Cover abundance of bryophytes
106
Thematic Research
percent. This potential has been demonstrated in a similar, independent asb study in
northern Thailand (Gillison and Liswanti 1999).
Table 4.6 outlines correlations between plant-based variables and a range of soil
physicochemical variables; only the most statistically significant are listed. These
include highly significant correlations between certain soil variables such as bulk density, pH, organic carbon, total nitrogen and aluminum, species and pft richness,
vegetation structure, and V-index. There is no immediate explanation as to why these
soil attributes correspond more closely than others with both plant species and pft
richness. Land use practices also confound speculation about the biodiversity–soil
nutrient dynamic. In Jambi, Sumatra, for example, total soil nitrogen is highest in
monoculture rubber plantations (added artificial fertilizer), with only moderate species and pft richness, and in the (unfertilized) jungle rubber plots (plots 10 and
11, table 4.1) that are richest in plant taxa and pfts. Among the soil variables, bulk
density corresponds most closely with species and pft richness. Although diversity
indexes are rarely accepted without question as biodiversity indicators, in the present
study each of the pft-based, Shannon-Wiener, Simpson’s, and Fisher’s alpha values
is significantly correlated with a variety of key soil variables (table 4.6). The reasons
underlying this correlative pattern warrant study if cause-and-effect relationships are
to be better understood.
Evidence of plant morphological adaptation such as pfas (and by association pfts)
to varying soil nutrient conditions is widely documented along gradients of salinity,
pH, total and available nitrogen, phosphorus, and potassium and in certain extreme
soil and parent rock mineral complexes such as limestone and serpentinites. These
are characterized among well-documented plant assemblages such as “calcicolous” or
“serpentinite” flora. Despite clear trends between pfts and the nutrient and physical
substrate, physiological explanations for these phenomena usually are extraordinarily
complex (Larcher 1975) and are likely to be further confounded by soil–climate interaction. Apart from the correlates revealed here for humid, lowland tropical forested
lands, in boreal forests pH and soil organic matter content are considered to be among
the best soil-related predictors of biodiversity (Koptsik et al. 2001). Nevertheless, the
Sumatran study suggests that, for this area at least, despite a lack of evidence for cause
and effect, the utility of plants as indicators of biodiversity and related soil nutrient
availability (and hence potential agricultural productivity) is clearly enhanced by the
use of species richness, pft richness, and their ratios both individually and in combination. When combined with vegetation structural predictors of animal distribution (such as mean canopy height and basal area) these plant-based attributes become
potentially powerful indicators of animal habitat. Whereas terrestrial animal diversity
is governed largely by plants, in the study area, plant-based diversity in turn can be
shown to vary predictably with soil nutrients as well as pH and bulk density across all
luts. The Sumatran study does not aim to provide generic soil-based indicators of
biodiversity or to elucidate soil–plant dynamics. But it has produced a readily testable
hypothesis that certain soil variables are distributed in a predictable way with certain
Above-Ground Biodiversity Indicators
107
key plant and animal assemblages. If this model can be shown to hold, it will have
positive implications for adaptive management.
Multidimensional scaling of sites in Indonesia, Cameroon, and Brazil using the
plant-based variables listed in tables 4.1, 4.2, and 4.3 (with the exception of crown
cover percentage) reveal tight clustering of complex agroforests adjacent to intact forest. In Indonesia these are represented by jungle rubber (figure 4.1), in Cameroon by
both jungle and mixed Cacao plantations (figure 4.2), and in Brazil by complex agroforests containing cupuaçú, coffee, Bactris palm, and Brazil nut (Bertholletia excelsa
Humb. & Bonpl.) (figure 4.3). These clusters represent best-bet agroforestry scenarios
in each country. The ordinations (figures 4.1, 4.2, and 4.3) that compare similar luts
in Brazil, Cameroon, and Indonesia reveal consistent trends between plant-based biodiversity in complex agroforests and jungle rubber and Cacao along land use intensity gradients. These are clearly evident when examined in the context of gradient
extremes between degraded or highly simplified grasslands (including improved pastures) and intact forest. When the datasets from each ecoregion are combined and the
mds repeated (figure 4.4), a central zone for best bets is indicated, with the separation
between agroforests reflected mainly by regional differences in species richness and
with Sumatra and Cameroon indicating higher forest species and pft richness than
the Brazilian sites sampled in this study.
Figure 4.1 Multidimensional scaling of 16 plots along a land use intensity gradient in Sumatra. Dashed
lines indicate area of best-bet alternatives to slash-and-burn (in this case jungle rubber). See table 4.1 for
plot details and context of land use types.
Figure 4.2 Multidimensional scaling of 21 plots along a land use intensity gradient in Cameroon. Dashed
lines indicate area of best-bet alternatives to slash-and-burn (in this case periodically tended Cacao plantation and jungle Cacao). See table 4.3 for plot details and land use types.
Figure 4.3 Multidimensional scaling of 25 plots along land use intensity gradient in Brazil. Dashed lines
indicate area of best-bet alternatives to slash-and-burn (in this case periodically tended, mixed agroforestry plantation: cupuaçú, Bactris, and Brazil nut). See table 4.2 for plot details and context of land use
types.
Above-Ground Biodiversity Indicators
109
Figure 4.4 Multidimensional scaling of site data from all three ecoregions showing relative positioning
of relative best-bet agroforests in Sumatra (solid triangles), Cameroon (solid diamonds), and Brazil (solid
squares).
The V-index values for each ecoregion (figures 4.5, 4.6, and 4.7) reflect patterns
of vegetation complexity that correspond with an intuitive assessment of land use
intensity and, in the case of Sumatra, with patterns of plant and animal biodiversity.
As expected, across all ecoregions, similar values for low-productivity land use such as
cassava (Manihot exculenta Crantz) and degraded grassland are evident at the lowest
index values, with highest values recorded for older-growth and secondary forests. The
V-indexes are not designed to produce generic values for luts but rather a relative
within-region index that may be potentially useful in regional planning. It is of interest nonetheless that the two most similar land use gradients (Sumatra and Cameroon)
present similar V-index values for best-bet jungle rubber (Jambi sites 10 and 11, with
V-indexes of 7.9 and 7.6, respectively) and jungle cacao and 30-year-old plantation
cacao (Cameroon sites 10 and 15, with V-indexes of 7.0 and 7.7, respectively). The
Brazilian mixed agroforest plots 13 and 14 have V-indexes of 6.4 and 6.0, respectively
with higher values of 7.8 occurring in Capoéira secondary forest (forest that has reinvaded abandoned pasture land). The lower values for the Brazilian agroforests may
reflect age since establishment (7–8 years) where V-indexes can be expected to increase
with time but also the more intensively managed nature of the Brazilian systems.
Although the V-index is an integrated measure of vegetation complexity (species,
pfts, and structure) rather than biodiversity, the high correlations between V-indexes
and animal groups, especially birds (table 4.5), suggests it may have a useful role in
biodiversity assessment.
Figure 4.5 Land use types in Jambi, central Sumatra, ranked by vegetation index (V-index).
Figure 4.6 Land use types in Cameroon (Mbalmayo and Makam), ranked by vegetation index (Vindex).
Above-Ground Biodiversity Indicators
111
Figure 4.7 Land use types in Brazil (Rondônia and Acre), ranked by vegetation index (V-index).
Despite the improvements in plant-based biodiversity indicators recorded here,
generalizations from these lowland studies must be made with due care because other
preliminary studies (Gillison et al. 1996) indicate that similar predictive relationships
may not hold in highland tropical environments. More robust predictive models therefore will require similarly calibrated surveys but within a wider array of ecoregional
variation. Results emerging from parallel asb studies in Thailand and South Sumatra
(Gillison 2000b, 2000c) on the impacts of differing tenurial systems in coffee and oil
palm management systems also support the concept that complex agroforests provide
the best options for long-term management, despite the fact that short-term profit is
greatest where capital exists to promote permanent, intensive farming systems.
There is increasing evidence that biodiversity, at least in certain circumstances (cf.
those described by Tilman and Downing 1994), contributes to ecosystem stability
and productivity, although this is not without debate (Hector et al. 1999; Huston et
al. 2000; Loreau et al. 2001). In the present study, apparent links between agricultural
productivity and profitability suggest that apart from fertilizer-enhanced, permanent,
intensive cropping systems in which biodiversity is greatly reduced and short-term
profitability increased, higher biodiversity is associated with higher soil nutrients and
site productivity under longer fallows and under complex agroforests. Therefore a key
challenge is to identify the principal biophysical and socioeconomic drivers of biodiversity and related profitability. Current asb activities are pursuing this goal, seeking
how best to identify and calibrate indicators that can be used directly in a policy
112
Thematic Research
analysis matrix and in the formulation of appropriate policy interventions needed to
sustain both economic growth and biological diversity.
C O N C LUSION
The present studies demonstrate highly significant correlations between key plant and
animal species, functional groups, vegetation structure, above-ground carbon, and key
soil variables. These represent improvements on biodiversity predictors so far evaluated in other lowland, tropical, forested landscapes under slash-and-burn. Although a
clearer understanding of the soil–plant–land use dynamic is needed to better manage
ecosystem productivity, the study reveals potentially useful links between land use
type and biodiversity. As shown in this and other studies in tropical forests, elements
of vegetation structure can be used as a primary indicator of site productivity potential
and biodiversity, and they can be significantly enhanced by the addition of readily
observable plant functional types and key plant species. A best-bet option for managers of forested and agroforested lands is to maintain a mosaic of land cover types with
a focus on complex agroforests rather than intensive monocropping. This strategy
seeks to maximize the availability of ecological niches and thus biodiversity while sustaining an adequate soil nutrient base. Not only is this likely to enhance biodiversity,
but it may also serve as an added buffer to unexpected variation in environmental
and socioeconomic change. Incentives for adopting best-bet alternatives will be made
more attractive to all stakeholders if these outcomes can be used to demonstrate more
specific links between biodiversity and profitability.
Appendix
Plant Functional Attributes and Elements Used in the Plant Functional Type Grammar
Attribute
Element
Description
nr
pi
le
na
mi
no
me
pl
ma
mg
ve
la
pe
co
No repeating leaf units
Picophyll (<2 mm2)
Leptophyll (2–25 mm2)
Nanophyll (25–225 mm2)
Microphyll (225–2025 mm2)
Notophyll (2025–4500 mm2)
Mesophyll (4500–18,200 mm2)
Platyphyll (18,200–36,400 mm2)
Macrophyll (36,400–18 × 104 mm2)
Megaphyll (>18 × 104 mm2)
Vertical (>30° above horizontal)
Lateral (±30° to horizontal)
Pendulous (>30° below horizontal)
Composite
Photosynthetic Envelope
Leaf size
Leaf inclination
Above-Ground Biodiversity Indicators
Chlorotype
Morphotype
do
is
de
ct
ac
ro
so
su
pv
fi
ca
Dorsiventral
Isobilateral or isocentric
Deciduous
Cortic (photosynthetic stem)
Achlorophyllous (without chlorophyll)
Rosulate or rosette
Solid 3-dimensional
Succulent
Parallel-veined
Filicoid (fern; Pteridophytes)
Carnivorous (e.g., Nepenthes)
ph
ch
hc
cr
th
li
ad
ae
ep
hy
pa
Phanerotype
Chamaephyte
Hemicryptophyte
Cryptophyte
Therophyte
Liane
Adventitious
Aerating (e.g., pneumatophore)
Epiphytic
Hydrophytic
Parasitic
113
Supporting Vascular Structure
Life form
Root type
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5
Below-Ground Biodiversity Assessment
developing a key f u n c t i o n a l g ro u p
approach in best-b e t a lt e r n at i ve s
to sl ash and burn
David E. Bignell
Queen Mary, University of London London, England
Jerome Tondoh
Université d’Abobo-Adjame Abidjan, Côte d’Ivoire
Luc Dibog
Institut de Recherche Agricole pour le Développement Yaoundé, Cameroon
Shiou Pin Huang
Universidade de Brasília Brasília, DF, Brazil
Fátima Moreira
Universidade Federal de Lavras Lavras Minas Gerais, Brazil
Dieudonné Nwaga
Université de Yaoundé Yaoundé, Cameroon
Beto Pashanasi
Universidad Nacional de la Amazonia Peruana Yurimaguas, Peru
Eliane Guimarães Pereira
Universidade Federal de Itajubá Itajubá, Minas Gerais, Brazil
Francis-Xavier Susilo
University of Lampung Sumatra, Indonesia
Michael J. Swift
Tropical Soil Biology and Fertility Institute of CIAT Nairobi, Kenya
T H E IMPORTANCE OF BELOW-GROUND
B I ODIVERSIT Y
Plants make up most of the living biomass in terrestrial systems, are the basis
of food webs, and are thus the primary determinants of ecosystem structure
and function. As members of the below-ground biotic community, plants
share the soil environment with a suite of other organisms ranging from large
animals to bacteria. The latter community also helps to shape the ecosystem
because soil biological processes play a vital role in maintaining ecosystem
functions (Hole 1981; Lavelle 1996; Brussaard et al. 1997; Lavelle et al. 1997;
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van Breemen and Finzi 1998). The most important of these functions are thought to
be as follows:
• Decomposition of organic matter. This is carried out largely by bacteria and fungi
but greatly facilitated by soil animals such as mites, millipedes, earthworms, and termites, which shred residues and disperse microbial propagules. Collectively, such animals are known as litter transformers. The organic carbon released can be mineralized
as CO2 or CH4 or incorporated into various kinds of soil organic matter, which vary
in their stability and longevity but are generally in equilibrium with the inflows and
outflows of carbon from the system.
• Nutrient cycling. This is closely associated with organic decomposition and
includes transformations of nitrogen, phosphorus, sulfur, and other essential elements
as well as carbon. Although microorganisms mediate most of these transformations,
grazing by micropredators (protozoa and nematodes) can be rate-limiting. Larger animals may enhance some transformations by providing niches for microbial growth
within their guts, excrements, or nests. Specific fungi (mycorrhiza) and root-nodulating bacteria may form mutualistic associations with plant roots, which improve nutrient acquisition. Some soil bacteria are chemolithotrophic, that is, involved in elemental transformations without direct dependence on organic matter as a food source, but
may nonetheless be affected indirectly by such factors as water content, soil stability,
porosity, and carbon content, which the other biota control.
• Bioturbation. Plant roots, earthworms, termites, ants, and some other soil
macrofauna are physically active in the soil, forming channels, pores, aggregates, and
mounds or moving particles from one horizon to another, in ways that affect and
determine physical structure and the distribution of organic materials. Such soil ecosystem engineers (sensu Stork and Eggleton 1992; Jones et al. 1994) thereby create and
modify microhabitats for other smaller organisms and determine soil properties such
as aeration, drainage, aggregate stability, and water-holding capacity. In addition, the
macrofauna produce feces, which are organomineral complexes, stable over periods of
months or more (Lavelle et al. 1997).
• Suppression of soilborne diseases and pests. It is widely assumed that reduced
species diversity renders agroecosystems vulnerable to harmful soil organisms by
reducing overall antagonisms. Critical interactions influencing population stabilities may be those between micropredators and the bacteria and fungi on which they
feed.
• Environmental service functions. Examples are biodiversity conservation (allowing the replacement of functionally important species that are temporarily lost),
watershed protection from the preservation of soil structure (especially constancy
of stream flow and water quality), mitigation of greenhouse gas emissions (carbon
sequestration into long-term pools of complex organic matter by fungi and eubacteria, and methane oxidation by archaea), and bioremediation after specific pollution
events (metabolism of pesticides by eubacteria and sequestration of heavy metals by
a variety of organisms).
Below-Ground Biodiversity Assessment
121
In this chapter, we define functional group as an assemblage of species, of any taxonomic affiliation and living at whatever spatial scale, whose collective impact in a soil
ecosystem is one of the aforementioned generic ecosystem functions, with the assumption that all five functions must be manifested in any soil that has sustainable fertility
and structural stability. There is limited knowledge of the extent to which the biota
below ground and the functions its species perform depend on the biota above ground,
and vice versa. This limits predictions of the effects of land use change on ecosystem
processes and the evaluation of specific scenarios such as climate change, agricultural
intensification, and pollution. Furthermore, the question remains as to what relationship exists between species diversity, functional diversity (the number of functional
groups), functional composition (the nature of functional groups), and the occurrence
and intensity of ecological processes. The question of possible links between species
diversity and ecosystem stability is topical in ecology (Naeem et al. 1994; Tilman and
Downing 1994; Gaston 1996; Lawton 1996; Lawton et al. 1996, 1998). However, in
soil systems the poor state of taxonomy and the lack of agreed or adequate methods for
extracting and enumerating many groups have driven both theoretical treatments and
practical fieldwork to the use of the functional group concept as an indispensable aid to
assessing the role of the biota in maintaining ecosystem processes.
The minimum number of functional groups, and species within functional groups,
to ensure soil resilience against natural and anthropogenic stresses is not precisely known.
Circumstantial evidence and intuition suggest that stress and disturbance (defined as
the removal or disruption by humans of functionally significant components of the
natural forest ecosystem) affecting functional groups that are composed of few species
are the most likely to cause loss or reduction of ecosystem services. To the best of our
knowledge this holds for shredders of organic matter, nitrifying and denitrifying bacteria, bacteria involved with single–carbon atom compound and hydrogen transformations, iron and sulfur chemolithotrophs, mycorrhizal fungi, and bioturbators.
Ecological impacts by plants that affect soil include vegetation cover determining
soil climate, root penetration and water extraction affecting soil structure, and nutrient
supply to soil organisms, which is derived from a variety of litters and plant exudates,
including photosynthate transferred directly to microsymbionts (Swift and Anderson
1993; Angers and Caron 1998). The reverse relationship, that is, the impacts of soil
organisms on plants, includes formation and stabilization of soil structure, texturing,
and horizonation (Wilson and Agnew 1992; Lavelle et al. 1997; Angers and Caron
1998); nutritional provision (Douglas 1995); and modifications of microbial growth
conditions (Visser 1985). To these extents, above-ground diversity and below-ground
diversity are linked and mutually dependent, but whereas above-ground changes are
visible and documented, changes in soil communities are commonly overlooked, not
only because they may be invisible but also because there is no common standard for
survey and assessment (Wolters et al. 2000).
Intensification of agriculture, defined here as a reduction in the period in fallow
to period in crop ratio, can lead to fundamental transformation of vegetation cover or
to gradual alterations of existing land use without obvious botanical change (Scholes
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and van Breemen 1997). The goal of maximizing crop yield rapidly overrides all other
factors controlling plant community structure, so the morphological impacts of plants
on the soil community (i.e., microclimate) are immediately altered, with subsequent
changes in resource provision to soil biota as litter and exudates. There is therefore
ample justification for studying below-ground biodiversity in the context of any program addressing the sustained improvement of agricultural productivity (Swift and
Anderson 1993).
Alternatives to Slash and Burn (asb) is a global program designed to identify
optimal schemes for tropical forest-based subsistence agriculture that are consistent
with alleviating poverty, providing increased food security, enhancing environmental
resilience, and conserving biodiversity (Kenyatta 1997). A part of the program specifically addresses biodiversity issues, both above and below ground, with four main
activities:
•
•
•
•
Improving rapid assessment tools for biodiversity
Developing a biodiversity assessment database and models
Devising techniques for restoring or conserving native biodiversity
Building capacity of biodiversity assessment expertise
The asb aims to answer the question, What is the effect of land use change on
biodiversity, and what are the implications for ecosystem services and resilience and
for agricultural productivity? Here we report on what has been achieved with belowground biodiversity, concentrating on the development of a rapid assessment method,
the organization of results into a biodiversity assessment database, and the establishment of basic trends that may implicate soil biota in the maintenance of good soil
function. Our work mainly encompasses development of rapid assessment tools for
biodiversity and a biodiversity assessment database and models.
A S B WO RKING HYPOTHESES
The asb Soil Biodiversity Network operates under the following series of linked
hypotheses, which our field sampling was designed to test:
a. Agricultural intensification (as we define it) results in a reduction of soil
biodiversity.
b. Reduction in soil biodiversity leads to a loss of ecosystem function detrimental to sustained productivity.
c. Above-ground and below-ground biodiversity are interdependent across
scales of resolution from individual plant communities to the landscape.
d. Agricultural diversification promotes soil biodiversity and enhances sustained productivity.
e. Sustainable agricultural production in tropical forest margins is significantly improved by enhancement of soil biodiversity.
Below-Ground Biodiversity Assessment
123
Hypotheses (a), (c), and (d) can be answered from the data generated by belowground biodiversity sampling discussed in this chapter. Hypothesis (b) is best considered in the context of all asb data (i.e., the global synthesis), whereas hypothesis (e) is
to be addressed in later work programs within and following asb.
A P P ROACH AND METHODS
L a n d U s e Systems Sampled
A list of land uses sampled for below-ground biodiversity is given in table 5.1. In most
cases, the same sites were also sampled for above-ground biodiversity and emissions
of greenhouse gases (see chapters 2–4, this volume). Because of inevitable differences
in crop types, traditional practices, biogeography, socioeconomic development, and
national science capacities, equal sampling regimes could not be imposed in all four
countries. Nevertheless, it was possible to group the seventy-six sites investigated into
nine primary land uses along an intensification gradient, which forms the basic level of
analysis reported here. Where appropriate to assist clarity, we have consolidated land
uses into four generic categories: forest, agroforest, fallow vegetation, and crops. Differences within land uses and land covers, such as age of fallow, type of agroforest, and
the mixture of food crops, were deliberately included to embrace the full spectrum of
practices typical of particular regions and remain an implicit part of the database, but
they will be examined elsewhere.
Ta rg e t O rganisms and Functional Groups
Because the taxonomic diversity of soil biota is very high and many species are undescribed (Eggleton et al. 1996; Lavelle et al. 1997; Lawton et al. 1998; Hooper et al.
Table 5.1 Land-Use Systems Sampled for Below-Ground Biodiversity by , Showing
Number of Sites for Each Country
Land Use System
Brazil
Cameroon
Indonesia
Peru
Total
Primary forest
Logged-over forest
Secondary forest
Fallows (by age)
Tree plantation (by type)
Pasture
Agroforestry (by type)
Crop field (by type)
Imperata grassland
Total
—
3
—
3
—
3
3
3
—
15
1
—
2
2
—
—
1
2
—
8
2
5
1
—
2
—
10
5
6
31
2
1
3
4
2
3
2
5
—
22
5
9
6
9
4
6
16
15
6
76
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Thematic Research
2000), selection of representative organisms to sample is essential before fieldwork
can be attempted. In addition, there is no single method available for addressing soil
biodiversity, so it is necessary to adopt a subset of protocols that can be accommodated
in a single field campaign, within the resources available. We selected seven target taxa
(table 5.2) on the basis of their diverse functional significance to soil fertility and overall ease of sampling simultaneously, across a range of land use types. These groups and
some of their important functional group affiliations are described here:
• Earthworms, which influence both soil porosity and nutrient relations through
channeling and ingestion of mineral and organic matter. Earthworms can be divided
into further functional categories: epigeic (living and feeding on the surface), anecic
(living below ground but feeding on the surface), and endogeic (living and feeding
below ground).
• Termites and ants, which influence soil porosity and texture through tunneling, soil ingestion and transport, and gallery construction and nutrient cycles through
transport, shredding, and digestion of organic matter. Ants can be further classified by
feeding habits: carnivores, generalists, seed collectors, and honeydew feeders. Termites
are heuristically divided into grass-feeders, wood-feeders, wood- and soil-feeders, and
soil-feeders (Bignell and Eggleton 2000), but other trophic functional classifications
are possible, based on gut content analysis (Donovan et al. 2001)
• Other macrofauna, which for our purposes includes woodlice, millipedes, and
some types of insect larvae that act as litter transformers, with an important shredding
action on dead plant tissue. Their predators (centipedes, larger arachnids, some other
types of insect) usually are sampled at the same time when pitfall traps are used and
can be included in enumerations. These other macrofauna may be considered together
with termites and ants (sampled separately), as “all macroarthropods.” All macrofauna
means all macroarthropods, together with earthworms.
• Nematodes, which influence turnover of carbon and nutrients in their roles as
root grazers, fungivores, bacterivores, omnivores, and predators; occupy existing small
pore spaces, in which they depend on water films; and usually have very high generic
and species richness. Nematodes can be given a functional classification as bacterivores, fungivores, plant parasites, omnivores, and predators (Yeates et al. 1993).
• Mycorrhizae, which associate with plant roots, improve nutrient and water use,
and reduce attacks by plant pathogens.
• Root-nodulating bacteria, which transform N2 into forms available for plant
growth.
• Overall microbial biomass, which is an indirect measure of the total decomposition and nutrient recycling community of a soil. It is contributed by fungi, protists,
and bacteria (including archaea and actinomycetes).
Functional distinctions are essentially idiosyncratic for any given taxon but helpful in data analysis. Two obvious exclusions from the taxa investigated are mesofauna
(principally mites, other small arachnids, and collembolans) and protists. The exclu-
Table 5.2 Biotic Groups Addressed by Below-Ground Sampling During Campaigns in
Four Countries
Biotic Group
Datasets Obtained, by Country
Brazil
Cameroon
Indonesia
Peru
All macrofauna
Abundance,
biomass
Abundance,
biomass
Abundance,
biomass
Termites
Abundance,
biomass
Ants
Abundance,
biomass
Abundance,
biomass,
-diversity
Abundance,
biomass
Earthworms
Abundance,
biomass
Abundance,
biomass
Abundance,
biomass,
functional group
diversitya
Abundance,
biomass,
-diversitya
Abundance,
biomass,
-diversitya
Abundance,
biomass, trophic
group diversitya
Abundance,
diversity indices
Abundance,
trophic
dominance
—
Abundance
—
—
Abundance
—
Diversity after
trapping
Quantitative,
morphotype
diversity
Percentage
examined
Percentage in
sample
Quantitative
Percentage in
sample
Quantitative
—
Percentage
examined
Diversity from
capture
—
Diversity from
capture
—
—
Quantitativec
Quantitative
Quantitatived
—
Quantitative
Quantitatived
—
—
—
Abundance,
biomass
Abundance,
biomass
Abundance,
biomass,
-diversity
Nematodes
Generic
Trophic group
Mycorrhizae (arbuscular mycorrhizal fungi)b
Generic
—
Spore counts
Quantitative
Root infection
—
Root-Nodulating Bacteria
Generic
Strain
Symbiotic efficiency
MPN
Microbial biomass
(as carbon)
Diversity from
explant
Limited diversity
data
Quantitativec
Quantitative
Quantitatived
-diversity, species richness; MPN, most probable number per unit of soil volume.
a
Not all sites.
b
Unless otherwise specified, quantitative indicates number per unit of soil volume.
c
Either shoot dry weight or nodule dry weight after capture.
d
Weight per gram of dry soil.
—
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Thematic Research
sion arises from the lack of adequate taxonomic expertise and, in the case of protists, a
real lack of practical sampling methods rather than ignorance of their important role
in soil systems.
Table 5.2 shows the types of data obtained for these seven broad taxonomic groups
in four countries. Although the asb campaign addresses biodiversity, resolution at the
species or strain level (α-diversity) was not achieved in every case. In diverse groups,
such as, Brazilian nematodes, which were distributed in 159 genera (S. Huang, pers.
comm. 1999), and termites, where morphospecies are commonly used (Dibog 1998;
Eggleton et al. 1999), generic diversity and morphospecies diversity are assumed to be
adequate surrogates.
Additionally, it is usually possible to add to basic data on abundance and biomass
by allocating specimens or whole taxonomic units to broad functional groups. This
is illustrated by the three groups of earthworms described earlier, a classification that
can also be applied to the “all macrofauna” category. For microsymbionts, raw data on
propagule abundance or inoculum potential in soil samples are less meaningful without some measure of efficiency or suitability for mutualism. In best practice, therefore,
microsymbiont diversity should be assessed after capture or trapping by candidate
host plants, although some information and taxonomic allocation can be made from
spore morphotypes.
To an extent, the biology of particular groups dictates the nature of the diversity
measurement; for example, abundance is not the same concept for macrofauna and
root-nodulating bacteria because the former are enumerated as living individuals of
whatever condition and the latter are numbered as nodule-forming units (i.e., on
the basis of viability as a symbiont). However, sampling methods also impose their
own constraints, particularly within the asb remit of applying rapid assessment techniques simultaneously across the entire taxonomic spectrum of soil biota. Lawton et
al. (1998) make the point that sampling effort and taxonomic difficulty in biodiversity measurement both increase with decreasing size of the organisms concerned. The
concept is neatly illustrated by the present study: Whereas macrofauna are sampled by
simple capture, nematodes first must be extracted and microsymbionts must be either
extracted and then multiplied or isolate, captured, and cultured. Available time and
resources therefore limit diversity data much more at the lower end of the size scale.
With bacteria, the task of determining diversity is daunting: Torsvik et al. (1996)
estimate that 1 g of soil could contain 108 to 1010 different strains. We argue that it
is therefore acceptable to add crude surrogates, such as percentage root infection and
total microbial carbon. In the absence of taxonomic expertise and resources, abundance and biomass data at the site level, without specific diversity indexes, are also
useful in addressing asb objectives.
A full dataset to meet all asb objectives for characterizing below-ground biodiversity would comprise the following:
• Diversity (or taxonomic richness) at the strain, species, genus, and higher
taxonomic level for target taxa
Below-Ground Biodiversity Assessment
127
• Abundance in mean individuals or colony-forming units per square meter
(transformation as [log10 x + 1] with 95 percent confidence interval is helpful; see Eggleton et al. 1996)
• Biomass in grams per square meter (normally on a wet weight basis, with
log transformation)
• Taxonomic community composition as a percentage per taxon (based on relative abundance and relative biomass)
• Functional community composition as a percentage per functional group
(based on relative abundance or relative biomass) or ± basis
• Diversity indexes combining species richness and relative abundance (see
Southwood 1978)
Th e F i e l d Transect
The methods used to sample soil biotas, the original Tropical Soil Biology and Fertility (tsbf) Programme protocols, and our current recommendations of best sampling
practice are summarized in table 5.3. A full discussion of sampling is beyond the
scope of this chapter (for a fuller consideration, see Swift and Bignell 2001), but our
approaches should be seen as an evolution of methods from the basic field transect
recommendation for macrofauna made by Anderson and Ingram (1993). The main
premises are to have rapid assessment (this roughly means completing field sampling
of any one site in 1 or 2 days) and to be able to address all the biotic groups targeted
at the same time and in the same place. This is the rationale of the short transect,
which also has the advantage of fitting into the small plots of fallow and food crops
that typify tropical subsistence agriculture. In larger plots a transect can, in theory,
examine whether proximity to the plot boundary (i.e., to the forest margin) influences
below-ground biodiversity.
The main additions to the original tsbf protocol are an increase in the length of
the transect from 25 to 40 m, increases in the number of monoliths (for macrofauna
assessment) and cores taken (for nematodes and microsymbionts) within the transect,
and extra sampling for termites and other macrofauna outside (but adjacent to) the
transect (Jones and Eggleton 2000). The modifications are intended to increase the
accuracy of biodiversity assessment by achieving resolution at both the species and the
functional group level but also to mitigate the variability of data from short transects
for groups with typically patchy distributions. There are two key issues: For quantitative sampling, how much replication is necessary to assess the true variance in the
abundances of soil biota? For qualitative sampling, how much of a given habitat must
be investigated to sample its inherent diversity adequately (this means identifying all
the functional groups present)? Although it is easy to design theoretical sampling that
is statistically sound, it is much more difficult to devise procedures that can be applied
across diverse taxa, within strict time limits and limited budgets, and often in remote
locations.
Peru
[Additionally]
Indonesia
Adopted
[Additionally]
[Additionally]
Cameroon
Adopted
[Adjacent 100-m
termite transect]
40- by 5-m transect
[10 pitfalls]
5 or 9 monoliths
[10 pitfalls]
5 monoliths
40 by 5 m transect
[Adjacent 100-m
termite transect]
—
5 monoliths
5–10 monoliths
Macrofauna
—
25- by 4-m transect
25- by 4-m transect
TSBF
recommendations,
ca. 1993
Brazil
Adopted
Sampling Plot
Suggested and
Adopted
—
—
—
—
—
10 composite cores (2)
5 cores, bulked
Nematodes
Table 5.3 Methods Used for Below-Ground Biodiversity Sampling by : Theory and Practice
—
—
8 composite cores
(20)
[Root inspection]
—
3 composite cores
(6)
5 composite cores
at 1-m separation
Mycorrhiza
1 core in each of 3
subplots
—
[Root inspection]
Same soil
[Nodule inspection]
20 cores, bulked
5 composite cores
at 1-m separation
and nodule
dissection
Root-Nodulating
Bacteria
Same soil with
fumigation and
extraction
Same soil with
fumigation and
extraction
4 composite cores
(5) with fumigation
and extraction
—
TSBF fumigation
and extraction
Microbial Biomass
40- by 5-m transect; 3
transects per site and
100-m termite transect
25- by 25-m plot
[Adjacent 100-m
termite transect]
40- by 5-m transect
10 monoliths of 25 by
25 by 10 cm and 10
pitfalls
10 or 20 monoliths in
1 or 3 transects per
plot
[10 pitfalls]
5 or 9 monoliths
[10 pitfalls]
5 monoliths
40 by 5 m transect
[Adjacent 100-m
termite transect]
—
—
—
3–5 composite
cores (20) at 4- or
5-m intervals
3–5 composite cores
(20) at ca. 4-m
intervals, using zigzag
sampling pattern
—
—
8 composite cores
(20)
[Root inspection]
—
—
—
—
—
—
—
3–5 composite
cores (20) at 4- or
5-m intervals
—
1 core in each of 3
subplots
—
[Root inspection]
Same soil
[Nodule inspection]
Amato and Ladd
(1988) fumigation
and extraction
—
Same soil with
fumigation and
extraction
Same soil with
fumigation and
extraction
—
Unless otherwise specified, monoliths are 25 by 25 by 30 (depth) cm and cores are 1 to 7 cm diameter to 20 cm depth. Bulked means all samples thoroughly mixed together. Composite
means mixing samples from a defined portion of the transect, such as two cores from each 1-m subsection. Number of samples mixed, where specified, is given in parentheses. One
transect is used per site, although this may be divided into subplots. Unless otherwise indicated, all sampling is within the transect; “[additionally]” indicates sampling added on local
initiative.
TSBF, Tropical Soil Biology and Fertility Programme.
[
Best practice (per
transect)
Peru
Adopted
[Additionally]
Indonesia
Adopted
[Additionally]
[Additionally]
Cameroon
Adopted
130
Thematic Research
Figure 5.1 Idealized field sampling protocol for below-ground biodiversity. Two quantitative transects of
40 by 5 m and one qualitative transect of 100 by 2 m are recommended per plot.
Figure 5.1 illustrates our concept of best sampling practice but is not intended
to be prescriptive. Although we recognize that two transects should be deployed per
plot, almost all the actual sampling we report has used only one. Sampling should
take place under the most stable conditions available, toward the end of the rainy season and at the maximum biomass of crops (before senescence). To avoid unintended
disturbance, we recommend sampling in the order pitfalls, then cores or roots, then
monoliths, then termite transect. In practice, no more than twelve people can be
involved without mutual interference and excessive trampling of a site.
I L LU S T RATIVE RESULTS
D e m o n s trating Biodiversit y Change in Rel ation
to L a n d Use
Taxonomic groups showed significant differences in below-ground biodiversity between
different land uses (table 5.4), but the trends differ between countries and between
taxa. For example, overall macrofaunal diversity across seven land uses in Jambi Province, Sumatra, Indonesia, varied from more than seventy species or morphospecies per
Table 5.4 Summary of Answers to Key Questions and Comments on Functional
Implications
ASB Question
Affirmative Evidence
Qualifying Comments
Functional
Implications
1. Does LUS change
affect BGBD?
Macrofauna, termites,
nematodes,
mycorrhizaRootnodulating bacteria
Macrofauna, termites
(reduction and
community change);
nematodes
(community change);
cf. mycorrhizae
(increase and
community change)
Macrofauna, termites
Not all countries or sites.
Sustainability or
renewal of soil fertility
may be compromised.
Not all countries or sites.
Trends different within
macrofauna (termites vs.
earthworms) and
between macrofauna and
smaller biota.a
Management systems
and site histories may
be influential.
Agroforestry retains
macrofaunal diversity in
three countries, but trend
is opposite for smaller
biota.
Loss of canopy reduces
some macrofauna, but
others are unaffected.No
consistent evidence for
smaller biota.
Link to woody basal
areas and plant
functional modi.
Link to shoot dry weight.
Canopy cover promotes
the large biota, but
agroforestry is variable
in its nature and
effects.
Soil ecosystem
engineers may be more
vulnerable.
2. Does agricultural
intensification reduce
BGBD or affect
community
composition?
3. Does agricultural
diversification promote
or sustain BGBD?
4. Is extreme
disturbance highly
damaging to BGBD?
Macrofauna, termites
5. Is BGBD linked to
AGBD or production?
Termites
Root-nodulating
bacteria
6. Is BGBD influenced
by proximity to forest?
Macrofauna, termites
7. Are there effects on
Macrofauna
abundance and biomass
independent of BGBD?
Microbial biomass
New crop fields and
small crop fields are
more forest-like.
Intermediate disturbance
favors ants and
earthworms.
Earthworms promoted at
intermediate disturbance
without great diversity.
Diminishes with
agricultural
intensification.
Termites are good
indicators of niche
diversity.
High soil abundance
may promote plant
production.
Short fallow rotations
are damaging to soil
biotas.
Soil biotas are robust,
except at extremes of
disturbance.
LUS, land use system; BGBD, below-ground biodiversity; AGBD, above-ground biodiversity.
a
Smaller biota means nematodes, mycorrhiza, and root-nodulating bacteria.
132
Thematic Research
transect in jungle rubber, to fewer than ten in a degraded cassava (Manihot esculenta
Crantz) garden site, with intermediate diversity in other sites including pristine forest
and tree plantations (figure 5.2). In Cameroon, an average macrofaunal diversity of sixty units was associated with the Chromolaena odorata (L.) King & H.E. Robins fallows
characteristic of low-input indigenous agriculture, compared with forty in mature forests and slightly lower levels (i.e., less than forty) in agroforest and crop fields. However,
there were fewer variations across land uses in Peru (eighteen to twenty-six taxa), Brazil
(ten to twelve taxa), and a site sequence in the Lampung region of Sumatra (fourteen to
nineteen taxa), suggesting that land management impact on diversity in these systems
is low, or perhaps that they are in a more depauperate state overall.
For Cameroon macrofauna, the expression of data as the Shannon-Weaver diversity index (which combines species richness and relative abundance) reveals a somewhat different pattern than α-diversity alone: the highest Shannon-Weaver value
(2.69 ± 0.43) was associated with agroforest, as was the highest α-diversity, but the
lowest (1.01 ± 0.35) was for primary forest, which had intermediate α-diversity. Fallows
were still high (2.40, 2.47), but two crop fields were also significantly different from
Figure 5.2 Summary of macrofaunal biodiversity, abundance, and biomass across a forest disturbance
gradient (left to right) in Jambi Province, Sumatra, Indonesia. Land uses are as follows: BS1, primary
forest; BS3, logged-over forest; BS6, silviculture plantation; BS8, rubber plantation; BS10, jungle rubber agroforestry; BS12, alang-alang (Imperata cylindrica [L.] Raisch) degraded grassland; BS14, cassava
garden. Taxonomic diversity score = ant species + termite species + earthworm species + other groups at
ordinal level.
Below-Ground Biodiversity Assessment
133
one another (1.59 vs. 2.81). This difference between the two assessments (species richness and diversity index) illustrates the high information content inherent in the data
but also the need for multivariate analysis to achieve resolution at all spatial scales.
A different approach for looking at effects of land use can be taken by focusing
on single taxa, which can be identified to species level (termites, ants, and earthworms in the present work). For example, about one-half of the macrofaunal diversity in the Jambi sequence (figure 5.2) is attributable to termites. There were thirty
species in primary forest, compared with ten in rubber (Hevea brasiliensis [Willd. ex
A. Juss.] Muell.-Arg.) plantation and twenty-one in jungle rubber (a form of agroforest). Ants have the opposite dynamic, rising from sixteen species in primary forest to
twenty-four in tree plantation and peaking at thirty-three in jungle rubber. The combination of ant and termite dynamics gives a more complete picture of biodiversity
changes than either taxon alone and is all the more remarkable considering that ant
abundance and biomass are not significantly different across the whole gradient (see
comments on abundance and biomass determinations later in this chapter). Earthworm diversity is generally low in tropical forest systems, but biomass contributions
can be extremely large.
Table 5.5 summarizes the data obtained for nematodes in Brazil. The different
diversity values of generic richness, Shannon’s and Simpson’s indexes, are consistent
with each other in showing that the lowest diversities are associated with pasture and
food crop fields and the highest with fallow and agroforest. Nematode abundance, on
the other hand, is lowest in agroforest and food crop fields and highest in pasture. The
abundance of root-nodulating bacteria is lowest in agroforest and highest in pasture
(table 5.6).
Data for mycorrhizal diversity are few and are insufficient to permit statistical
analysis, but in Cameroon there is some suggestion of a decline in richness from forest to other land uses. However, there is also a difference between diversity estimated
from the spores in soil and that resulting from bioassay. Arbuscular mycorrhizal fungi
cannot be cultured in vitro, so diversity assessment depends heavily on morphology.
Counts of arbuscular mycorrhizal spores in soils in Brazil and Indonesia showed higher abundance in crop fields and grasslands than in other land uses. However, diversity
data for Indonesia showed that richness varied only from twelve to fifteen species
across the sites (not tabulated), so the changes with land use may not be extremely
relevant. Diversity data are not yet available for rhizobia, but estimates of symbiont
efficiency (the diversity of host plants nodulated, arguably a reasonable substitute) do
not show distinctions between land uses.
D e m o n s t rating Functional Group Change in Rel ation
to L a n d Use
We argued earlier that functional groups can substitute for species (or strains) in organisms whose taxonomy is difficult, but they also provide relevant additional information
134
Thematic Research
Table 5.5 Assessment of Nematode Communities in Five Land Use Systems of Amazonal Forest
Margins
Parameter
Disturbed
Forest
Fallow
Agroforestry
System
Pasture
Annual
Crop
1.7145 aba
1.5966 ab
1.2985 b
2.4012 a
1.2258 b
7.305 ab
6.6912 bc
1.012 b
8.126 a
10.7709 a
1.177 a
8.24 a
8.7127 ab
1.132 a
5.819 c
5.7554 c
0.9337 b
6.821 bc
6.0437 c
0.9606 b
2.004 d
0.5279 a
69.65 a
10.6 d
2.978 a
0.3583 c
43.72 c
24.22 a
2.847 ab
0.3918 c
53.14 b
17.66 bc
2.171 cd
0.4902 ab
65.28 a
13.63 cd
2.559 bc
0.4182 bc
53.72 b
22.93 ab
0.9761 a
0.1638 d
0.2148 b
0.7609 a
0.7929 ab
0.4264 bc
0.6469 ab
0.2256 cd
0.5789 ab
0.5420 b
3.406 a
3.178 d
3.303 ab
3.566 bc
3.317 ab
3.801 ab
3.065 bc
3.994 a
2.929 c
3.444 cd
Abundance
Number 10–6/m3
Diversity
Generic richness
Simpson’s index
Shannon’s index
Trophic Function
Trophic diversity
Trophic dominance
Plant parasites (%)
Bacterial feeders (%)
Decomposition Pathway
Fungivores and bacterivores
(Fungivores bacterivores)/
plant parasites
Soil Disturbance Level
Maturity indexb
Plant parasitic index
Different letters in horizontal level indicate difference at Tukey’s test (p .05).
Lower values indicate more disturbed environments (Bongers 1990; Freckman and Ettema 1993).
a
b
about ecosystem function. The Brazilian nematode dataset (table 5.5) shows that the
reduction in generic richness and associated diversity indexes in pasture and food crop
fields, relative to forest, is not reflected to the same extent by the indexes of trophic
diversity, trophic dominance, and the abundance (percentage total) of plant-feeding
and bacterial-feeding groups. This can be interpreted as support for the conclusion
that the fauna remains functionally robust over the range of land uses, land covers,
and disturbances surveyed, with functional diversity being retained despite the reduction in generic richness. Fallow is noticeably different in functional composition, with
more bacterial feeders. However, the maturity index points to the food crop field as
the most disturbed land use. This index broadly assesses the balance between colonizers (species with high rates of reproduction and tolerant of disturbance) and persisters
(typically with long life cycles and low rates of reproduction). On the basis of all these
assessments, three tree-based systems (secondary forest, agroforest, and fallow) can be
distinguished from two nontree systems (pasture and food crop field).
Table 5.6 Trends in the Diversity of Mycorrhizal Fungi in Cameroon and in the Abundance of
Root-Nodulating Bacteria in Brazil, in Both Cases Across Disturbance Gradients from Forest to
Food Crop Field and Pasture a
Cameroon
Land Use
and Site
Brazil
Mycorrhizal Diversity Land Use and Abundance of Rootby Morphotypeb
Site
Nodulating Bacteria
Nodulation
Efficiency
From Field After
Soil
Trapping c
MPNd (cells 95%
per g soil)
Confidence
Interval
as Siratro
Shoot Dry
Matter (mg)e
—
—
Primary Forest
Akokas
5
10
Secondary Forest
Akokas
Nkolfoulou
6
8
5
6
3
4
6
6
210
1,684
346
73–604
585–4,856
120–998
25.34 bcde
19.32 efg
22.25 cdef
Theobroma 2
Pedro Peixoto
Theobroma 1
10,123
3,735
147
3,511–29,184
1,296–10,768
51–425
20.60 def
15.67 fg
28.20 abcd
21–177
87–724
5–42
32.18 ab
23.50 bcde
—
732–6,088
103–856
78–647
29.85 abc
23.65 bcde
27.12 abcd
3,511–20,184
58–480
35.47 a
22.27 cdef
29.10 abcd
Agroforest
5
6
Food Crop Field
Akokas
Awae
Theobroma
Pedro Peixoto
RECA
Fallow
Agroforest
Awae
—
Disturbed Forest
Fallow
Akokas
Nkolfoulou
—
5
1
RECA
Jı́-Paraná 2
Jı́-Paraná 1
61
251
15
Food Crop Field
9
8
Theobroma
Theobroma
Pedro Peixoto
2,112
297
224
Pasture
Pedro Peixoto
Jı́-Paraná
Theobroma
Total
17
different
morphotypes
22
—
20,000
10,123
166
—
—
RECA, Reflorestamento Econômico Consorciado Adensado.
a
Note that the two gradients are not exactly equivalent.
b
Identified to generic level from Morton and Benny (1990) and Schenck and Peres (1990).
c
Using Vigna unguiculata (L.) Walp and Pennisetum americanum (L.) Leeke as host plants.
d
From siratro cultured in sterile Jensen’s solution, inoculated with serial soil dilutions. MPN, most probable
number (method in Woomer et al. 1990).
e
Means with the same letter are not significantly different (Duncan 5%).
136
Thematic Research
Similar functional distinctions can be recognized in macrofaunal groups (between
feeding groups) and between root-nodulating bacteria (between promiscuous and
host-specific strains). As an example, the changes in termite diversity observed across
the Jambi, Indonesia, land use sequence (figure 5.2) consist largely of losses of soilfeeding species, whereas wood-feeding and grass-foraging species are less affected.
Taken together with abundance and biomass data, this might permit the conclusion
that termite-mediated wood and litter decomposition would be unchanged under
light and moderate disturbance, but the soil-conditioning role, normally the prerogative of soil feeders, might be compromised. Soil-feeding termites are known to be very
sensitive to canopy reduction, and in the same land use sequence it can be shown that
termite species richness and relative abundance are both highly significantly correlated
with botanical species richness, canopy cover and woody plant basal area (A. N. Gillison et al., unpublished data 2002).
Functional group classifications usually are taxon-specific. However, some simple
categorizations can be applied more generally. Figure 5.3 shows the relative change
in functional group abundance for macrofauna across the Jambi land use sequence,
using the epigeic, anecic, and endogeic classification first established for earthworms
(Lavelle et al. 1997). The broad trend here is the loss of anecic and endogeic species
as disturbance intensifies (jungle rubber is a possible exception). These are the organisms responsible for soil conditioning (rather than decomposition per se). The result
Figure 5.3 Proportion (by abundance) of macrofaunal functional groups across a forest disturbance gradient (left to right) in Jambi Province, Sumatra, Indonesia. For land uses, see figure 5.2.
Below-Ground Biodiversity Assessment
137
therefore underscores the conclusions reached from termite diversity and shows that
functional diversity can be more useful in demonstrating significant changes in the
below-ground community than trends of abundance and biomass.
A bu n d a n ce and Biomass in Rel ation to Land Use
Abundance and biomass are problematic parameters for soil biotas because of high
variance and the impracticality of sampling at high replication (see Eggleton et al.
1996; Swift and Bignell 2001). Unsurprisingly, species richness and functional group
diversity often provide a distinction between land uses more readily, and with much
less effort (Eggleton and Bignell 1995; Jones and Eggleton 2000). Nevertheless, the
delivery of any given role or process in an ecosystem must be related to the abundance or biomass of the organisms responsible, and therefore these quantities cannot
be ignored. As an example, figure 5.2 shows that trends in the total abundance and
biomass of macrofauna across the Jambi land use sequence are different from and less
clear-cut than those of taxonomic diversity. The notable peaks associated with tree
plantation (BS6) and jungle rubber (BS10) are contributed largely by earthworms,
although their diversities are hardly rich and exceed those of other sites by only one or
two. In the same land use sequence, there are no significant differences for ant abundance and biomass. With termites, post hoc comparisons by Mann–Whitney show
that the pristine primary forest site has significantly higher abundance and biomass
than any of the others, but otherwise there are few differences between land uses,
except for the degraded Imperata grassland, which has few termites and is depauperate.
These results further emphasize the value of the functional group concept in achieving
resolution between different agroecosystems.
Data on microbial biomass in the Brazilian land use sequence show that the secondary forest had significantly greater microbial carbon than pasture and agroforest.
In Indonesia (Lampung sites), secondary forest had significantly more microbial carbon than all other sites, followed by agroforest, which was significantly greater than
tree plantation and Imperata grassland, both of which were significantly greater than
food crop fields. Therefore there is some agreement between data for different microbial groups and data for microbial biomass, at least to the extent of suggesting that
agroforest and food crop field land uses may be impoverished compared with fallow,
if not with forest.
C O N C LU SION
Assessment of the value of the work completed to date turns on three issues: Have
we answered the asb questions in whole or in part? Are we justified in our selection
of taxa or functional groups? Have we learned from our experience by changing our
methods and improving our skills?
138
Thematic Research
The asb below-ground biodiversity working hypotheses have been reworked into
questions, which are presented in table 5.4. Some answers can be offered to at least
some of those questions from the results presented earlier. An obvious criticism is that
too many examples of links between land use and below-ground biodiversity are drawn
from the macrofauna, which are the easiest group to sample. This does not invalidate
evidence from macrofauna but does point to the need for improved methods with
other groups that mediate different functions in the ecosystem. The observation that
trends across land use sequences and along disturbance gradients differ between taxonomic groups self-evidently justifies extending biodiversity surveys to microfauna and
microsymbionts. Because of the large numbers of individuals, in different functional
groups, that can be extracted from a small number of soil samples, the potential for
data accumulation from nematodes, given adequate taxonomic expertise, is impressive
and should have good predictive value for ecosystem processes. In work with termites
and nematodes, taxonomic resolution can be obtained at the genus or species level,
and it is also possible to make functional group allocations from the morphology of
each specimen. Better discrimination between land uses is then possible because the
balance of functional groups, as well as species or generic diversity, can be assessed at
the same time. Despite this, there is no evidence that any one taxonomic group can
serve as a surrogate for others. Existing evidence points to the opposite conclusion. For
example, in Cameroon Lawton et al. (1998) found that each of five unrelated animal
groups (birds, beetles, ants, termites, and nematodes) showed its own pattern of diversity change across the same disturbance gradient (forest through tree plantation to
cleared ground) and that the changes in one group did not predict changes in others.
The main addition to our protocol since the project began has been the 100-m
termite transect. This places substantial demands on resources (20 work-hours for
sampling, up to 300 work-hours for taxonomy; see Lawton et al. 1998) but provides
high resolution and has the additional advantage that specimens can be allocated to
functional groups directly from taxonomic affiliation (Jones and Eggleton 2000).
Other improvements, tabulated under best sampling practice (table 5.3), address replication issues: increasing the number of monoliths per transect from five to eight or
ten and avoiding or reducing the bulking of cores for nematodes and microsymbionts.
Such modifications are easy to recommend but carry large resource implications. Similarly, the move toward molecular methods in characterizing root-nodulating bacteria
(Bruijn et al. 1997) necessarily restricts the number of laboratories able to undertake
such work in the short term.
Table 5.7 summarizes the difficulties attached to work with particular groups.
Inevitably, although sampling expertise can be readily taught and disseminated, taxonomic bottlenecks are the main obstacles to assembling good datasets (see Eggleton
and Bignell 1995; Lawton et al. 1998). Termites, earthworms, nematodes, mycorrhizal fungi, and rhizobia can all be cited as groups whose taxonomy is moderately
difficult or difficult. However, these are also the groups where species or strain-level
resolution is valuable in distinguishing between land uses.
Below-Ground Biodiversity Assessment
139
Table 5.7 Comparative Merits and Difficulties of the Biotic Groups Selected
Group
Main Processes
Mediated
Ease of Sampling (S)
and Taxonomic
Processing (T)
Resolution of
Diversity
Needed
Indicator
Value
All macrofauna
Litter transformers
and macropredators
Decomposition and
bioturbation r soil
structure and
quality
Easy (S), easy (T)
Generally to
ordinal level
Species level
Moderate
Moderate
Good
Good
Moderate
Moderate (S), difficult (T)
Species level
Species level
Generic level
Species or spore
morphotype
Genus or strain
Easy (S), difficult (T)
—
Low
Termites
Ants
Earthworms
Nematodes
Mycorrhiza
Moderate (S), difficult (T)
Easy (S), easy (T)
Difficult (S), moderate (T)
Micropredators
Difficult (S), difficult (T)
Nutrient acquisition Moderate (S), moderate (T)
Root-nodulating
Nitrogen fixation
bacteria
Microbial biomass Primary
transformations
Good
Good
A final question concerns the scaling of sampling. Is the assessment of belowground biodiversity consistent from sampling point to plot and from plot to land use?
To some extent this question returns the argument to the issues of replication of sampling and the variance of data. Are we justified in drawing conclusions about regional
land uses from spot sampling in a few sites, albeit well-documented ones? Data on soil
macrofauna from Indonesia, where replication of sampling arguably has been more
extensive than elsewhere, suggests that for any given land use, average taxon diversity
is consistently greater at the sampling location level (i.e., mean of taxa sampled over all
locations) than the sampling point level (i.e., mean of all sampling points in all locations). This is as expected, given that a few samples will be highly taxon-rich whereas
the majority will have lower diversity and, consequently, the maximum diversity found
at any single point will be greater than the average of locations. However, the magnitudes of both these difference are consistent across five land uses from mature forest to
degraded Imperata grassland (van Noordwijk 1999). This suggests that despite their
inadequacies, our sampling methods are giving real information on the links between
land management and soil biodiversity.
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6
Sustainability of Tropical Land Use Systems
After Forest Conversion
Kurniatun Hairiah
Brawijaya University Malang, Indonesia
Meine van Noordwijk
ICRAF, Indonesia Bogor, Indonesia
Stephan Weise
IITA Humid Forest Station Yaoundé, Cameroon
F
armer decision making involves the weighing of many options, including those off farm and off site, and includes the possibility of migrating
elsewhere. Of particular interest to natural resource management research
is the balance between decisions for activities in the rural landscape that
invest, plant, care, and conserve and those that exploit, harvest, and market
the resources. When exploitation and harvesting dominate, the resources are
likely to degrade, but the returns to labor and short-term profitability may be
high. When conservation, planting and other types of investment dominate,
the resources may recover from past exploitation but may not meet current
livelihood demands. Finding a balance between these aspects within the landscape depends very much on the interactions between actors and stakeholders. Sustainability issues will play a role in farmers’ decisions only if they are
made aware of the problems and have other options.
Where a secure system of land tenure exists, the precept that “a man
should always aim to hand over his farm to his son in at least as good a condition as he inherited it from his father” (Russell 1977) has been a major factor
in promoting sustainable land management. Although the details may vary
in different parts of the world (daughters may inherit farms, from either their
mother or their father), the message remains clear: We have borrowed the
resources from future generations and are supposed to return them intact.
There are many definitions of sustainability (table 6.1). Shifting cultivation systems can be sustainable if the fallow length is sufficient to undo the
loss of productivity that occurs during a cropping period. If one looks at the
cropping period in isolation the system appears to degrade, but when crop-
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Table 6.1 Definitions of Sustainable Agricultural Systems
Definitions
Source
The successful management of resources for agriculture to satisfy
changing human needs while maintaining or enhancing the quality of
the environment and conserving natural resources.
FAO (1989)
A system that maintains an acceptable and increasing level of
productivity that satisfies prevailing needs and is continuously adapted to
meet the future needs for increasing the carrying capacity of the resource
base and other worthwhile human needs.
Okigbo (1991)
A system in which the farmer continuously increases productivity at
levels that are economically viable, ecologically sound, and culturally
acceptable through the efficient management of resources and
orchestration of inputs in numbers, quantities, qualities, sequences, and
timing, with minimum damage to the environment and human life.
Okigbo (1991)
A system that involves the management and conservation of the natural
resource base and the orientation of technological and institutional
change in such a manner as to ensure the attainment and continued
satisfaction of human needs for present and future generations. Such
sustainable development conserves land, water, plant, and animal genetic
resources and is economically viable and socially acceptable.
FAO (1991)
A cropping system is not sustainable unless the annual output shows a
nondeclining trend and is resistant, in terms of yield stability, to normal
fluctuations of stress and disturbance.
Spencer and Swift (1992)
A sustainable land management system is one that does not degrade the
soil or significantly contaminate the environment while providing
necessary support to human life.
Greenland (1994)
Source: Greenland (1994).
ping and fallow periods are combined the basic resources are maintained from one
cycle to the next and allow continued exploitation. This example may illustrate some
of the considerations necessary for an assessment of sustainability:
• Sustainability of a larger system (crop and fallow) may be maintained even if a
subsystem (the cropping period) is nonsustainable.
• Sustainability of a human livelihood system can be maintained even if specific
activities are not sustainable as long as a sufficient array of options is maintained.
Whenever a specific form of land use runs into problems with one of the resources
on which it depends, there may be alternative solutions that maintain the overall functioning of the system. These solutions may be more costly, but the fact that they exist
means that sustainability assessments really depend on the boundary conditions that
we set for such potential adaptations.
Sustainability of Tropical Land Use Systems
145
In general, however, it is easier to define what is nonsustainable than it is to
say what is sustainable. Any system that does not maintain all essential parts of the
resource base is nonsustainable, so finding one violation of the resource conservation
rule is enough to characterize the system as a whole as nonsustainable. We can confirm
that a system is sustainable only if we know the fate of all parts of the resource base
and the degree to which they are essential; this is not a trivial task by any means. Sustainability at any level of complexity (from sustainability of cropping systems to that
of human livelihoods) can be based on the sustainability of its components, possible
adaptations, or the adaptive response of the key actors at each level in finding and fitting in new components (figure 6.1).
Sustainable livelihood options do not necessitate sustainable cropping systems
or crops if there are enough potential alternatives. Existing sustainability indicators
Figure 6.1 At any single level in the hierarchy from abiotic resources to global livelihoods, sustainability
can be defined either as the persistence of the underlying level (the resource base) or as the availability of
options (allowing the manager to be resourceful or agile in making adaptations).
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appear to focus on persistence, ignoring adaptation and change. Yet options for change
are not the same everywhere, so they should be taken into account as well.
If we combine a persistence view of sustainability with the options for dynamic
change (figure 6.1), we see that sustainability at one scale does not extend to the scales
above or below. Changes in the resource base and options for future change can affect
sustainability at higher levels in the hierarchy, even if persistence criteria for the current system are met. Conversely, lack of sustainability at any level can be compensated
for to achieve sustainability at a higher level in the hierarchy if options for adaptation
are maintained. Therefore we have to be explicit in the system boundaries before we
can measure, quantify, or assess sustainability.
In the context of our integrated assessment of land use options for the humid
tropics, we will discuss the following:
• Assessments of sustainability of land use practices at plot level
• Assessments of sustainable agricultural livelihood systems at landscape
scale
A S S E S S MENTS OF SUSTAINABILIT Y OF L AND USE
P R AC T I CES AT PLOT LEVEL
Sustainability of a range of land use systems that follow forest conversion can be
assessed if we first specify the threats to persistence (figure 6.2). Four ways by which
continued farming degrades its own resource base to a level that impairs future productive use of the land are as follows:
A. Not maintaining soil of sufficient structure
B. Not balancing the budget of nutrient exports and imports
C. Letting pest, weed, and disease problems reach unmanageable proportions
D. Not maintaining essential soil biota, such as mycorrhizal fungi and Rhizobium
Any of these problems can become such a constraint to continued farming that
land may have to be abandoned, at least temporarily. Therefore the most serious category of problems determines the overall sustainability.
Other threats to continued farming that may dominate discussions of agricultural
sustainability, especially in developed countries, are threats to water quality and quantity (E), air quality (F), and biodiversity (G) (figure 6.2). If there are serious negative
effects on these factors, then outside stakeholders may take measures to stop the land
use practice in its current form. Another threat is producing products of insufficient
quality to meet consumers’ expectations (H).
Categories A to D are essentially agronomic in nature; categories E to H depend
on the perceptions and responses of consumers and other outside stakeholders, so
Sustainability of Tropical Land Use Systems
147
Figure 6.2 Threats to agricultural sustainability: The inner circle is essentially agronomic and the outer
circle is more focused on environment and market issues (van Noordwijk and Cadisch 2002).
they necessitate very different methods of investigation. They affect farming through
government or local regulations and financial incentives. Other threats to continued
farming are based on the lack of financial viability of a farm, changes in prices for the
products, and a lack of options for change.
For each category of threats, numerous indicators can be developed at two levels:
• Easily observable phenomena that can be used in rapid qualitative assessments
• Real measurable parameters for which standardized protocols and interpretation schemes (which include specific threshold values) can be made
Qualitative field-level indicators may be sufficient for monitoring on-site changes
by (forest) farmers or other land users. To them, the presence of a surface litter layer
and clear forest streams may be enough to indicate that the system they work with is
sustainable. Yet such simple indicators are not sufficient for legally binding commitments. The latter require rigorous, quantifiable indicators, but even with such procedures, the interpretation of data may not be unequivocal because absolute reference
values are lacking for many of the parameters. For example, a debate on how often
landslides occur in “natural forest” landscapes can cast doubt on any data on sediment
loads of rivers after forest conversion.
No agricultural land use can consistently yield harvests of produce without management efforts being invested in maintaining the system. Therefore, all judgments
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Thematic Research
of sustainability must be made in the context of a specified management regime and
farmer efforts to overcome obstacles. For each indicator a tentative threshold has to
be identified, which allows a final judgment to be expressed, for example, in terms of
three categories:
0: No major problems beyond the range that normal farm management can
address.
–0.5: Additional effort will be needed to address these issues, which may affect the profitability of the land use system but may otherwise be within
the range of farmers’ management options.
–1: Problems may be beyond farmers’ ability to resolve.
In the Alternatives to Slash-and-Burn (asb) project, a set of criteria and indicators
was developed that can be measured easily, often using data already collected as part
of the integrated survey of biodiversity, carbon stocks, and greenhouse gas emissions.
Details of the various criteria that were used are presented in the following sections.
After that, the values and results obtained in the assessments in Indonesia, Cameroon,
and Brazil are discussed.
Criteria for evaluating the impacts of land use on former forest soils (table 6.2)
can be grouped by soil function, focusing on the sustainability of land use practices
and on externalities or effects on environmental functions of forest soils. However, the
measurables for these various functions show a high degree of overlap. Many of them
are linked with the maintenance of surface mulch and soil organic matter.
C ri t e ri on A: Soil Structure and Biological Activit y
The following indicators can be used.
A1: Soil Compaction
Soil compaction is measured from soil bulk density (dry weight per unit volume, g/cm3)
in the topsoil relative to that of a forest soil of the same texture. Isolated, individual
measurements of soil bulk densities are difficult to interpret because soils of differing
texture have different inherent bulk densities such that values that are high and unsustainable for one soil type may not be for another. By using a “pedotransfer” function we
can estimate the normal bulk density (BDref ) of a soil of the same texture, and we can
use the ratio BD/BDref as an indicator of change from the reference situation. Values
above 1 indicate compaction, values below 1 a structure that is better than average (in
the reference set). Wösten et al. (1995, 1998) derived such a pedotransfer function for
a large set of soils from the temperate region that are under agricultural use:
Table 6.2 Criteria and Indicators for Evaluating Sustainability of Plot-Level Land Use on
Previous Forest Soils in the Project
Criteria
Indicators (qualitative)
Measurable Parameters
(quantitative)
Erosion: absence of gullies,
presence of riparian filter
strips and other sedimentation
zones, soil cover by surface
litter or understory vegetation
Compaction: use of
penetrometer
Soil structure: spade test, root
pattern
Soil cover and absence of
gullies as indicators of
infiltration; absence of surface
sealing and crusting
Annual exports of phosphorus
and cations as fraction of total
and available stock
Annual exports of nitrogen
minus inputs from biological
N2 fixation as fraction of total
nitrogen content of the soil
Financial value of net nutrient
exports as fraction of potential
replacement costs in fertilizer
Absence of major diseases and
weeds
Net soil loss internal soil loss
– internal sedimentation.
Percentage soil cover, integrated
over the year (or over annual
rainfall).
Bulk density of topsoil.
Soil macroporosity and H2O
infiltration rates.
Water infiltration vs. runoff.
Soil water retention.
Effective rooting depth.
I. Maintain on-site productivity
A. Maintain soil as a matrix of
reasonable structure, allowing
root growth and buffering
water between supply (as
precipitation) and demand
(for transpiration)
B. Maintain the nutrient
balance: buffer nutrients
between supply from inside
and outside the system and
demands for uptake
C. Keep pest, weed, and
disease problems within a
manageable range
D. Maintain essential soil
biota, such as mycorrhizal
fungi and Rhizobium, and
ecosystem engineers
Sporocarps (mushrooms) for
ectomycorrhizal species
Signs of ecosystem engineers
among the soil fauna:
earthworms, termites
Changes in stocks of plant
available nutrients.
Changes in mineralization
potential or size of organic matter
pools.
Carbon saturation deficit.
Limiting-nutrient trials.
Rate of increase of pest incidence.
Change in composition and
quantity of weed flora.
Spore counts for vesicular
arbuscular mycorrhiza.
Mycorrhizal infection and
nodulation in roots in the field
and in trap crops in the lab.
For details see chapter 5.
II. Externalities: Don’t make the neighbors angry
E. Provide a regular supply of
high-quality water
Stream flow response time
after rain storms; downstream
areas free of floods and
droughts
Turbidity of streams
Stream flow amounts and
variability.
Sediment load of streams.
Absence of agrochemicals in
water.
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Thematic Research
Table 6.2 (Continued)
Criteria
Indicators (qualitative)
Measurable Parameters
(quantitative)
II. Externalities: Don’t make the neighbors angry
F. Air filter: mitigate net
emission of greenhouse gases
Above-ground carbon stocks
in biomass and necromass
G. Maintain biodiversity
reservoirs: allow recolonization
of depleted neighboring
landscape units and
germplasm collection for ex
situ exploitation
Diversity of above-ground
vegetation, based on diversity
of plant functional attributes
Soil carbon stocks relative to soil
carbon saturation deficit.
Net emissions of NO2 and CH4.
Diversity of plant species.
Diversity of soil biota in selected
indicator groups.
III. Keep the consumers happy
H. Maintain a product quality
that consumers want to buy
Actual consumer response
Criteria based on the consumer’s
perception of quality. These may
involve positive attributes (e.g.,
taste, nutritional value), lack of
negative attributes (e.g., no
chemical residues or genetically
modified components), or lack of
production process (social and
environmental concerns).
For soils with Clay% + Silt% < 50 percent the following equation is used:
BDref = 1/[–1.984 + 0.01841 × OM + 0.032 + 0.00003576 × (Clay% + Silt%)2 +
67.5/MPS + 0.424 × ln(MPS)],
where OM is the soil organic matter content (=1.7 × Corg) and MPS is the mean particle size of the sand fraction, with a default value of 290 µm.
For soils with Clay% + Silt% > 50 percent the following equation is used:
BDref + 1/[0.603 + 0.003975 × Clay% + 0.00207 × OM2 + 0.01781 × ln(OM)].
Although these equations were based on agricultural soils in temperate regions,
they have been used here to approximate bulk density values for soils from differing
land uses and with differing texture. This pedotransfer refers to soil under normal
agricultural use rather than under forest, so we expect BD/BDref values to be below 1
for forest conditions.
Sustainability of Tropical Land Use Systems
151
A2: Soil Carbon Saturation
Soil organic matter is considered to be a key characteristic in judging the sustainability
of land use systems. Yet total soil organic matter content is not a very sensitive indicator because it changes slowly under different management regimes and often has a
high spatial variability linked to variability in soil texture, pH, and elevation.
Current methods for inventory of soil organic matter are based on an estimate of
the soil carbon stored under natural vegetation and relative changes caused by aspects
of human land use, including soil tillage, drainage, and a reduction in organic inputs
compared against the natural vegetation. The difference between current and potential carbon storage can then be expressed as a carbon saturation deficit (van Noordwijk
et al. 1997, 1998). We can now calculate a carbon saturation deficit on the basis of the
difference between the actual soil carbon content and amount that would be expected
for a forest soil with a long history of large litter inputs for the same type of soil.
CsatDeficit = (Cref – Corg)/Cref = 1 – Corg/Cref,
where Corg/Cref = soil organic carbon content relative to that for forest soils of the same
texture and pH, and Cref = a reference soil carbon level representative of forest soil.
More details on the basis for the equations and values for the carbon saturation
deficit can be found in chapter 2. If the value of the Corg/Cref ratio is 1, this means the
soil is similar to that of a forest and basically carbon saturated, and values less than 1
indicate a carbon deficit relative to the forest soil.
A3: Active Soil Carbon
Microbial biomass forms only 1 to 4 percent of the total carbon content of a soil, but
it is the most active fraction because nearly all transformations in the soil depend on
microbial activity. Numerous indicators have been identified for comparing the size of
this microbial pool or some other fraction or activity of the labile soil carbon in different
land use types in a given area relative to the natural forest on an equivalent soil type.
• Microbial biomass is generally estimated by comparing the amount of carbon
or nitrogen that is released into the soil after a chloroform fumigation that (supposedly) kills all microbes. It is measured through incubation or extraction methods.
Microbial biomass estimates derived in this way often correlate well with soil nitrogen
mineralization rates and crop yields and therefore are an indication of soil microbial
activity and fertility. Soil microbiologists generally prefer other methods that target
specific groups of soil microbes or have a stricter separation of live and dead fractions
of the biomass, but for a first assessment the overall microbial biomass measurement
still has value.
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• Soil respiration or nitrogen mineralization (during lab incubation) can be used
as an indication of the biological activity of the soil.
• Dry weight of the light fraction of soil organic matter represents recent inputs
of organic matter as food for soil biota. This fraction can be obtained using a separation technique based on liquids of different densities, called the size–density fractionation procedure (Sitompul et al. 2000).
• It is becoming apparent that individual measures of microbial biomass or light
fraction may not reflect the active or labile fraction of soil organic matter (som)
because both fractions contain labile carbon. Chemical oxidation approaches such as
that described by Blair et al. (1997) may be a more integrative measure of labile soil
carbon.
The use of these parameters is valid when they are judged against the values
obtained for natural forest sites. Yet there are still no critical values below which one
can say the system is no longer sustainable.
A4: Soil Exposure
Soil exposure (se) to the direct impact of raindrops and the sun, if frequent or for
long periods of time, can lead to deterioration of soil structure. Therefore, a soil cover
such as a surface litter layer or green leaves of plants growing close to the ground can
protect the soil. Tree canopies alone do not count, however, because the energy of the
splash impact of drips from the leaves can exceed that of rainfall.
Several indicators were developed to reflect both the percentage of time that a soil
is exposed and the length of the cycle. The soil cover index integrates the information
of both soil exposure and open time into one indicator. The indicators include the
following:
Soil exposure = 100 × number of months of low (less than 75 percent) soil
cover/length of system cycle in months, that is, proportion of the length of
the whole cycle that the soil has a low cover
Time between clearing events, that is, the frequency of the removal of a
protective canopy cover = total length of system cycle (in years)
Soil cover index = length of system cycle in months – soil exposure time in
months
C ri t e ri on B: Nutrient Bal ance
Three indicators were developed to judge whether the nutrient balance is (or could
potentially be) maintained in a cropping system.
Sustainability of Tropical Land Use Systems
153
B1: Net Nutrient Export
Net nutrient export (nne) can be calculated as the total nutrients contained in all
harvested products (which are removed from a field) minus the amount of nutrients
added in the form of fertilizer inputs for nitrogen, phosphorus, and potassium, in
kilograms per hectare per year. The value does not include the nutrients that are recycled in the system such as litterfall or prunings, crop residues, or manures. High net
exports indicate the likelihood of depletion of the resource base; high net surpluses, on
the other hand, may indicate excessive fertilizer use and risks of pollution of ground
and surface water. Nutrient imports can also include dinitrogen (N2) fixation from
legumes in the system.
B2: Nutrient Depletion Time Range
Nutrient depletion time range (ndtr) represents the theoretical length of time (number of years) it would take for nutrient stocks to be depleted to zero (if current trends
are extrapolated linearly). In any system, if nutrient stocks in soil and vegetation are
large relative to net nutrient exports, nutrient offtake can be part of a wise natural
resource management strategy. If exports are large relative to stocks, however, one can
expect that yields will decline in the near future unless nutrient inputs are increased.
Two types of estimates were used for nutrient stocks in the system:
• The directly available nutrient pool in the soil
• The total nutrient content of soil plus vegetation (including less accessible
pools in the soil)
Neither estimate is directly satisfactory, however, because measures of the available
nutrient pool include arbitrary fractions and there is wide variation between plants in
ability to access nonavailable nutrient sources. Because nutrient stocks depend on the
soil type and vegetation cover, one cannot directly assign an ndtr value to a land use
system. As an example from the peneplain of Sumatra, the inherently more fertile soils
closer to rivers with a higher clay and silt content will have larger nutrient stocks than
the sandier soils of the rest of the lowland peneplain. Thus, figures obtained may be
accurate only within an order of magnitude.
B3: The Relative Nutrient Replacement Value
The relative nutrient replacement value (rnrv) relates the export of nutrients in harvested products to the costs of putting them back into the agroecosystem in the form
of chemical fertilizer. This assessment is based on the harvested products rather than
the full production system.
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C ri t e ri on C: Crop Protection from Weeds, Pests,
a n d D i s eases
For criterion C, two indicators have been proposed, both based on expert opinion
rather than direct measurements:
C1: Potential for Weed Problems
Weed problems become a major constraint in the system unless addressed by additional labor or technical input.
C2: Potential for Pest or Disease Problems
Pest or disease problems become a major constraint in the system unless addressed by
additional labor or technical input.
C ri t e ri on D: Maintenance of Essential Soil Biota
The relationship of different groups of soil biota to certain soil and ecosystem functions is discussed in chapter 5. Certain functional groups such as macrofauna (ants,
termites, earthworms), nematodes, and plant microsymbionts have been identified as
key to the maintenance of certain soil and ecosystem processes, but no critical values
have been set.
C A S E S TUDIES: RESULTS FROM ASB INDONESIA
( S U M AT RA), CAMEROON, AND BRAZIL
C ri t e ri on A: Soil Structure and Biological Activit y
Data collected from the Lampung and Jambi benchmark sites in Indonesia (table
6.3) show that there is a clear difference in mean bulk density between undisturbed
forests and land under a cassava–Imperata cycle, with intermediate degrees of compaction under agroforests and other tree-based production systems. Serious localized
soil compaction was clear in logged-over forest where tracks and logging ramps were
compacted beyond easy recovery. It is easy to compact a soil, but in systems without
soil tillage it can take a long time before the soil recovers. Soil compaction can affect
water infiltration, root growth, and greenhouse gas emissions but probably stayed
below critical levels in all cases observed.
Sustainability of Tropical Land Use Systems
155
Table 6.3 Measured Soil Fertility Indicators for the Integrated Biodiversity Survey in Lampung
and Jambi, Benchmark Area (SeptemberNovember 1996)
Forest
BD/BDref,
2–7 cm
Corg/Cref, Light Organic
0–5 cm Matter, 0–5 cm
(g/kg)
Bacterial
Population/
Corg
Bacterial
Population/
(Cref/Corg)
Soil
Respiration
(mg CO2/
kg/d)
0.85
0.91
3.22
13.5
37
12.9
0.99
1.21
1.14
1.26
0.75
0.73
0.52
0.66
0.77
0.81
0.35
0.58
1.48
1.78
1.56
1.59
Relative to Forest
Agroforest
Regrowing trees
Cassava
Imperata
1.43
1.69
1.51
1.62
0.91
0.84
0.59
0.80
Soil samples were taken at the surface layer (05 cm only), except for bulk density ( ), at 2–7 cm. See text
for indicator descriptions.
The carbon saturation (Corg/Cref ) data show that no land use systems fully maintain the soil organic matter levels in the topsoil of a natural forest, as is shown by the
values of Corg/Cref of less than 1.0. Declines greater than 25 percent were found only
for the cassava–Imperata land use type, with the greatest reductions of almost 50 percent measured in cassava fields. The low current value of carbon saturation may have
resulted partly from reclamation history and current land use (bulldozer land clearing
can remove part of the topsoil to outside the field boundaries). The frequent fires and
soil tillage, together with low organic inputs through cassava litterfall (0.6 Mg/ha/yr
compared with 12 Mg/ha/yr in secondary forest), are the likely causes.
These same land uses, except for cassava, had a high respiration rate, but when
estimates of total microbial population size are scaled by soil organic matter content
or carbon saturation, the active fraction of the total soil organic matter pool in forests
appears to have been lowest. On the basis of this evidence and other data in the soil
biodiversity survey (see chapter 5, this volume) we conclude that there is no lack of
active soil biota in any of the land uses for the basic functions of nutrient cycling and
decomposition, and Imperata grasslands are not depleted ecosystems from a soil biological perspective, even though their soil organic capital has been reduced.
The indicator of soil cover (A4) requires inferences over the lifespan of the system
rather than point measurements. Figure 6.3 shows that the nature of soil cover can
shift from dead wood and leaf litter in forests to covers dominated by green biomass in
a Chromolaena fallow. Bare soil is rarely exposed in the landscapes of the peneplains. In
all land use systems with a slash-and-burn land-clearing event, soil may be exposed for
about 6 months per cycle (or 2 percent of the time for a rubber system with a 25-year
cycle). The only land use system in which soil exposure may be an issue is the cassava–
Imperata cycle, where soil may be exposed during the first 3 months of a cassava crop
and for about 1 month per year in all cases when the Imperata fallow is burned. Com-
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Thematic Research
Figure 6.3 Soil cover in different land use types in Jambi. CS/Imp, cassava–Imperata; FL, Chromolaena
fallow; Imp, Imperata; LOF, logged-over forest; NF, natural forest; PL, timber plantation (Paraserianthes);
RAF, rubber agroforest; RMO, rubber monoculture.
bined, this may lead to about 10 percent of the time with incomplete soil cover, when
the soil is vulnerable to the direct impact of rain and sun.
In the case of Cameroon (table 6.4), the systems have the soil exposed from 7
(long fallow) to 20 percent (short fallow) of the cycle, with intermediate values for
the other systems. However, these values do not adequately reflect the fact that these
exposure events occur much less often in some of the systems, resulting in soil cover
indexes six and two times higher than those of the short and long fallow systems,
respectively. Therefore the combined soil cover index probably is much more useful
when such different systems are compared.
To summarize all the soil measurements, sustainability ratings were assigned to
the different land use types on the basis of criterion A (maintenance of soil structure and biological activity) (table 6.5). The measurements were translated into a
qualitative value within the range of 0 to –1, where –1 = problems beyond those
that farmers can solve, 0 = no major problems, and –0.5 = problems within the range
of farmer management. For numerous land use systems the overall rating is thus
–0.5. Only the cassava–Imperata system has questionable sustainability according
to several criteria.
Table 6.4 Soil Exposure, Time Between Clearing Events, and Soil Cover Index in Different
Land Use Systems in the Cameroon Benchmark Area
Land Use Systems
Soil Exposure
Time Between
(% of cycle length) Clearing Events (yr)
Soil Cover
Index (mo)
SF: food intercrop
LF: food intercrop
SF: intensive cocoa with or without fruit
FOR: extensive cocoa with or without fruit
SF: oil palm
FOR: oil palm
Community-based forest management
19.4
7.3
11.1
10.8
16.7
17.5
0.0
58
178
320
321
300
297
360
6
16
30
30
30
30
100
SF, short fallow; LF, long fallow; FOR, derived from forest.
Source: Kotto-Same et al. (2000).
Table 6.5 Overall Assessment of Severity of Sustainability Problems of Various Land Use
Systems for the Peneplain of Sumatra
Land Use System
A1
A2
Natural forest
0
0
0
0
Community-based
forest management
Commercial logging –0.5 0
Rubber agroforests
0
0
0
0
Rubber agroforests
with selected
planting material
0
0
Rubber
monoculture
0
0
Oil palm
monoculture
0
0
Upland rice–bush
fallow rotation
Cassava–Imperata
–0.5 –0.5
rotation
A3 A4
B1
B2
B3
C1
C2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
–0.5
0
0
0
0
–0.5 –0.5
0
0
0
0
0
0
–0.5 –0.5
–0.5 –0.5 –0.5 –1
Overall Main
Issues
0
0
0
–0.5
0
–0.5
–0.5 –0.5
–0.5 –0.5 –0.5
–0.5
0
–0.5
–0.5 –0.5
0
–1
C
C, K, W, P
W, P
Fert
Fert, P
C, Fert, W
C, soil compaction; K, potassium balance; W, weeds; P, pests and diseases; Fert, price of fertilizer.
0, no problem; –0.5, problem that probably can be overcome by the farmer, –1, problem probably out of
reach of farmers’ solutions.
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Thematic Research
C ri t e ri on B: Nutrient Bal ance (Indonesia)
At yield levels of 15, 2, 10, and 0.7 Mg/ha/yr for cassava, upland rice, oil palm, and
rubber, respectively, the expected annual nutrient removals with harvested products
can be derived from table 6.6 to be highest for cassava (40 kg N/ha/yr, 5 kg P/ha/yr,
60 kg K/ha/yr), followed by oil palm (30 kg N/ha/yr, 5 kg P/ha/yr, 40 kg K/ha/yr),
and lowest for rubber (4 kg N/ha/yr, 1 kg P/ha/yr and 3 kg K/ha/yr).
Many farmers in the benchmark area appear to use no fertilizer at all in the
cassava–Imperata cycle. For such no-input versions the nutrient balance is clearly
negative. A clear tradeoff may exist for this land use type between sustainability and
profitability.
The nutrient depletion estimates showed that the nutrient for which the most
rapid depletion may occur is potassium. If only the directly available pool is considered, depletion within a 25-year time frame may occur for the rubber systems and
Table 6.6 Relative Nutrient Replacement Value for Main Products of Various Land Use
Systems
A.
P
K
Nutrient
Replacement
Value
(Rp/kg) (a)
2
5
3
0.20
0.50
0.30
1
5
6
10
24
28
20,000
500
1,000
2.5
6.3
2.9
11.8
2.8
0.25
1.20
0.55
2.90
0.36
1.5
4.4
3.9
2.7
3.9
13
42
25
70
22
108
2,000
60
400
50
Nutrient Removal
(g/kg product)
N
NTFPs, rotan
NTFPs, petai and jengkol
NTFPs, durian
NTFPs, others
Timber
Rubber (latex)
Oil palm (bunches)
Rice
Cassava
Farmgate
Value of
Product
(Rp/kg) (b)
Relative
Nutrient
Replacement
Value (a/b)
0.001
0.05
0.03
0.001
0.12
0.02
0.41
0.17
0.44
B. Data Needed for Calculating Nutrient Replacement Values
Replacement price per nutrient exported, Rp/g [x/( y z 1000)] (a)
Fertilizer price, Rp/kg (x)
Proportion of nutrient in fertilizer ( y)
Nutrient recoverya by crops or products (above) (z)
Rupiah prices before July 1997, $1 2300 Rp.
NTFPs, nontimber forest products.
a
See text.
Source: Modified and extended from van Noordwijk et al. (1997a).
N
P
K
2.3
260
0.45
0.25
12.0
480
0.2
0.2
2.9
400
0.46
0.3
Sustainability of Tropical Land Use Systems
159
shifting cultivation as well as cassava production. If total stocks are considered (at least
part of “nonavailable” potassium can be accessed by plants), the time frame to depletion becomes several decades at least. For nitrogen, no problems are to be expected for
the land uses described here according to this calculation. However, these calculations
are based on total soil nitrogen, and only 2 to 4 percent of that is mineralized and
therefore available in any year. Also, the calculations do not include nutrient losses
other than in harvested products, and substantial nitrogen losses, up to 80 percent of
the nitrogen in the vegetation, occur during slash-and-burn clearing of forest lands
and by leaching during subsequent periods of low nitrogen demand by the vegetation
relative to the nitrogen supply from mineralization. A more refined estimate would
have to include the full spectrum of processes incorporated in the Century model
(Palm et al. 2002) and goes beyond the current sustainability assessment.
In the calculations for relative nutrient replacement values in table 6.6, the amounts
of fertilizer needed to replace the nutrients exported in the harvested products are
corrected for (long-term) nutrient recovery. It was assumed that only 25 percent of
nitrogen, 20 percent of phosphorus, and 30 percent of potassium fertilizers that were
applied were actually recovered (taken up) by the products or crops. Thus, for every
gram of nitrogen exported in a harvested product, 4 g of nitrogen had been applied
in the form of nitrogenous fertilizer. The N2-fixing trees petai (Parkia speciosa) and
jengkol (Pithecellobium jiringa) included in the nontimber forest products (ntfps)
scenario were assumed to derive two-thirds of their nitrogen from the atmosphere.
The nutrient replacement value (a in table 6.6A) is calculated as the weight of each
nutrient removed, multiplied by the replacement cost per nutrient (in table 6.6B),
then totaled for nitrogen, phosphorus, and potassium (neglecting other nutrients).
Most relative nutrient replacement (rnrv) values are below 10 percent, and this
indicates that nutrient replenishment would be within reach of farmers if, when, and
where actual nutrient responses of the crop make fertilizer use necessary. For rice, the
value is around 15 percent, and this indicates a range in which details of fertilizer use
(and the various assumptions on efficiency made here) will be important for farmers’
decisions on fertilizer use.
For oil palm and cassava the rnrv values are around 45 percent, indicating that
fertilizer costs would be a major part of the farm budget if farmers had to balance
the nutrient budgets. The high rnrv values for both products are caused by their
low price (at the farmgate) per kilogram of product. For oil palm, marketing of fruits
instead of bunches could reduce the nutrient exports and hence the rnrv. For cassava
only a shift in farmgate prices of the product or of fertilizers could make fertilizer use
more attractive.
To summarize all measurements, sustainability ratings were assigned to the different land use types on the basis of criterion B, maintaining nutrient balance (table 6.5).
Only the cassava–Imperata rotation appears to be unsustainable in all the nutrient
indexes and cannot be solved in most cases because of the current costs of fertilizers.
Therefore it will be interesting to observe the economic and environmental trajectory
of this land use system.
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Thematic Research
C ri t e ri on C: Crop Protection from Weeds, Pests,
a n d D i s eases (Indonesia)
Weed problems are related mostly to Imperata (table 6.7), which is hard to control
without herbicides that are often too expensive for smallholder food production or
plowing (van Noordwijk et al. 1996a). In rubber-based agroforestry systems, damage
by pigs and monkeys in newly planted fields can be a serious obstacle when clonal
planting material is used because it is more expensive than the traditional planting
stocks (Williams et al. 2001), whereas in the existing system, substantial tree losses are
tolerated by planting low-cost seedlings at high densities. The natural secondary forest
regrowth in rubber agroforests is probably less problematic as a “weed” than the grass
or fern vegetation that develops under attempts at weed control.
Sy n t h e s is of Sustainabilit y Indicators for Sumatra
When all indicators are combined (table 6.5) we conclude that
• Most land use systems considered have one or more aspects that need attention,
but most of these stay within the range of problems that are solvable at farm level.
• The cassava–Imperata cycle has numerous problems associated with it, and one
of these (maintaining a nutrient balance) is so serious that it probably cannot be
resolved at the farm level within the current constraints.
A n O ve rall Assessment for C ameroon
The overall assessment of agronomic sustainability for Cameroon is based on the
information presented in table 6.8.
Soil Structure
A significant decline in soil structure over time is observed in intensively managed,
short fallow, annual food crop systems. This decline is related to the frequent disturbance of the fallow vegetation, which is reflected in the longer soil exposure and soil
cover index in this system (table 6.4). Fire used for getting rid of the slashed vegetation and the soil tillage accompanying planting operations may also contribute to
this decline. With shortening fallows, the fallow vegetation itself shifts to thickets
often dominated by Chromolaena or grasses. Alternative planted fallow systems that
fix nitrogen and contribute to the stabilization of the soil organic matter pool may
Forest extraction
Multistrata agroforestry systems
Simple tree crop systems
Crop–fallow systems
Continuous annual cropping systems
Pastures
0
0–0.5
–0.5
0–0.5
—
0–1
0
0–0.5
0–1
–0.5–1
—
—
–0.5
0
0
0
–0.5
—
0
–0.5–1
–0.5
0–0.5
—
–0.5
0
–0.5–1
–0.5
0–1
—
—
Cameroon
Brazil
Indonesia
Brazil
Cameroon
Nutrient Balance
Soil Structure
Table 6.7 Cross-Site Comparison of Assessments of Agronomic Sustainability
0
–0.5
0–0.5
0
–0.5
—
Indonesia
0
0–0.5
–0.5
–0.5–1
—
–0.5–1
Brazil
0
–1
–0.5
0–1
—
—
Cameroon
Crop Protection
0
–0.5
0–0.5
0
–0.5
—
Indonesia
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Thematic Research
Table 6.8 Overall Sustainability Assessment of Soil Structure, Nutrient Balance, and Crop
Protection Status in Different Land Use Systems in the Cameroon Benchmark Area
Land Use Systems
Soil Structure
Nutrient Balance
Crop Protection
SF: food intercrop
LF: food intercrop
SF: intensive cocoa with fruit
SF: intensive cocoa without fruit
FOR: extensive cocoa with fruit
FOR: extensive cocoa without fruit
SF: oil palm
FOR: oil palm
Community-based forest
–1
–0.5
0
0
–0.5
–0.5
0
–1
0
–1
0
–1
–1
–0.5
–0.5
–0.5
–0.5
0
–1
0
–1
–1
–1
–1
–0.5
–0.5
0
SF, short fallow, LF, long fallow, FOR, derived from forest.
Scores: 0, no problem; –0.5, problem that probably can be overcome by the farmer; –1, problem probably
out of reach of farmers’ solutions.
Source: Kotto-Same et al. (2000).
reduce this potential problem. Converting the short fallow land into a perennial crop
system would also help to protect the soil better than annual cropping systems because
of their reduced disturbance and exposure. In contrast, a deterioration of soil structure
is expected when perennial crop systems are planted into fields newly cleared from
forest. This is associated with the initial exposure of the soil and the regular traffic
associated with the management of the systems. However, there is greater concern
about soil compaction in oil palm systems than in cocoa systems because of the slower
canopy closure at establishment in the former and the more regular traffic needed for
harvesting bunches.
Nutrient Balance
The systems that cause most concern in terms of overexploitation of nutrients are the
intensive perennial cocoa and oil palm systems. The potassium lost in the oil palm systems is compensated for by fertilizer use; however, no fertilizer is applied in the intensive cocoa system. The extensive cocoa system is of somewhat less concern because the
yield levels are significantly lower. Fertilizer use can alleviate most of these concerns,
and farmers are willing to use them if the institutional and financial environments are
conducive. Although the nutrient exports from the short fallow and food crop system
are moderate, we must assume that the nutrient stocks are already low in a system
where the fallow period is only 4 years. Given that short fallows often are planted
to subsistence crops with little cash return, the probability of farmers using external
inputs is very low. Only the association of higher-value annual food and horticultural
crops, such as tomato, with these systems would enable the use of fertilizers. Nitrogen
Sustainability of Tropical Land Use Systems
163
could be supplied by the planting of N2-fixing fallow species. Finally, no nutrient
problems are expected in the long fallow and community forest systems.
Crop Protection
Major weed, pest, and disease complexes can develop in recurrent short fallow systems. The lack of longer fallows that allow trees to shade out the arable weeds, including Chromolaena, result in greater weed pressure and the emergence of weeds that are
more difficult to manage manually (e.g., Sida spp. and grasses). Intensive weed management associated with a prior high-value crop (e.g., tomato) may reduce the weed
pressure in subsequent subsistence food crops. Short fallows also allow volunteer crops
to survive during the fallow phase, facilitating carry-over of pests and diseases into
the next cropping period (e.g., the African root and tuber scale in cassava). Breeding
crops for resistance associated with appropriate integrated pest management practices
can reduce crop loss. The cocoa systems also face a major challenge in terms of pest
and disease problems. If not treated, black pod disease can reduce yields up to 80
percent, and mirids can kill trees. Managing these entails a concerted control effort at
the farm and community levels, with significant inputs of pesticides, unless integrated
tree management options are further developed and adopted. Weeds are a threat only
during the establishment of all perennial systems.
Overall Agronomic Sustainability
The most sustainable systems appear to be the long fallow and the community forest
systems. The next sustainable is the establishment of oil palm systems on land previously under short fallows. All other systems have important agronomic constraints
associated with them or lead to possible deterioration of the resource base. As indicated earlier, there are potential solutions, but the financial and institutional environment must be conducive.
C o m pa ri s on of Sustainabilit y Indexes Across Land Use
Sy s t e m Types and Benchmark Sites
Table 6.7 provides an overview of the assessment of three components of agronomic
sustainability—soil structure, nutrient balance, and crop protection—for the Indonesia, Cameroon, and Brazil benchmark sites. If commercial logging is excluded, all
sites reported that forest extraction was the most sustainable system. The main issues
of concern in multistrata agroforests relate to crop protection problems, such as pod
rot in cocoa in Cameroon, and potentially negative nutrient balances depending on
the specific systems assessed. The nutrient balance problem is greatest in the Brazilian
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Thematic Research
multistrata agroforestry systems based on fruits, which have a net negative nitrogen
balance of –109 kg N/ha/yr, whereas the values for the complex rubber agroforests
in Indonesia are generally low (e.g., –5 kg/ha/yr) because they are based on latex
harvest. Simple tree crop systems often are linked with problems of soil structure,
besides crop protection concerns. However, these plantation systems often receive
fertilizers and therefore exhibit less negative nutrient balances. Crop–fallow systems
vary greatly in their effect on agronomic sustainability. The long fallow systems with
low cropping intensity in Indonesia and Cameroon (traditional slash-and-burn shifting agriculture systems) are sustainable, but unimproved short fallow systems with
intensified cropping, as in Cameroon, can have a detrimental effect on soil structure, nutrient balance, and crop health. Planted fallow systems with herbaceous and
tree legumes can improve soil structural and nitrogen balance concerns. Continuous
annual cropping, as with cassava in Indonesia, is problematic at all levels. Pastures,
particularly with improved management practices, tend to have a medium level of
impact on the natural resource base, although impacts on global environmental issues
(biodiversity and greenhouse gas emissions) may be large (see chapter 4, this volume;
Palm et al. 2004).
S U S TA I NABILIT Y ASSESSMENTS OF AGRICULTURAL
L I V E L I HOOD SYSTEMS AT THE L ANDSCAPE SCALE
Fa rm e r Perceptions of Sustainabilit y
As part of the characterization process at the asb sites, farmers were asked for their
views on the threats and constraints to various land use options. This is essentially an
assessment at farm level and includes elements other than the plot-level sustainability
discussed so far. Several problems in four types of cropping systems (sawah–lowland
rice, upland food crops, sugar cane, and tree crop–based systems) that were identified
by farmers in North Lampung are presented in figure 6.4.
Four common problems were reported for all the systems: soil fertility, drought,
fire, and the weed Imperata cylindrica. The upland food crop system was perceived to
have the greatest amount of problems of the four cropping systems.
M a i n ta i ning Options for Land Use Change
The final criterion for sustainability is the possibility of continuing to farm on a given
piece of land, keeping all threats at manageable levels. However, continued farming
may depend on the ability to change and develop a farm in new directions. Whereas
certain land use practices, such as cultivation of very efficient nutrient scavengers such
as cassava, may meet the criterion of persistence for a period of, say, 20 years, this
Sustainability of Tropical Land Use Systems
165
Figure 6.4 Problems identified by farmers in the asb North Lampung benchmark area (van Noordwijk
et al. 1996b).
practice is likely to reduce the number of future options because the soil depletion it
induces will necessitate substantial reinvestment in soil nutrient stocks before other
crops can be grown. The criteria used in the previous sections apply to the field-level
land uses per se, because they are measurable, whereas a full land use transition matrix
can be assessed only by other means. Such adaptive capacity research has to specify
the range of options available and the way these options themselves change in time
and differ between stakeholders. It is unlikely that land uses will remain unchanged
over more than one (or a few) human generations, so it may be interesting to evaluate
which options are kept open with a given land use system (table 6.9).
Natural forest can be used as the starting point for all land use types, but in a
strict sense it can originate only from forests; community-managed forests, some logging techniques, and extensive rubber agroforests can lead to a return of a vegetation
close to that of natural forests. At the other end of the spectrum, the cassava–Imperata
cycle can be started after any land use system but forms a dead end because it cannot
maintain its own productivity, and substantial efforts and expense for nutrient replenishment and Imperata control (Friday et al. 1999) are needed to return to other more
profitable and sustainable land use types. The various tree crop systems appear to be
freely convertible into each other, but extensive rubber agroforests change in character
Table 6.9 Land Use Transformations That Are Feasible in a 20- to 50-Year Period
Land Use System
1
2
3
4
5
6
7
8
9
Comment
1. Natural forest
X
X
X
X
X
X
X
X
X
Universal starting
point
2. Community-based
forest management
3. Commercial logging
4. Rubber agroforests
5. Rubber agroforests with
clonal planting material
6. Rubber monoculture
7. Oil palm monoculture
8. Upland rice–bush fallow
rotation
9. Cassava–Imperata
rotation
?
X
X
X
X
X
X
X
X
?
?
X
X
?
X
?
?
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
?
?
?
X
?
Self-incompatible, a
dead end
Crosses indicate where transitions from one land use system to another are possible. See text for discussion of
“?” cases.
Figure 6.5 Resource base for local and externally acquired new components that can be incorporated into
fanning systems during an adaptation process (five types of capital: F, financial; H, human; N, natural; P,
build up or infrastructural; S, social).
Sustainability of Tropical Land Use Systems
167
once the seedbank of original natural vegetation is depleted and the site is far from the
natural vegetation, thus decreasing the possibility of seed dispersal. Table 6.9 strengthens the conclusion that the cassava–Imperata system is the most problematic of the
land use systems considered here.
The resource base for adaptive capacity (resilience) can be viewed in light of the five
types of capital described in Carney (1998): natural resource, human, social, physical,
and financial capital. Adaptation of agroecosystems can be based on two mechanisms,
one internal and one external to the current system. Agroecosystems, especially those
rich in natural resource capital (agrodiversity and biological resources), can adapt by
increasing the use of currently underexploited local resources or on the basis of new
technology and resources (new crops, new cultivars, new management practices, new
external inputs), depending on their financial, human and social capital. An indication of the types of capital needed for the various adaptive capacity aspects is given
in figure 6.5. Agricultural research has supported a drive toward the simplification
of agroecosystems. This drive results at least in part from the fact that research is less
effective in dealing with more complex systems even if they would be superior (Vandermeer et al. 1998). Access to the fruits of this increasingly commercialized research
depends on financial and social capital and is less likely in the less endowed parts of
the world.
Adaptive capacity based on resources in the current landscape becomes more
likely with an increasing choice of new components and resources in more complex
agroecosystems, although we are not yet able to quantify how much complexity is
needed for how much resilience (Vandermeer et al. 1998).
C O N C LU SION
Our search for indicators and thresholds of agronomic sustainability has yielded
numerous yardsticks that can be used to assess land use options at plot level. Production of bulk products of low value per unit biomass (such as the cassava in our example) is likely to cause nutrient depletion of the soil because the nutrient replacement
costs by fertilizer use probably will exceed the value of the products. Systems relying
on products with a high value per unit biomass, such as many tree products, are likely
to be more sustainable because farmers will be (financially) able to maintain the nutrient balance. Systems with low soil exposure times, such as long fallow and perennial
tree crops, reduce chances of soil compaction and the subsequent erosion and runoff
problems that compromise sustainability.
For the broader issue of farming sustainability, however, we do not yet have a
satisfactory set of indicators. Options for future change should be an essential part
of the assessment, as should the interactions of farms with feedback loops through
society, the economy, and government policies, which may have overriding influences
on sustainable land use.
168
Thematic Research
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the Netherlands.
7
The Forest for the Trees
The Effects of Mac ro e co n o m i c
Factors on Defore s tat i o n i n
Brazil and Indone s i a
Andrea Cattaneo
Resource Economics Division Economic Research Service,
USDA Washington, DC
Nu Nu San
College of Agriculture, Forestry & Consumer Science West Virginia
University, Morgantown, West Virginia
S
ince colonial times, the settlement of new frontiers has been undertaken
to open access to land and other types of natural resources. In this chapter,
we take the approach adopted by Findlay (1995) in which frontier movement
is described as the process of incorporating a periphery into an economic
center through a network of trade, investment, and migration. Adopting this
perspective, the recent Indonesian and Brazilian cases of forest frontier expansion have many commonalities but also interesting distinguishing features.
We assume that relative product prices, factor availability, and transportation
costs are the main economic factors affecting the movement of a frontier.
In Brazil, macroeconomic policies, credit and fiscal subsidies to agriculture, and technological change in agriculture have all acted as push factors
in the migration process to remote areas that are, to this date, still sparsely
populated (2.7 inhabitants per square kilometer). In this respect, the Indonesian case is very different, with the island of Java having an average population density of 799 inhabitants per square kilometer and Sumatra having 77 inhabitants per square kilometer. This difference between the Latin
American and the Southeast Asian situations is bound to have repercussions,
through labor availability, on the adoption and impact of the technologies
proposed in the Alternatives to Slash and Burn (asb) matrices developed
for the two regions. In Brazil, regional development policies have attracted
economic resources to the Amazon through the expansion of the road network, colonization programs, and fiscal incentives to agropastoral projects
(Binswanger 1991). The Sumatran case shares some of these characteristics:
Annual population growth rate here has been the highest in Indonesia (3.1
The Forest for the Trees
171
percent annually) and is linked to the government transmigration program that has
so far resettled 220,000 families (ca. 1 million people) to Sumatra. The land allocated
to transmigrants is well mapped and totals 6 percent of Sumatra’s land surface.
Continuing the comparison, if we assume that there are two interconnected components to deforestation, namely logging and land clearing for agricultural purposes,
it is interesting to note that in Sumatra commercial logging concessions started in the
1970s and reached their peak in the 1980s. Of the total area of Sumatra, 30 percent
is under active or passive logging concession today. In Brazil, deforestation is considered to be driven by land clearing for agricultural purposes with much of the timber
extracted as a byproduct of land clearing (Mahar 1989). This may be an oversimplification, given the heterogeneity in productive activities in the Amazon; in fact, it
has been estimated that logging has accounted for approximately 10 percent of total
deforestation in the state of Pará (Watrin and Rocha 1994). Because of its selective
nature, logging in the Amazon rarely leads to complete land clearing, but it appears
to increase deforestation by facilitating access to forested areas for farmers (Uhl and
Vieira 1989; Burgess 1993). Even so, one can safely state that logging, as a component
of deforestation, is less predominant in the Amazon than in Sumatra.
High transportation costs between the Amazon and the rest of the country, leading to high agricultural input costs and limiting interregional trade, also affect deforestation rates. This is confirmed by Pfaff (1997), in which greater distance from markets
south of the Amazon leads to less deforestation. Transportation costs are less likely to
limit Sumatran development because almost all areas are within 20 km of a river and
50 km of a road.
The potential drivers of deforestation in both Brazil and Sumatra occur at different geographic scales, are linked to economic processes guided by different macroeconomic policies, and are conditioned by region-specific factors such as labor supply,
technology, and land tenure regimes. Computable general equilibrium models generally are used to capture fundamental differences in factor endowments and economic
structure and to assess the effects of changes in exogenous shocks (e.g., changes in
exchange rates) on land use and deforestation.
The next section clarifies the modeling strategy considered appropriate for the
problem at hand, describes the database, and presents the results of devaluation simulations. Later in this chapter we present the results of an in-depth analysis of Brazil to
determine the relative importance of different drivers of deforestation. The chapter
concludes with an overview of results and a discussion of their policy implications.
M O D E L CHARACTERISTICS
Thiele (1994) and Wiebelt (1994) model deforestation in Indonesia and Brazil, respectively, using computable general equilibrium (cge) models and consider deforestation
to be driven by forest harvesting for logging purposes, following optimal intertemporal management practices (which assume replanting). The limitation of this approach
172
Thematic Research
to deforestation in both countries is that in reality logging is more similar to an extractive process than a managed forest operation. Second, in the Amazon deforestation is
driven mostly by clearing for agricultural purposes.
Our approach in both the Brazil and Indonesia models is centered on the role
of land as a factor of production. Land is endowed with different characteristics that
affect the profitability of agricultural activities. Economic agents know this and use
these characteristics, among other things, to determine product mix and production
technology on particular types of land. To better describe this approach, it is useful to
define some terms and concepts. In both models, land is differentiated into land types
on the basis of land cover. For example, there are three land types in Brazil: forested
land, arable land, and grassland or pasture. There are two ways to switch from one
land type to another. The first (important in Brazil but less so in Sumatra and hence
not included in the Sumatra model) is via the biophysical process of land transformation brought about by certain agricultural activities. An example is the transformation
of arable land cultivated for upland rice (Oryza sativa L.) into grassland or pasture by
the extraction of soil nutrients. Land transformation processes were modeled as firstorder stationary Markov processes, with land use entering as an exogenous variable
(Van Loock et al. 1973; Baker 1989).
Second, land conversion describes a transition between two land types brought
about intentionally by economic agents as an investment. Examples of land conversion included in the models are as follows: In the Brazilian case, farmers clear forest to
obtain arable land; in the Sumatran case, land can be converted from secondary forest
to arable land.
The modeling approaches taken in the Sumatran and Brazilian case studies were
also different in several other respects. First, the geographic level of aggregation in the
two cases was different. In Brazil, a multiregional approach was adopted in which the
Brazilian Amazon was one of four Brazilian macroregions modeled. For Indonesia,
instead of modeling the whole country and including a Sumatra component, a standalone regional model of Sumatra was developed. Second, because of model size and
data constraints, the level of detail incorporated in the two models was quite different.
The Brazil model had a simpler sectoral and factor disaggregation than the Sumatra
model.
In both cases we modeled deforestation processes as realistically as possible. In
the Brazil case, the model adopted builds on the approach introduced by Persson
and Munasinghe (1995) for a study of Costa Rica. They include logging and squatter
sectors and therefore markets for logs and cleared land. We extend their approach to
include land degradation as a feedback mechanism into the deforestation process. For
the Sumatra case, deforestation is computed as the sum of the land under logging and
the expansion of the sectors that are known to drive deforestation for agricultural purposes (we did not include explicitly a squatter deforestation sector). A comprehensive
review of cge model applications to deforestation can be found in Kaimowitz and
Angelsen (1998).
The Forest for the Trees
173
R e p re s e n tation of Production: Brazil
The production activities considered in the Brazil model are presented in table 7.1,
along with the factors used in production and the commodities produced by these
activities.
For Brazil, agricultural production is disaggregated by region (Amazon, center-west, northeast, and rest of Brazil), activities (annuals, perennials, animal production, forest products, and other agriculture), and scale of operation (smallholder, large farm enterprise). Regional agricultural producers sell their products
to a national commodity market. All factors used by agriculture are region-specific.
Agricultural technologies are specified as two-level production functions, with the
first level representing an agricultural activity’s use of primary factors of production and intermediate inputs in producing output that is transformed and the
second level divided into commodities according to smooth, concave transformation frontiers. Each agricultural activity produces several agricultural commodities.
This specification of production allows farmers to consider certain agricultural
commodities as substitutes, and others as complements, in the production process.
Table 7.1 Production Activities, Commodities, and Factors of Production in the Brazil Model
Production Activities
Commodities Produced
Factors of Production
Annual crop production
Perennial tree crop
production
Corn, rice, bean, manioc, sugar,
soy, horticultural goods, and
other annual crops
Coffee, cacao, other perennial
tree crops
Animal products
Milk, livestock, poultry
Forest products
Other agriculture
Nontimber tree products, timber,
and deforested land for
agricultural purposes
Other agriculture
Food processing
Food processing
Arable land, unskilled rural labor,
skilled rural labor, agricultural
capital
Arable land, unskilled rural labor,
skilled rural labor, agricultural
capital
Grassland, unskilled rural labor,
skilled rural labor, agricultural
capital
Forest land, unskilled rural labor,
skilled rural labor, agricultural
capital
Arable land, unskilled rural labor,
skilled rural labor, agricultural
capital
Urban skilled labor, urban
unskilled labor, urban capital
Mining and oil
Industry
Construction
Trade and transportation
services
Mining and oil
Industry
Construction
Trade and transportation services
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Thematic Research
Product mix and technology choice decisions are responsive to changes in relative
prices (via own-price elasticities, which measure the percentage change in supply of
a good associated with a change in its price) and are conditioned by technological
constraints in transforming agricultural output from one commodity to another (via substitution elasticities, which measure the change in production of one
commodity when the amount produced of another commodity changes). Values
for substitution elasticities were obtained through expert interviews of researchers
from the International Food Policy Research Institute (ifpri) and Empresa Brasiliera de Pesquisa Agropecuária (Embrapa). Degrees of cross-commodity substitution are summarized in table 7.2.
Given that deforestation for agricultural purposes appears to be important in the
Brazilian Amazon, a regional deforestation sector was introduced in the model. The
Table 7.2 Cross-Commodity Substitution Possibilities in the Brazil Model
Commodity
Category
Commodity 1
Commodity 2
Degree of
Substitutability
Annual crops
Corn
Corn
Corn
Rice, bean
Manioc
Sugar, soy, horticulture,
other annuals
Bean
Manioc
Sugar, soy, horticulture,
other annuals
Manioc
Sugar, soy, horticulture,
other annuals
Sugar, soy, horticulture,
other annuals
Soy, horticulture, other
annuals
Other annual crops
Cacao
Other perennials
Other perennials
Milk
Livestock, milk
Timber
Low
Low–medium
Medium–high
Rice
Rice
Rice
Beans
Beans
Manioc
Sugar
Perennials tree crops
Animal products
Forest products
Horticultural products
Coffee
Coffee
Cacao
Livestock
Poultry
Deforested land
(agriculture)
Deforested land
(agriculture)
Nontimber tree products
Low
Low–medium
Medium–high
Low–medium
Medium–high
Medium
High
Medium–high
High
Medium
Medium–high
Medium
Medium–high
Low–medium
Nontimber tree products
High
Timber
High
Source: International Food Policy Research Institute and Embrapa expert interviews.
The Forest for the Trees
175
price for arable land produced by this sector, Par, is determined by the demand for agricultural land. In an infinite horizon framework, the flow return from an asset divided
by the asset price must be equal to the rate of interest in the steady state. Deforesters, being the suppliers of arable land, are faced with this price, and the amount of
land that will be deforested depends on Par and on the deforesters’ profit-maximizing
behavior and technology. The behavior of agents carrying out the land clearing can
be differentiated according to whether forest is an open-access resource or whether
property rights governing the use of the forest resource are well defined and enforced.
In this chapter, forests are considered an open-access resource, so the returns from
standing forest are not included in calculating the profits of deforesters. By assuming
an infinite planning horizon when using arable land, we allow agents to acquire full
property rights through deforestation.
We assume that deforesters provide agricultural land to be sold to whatever agricultural entity is expanding its cultivated area and that logging, though not directly
causing deforestation, is a complementary activity to land clearing (the price of lumber therefore indirectly affects deforestation rates). We also assume that reductions in
soil productivity caused by annual crop production and cattle (Bos taurus) grazing add
substantially to pressure to clear forests.
R e p re s e n tation of Production: Sumatra
The production activities included in the Sumatra model, along with the commodities
being produced by these activities and the specification of factor types, are presented
in table 7.3. The emphasis in this case was on disaggregating the regional economy to
capture all the sectoral linkages. Unlike in the approach taken for Brazil, each activity
produces one commodity, allowing a more detailed description of the links between
factor use and commodities produced but not permitting any representation of complementarity (or substitutability) in the production of different commodities between
activities, as was done for Brazil.
Among the factors, labor is divided into ten categories according to location
(urban or rural), skill level (skilled or unskilled), and employment relationship (hired
or family). There are five land types, categorized according to the activities with
which they are associated. Secondary forest sustains complex agroforestry systems;
perennial land is used for monoculture rubber, oil palm, coffee, and other tree crop
plantations; arable land permits the planting of annual crops; grassland sustains grazing; and aquaculture land is used only for fish or shrimp farming.
An important structural characteristic of production captured in model disaggregation is the distinction between smallholder and estate production of rubber and
oil palm. This distinction is important because production techniques and land types
used by smallholders and estate farms differ greatly.
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Thematic Research
Table 7.3 Production Activities, Commodities, and Factors of Production in the Sumatra Model
Production Activity
Commodities Produced
Factors of Production
Rice
Cassava
Soybean
Maize
Horticulture
Other food crop
Estate rubber
Smallholder agroforestry rubber
Estate oil palm
Smallholder oil palm
Sugar cane
Coffee
Other estate crop
Livestock
Forestry
Fishery
Rice
Cassava
Soybean
Maize
Horticulture
Other food crop
Rubber
Rubber
Oil palm
Oil palm
Sugar cane
Coffee
Other estate crop
Livestock
Forestry
Fishery
Labor
Nonagriculture
Nonagriculture
Food processing
Mining
Other manufacturing
Wood processing
Chemical and rubber
Services
Construction
Trade and transportation
Food processing
Mining
Other manufacturing
Wood processing
Chemical and rubber
Services
Construction
Trade and transportation
Rural agriculture, paid
Urban agriculture, paid
Rural agriculture, unpaid
Urban agriculture, unpaid
Rural production, machinery
operator
Urban production, machinery
operator
Rural clerical and services
Urban clerical and service
Rural professional
Urban professional
Land
Secondary forest
Perennial crop
Grass
Arable
Aquaculture
Capital
Food crop
Tree crop
Livestock
Forestry
Nonagriculture
M AC RO ECONOMIC SHOCKS: CRISIS AND
S T RU C TURAL ADJUSTMENT
Beginning in August 1997, Indonesia suffered one of the greatest real exchange rate
devaluations in recent economic history. In January 1999, Brazil followed suit when
the widespread rumor that states might default on their debt to the Brazilian federal
government sent foreign investors fleeing. Having to choose between making a stand
for its overvalued currency or deciding not to intervene, the Brazilian government
opted not to intervene and floated the exchange rate. The effect was an 80 percent
nominal devaluation.
In this section we briefly review the mechanisms though which a devaluation can
affect land use and deforestation, set out some basic assumptions regarding consumer,
investor, and government behavior in the event of a devaluation, and present the
The Forest for the Trees
177
results of model simulations of devaluations ranging from 5 to 40 percent. Where
welfare effects are identified, they are reported.
The effects of a large devaluation reverberate through an economic system by
affecting relative prices. On the supply side, prices of export goods rise relative to
those of nontraded goods sold domestically (e.g., services and construction). This
prompts production shifts toward sectors that produce goods with a high export share.
On the demand side, the rise in price of imported goods leads to a greater demand for
domestic substitutes for the imported goods. Given enough microeconomic detail in
the cge model, it is possible to follow the reverberations of a macroeconomic shock
throughout the economy, for example, to regional agricultural production sectors and
logging.
The basic assumption is that the macroeconomic shock is transmitted through
the price system to reach a new equilibrium in all markets; however, other assumptions must be made at the macroeconomic level for the price transmission mechanism
to be complete. First, one has to specify the behavior of macroeconomic aggregates,
such as the country’s savings rate, which affects aggregate levels of consumption and
investment. Second, one has to specify the mobility of factors of production, such as
capital and labor, across sectors and regions. We will refer to the set of assumptions as
macroeconomic closure rules.
Among the different possible specifications for savings and investment behavior,
we define balanced adjustment to be a balanced contraction of demand under a financial crisis scenario associated with a flexible savings rate (government consumption
and investment spending as fixed shares of total demand) and capital flight as the
extreme case in which both the government and consumers do not respond to a crisis
but maintain fixed savings rates, and the capital flight resulting from the crisis occurs
completely on the investment side of demand. Regarding factor mobility, scenarios
are distinguished by the time horizon of the adjustment process devaluation as either
short run (this assumes that wages are rigid, so excess supply in the labor market is
possible; we assume that in the short run migration of labor and capital between
regions is not possible) or long run (which assumes wages are flexible and that interregional migration of factors is unobstructed).
Combining the closure rule assumptions listed earlier, we obtain four possible
scenarios: balanced adjustment in the short run and in the long run and capital flight
in the short run and in the long run. Because the mechanisms underlying equilibrium in the labor and capital markets are complex and the relationship between factor
migration and differences in factor wages is uncertain, the results are presented as a
range of possible outcomes. Where in this range of outcomes an economy will actually reestablish equilibrium depends on the speed of adjustment of factor markets,
among other things. Where appropriate, brackets containing the results attributable
to changes in critical model parameter values are included. In particular, we identify
upper and lower boundaries in deforestation rates to highlight the wide range of
parameter-specific outcomes that can occur.
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Thematic Research
D eva luations in Brazil
In what follows we present the results for logging activities (table 7.4) and deforestation for agricultural purposes in the Amazon (figure 7.1) of model simulations of a
range of devaluations under different model closure rules. Note that deforestation for
agricultural purposes and logging react differently to devaluations, and the reaction
depends on closure rules.
Logging in the Amazon (table 7.4) increases uniformly with the degree of devaluation in all simulations, with the capital flight scenario leading to slightly greater
increases in logging than the balanced contraction scenario. This increase in logging
arises from a substantial increase in the exports of processed wood products. From a
policy standpoint, the only option to avoid this increase would be to place an export
tax on processed wood products.
Deforestation to clear agricultural land (figure 7.1) is very sensitive to the aggregate behavior of the national economy and hence to model assumptions regarding
aggregate responses to devaluation. The balanced contraction scenario, with a balanced reduction of private consumption, government demand, and investment,
would lead to a reduction in deforestation that would be substantial in the short run,
but the effect would be attenuated in the long run. The capital flight scenario, where
government expenditures and household savings rates are left unchanged (meaning
investment must decrease drastically), would lead, in the short run, to a small increase
in deforestation for low levels of devaluation and a small decrease for higher levels. In
the long run under the capital flight scenario, a substantial increase in deforestation
rates would occur. Even with the uncertainty underlying the adjustment of factor
markets to devaluation, the differences in these results underscore the importance of
taking macroeconomic policy into account when analyzing deforestation: The types
of policies adopted to address the shock are as important as the shock itself in understanding deforestation rates. For example, a 40 percent devaluation causes, in the long
run, either a 12 percent increase or a 12 percent decrease in deforestation depending
on policy variables; in absolute terms, this represents a difference of approximately
5000 km2 in the amount of forest cleared.
The mechanism underlying the decrease in deforestation for the balanced contraction scenario is linked to the performance of Amazon agriculture relative to agriTable 7.4 Effects of Devaluation on Logging in the Amazon, by Model Scenario
Model Scenario Assumptions
Percentage change
in logging
Balanced contraction
Capital flight
Devaluation (%)
Short run
Long run
Short run
Long run
10
20
30
40
3.9
4.4
4.5
4.9
8.0
8.8
9.4
10.0
12.3
13.4
14.8
15.4
17.0
18.3
21.1
21.3
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179
Figure 7.1 Effects of devaluation on deforestation in the Amazon, by model scenario: (a) balanced plan,
(b) capital flight.
culture in the three other regions of Brazil. A devaluation usually is thought to favor
agriculture because it produces exportable goods; therefore one would expect that the
incentive to deforest for agricultural purposes would increase with the devaluation.
This does not occur in the balanced contraction scenario for two reasons:
• The Amazon has a smaller share of its agricultural production allocated to
exports; although agriculture as a whole does expand, Amazon agriculture reaps little
benefit from the devaluation relative to the other regions of Brazil that produce a
larger share of exportable agricultural products.
• Because the Amazon produces primarily for the domestic market, the contraction in private consumption affects Amazon agricultural production more than production in the other regions.
In the capital flight scenario, the main component of demand to be adversely
affected is investment. This has two important implications: Demand for agricultural
products is not as affected as in the balanced contraction case, and sectors producing
investment goods (construction and industry) undergo a dramatic contraction, especially the sectors producing nontraded goods. The combined effect of these changes is
to increase deforestation because although the Amazon is still less favored than other
regions in producing exportable agricultural goods, agriculture as a whole performs
better than in the balanced contraction scenario and, furthermore, the contraction
in industry and construction leads to an increase in unemployment. This leads to a
larger migrant pool of displaced workers who move into agriculture and thereby affect
the movement of the agricultural frontier in the Amazon. That said, it is important to
note that the effect on deforestation is extremely dependent on the migration flows;
for example, a 30 percent devaluation combined with restricted urban–rural labor
flows generates a decrease in deforestation of –5 percent, whereas the same devaluation in a scenario permitting urban–rural labor flows generates a 35 percent increase
in the deforestation rate.
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D eva luations in Indonesia
The first step in determining the impact of a devaluation on the Sumatran economy
was to simulate the impact of the shock on the Indonesian economy as a whole using
an already available cge model for Indonesia. The devaluation results for Sumatra
were then attained by imposing the commodity prices obtained from the national
model as exogenous border prices for the Sumatran economy (conceptually similar to
the world prices faced by sovereign countries).
The findings are less varied than in the Brazilian case, perhaps because of the
absence in the models of feedback from Sumatra to the rest of the Indonesian economy. The change in deforestation rates, represented as the total increase in land under
Figure 7.2 Effects of devaluation on deforestation in Sumatra, by model scenario: (a) balanced plan,
(b) capital flight.
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181
logging and estate farming, is presented for the different macroeconomic scenarios
in figure 7.2. The area bounded by the short-run and long-run results is very small,
implying that they are very similar to each other for both the balanced plan and the
capital flight scenario. The reason for this narrow response range is the high population density in Sumatra; labor is not a binding constraint for deforestation and can
actually substitute for other factors of production that are fixed in the short run.
In the capital flight scenario, deforestation is slightly lower because capital flight
causes investment to fall. This leads to a slower growth in the logging sector that provides an output that serves as an input to construction, which is an important component of investment demand. Overall, the impact of devaluation on deforestation in
Sumatra is comparable, in terms of percentage change, to the highest levels obtained
in the Brazilian case.
T H E E F F ECTS OF CHANGES IN SOCIOECONOMIC
C H A R AC TERISTICS ON DEFORESTATION IN BRAZIL
This section reports the results of the Brazil model simulations run to examine the effects
on Amazonian deforestation of government investments in infrastructure, changes in
land tenure regimes, and policy-induced changes in agricultural technology.
L i n k s B e t ween Improvements in Transportation
I n f r a s t ructure and Deforestation
Large investments in transportation infrastructure are once again under way in the
Brazilian Amazon. For example, a road through the Amazon to the Pacific is under
construction in Acre, and a recently completed port facility in Rondônia has dramatically reduced transport costs for soybean (Glycine max [L.] Merr.) and other products
of the region. On the eastern side of the Brazilian Amazon, the “center-north multimodal transportation corridor,” including southeastern Pará, eastern Mato Grosso,
and southern Maranhão will reduce the transportation costs of grains with investments in roads, railways, and waterways. The incentives that shape current deforestation rates and land use patterns in the area therefore may shift.
To assess the effects of these and other infrastructure investments, we assume that
costs are reduced uniformly for all agricultural products of the Amazon. In all cases,
a reduction in costs for transportation between the Amazon and the rest of Brazil
increases deforestation rates (figure 7.3a). For small decreases in transport costs, one
can ignore the uncertainty surrounding the elasticity of the response of the national
commodity market to increased agricultural products from the Amazon. For large
decreases in costs, though, it is important to know how the agricultural commodity markets react to such a shock. Because data to estimate such elasticities are not
available, the results provided here are based on sensitivity analysis: Simulations were
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Figure 7.3 The effects of reduced transportation costs in the Amazon on deforestation (a) when deforestation and logging are complements in production and (b) when logging and deforestation are substitutes
in production.
performed with values for these elasticities of between 1 and 12. Because similar agricultural products produced in different regions are generally good substitutes for one
another, this range should bracket the true but unknown elasticity values. Model
results indicate that a 20 percent reduction in transportation costs for all agricultural
products from the Amazon causes an increase in deforestation in the range of 21 to
39 percent (figure 7.3a).
Therefore deforestation rates can be expected to increase as transportation costs
in the region decline. However, the extent of increase in deforestation was found to
depend on the degree of complementarity in production between logging and deforestation activities. In the base run (figure 7.3a) the two activities were assumed to be
complementary (elasticity of transformation 0.3). If instead it is assumed that producers view these activities as substitutes (elasticity of transformation 2.0), in effect
decoupling them in their productive decisions and reacting based only on their relative financial returns, the deforestation rate after the reduction in transportation costs
increases dramatically (figure 7.3b). This is because the reduction in the gap between
farmgate and market prices benefits agriculturalists more than loggers, so in the base
simulation deforesters are constrained by their complementarity with a product for
which costs are not decreasing. If this forced complementarity is removed, which
would be the case if deforesters decided to burn the logs instead of marketing them,
which they often do, increased returns to Amazon agriculture would translate into
dramatic increases in deforestation.
In general, as agricultural production in the Amazon becomes more profitable,
the price of arable land increases, thereby increasing the incentive to deforest. But this
induced deforestation (the environmental implications of which are reported elsewhere in this publication) can have welfare implications. The increase in profitability
leads, in the long run (with mobile agricultural labor and capital), to a 6 to 23 percent
increase in production by smallholders and a 3 to 9 percent increase in production
by large farms. However, welfare effects at the national level are very limited (rural
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183
households at the national level gain only 0.5 to 0.9 percent in real income). This
is because the increase in Amazon production, except for the share that is exported,
replaces previous production from other regions; therefore, the positive regional welfare impact on Amazon development is offset by the negative welfare impact on other
agricultural areas of Brazil.
The reduction in transportation costs scenario highlights how changes exogenous
to the land use systems can dramatically affect deforestation by affecting the profitability of a single agricultural activity or, as in this case, the agricultural sector as a whole.
Furthermore, the dampening effect of the complementary relationship between logging and land clearing for agricultural purposes stresses the importance of the wider
context (of which a land use system is a component). The promotion of a specific land
use alternative (e.g., one or more elements of the asb matrix) may lead to unexpected
results if the substitution and complementarity relationships it has with other productive activities have not been considered.
L a n d Te n ure Regimes and Deforestation in the Amazon
The economic literature linking deforestation to tenure regimes has adopted either a
partial equilibrium approach (Mendelsohn 1994) or an econometric approach based
on the explanatory power of measures of tenure security using cross-country data
(Deacon 1994, 1999; Alston et al. 1996). The approach adopted here is similar to
Mendelsohn’s partial equilibrium description, but the context in our case is one of
general equilibrium. Whereas in the partial equilibrium setting deforesters had the
choice between sustainable forest uses and a destructive agricultural process with
decaying physical output, in a general equilibrium framework, deforesters have an
array of additional choices ranging from wage labor on large farms to migrating to
urban areas to simply cultivating the already-cleared land.
The assumptions made in simulating changes in tenure regimes must be laid out.
We assume in this chapter that deforestation is done exclusively to clear land for agriculture and that by doing so farmers acquire informal property rights to unclaimed
land. The impact of a change in tenure regimes is simulated by making informal
property rights less secure through eviction. This change can be represented in one of
two ways: as an increase in the discount rate equal to the probability of eviction (Mendelsohn 1994) or as a decrease in the expected time of residence on the plot before
eviction. In the analysis that follows, the latter option is adopted (see the appendix
for details).
The results (figure 7.4) show the change in deforestation rate as a function of the
expected time to eviction. The shaded area represents the range of discount rates (15
to 50 percent) believed to bracket the true discount rate of farmers in the Amazon.
The lower boundary of the region occurs when the discount rate is 15 percent and
shows a slow decrease in the deforestation rates that occur as a result of reducing the
expected time of residence on the plot from 22 to 14 years (–18 percent) and a marked
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Figure 7.4 Effects of changes in land tenure on deforestation in Brazil.
decrease from there on (–27 percent for 12 years). The deforestation rate levels off at
around 37 percent of its original value when the expected time of residence is reduced
to 8 years.
The leveling off occurs because as the risk of being evicted increases it becomes
more convenient to deforest previously tenured forest land rather than unclaimed
land. A switch in behavior occurs from deforesting as capitalization on property right
acquisition (even if unsecured) to deforesting solely for the value added that comes
from agricultural activities. An optimal deforestation rate (given the 1994–1996 average) would be around 7400 km2/yr. This value, though far from arresting deforestation, is still much lower than the current trend, suggesting that the mode of tenure
acquisition and its enforcement should be top priority issues. On the other hand, if
the discount rate is higher than 15 percent, the leveling off will be reached for expected times lower than 8 years (the upper boundary, using a discount rate of 50 percent,
reaches the leveling-off value at 2 years).
The assumption that all current deforestation occurs on unclaimed land may
cause the results to overemphasize the impact of regulating tenure. If a share of the
deforestation is already occurring on tenured land, then this will raise the floor in the
deforestation rate because this component will not be affected by changing tenure
regimes. Because by construction we begin from an equilibrium point, we can neither validate nor contradict the hypotheses that tenure leads to more deforestation
(Vosti et al. 2002) or to less deforestation (Deacon 1999). All this analysis can say is
that relative to the 1995 base structure of the economy, assumed as an equilibrium,
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185
if unclaimed land is being deforested, then increasing the probability of eviction will
decrease the deforestation rate to the point where it is profitable to clear only previously tenured land. In this respect, the results contradict the partial equilibrium results
of Mendelsohn (1994), who stated that the possibility of eviction leads to destructive
land uses.
The relevance of simulating the tenure regime modification is that it highlights
how institutional issues may have to be pursued outside the domain of land use systems to reduce deforestation in certain areas of the tropics. It also reminds us that if a
specific land use system is to be promoted, changes in tenure regimes could drastically
alter its appeal to farmers. For example, with the possibility of eviction, few farmers
will adopt technology involving perennial tree crops because the time gap between
planting and fruit bearing can be beyond the expected presence on the farm of any
one occupant.
Te c h n o logical Change in Am azonian Agriculture
At the level of land use systems or specific production activities, much research has
been done on technological change in agriculture in the Amazon. Different farming
and cattle-raising systems have been analyzed (Serrão and Homma, 1993; Mattos and
Uhl 1994; Almeida and Uhl 1995; Toniolo and Uhl 1995), paying particular attention to characteristics such as profitability, credit requirements, agronomic sustainability, and other factors that can influence adoption. We address the issue of technological change at the sectoral level and examine the effects of different types and degrees
of technological change within and across broad geographic regions. Technological
change is assumed to be exogenous to farmers but not to policymakers, and although
the values of key parameters examined here represent a reasonable range of technology
options, they are not based on case studies.
We simulate technological change in the production of annual crops, perennial
tree crops, and animal products and distinguish between smallholder and larger-scale
production systems. Different degrees and types of technological change are analyzed
for each activity. Our reference simulation incrementally increases total factor productivity (tfp) by 70 percent equally across all factors of productions, a process known
as disembodied technological change. Other simulations replicate these incremental
levels of overall productivity increase but spread increases unevenly across factors of
production, a process known as embodied technological change. In these cases, the
extent of specific factor productivity increase is inversely proportional to that factor’s
value share in production. Comparisons across simulations of the different types of
technological change are presented in the form of a tfp index (see the note to figure
7.5 for details of this index).
Table 7.5 shows the different types of technological change examined in the simulations. Because it is difficult to imagine innovations at the Amazon-wide level that are
purely labor improving or capital improving, results represent a range of possibilities
Figure 7.5 Short-run impacts of technological change on deforestation, by type of productivity improvement and scale of operation. CAP_PRD, improved productivity of capital; LAB_PRD, improved productivity of labor; LAND SAV, improvements in labor and capital productivity that increase the overall
productivity of land. The TFP index associated with technical change embodied in factor f is defined as
TFP index = ∆productivityf (factor share).
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Table 7.5 Types of Technological Change
Name
Comments
Acronym
Total factor productivity
increase
Labor productivity increase
Disembodied technological change:
Improvements spread across all factors evenly.
Improved labor productivity: Returns to labor
increase.
Improved capital productivity: Returns to
capital increase.
Replicates land intensification: Less land is
needed to produce a unit of output.
TFP
Capital productivity increase
Labor and capital productivity
increase (land saving)
LAB_PRD
CAP_PRD
LAND SAV
covering all four types of technological change and their combinations. We will not
discuss in detail all the possible combinations of technological change; rather we will
describe for each activity the innovations that lead to the best- and worst-case scenarios in terms of deforestation rates.
We carry out simulations for the short run (can be interpreted as 1 to 2 years), in
which agricultural labor and capital are confined to their regions, and for the long run
(5 to 8 years) by allowing these factors to migrate interregionally.
S h o rt - R un Effects on Deforestation of
I m p rov i n g Technologies
Figure 7.5 presents the results over the short run of different types and degrees of
product-specific technological change on deforestation for small-scale and large-scale
production systems. The upper bound of each figure represents the results of balanced
cross-factor productivity increases (tfp) for different production systems (annual
crops, perennial tree crops, and livestock); the lower bounds of each figure represent
the results of simulations that allowed some factors to benefit more than others from
productivity gains and that were most forest-saving.
Increasing the productivity of annual crop production causes an increase in the
deforestation rates of both smallholders and large farm enterprises, but especially the
latter, which shift resources away from livestock into annual crops on their own farms
and also force smallholders out of annual crops and into cattle production. Balanced
technological change (the upper-bound, tfp cases in figure 7.5a and 7.5b) increases
deforestation on large farms by more than 20 percent for high productivity gains (high
tfp index readings). The lower boundaries of the shaded area in these figures represent types of technological change that are least disruptive to forests: for smallholders,
land-saving technological change causes the least amount of forest loss; for large farms
capital-intensive technological change actually reduced deforestation by attracting
resources away from capital-intensive livestock.
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Increasing productivity of perennial tree crop production in the short run generally reduces deforestation (figure 7.5d). Any technical change in production of perennials embodied in capital or labor has the effect of decreasing the demand for arable
land, thereby allowing arable land to be used as pasture (lowering the price of pasture).
The underlying cause of this shift is that perennials make intensive use of labor and
capital per hectare cultivated (compared with annual crop production). This implies
that as resources are drawn to perennials there will be less overall demand for arable
land. A second reason for the decrease in deforestation is that perennials, as opposed
to annuals, do not transform arable land to grassland. Therefore, there is a stock
effect whereby the amount of available arable land increases, tending to reduce the
demand for deforestation. Smallholders and large farms react differently to different
types of technological change in perennials: Smallholders adopt innovations that are
labor intensive, whereas large farms prefer capital-intensive changes. Thus, in figure
7.5c and 7.5d the lower boundaries of the shaded areas represent, respectively, laborintensive innovation for smallholders and capital-intensive change for large farms.
The case of smallholders experiencing balanced technological change (figure 7.5c)
appears to be the only exception to the decrease in deforestation associated with productivity gains in perennials. This occurs because the reduction in demand for arable
land is offset by the increase in land productivity associated with a tfp improvement, which in turn raises the return to arable land. In practical terms, technological
improvements in perennials will always have some positive spillover to land values. In
any case, as long as the improvement in the productivity of land does not exceed the
improvement in the productivity of the other factors, deforestation will decrease in
the short run.
There is an expectation that improved pasture management and cattle production techniques in the Amazon will reduce deforestation by making more profitable
and productive use of existing grasslands (Mattos and Uhl 1994; Arima and Uhl
1997). The model results presented in figure 7.5e and 7.5f suggest that the effects on
deforestation depend on the type of technological change and the scale of operation.
Almost all forms of technological change on small-scale farms increase deforestation; balanced tfp changes sharply increase deforestation rates, whereas no change
in deforestation is evident in the land-saving scenario (figure 7.5e). The increase in
deforestation rates can be traced back to the transfer of smallholder resources from
annuals and perennials into livestock activities that use more land per unit value of
output. Even arable land is converted to pasture as the livestock sector becomes more
profitable. This is the least-cost solution in the short run; in fact, with a tfp index of
3, smallholder demand for arable land is reduced by 43 to 53 percent in all scenarios
except the tfp case.
Technological improvement in cattle production systems operated by large farms
appears to have great potential to reduce deforestation rates, especially if it is of the
land-saving form (figure 7.5f ). The difference vis-à-vis smallholders is that large farms
already have large shares of their resources allocated to cattle production. By adopting new land-saving techniques, large farms reallocate resources between cattle and
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189
pasture management activities, reducing their land needs. When this is combined
with arable land being used in part for pasture and reductions in the value of grassland
caused by excess supply, the incentives to deforest decrease. Only the balanced productivity gains scenario (tfp) causes an increase in deforestation.
L o n g - R u n Effects on Deforestation of
I m p rov i n g Technologies
Figure 7.6 presents the results over the long run of different types and degrees of
product-specific technological change on deforestation for small-scale and large-scale
production systems. The format of presentation of figure 7.6 is the same as that of
figure 7.5.
Extending (to 5 years or more) the time horizon of analysis by allowing complete intersectoral and especially interregional migration of labor and capital generally causes all forms of technological change in agriculture to cause more deforestation than comparable short-term results. For example, technological improvements
in annual crop production in the long run lead to higher deforestation rates than in
the short-run case, especially for large farms (compare figure 7.5a with figure 7.6a
and figure 7.5b with figure 7.6b). The basic tenet is that with all factors mobile land
becomes the scarce factor. This implies that the returns to arable land are higher than
in the short-run case, creating incentives to deforest.
Productivity gains in perennial tree crop production remain more likely to save
forest than gains in other activities (figure 7.6c and 7.6d). For smallholders, the laborintensive innovations save the most because producing more perennials leaves less
labor for annual and cattle production activities. The underlying process is unchanged,
but with migration there is no surplus arable land to be used as pasture; in fact, arable
land increases in value. However, deforestation is still reduced by the dampening effect
of lower returns to pasture land arising from factors shifting toward the production of
perennials (which uses arable land). This dampening effect is also present in the tfp
and the more capital-intensive scenarios, but it is not enough to offset the prospect
of higher returns from arable land, so deforestation increases in the long run if smallholders adopt these types of innovations.
Increasing by whatever means the productivity of perennial tree crop production
is a safe bet to reduce deforestation on large farms. The upper boundary in figure 7.6d
is given by the capital-intensive innovation, which was also found to reduce deforestation in the short run. The lower boundary is now given by labor-intensive technological change scenario. The reason for this reversal is that in the short run labor is scarce
and capital is abundant for large farms, so capital-intensive technological change is
preferred by large farms. However, perennials are very labor intensive and therefore
in the long run (i.e., when labor availability is no longer an issue) large farms favor
labor-intensive innovations. In each case, the preferred option is the one that leads to
the greatest expansion of perennials and a decrease in deforestation.
Figure 7.6 Long-run impacts of technological change on deforestation, by type of productivity improvement and scale of operation. (See figure 7.5 for abbreviations.)
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191
The expectation or hope that improved cattle and pasture management techniques in the Amazon can reduce deforestation rates is supported only by some shortrun scenarios. This short-run perspective does not take into consideration the longterm effects of a more profitable cattle-ranching sector in the Amazon. In the long
run (figure 7.6e and 7.6f ), as resources are allowed to flow from other regions to the
Amazon, the increased demand for pasture is met by increased deforestation. In all of
the long-run scenarios, improving livestock productivity by any means will substantially increase deforestation. The increase in deforestation rates is particularly strong if
the adoption of technological change in the livestock sector is carried out by the large
farms (figure 7.6f ). The reason for this dramatic increase is that, in the case of large
farm adoption, returns to pasture land increase substantially and the price of arable
land increases. The increased price of arable land comes about because production of
annuals leads to land degradation and subsequent use of the land as pasture; therefore,
as keeping the land in pasture becomes more attractive, the demand for arable land
increases in expectation that it will be used as pasture in the future. In fact, in all the
long-run scenarios, production of annual crops increases alongside that of livestock
(although at a lower rate). Perennial tree crop production, also pursued on arable
land but not a cause of land degradation, does not expand and in some cases actually
declined.
Summarizing the results of technological change scenarios, the best option for
reducing deforestation is to promote technological change in perennial tree crop production. This option has the added benefit of increasing smallholder incomes relative
to those of large-farm enterprises. However, from a purely revenue-driven perspective,
cattle production is the best alternative for both small and large farms. This result is
problematic because any form of technological improvement in livestock will lead to
higher deforestation rates in the long run. Improvements in annual crop production
are possible in some parts of the Amazon and would yield returns roughly equivalent
to those of improvements in perennial systems, but the former probably would cause
higher deforestation rates than the latter.
C O N C LU SION
This chapter used economy-wide models of Brazil and Sumatra, Indonesia, to examine the effects of major currency devaluations on deforestation rates and then explored
in detail the effects of infrastructure improvements and technological change in agriculture on deforestation in the Brazilian Amazon.
A major devaluation of the exchange rate can have an impact on deforestation
that is similar in magnitude to that of technological change, but the direction of
the effect of devaluations on deforestation cannot be known a priori. In the Sumatran case, devaluation leads unequivocally to higher deforestation rates because of
the higher profitability of products exported by the agriculture and forest sectors.
In the Brazil case, by contrast, policies adopted to address a major devaluation are
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as important as the shock itself in determining the direction of effect on deforestation rates: In the long run, a 40 percent devaluation causes either a 12 percent
increase or a 12 percent decrease in deforestation rates, depending on the policy
response. Consequently, understanding the processes that lead to these different
outcomes is important when evaluating the vulnerability of specific land use systems to such macroeconomic shocks; systems producing exportable commodities
are least vulnerable. However, the overall performance of agriculture in specific
regions can also powerfully influence farmers’ choices of land use systems and production technologies.
In the Brazilian Amazon, where transportation costs for agricultural products are
much higher than the national average, improving transportation infrastructure will
lead to substantial increases in deforestation rates. That said, assessing the effects of
reduced transportation costs on the use of cleared land will be more challenging; different products have different transportation costs per unit value, so across-the-board
reductions in transportation costs can alter product mix and choice of production
technique. The link between logging and deforestation solely for agricultural purposes
also affects the impact of a reduction in transportation costs on deforestation rates,
as does the potential for the national economy to absorb products produced in the
Amazon.
Regarding regional policy, regulating and enforcing land tenure is the best option to
reduce deforestation, assuming that current deforestation is in large part occurring at the
hands of untenured deforesters who acquire tenure in the process. Regulating tenure far
surpasses the impacts of any form of technological change in agriculture. Unfortunately,
new tenure regimes are difficult to develop, implement, and enforce in a region the size
of the Brazilian Amazon. However, this result supports initiatives that aim to create buffer zones with integrated participatory management, create clear property rights in these
buffer zones, and discourage any encroachment into protected areas.
Most forms of productivity-enhancing technological change in the Amazon were
found to increase deforestation rates, especially over the long run, when interregional
flows of capital and labor migrated to the Amazon to take advantage of productivity gains. Improvements in cattle production systems were likely to cause the largest increases in long-run deforestation rates, especially if large-scale ranchers adopted
improved technologies. These systems remained the most lucrative even after technological advances in alternative systems were taken into account.
Technological improvement in perennial tree crop production systems was the
only case that led to reductions in deforestation; increased productivity and profitability of this labor-intense product could draw labor and capital away from extensive
alternative systems, especially if adopted by large farms.
The striking difference in the effects on deforestation rates of technology change
between the short run and the long run highlights the importance of interregional
flows of labor and capital in determining the expansion of the agricultural frontier.
This distinction is very important in evaluating the benefits of alternative land use systems: A given system may be expected to reduce deforestation because it is land saving
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193
or because it diverts labor away from deforesting and activities that make extensive use
of land; however, if this system is successful it may attract resources (labor or capital)
from other regions and ultimately accelerate expansion of the agricultural frontier.
Finally, the asset portfolios of agriculturalists mattered greatly in determining the links
between technological change and deforestation; the behavior of smallholders often
was quite different from that of large farms.
Unless deforestation is driven by subsistence needs in isolated areas, the transmission mechanisms from nonfrontier regions to the agricultural frontier are many and
intertwined. Understanding these mechanisms is important in predicting the impact
of policy changes and technological innovations on deforestation, something partial
equilibrium analyses are not well equipped to do.
AC K N OWLEDGMENTS
The authors wish to thank Steve Vosti, Sherman Robinson, Hans Löfgren, and seminar participants at the International Food Policy Research Institute (ifpri), and participants at the Center for International Forestry Research workshop, “Technological Change in Agriculture and Deforestation,” held in Costa Rica in March 1999.
We are also indebted to Eustaquio Reis and all the staff at the Instituto de Pesquisa
Econômica Aplicada for making this research possible and for their comments. This
research was supported by ifpri and Danish International Development Assistance
through its contribution to the asb Programme. The authors thank the two reviewers, Polly Ericksen and Steve Vosti, for providing helpful comments and suggestions
on earlier drafts.
A P PE N D IX: DATABASES AND KEY
M O D E L ASSUMPTIONS
Brazil
The data used in this model were drawn from Cattaneo (2002). The original sources
used to construct the social accounting matrix were the 1995 Input–Output (io)
table for Brazil (ibge 1997a), and the national accounts data (ibge 1997b). These
source were integrated with the agricultural census data for 1995–1996 (ibge 1998)
to yield a regionalized representation of agricultural activities. Household data were
obtained from the national accounts and the household income and expenditure surveys. Total labor, land, and capital value added were allocated across the agricultural
activities based on the agricultural census. Labor was disaggregated into agricultural
and nonagricultural labor and further differentiated as skilled or unskilled. Gross profits in agriculture were allocated in part to land based on the return to land being used
by the activity (fgv 1998) and the remaining part to capital.
194
Thematic Research
Regional marketing margins were estimated by calculating the average distance to
the closest market and using the ratio of these values relative to the industrial South
to multiply the trade and transportation coefficients of each agricultural sector as
obtained from transportation cost surveys (sifreca 1998).
Deforestation (in hectares) in 1995 was assumed to equal average deforestation
between 1994 and 1996. The coefficients for deforestation technology were obtained
from Vosti et al. (2002). Estimates of timber production were obtained from the agricultural census. The economic rent to timber was based on a technological specification proposed by Stone (1998). Elasticities of substitution between production factors
for industry were taken from Najberg et al. (1995). For agriculture, the substitution
elasticity between land and capital was set at 0.4 for smallholders and 0.8 for large
farms. These values are judgment-based estimates, assuming large farms can substitute
more easily between factors. The substitution elasticities in the production process
of agricultural commodities were obtained through expert interviews. Arable land
is assumed to sustain annual production for 4 years before being transformed into
pasture or grassland. Livestock can be sustained for 8 years on pasture or grassland
before degrading land completely. This implies that, on average, 25 percent of arable
land in annuals and 12.5 percent of pastureland in livestock is transformed through
biophysical processes.
We note two limitations in the data and model formulation. Because of the uncertainty surrounding the elasticities, the results of the simulations are meant to clarify
the sign and order of magnitude of impacts of regime shifts and should not be interpreted as precise quantitative measures. For this reason, the results are presented as
a range of possible outcomes given the range of possible parameters. Second, this
chapter compares the impacts of policy shocks in a comparative static framework; the
dynamics of adjustment processes are not considerations.
S u m at r a
The Sumatra model is based on Indonesia’s 1990 intraregional io table (bappnas
and jica 1995) and on Indonesia’s 1990 national social accounting matrix (bps
1994). Complementary data allowed further disaggregation. For example, provincial
crop production data for Sumatra for 1993 were used to disaggregate agricultural
production. The 1993 population survey data were used to calculate factor payments
to households. Disaggregated household consumption data were derived from the
Sumatra household expenditure survey. For each household type, savings were calculated as a residual of income minus expenditures. Regional government revenue was
derived from bps (1996, 1997). Regional government savings were calculated as a
residual of revenues minus expenses. A cross-entropy approach was used to balance
the social accounting matrix (Robinson et al. 1998). The Sumatra model also adopted
a comparative static framework.
The Forest for the Trees
195
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iii. s i t e - s pe c i f i c a lt e r n at i ve s to
s l a s h - a n d - bu r n ag r i c u lt u re
8
Sustainable Forest Management
for Smallholder Farmers in the
Brazilian Amazon
Marcus V. N. d’Oliveira
Embrapa–CPAF–Acre Rio Branco, Brazil
Michael D. Swaine and David F. R. P. Burslem
Aberdeen University Aberdeen, United Kingdom
Evaldo M. Bráz and Henrique J. B. de Araújo
Embrapa–CPAF–Acre Rio Branco, Brazil
T
he conventional forest management system in effect for the Brazilian
Amazon is not widely applied because of political and technical constraints (Hummel 1995). On the technical side, there is a lack of appropriately trained foresters with the necessary skills. On the political side, a legal
document (Forest Management Project) approved by the federal authority
(Brazilian Institute for the Environment and Natural Resources [ibama]) is
required to practice forest management. Acquiring this document can be a
complex and lengthy process. In addition, the existing forest management
system requires substantial investment, which is worthwhile only for large
areas of forest. By contrast, most properties in the settlement projects have
forest reserves areas of only 30 to 50 ha. The 20- to 30-year felling cycles
discourage owners from implementing forest management. Forest conversion
yields large volumes of timber, whereas managed forest produces less timber
with higher costs. Timber from both practices competes in the same market,
with the result that timber prices are low. In addition, policy for the Amazon
was originally focused on agricultural systems, especially cattle (Bos taurus L.)
ranching, and effectively encouraged forest clearance. The net result is that
smallholders are more likely to convert their forest area to nonforest use. A
change in the dominant paradigm governing forest management is needed
if the small producers, such as colonists and rubber tappers, are to become
involved. This change is needed to allow the implementation of techniques
and levels of intervention appropriate to the scale of the production and the
availability of investment capital for smallholders.
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Site-Specific Alternatives to Slash-and-Burn Agriculture
According to the forest code, 50 percent of the area of properties with less than
100 ha must be preserved as a legal forest reserve in the Brazilian Amazon. The only
legal commercial uses of this land are extractivism and sustainable forest management.
Despite the government’s efforts to control land use, some of those forest reserve areas
have already been converted to traditional shifting cultivation and pastures. In 1994,
40 percent of the area was deforested on farms sampled in Colonization Project (pc)
Peixoto and Theobroma in Rondônia state, representing a mean deforestation rate of
natural forest of 2.4 ha/yr per farm (Witcover et al. 1994). Assuming the same deforestation rate in 1999 as in 1994, the farmers in these settlement projects are reaching
the 50 percent limit that they can legally slash and burn. It is likely that they will not
stop, or even reduce, the deforestation rate on their properties unless they can find an
economic and ecologically sound use for their forests.
Riverine populations of the flooded areas (várzeas) of the Amazon Basin have been
harvesting timber for generations. In Amazonas state, the production of timber by riverine populations represents a significant proportion of total wood production (Santos
1986; Bruce 1989; Oliveira 1992). The harvesting intensity is low because only a few
species are used and because of the high-diameter felling limit, making the practice
as a whole environmentally sound (Oliveira 1992). This practice is also found in the
terra firme (upland) forest but varies in intensity according to access and market proximity. The sustainability of the system is determined by the farmers’ capacity to extract
wood and the opportunity that they have to sell it because of the absence of rules and
control. In these systems, timber extraction is a seasonal activity and integrated with
hunting, fishing, nontimber product extractivism, and subsistence agriculture.
The existence of these traditional forest exploitation methods is proof of the
ability of local people in the Amazon to implement sustainable forest management
activities. However, the practice has not yet been formalized as a silvicultural system
and documented sufficiently to allow its application in a systematic way. The forest management model proposed here is a formalization of these traditional methods and was designed for small farmers to generate a new source of family income.
An additional aim is to maintain the structure and biodiversity of the legal forest
reserves, conferring more value on forest than alternative forest uses (Dickinson et al.
1996), thereby increasing their importance for conservation. Formalization helps to
reduce ad hoc changes in the method when external conditions change, such as drops
in the price of extractivist products, economic recession, or third-party greed. In the
absence of formal procedures, short-term changes in economic circumstances undermine the long-term perspective needed for sustainable forest production by small
producers and may lead to fluctuations in harvesting rates and damaging impacts on
the forest.
The ecological basis for this sustainable forest management system, the components of the management system, and their application in a pilot project on smallholder farms in the pc Pedro Peixoto in Acre state in the western Brazilian Amazon
are described in this chapter. Preliminary results from the pilot project on tree growth,
mortality, and recruitment after an initial harvesting are also discussed.
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201
R AT I O N ALE AND ECOLOGIC AL BASIS FOR THE
F O R E S T MANAGEMENT SYSTEM
The proposed forest management system is based on low-intensity harvesting, lowimpact disturbance, and short rotation cycles, which combined may alter the subsequent vegetation dynamics and composition compared with conventional forestry
practices. Selective logging creates disturbances and canopy openings similar to those
of natural tree falls that stimulate the growth of trees in advanced regeneration stages
(Uhl et al. 1990). In contrast, conventional mechanized forest exploitation methods
create significant simultaneous gaps (Johns et al. 1996). In addition, because mechanized logging operations usually are not planned, forest damage is greater, with the
opening of unnecessary skid trails and excessive skidder maneuvering (Uhl and Vieira
1988; Oliveira and Bráz 1995; Johns et al. 1996). Large gaps may take longer to
recover than small gaps because succession starts at the pioneer phase. Pioneer plants
establish and grow rapidly, thus reducing the growth rate of desirable commercial
species through competition. This pioneer effect imposes a longer cutting cycle and
reduces yield. On the other hand, if the impacts of logging are distributed over time,
a lower number of gaps will be created at the same time, and it is likely that the contribution of pioneer species to the natural regeneration will be lower.
Many factors affect decisions about the harvesting cycle length and intensity. The
final choice is a balance of factors including financial needs, species composition, and
site characteristics. Harvesting at low intensities but shorter intervals allows seed production and regeneration because most of the reproductively mature trees are retained
in the residual stand. This is in contrast to long-rotation production systems in which
entire populations of adult trees can be removed at harvesting. Retaining seed trees
between harvesting events helps to maintain the genetic diversity of populations over
time, particularly for species with intermittent reproduction and buffers the population against the possibility of stochastic disturbance events eliminating smaller size
classes (Primack 1995). Shorter cutting cycles can also allow better biological control
than longer cycles because diseased or infested trees can be cut more often. It is also
easier to salvage dead trees if the smaller trees are marketable.
On the other hand, polycyclic silvicultural systems have been criticized for the
damage they cause to the soil and residual trees because of the need to return to the
forest at short intervals (Dawkins and Philip 1998). This damage can be minimized by
reusing old logging roads and skid trails and through better-planned and -controlled
logging operations (Silva et al. 1989; Bráz and Oliveira 1995). The use of mechanized
logging in short-cycle systems probably is limited for both technical and economic
reasons.
In summary, the proposed system is based on the hypothesis that low-impact disturbance at short intervals, combined with silvicultural treatments, will create gaps of
different ages and permit the maintenance of a forest with a structure and biodiversity
similar to those of the original natural forest. However, the longer-term ecological fac-
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Site-Specific Alternatives to Slash-and-Burn Agriculture
tors that are needed to ensure forest recovery of short-cycle systems must be balanced
with the need for a minimum harvest volume intensity to make the activity economically viable.
M E T H O DS
S i t e D e scription
The pc Pedro Peixoto was created in 1977 in an original area of 408,000 ha that was
later reduced to 378,395 ha. It includes the municipal districts of Rio Branco, Senador Guiomar, and Placido de Castro and is planned for settlement by 3000 families
(Cavalcanti 1994). The forest management pilot project is located in two trails on the
road BR-363, 80 and 90 km from Rio Branco and involved eleven farms with 80 ha
each. Because the forest management area represents 50 percent of the properties, each
farm has about 40 ha for forest management.
The nearest meteorological station to the area is the Centro de Pesquisa Agroflorestal do Acre (cpaf/ac) meteorological station at 160 m altitude, 9°58´22˝S,
67°48´40˝W. The climate is classified as Awi (Koppen) with an annual precipitation
of 1890 mm/yr and an average temperature of 25°C (all data from Embrapa–cpaf–
Acre 1996a, 1996b).
C o m p o n ents of the Management System
The formalized systematic application of the forest management practices used by
small farmers in the Brazilian Amazon entails the implementation of techniques for
evaluating the production capacity of the forest (inventory), planning exploitation
activities, and monitoring (Bráz and Oliveira 1996). The management system serves
both harvesting and silvicultural treatments (Hendrison 1990). The basic components and operations of the proposed management system and the specifics of how
they were applied in pc Pedro Peixoto are described in this section. Also refer to figure
12.6a in this volume.
Forest Inventory
A forest inventory is conducted 1 to 2 years before the first harvesting to characterize
the structure and species composition of the forest and evaluate the potential for wood
production.
A forest inventory was conducted in the managed forest areas of the pc Pedro
Peixoto, the inventory was distributed among the 440 ha of the eleven farms, each
with legal forest reserves of 40 ha. The inventory was performed using a systematic
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203
sampling design, with 10- by 100-m plots distributed along ten lines. There were
twenty plots for each area, totaling 214 samples and a total sampled area of 21.4 ha,
4.87 percent of the total area. Later these lines were used as access routes for implementing all activities of the management plan.
All plants larger than 10 cm dbh were measured and identified. The natural
regeneration (plants taller than 1.5 m and less than 10 cm dbh) were sampled in 10by 10-m subplots located in the first 10 m of each plot. The species were identified
by vernacular names by the Acre State Technological Foundation (funtac), mateiros
(local people with great experience in field identification of species), and herbarium
work.
In 2000, Empresa Brasileira de Pesquisa Agropecuária (Embrapa) performed an
inventory of the whole forest area of pc Pedro Peixoto (150,000 ha). This inventory
will be used for future forest management planning in this site.
Forest Management Compartments
Compartments are established within the forest area that will delimit the areas for
the harvesting intervals according to commercial timber volume and cutting cycle
length.
In the case of the Pedro Peixoto, the decision on cutting cycle length must be
based on the small forest areas, the short time to execute all operations, the limited
labor availability, and the use of animal traction for extraction. The small size of the
felling area prevents the creation of many compartments and eliminates the possibility
of using long cycles (at least when annual incomes are desired). For small properties
the cutting cycle may be shortened so that it equals the number of annual felling compartments to create an annual income that allows the owner to pay taxes and forest
management costs (Leuschner 1992).
Figure 8.1 provides a layout of a typical farm in Pedro Peixoto and includes ten
compartments, measuring 100 by 400 m, in the forest reserve that will be harvested
during the 10-year rotation. The compartments are harvested sequentially, with only
one compartment harvested per year.
Prospective Forest Inventory
A prospective forest inventory is performed in each targeted compartment 1 year
before harvesting to allow planning of exploitation activities, defining the trees to be
treated, logged, or preserved. The resulting map can include other information such
as topographic features, the location of skid trails, and preservation areas.
All trees larger than 50 cm dbh are measured, identified, and plotted on a map.
Usually only commercial species are measured in such inventories, but considering the
small size of the plots in the Pedro Peixoto farms, all trees were mapped. This allows
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Site-Specific Alternatives to Slash-and-Burn Agriculture
Figure 8.1 Layout of a typical farm in the Pedro Peixoto colonization project, showing the distribution
of the agricultural land (crops and pastures) and the legal forest reserve. The forest reserve area shows the
forest management compartments based on a 10-yr rotation.
future decisions about which trees might be included in silvicultural treatments. In
addition, the list of commercial species is changing rapidly, and recording all trees on
prospective inventories helps to locate the commercial stems at future harvests.
Skid trails are planned on the basis of the prospective forest inventory. For this
system, a main skid trail 1.5 m wide crosses the middle of the compartment, perpendicular to the direction of the nearest secondary road (figure 8.1). This trail is opened
from the first to the tenth compartment at a rate of 100 m (the width of the compartment) per year.
Some silvicultural treatments can also be applied at this time. The only silvicultural treatment currently incorporated into the management system is climber cutting.
Climbers often bind trees together, and when one is felled others come down; cutting
climbers sufficiently ahead of time may significantly reduce damage (Fox 1968; Liew
1973). Because of the low harvesting impact (no more than two trees per hectare) of
this system, treatments such as protective tree marking (Chai and Udarbe 1977) are
not necessary, and the residual trees will be protected using the prospective inventory
information (i.e., map of trees) and the practice of directional felling.
Determination of Felling Rate
Species are selected and the felling rate determined on the basis of species diameter
distribution, growth rate, and seed dispersal based on information obtained in the
prospective forest inventory. The annual harvesting rate for Pedro Peixoto was determined on the basis of a minimum felling cycle of 10 years and harvesting intensity
of 5 to 10 m3 of timber per hectare. This recommendation is based on a conservative
yield estimate of 1 m3/ha/yr (Silva et al. 1996). The low yield predictions are based,
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205
in part, on the low level of silvicultural intervention that will be used, although it
has been shown that usable timber volume can be increased silviculturally up to 5
m3/ha/yr (Miller 1981; Silva et al. 1996). An additional harvesting rule will be applied
whereby a maximum of one-third of the total commercial volume (stems of commercial species greater than 50 cm dbh) is taken. A similar harvesting rate was used in
Osa Peninsula, Costa Rica, where all trees larger than 60 cm dbh were felled in three
cycles of 10 years (Howard 1993). This rule guarantees that there will be at least three
rotations of the management system. Predicted yields may increase in the future after
the growth studies on permanent plots.
Selective Logging Operation
Logging is then conducted. Trees are directionally felled, when possible, to facilitate
their transport and minimize damage to the forest. The logs are converted in the forest
by chainsaw or one-person sawmills into planks, boards, or other products according
to the characteristics of the timber and market demand. This phase is the most expensive and labor-intensive component of the entire system. Three different studies were
conducted to determine the effectiveness and costs of the different phases of logging.
These studies are described later in this section.
In upland forests, such as at Pedro Peixoto, it is also necessary to saw the logs so
that animal traction can be used to skid them from the forest to the secondary roads.
First the planks are carried to the main skid trail with the use of a zorra (an implement
used regionally to skid planks), and then the planks are moved by wagon from the
main skid trail to the secondary road. Haulage by animals has the advantage of generating less soil compaction and modification, and less damage to residual trees, than
mechanical skidding equipment (Dykstra and Heinrich 1992; Ocaña-Vidal 1990;
fao 1995).
Artificial Regeneration
Desirable species are planted in the felling gaps and on skid trails after logging. One
of the challenges of forest management is to promote the regeneration of species with
high economic value, maintain their populations, and preserve their genetic variability. The regeneration of some desirable species is difficult to achieve without intervention (Evans 1986). This difficulty is characteristic of several species that are under
strong exploitation pressure in tropical forests (e.g., Swietenia spp. in South America,
Khaya and some Entandrophragma spp. in West Africa).
The implementation of artificial regeneration is strongly limited by economic
factors and the heavy demand for labor (Thang 1980). Therefore, its adoption can be
enforced only by the force of law (presupposing an effective policing) in very favorable
economic conditions (e.g., financing, subsidies, fiscal incentives, or elevated return
206
Site-Specific Alternatives to Slash-and-Burn Agriculture
rates) or only at small or medium management scales (Ramos and del Amo 1992).
The most common technique is enrichment planting (Ramos and del Amo 1992),
but in practice the application of these techniques has not been effective in Amazon
because growth and survival has been low (Verissimo et al. 1995).
The artificial regeneration technique proposed for Pedro Peixoto pilot project is
to establish species such as Swietenia macrophylla King, Torresia acreana Ducke, Ceiba
pentandra (L.) Gaertn., Bertholletia excelsa Humb. & Bonpl., and Cedrela odorata L.
in gaps and skidding trails immediately after forest exploitation, using the planting
techniques proposed by Oliveira (2000). The planting will be carried out using a
spacing of around 5 by 5 m. Before planting, manual cleaning of the areas must be
executed. The farmers plant seedlings about 30 cm in height at the end of the dry
season between October and December. No cleanings or other silvicultural treatments
are needed after planting.
Forest Monitoring
Monitoring of the forest responses to forest management is achieved through the
study of the forest dynamics (growth, ingrowth, recruitment, damage, and mortality)
in the permanent sample plots (psps) that were established during the prospective
forest inventory. Forest dynamics are monitored in the psps 1 year before harvesting
and then 1, 3, 5, and 10 years after logging to estimate logging damage and stocking
of the residual stand.
In the pc Peixoto management areas, tree growth, recruitment, mortality, and
species richness and diversity were monitored in five permanent psps for 3 years, with
measurements starting before logging and repeated 1 and 2 years after logging. The
psps were installed in five different management areas, two on the Nabor Junior trail
400 m apart and three on the Granada trail (the first two 400 m from each other and
the third one about 800 m from the second). The distance between the two trails is
10 km. Each psp is a square 1-ha plot, divided into 100 subplots each of 100 m2 (10
by 10 m). All trees larger than 20 cm dbh were tagged, identified, and measured. In
twenty randomly selected subplots in each psp, all trees larger than 5 cm dbh were
also tagged, identified, and measured.
Tree crown exposure was assessed following the same classification as Silva et al.
(1996): full overhead light, when the complete crown received direct sunlight; some
overhead light, when the crown receives some direct sunlight; and shaded, when the
crown does not receive direct sunlight.
Species groups were assigned to the following categories: pioneer species that
included both short-lived pioneers and large pioneers, shade-tolerant species divided
between understory trees and canopy trees, and commercial species that included all
species that have been sold in Rio Branco market by the farmers.
Species richness was defined as the total number of species on plots (Kent and
Coker 1992) and diversity was expressed using Fisher’s α. This index was chosen
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207
because it is stable with changes in sample sizes and can be used to predict the number
of species in larger samples (Condit et al. 1996).
Mean annual mortality rates (amrs) were calculated using the formula of Sheil et
al. (1995): amr = 1 – (N1/N0)1/t, where N0 and N1 are population counts at the beginning and end of the measurement interval, t.
Recruitment rate includes all plants that attained the minimum measurement
diameter of 5 cm dbh. Recruitment rate was standardized by dividing the total number of recruits in one census by the number of adults in the previous census, then
dividing by the census interval (Condit et al. 1996).
Growth rates were calculated using the formula (dbh2 – dbh1)/t, where dbh1 and
dbh2 are diameters at the beginning and end of measurement interval t, respectively.
Differences in growth rates were tested statistically using Tukey’s test after one-way
analysis of variance (anova) for species groups and crown exposure. Where there was
evidence that the residuals were not normally distributed, the data were transformed
using the Box Cox transformation (Minitab 12.23).
Growth of Residual Trees
Growth of the residual trees and artificial regeneration of desirable species are assisted
by removing badly formed or undesirable trees 5 years after logging.
F o re s t E xploitation Experiments
Tree Felling and Conversion of Logs to Planks
A study was conducted to determine the time needed for each phase of the logging
operation (tree felling, cutting the log, and converting the logs to planks). The efficiency of the conversion to planks was determined as the final volume of planks relative to the initial volume of logs. The study took place in two managed areas, one
off the Nabor Junior secondary road and the other off the Granada secondary road.
The data were collected during four logging events, using trees of Guarea pterorachis
Harms, Hymenolobium excelsum Ducke, and Dipteryx odorata (Aubl.) Willd. from 45
to 97 cm dbh. A total of twenty-eight logs, each 2.2 m long, were processed by a team
of three men.
Plank Skidding
In this study, the time needed for the different steps in the skidding cycle were measured: the travel (unloaded) from the edge of the secondary road to the felling gap in
the forest, loading of the planks, the time to travel back (loaded) to the secondary road,
208
Site-Specific Alternatives to Slash-and-Burn Agriculture
and the unloading of the planks. The time needed to rest the animals was considered
wasted time. This study was carried out in two managed areas, both off the Granada
secondary road. The data were collected in five skidding events and forty skidding
cycles, where planks of four species were being skidded (Couratari macrosperma A.S.
Smith, Dipteryx odorata (Aubl.) Willd., Protium apiculatum Swartz, and Peltogyne sp.).
The skidding distances varied from 200 to 1400 m, and the planks were loaded onto a
zorra. The skidding was performed with two teams of two men working with an ox on
each team. The oxen used for skidding the planks were two individuals of the Melore
breed of age 5 and 8 years and weighing around 500 kg.
Forest Management Costs and Economic Analysis
Costs were estimated on the basis of the minimum salary offered in Brazil in 1997 of
us$100 per month, a working day of 6 hours, a 5-day working week, and a team of
three people for all activities except the skidding of the planks, where the team consisted of only two men. The depreciation of the chainsaw was calculated as 25 percent
per year and the useful life of the oxen 10 years. The harvesting and conversion of the
logs to planks was performed with a Stihl 051 chainsaw.
R E S U LTS AND DISCUSSION
F o re s t I nventory
The vegetation is predominantly evergreen tropical forest with some deciduous species that included Tabebuia serratifolia (Vahl) Nichols., Ceiba pentandra (L.) Gaertn.,
and Cedrela odorata L. Structure varied from open (low-stature forest with a dense
understory and high occurrence of lianas and palm trees) to dense (taller forest with
greater standing timber volume and no dense understory). The structure depended on
the drainage and topographic status of the site.
In total, 307 species were identified, from 185 genera and 54 families. The most
common family was the Caesalpinaceae, with eighteen genera and twenty-three species sampled. The distribution of the species across the area was very irregular, with
some species common (e.g., Protium apiculatum Swartz) and other rare species sampled only once in all 214 samples (e.g., Macrolobium acaceifolium Benth.).
The forest had an average of 375 trees/ha (trees larger than 10 cm dbh), an average basal area of 22 m2/ha, and total volume of 180 m3/ha. The volume of trees below
commercial size of 50 cm dbh was 107.4 m3/ha, and the volume of trees of commercial size was 73.1 m3/ha (table 8.1).
The forest contained a high volume of commercial species, (46.5 m3/ha above 10
cm dbh). This volume is composed of hardwood species used in construction, such as
Dipteryx odorata (Aubl.) Willd. and Hymenaea courbaril L., and species with an inter-
Sustainable Forest Management
209
Table 8.1 Results of the Forest Inventory at Pedro Peixoto Colonization Project Showing Mean
Values of Tree Density, Basal Area, Volume, and Standard Deviation (SD) and 95% Confidence
Interval for Estimates of Total Volume
Average number of trees (dbh 10 cm)/ha
Basal area
Total volume of timber (dbh 10 cm)
Standing volume (dbh 50 cm)
Standing volume (dbh 10–50 cm)
Volume confidence interval (p .05)
Minimum
Maximum
SD
SE (%)
375.4
22.0 m2/ha
180.4 m3/ha
73.1 m3/ha
107.4 m3/ha
171.0 m3/ha
189.7 m3/ha
71.6
4.8
mediate commercial value, such as Aspidosperma vargasii A.D.C., Protium apiculatum
Swartz, and Peltogyne sp. However, highly desirable species such as Cedrela odorata L.
and Torresia acreana Ducke were present but with low commercial volume.
The volume of commercial timber in the study site is around 20 to 30 m3/ha.
Although the conventional forest management system in the Amazon uses a harvesting rate of 30 to 60 m3/ha on a 30-year cycle, it does not usually exceed 30 m3/ha
(Johns et al. 1996). Thus, the outcome in terms of yield will be equivalent to the standard rotation of 25 to 30 years established by ibama for mechanized management.
The annual felling rate should not fall below 5 m3/ha/cycle; otherwise, harvesting is
likely to be uneconomic, returning less than the minimum salary practiced in Brazil
around us$100.
Some species were very common in the natural regeneration such as Trinorea
publifora (Benth.) Sprang & Sandwith, but others were rare, such as Chrysophyllum
spp. Some species were recorded only in the regeneration and not in the adult population (e.g., Piper hispidinervum C.D.C.) because they have a low maximum size or are
shrubs. Almost all commercial species were found in the regeneration. Some of the
species not present in the inventory samples (e.g., Torresia acreana Ducke) were later
sampled in the natural regeneration areas of the felling gaps study.
M o n i to ring Permanent Sample Plots
Mean Diameter Growth Rate
During the study period, diameter increment varied from 2 cm/yr (e.g., Jaracatea
spinosa Aubl.) to 0.1 cm/yr and even less for some understory species (e.g., Quaribea
guianensis). The pioneer and shade-tolerant species groups showed significant differences in mean relative growth (table 8.2). The large difference in the mean diameter
increment of canopy species and understory species indicates that even after group-
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Site-Specific Alternatives to Slash-and-Burn Agriculture
Table 8.2 Annual Diameter Increment (mean and SE) for Species Groups of the Trees in the
Five Permanent Sample Plots in Pedro Peixoto
Group
Growth Ratea (cm/yr)
SE
Short-lived pioneer species
Big pioneer species
All pioneer species group
Canopy species
Understory species
All tolerant species group
All trees
0.63a
0.57ab
0.61a
0.29b
0.21b
0.26b
0.28
0.25
0.29
0.25
0.03
0.03
0.28
0.04
Means followed by the same letter are not significantly different (Tukey test, p .05).
a
ing into shade-tolerant and pioneer species, there are still species with very different
growth patterns in the groups.
Crown exposure had a strong influence on diameter increment, independent of
ecological grouping. On the psps, the variation in mean diameter increment resulting
from crown exposure was from 0.47 cm/yr (trees with full overhead sunlight) to 0.19
cm/yr (shaded trees). Trees that only received some direct sunlight had a mean growth
rate of 0.34 cm/yr (table 8.3).
Diameter increment was not affected by diameter class when analyzed within
crown exposure classes. The expectation that diameter increment increases with tree
size may exist because most of the slow-growing trees die when they are small and
because the big tree class includes no understory species (Swaine et al. 1987).
Table 8.3 Mean Annual Diameter Increment by Diameter Class and Crown Illumination on the
Permanent Sample Plots at Pedro Peixoto
Diameter Class
5–10
10–19.9
20–29.9
30–39.9
40–49.9
50–59.9
60.0
Average for all plantsa
Full Overhead Light
Some Overhead Light
Shaded
Growth Rate
(cm/yr)
SE
Growth Rate
(cm/yr)
SE
Growth Rate
(cm/yr)
SE
0.42
0.57
0.38
0.50
0.40
0.55
0.45
0.46a
0.05
0.11
0.03
0.05
0.06
0.07
0.04
0.18
0.29
0.43
0.32
0.30
0.37
0.34
—
0.34b
0.06
0.04
0.02
0.02
0.05
0.01
—
0.06
0.20
0.21
0.25
0.32
0.36
0.22
—
0.20c
0.02
0.01
0.02
0.04
0.10
0.08
—
0.03
Means followed by different letters are significantly different (Tukey test, p .05)
a
Sustainable Forest Management
211
The annual diameter increments recorded here were similar to other values
obtained in tropical forests (e.g. Okali and Ola-Adams 1988; Chiew and Garcia 1989;
Rai 1989; Silva et al. 1996), showing an average of 0.27 cm/yr for the plants measured
on all psps in the period (cpaf/ac and pc Peixoto).
The effect of crown exposure on the growth rate of trees is well known and has
been reported before (e.g., Silva et al. 1989; Silva and Whitmore 1990). However, the
results presented in this work demonstrate that a large increase (of up to 100 percent)
in the mean annual diameter increment can be expected after a change of the crown
exposure of a tree (table 8.3). This finding provides strong support for the application
of silvicultural treatments in the region.
Stand Basal Area Increment
The total stand basal area in the psps before logging was 24.28 m2/ha, and that of
the commercial species was 5.96 m2/ha. The logging of the areas caused a reduction
in these to 22.93 and 4.89 m2/ha, respectively. Two years after logging the mean total
stand basal area was 23.12 m2/ha, with 5.33 m2/ha for the commercial species. These
changes represent a mean annual increment of 0.09 m2/ha/yr (0.76 m3/ha/yr) for the
total stand basal area and 0.13 m2/ha/yr (1.06 m3/ha/yr) for the commercial species.
The greater volume increment of the commercial species (1.06 m3/ha/yr) in the
psps at pc Pedro Peixoto compared with the total volume increment (0.76 m3/ha/yr)
can be interpreted as an increase in the population of the commercial species in the
total volume in the forest. This might be an affect of directional felling, which aimed
to reduce the environmental impact of logging and the protection of residual trees of
commercial and potential species. The volume increment of commercial species was
compatible with the logging intensity and cycle length proposed.
Mortality and Recruitment Rates
Tree mortality immediately after logging was 3.7 percent and 2 years after was 3.2
percent per year. The average for the period was 3.0 percent per year. A peak in the
mortality was observed from 1998 to 1999 (4.0 percent), which might have been
influenced by the El Niño event that year because 1 year after logging the mortality
was only 2.2 (figure 8.2).
High recruitment rates of thirty-six plants per hectare per year in the first 2 years
after logging were found in the pilot project. This rate is high partly because it included all trees above 5 cm dbh. Because recruitment considered only trees larger than
5 cm dbh, the time of the study was insufficient to include the cohort of trees that
germinated immediately after the logging. Thus, an increase in the recruitment rates
in those areas may be expected in the next few years.
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Site-Specific Alternatives to Slash-and-Burn Agriculture
Figure 8.2 Mortality of trees >5 cm dbh in the five permanent sample plots immediately after logging
(1996–1997), 1 yr (1997–1998), and 2 yr (1998–1999) after logging, and the mean rate (gray bar) for
the 2 yr after logging (1996–1999). Lines indicate SD.
Damage by Timber Exploitation and Natural Causes
In this study, logging damage for all trees was estimated from the basal area of trees
that fell or had their crowns destroyed in or around felling gaps (Oliveira and Bráz
1995). Therefore, it includes even the trees that fell as a result of natural causes (e.g.,
high winds and storms); logging operations were considered responsible by increasing
the tree’s crown exposure.
The damage caused by the low-impact forest management logging operations
(sensu Oliveira and Bráz 1995) affected 1.21 m2/ha or 5.1 percent of the stand basal
area 1 year after logging. The damage caused by natural causes (e.g., wind and storms)
in the same period was 1.02 m2/ha, or 4.3 percent of the stand basal area (figure 8.3).
The canopy opening caused by the harvesting was minimized by the low harvest intensity (two trees per hectare) and the use of oxen to skid the planks. The damage caused
by logging was greater in the first years after logging, probably because of the death
of damaged trees. Two years after logging there were still some effect of the logging,
but the damage to the forest from natural causes was higher. The damage produced by
natural causes showed a tendency to increase after the harvesting, from 0.61 m2/ha 1
year before to 1.61 m2/ha 2 years after logging (figure 8.3). The increased damage can
be associated with the logging impact but was probably also associated with the fact
that 1998 was an El Niño year, with more frequent and stronger storms in the area.
Species Richness and Diversity
Two years after logging the number of species was lower in the managed area than
before harvesting (235 and 259, respectively). The density of stems of commercial
species larger than 5 cm dbh was similar before and 2 years after logging and therefore
Sustainable Forest Management
213
Figure 8.3 Mean basal area of nondamaged (white bars), damage caused by natural causes (dark bars), and
damage caused by logging (light bars), before logging (1996), 1 yr (1998), and 2 yr (1999) after logging.
Lines indicate SE.
apparently was not affected by a harvesting intensity of one or two trees per hectare.
Fisher’s index varied from around 84 before harvesting to 81 after logging (table 8.4).
The variation in species richness and diversity before and after logging was too low
to be considered significant. It is possible that diversity will increase above that before
management started because opportunities for invasion by pioneer species increases
with canopy opening.
F o re s t E xploitation Experiments: Preliminary Results
Tree Felling and Conversion of Logs to Planks
The efficiency of conversion (in volume terms) of logs to planks was between 61 and
41 percent for the biggest and smallest trees, respectively, with an average of around 50
percent. The total time to convert 1 m3 was 5.1 work-hours. For a 6-hour work day,
214
Site-Specific Alternatives to Slash-and-Burn Agriculture
Table 8.4 Species Richness and Diversity in the Permanent Sample Plots of Colonization
Project Pedro Peixoto Before and 2 Years After Logging
Before logging
Two years after logging
Total
Number
of Stems
Number of Stems
of Commercial
Species
Total
Number
of Species
Number of
Commercial
Species
Fisher’s
Based on
All Species
1737
1390
265
225
259
235
35
32
84.3
81.1
a team of three people produced 3.6 m3 of sawn timber, which represents a very low
productivity even when compared with that of a small sawmill (around 10 m3/day).
On the other hand, because the annual potential production of these farms is only
about 40 m3 (10 m3/ha × 4 ha/yr), the maximum annual labor requirement therefore
is only about 18 work-days to convert this unsawn timber into about 20 m3 of planks
(table 8.5).
Skidding the Planks
The number of skidded pieces varied between one to four per ox per trip according
to their shape and weight. The load therefore varied from around 0.19 m3 (Dipteryx
odorata [Aubl.] Willd.) to 0.39 m3 (Couratari macrosperma A. S. Smith), with an average of 0.28 m3. The loading and unloading of the zorra also were strongly affected by
the shape and specific weight of the wood. The pace of the oxen was approximately
4 km/hr and was kept constant even when the skidding distance increased from 200
to 1200 m. However, when the distance increased to 1400 m the time needed to load
and unload the zorra was not long enough to rest the animals for continuous operation. The total volume skidded in 1 day by a team of two men and one ox varied
according to skidding distance, from 1.14 m3 (skidding distance 1400 m) to 3.36 m3
(skidding distance 250 m) (table 8.6).
Table 8.5 Work-Hours Needed to Complete Each of the Phases Involved in Felling Trees and
Converting the Timber into Planks
Phase
Time for the Complete Tree
(work-hours, mean [SD])
Time for 1 m3
(work-hours, mean [SD])
Cutting the tree
Cutting the logs
Converting logs to planks
Chainsaw maintenance
Wasted time
Total time
0.5 (0.20)
1.0 (0.07)
23.0 (0.80)
6.0 (0.88)
1.8 (0.32)
32.3 (1.97)
0.1
0.2
3.5
0.9
0.4
5.1
Sustainable Forest Management
215
Table 8.6 Breakdown of the Performance and Volumes Skidded by Two Teams of Two Men
with One Ox per Team over Three Skidding Distances (200, 1200, and 1400 m) in the
Managed Forest of the Pedro Peixoto Colonization Project
Performance and Volume
Mean
SD
Skidding Distance (m)
200
1200
1400
Effective work day average (work-hours)
Total wasted time per day (work-hours)a
Average time for complete cycle (work-hours)
Number of cycles per day
Average volume skidded per cycle (m3)
Average volume skidded per hour (m3)
Total volume skidded per day (m3)
13.7
0.5
1.1
12
0.28
0.43
3.36
11.00
1.0
1.7
6
0.28
0.26
1.68
12.3
2.0
1.1
6
0.19
0.13
1.14
0.19
0.07
Mean
SD
0.13
0.04
Mean
SD
0.45
0.07
The time to rest the ox was counted as wasted time.
a
Costs and Economic Analysis of the Proposed Forest Management System
The production costs were between us$33.5 and us$35.5/m3 of sawn planks at the
roadside before transport to the market (table 8.7). Considering the costs of transportation, at around us$15/m3, the total costs would be around us$50/m3. The current
market price for wood in Rio Branco varies between us$100 and 150/m3, according
to species and the quality of the planks. Therefore, even with the low level of technology and experience available to the farmers for this activity, it was possible to achieve
ratio of benefits to costs of around 2:1 (table 8.7). In a similar small-scale forest management system in Nicaragua, Castañeda et al. (1995) found a return of us$47 per
work day and production costs around us$43 to us$65/m3.
Table 8.7 Mean Cost of Each Phase of the Forest Management System per Cubic Meter of
Harvested Timber
Forest Management Phase
Cost ( $)
Trail opening
Prospective inventory
Silvicultural treatment
Felling and converting logs to planks
Skidding with animals
Transportation
Total
4.2
1.4
0.8
19.9
7.1
15.0
48.4
216
Site-Specific Alternatives to Slash-and-Burn Agriculture
I M P L I C ATIONS FOR THE FOREST
M A N AG EMENT SYSTEM
F o re s t Exploitation and D ynamics After Logging
Production is generally quite low in lightly exploited forests without silvicultural treatments (De Graaf 1986). The increased growth of the trees remaining after harvesting
tends to disappear after only 3 to 4 years after the harvesting (Silva et al. 1989). Therefore, harvesting timber in a simple polycyclic system and leaving the forest to regenerate
without further silvicultural assistance, such as enrichment plantings and refinement, is
not a satisfactory approach for maintaining forest productivity (De Graaf 1986).
The implementation of liana cutting, directional felling, and planning the skid
trails in this management system reduces the damage caused by logging and extraction
and contributes to the maintenance of forest productivity (Pinard and Putz 1996).
Additional silvicultural treatments should be considered, such as the elimination of
badly formed trees, refinement of undesirable species, crown liberation (for commercial species), and gap liberation (sensu Kuusipalo et al. 1996). The goal of refinement
should not be to eradicate undesirable species but to reduce their proportion and
competitiveness in the stand (De Graaf 1986).
The proposed system will facilitate the application of silvicultural treatments,
which are planned as part of the conventional system. Because of their high labor,
demand and costs usually are not executed. Farmers regularly enter the forest management area on their properties during the work day for hunting, fishing, and rubber
tree tapping. Therefore, it would be a simple matter to carry out the silvicultural treatments proposed here as part of the daily work schedule.
The use of the zorra over long distances reduces the productivity of the skidding
phase. Alternatively, a small wagon pulled by one ox for the primary transport of the
planks from the main skid trail to the edge of the secondary roads limits the skidding
by zorra to the distance from the felled tree to the main skid trail, or a maximum journey of 200 m. This does not compromise the productivity of the overall operation.
Acquisition of more data from psps will allow the system to be fine-tuned by calculations of future harvest rates and the length of future felling cycles. This phase may
be executed by a partnership between research and teaching institutes and the local
people. The system also allows ongoing modifications of the basic model according to
feedback provided through monitoring and data acquisition.
E co n o m i c and Social Benefits: Limitations
a n d S t rengths of the Propo sed System
It must be recognized that the system has a low profitability when compared with
the yields obtained by mechanized forest management. A low profitability is to
Sustainable Forest Management
217
be expected for a system designed to be applied in communities with a shortage
of investment capital. In this case, the social benefits obtained by returning low
profits to the colonists rather than higher profits to forestry companies can be used
to justify the application of the system. On the other hand, the other available
land use options for small farmers and colonists (shifting cultivation, extractivism, and small-scale cattle ranching) also usually return low profits (Vosti et al.
2001).
The price of timber is likely to increase in the future because of the rise in the
demand for tropical timber worldwide and the restriction in supply, especially of the
more valuable timbers. The constant restrictions on the availability of the timber of
certain highly valued species, combined with international pressure for preservation
of some of these species, has created a strong incentive for introducing new species to the market. There is also a potential market for plywood species (e.g., Ceiba
spp.), which was not considered because of the low prices in the local market for the
wood sold in logs. The group of commercial species is changing quickly. Therefore
the current standing stock of timber represents an investment rather like a savings
account.
The small property, as a unit of production, does not prevent collective or cooperative agreements between neighboring proprietors. Indeed, the aggregation of producers into larger units may facilitate the acquisition of new technologies (e.g., oneperson sawmills, oxen, and small tractors), result in increased prices in local markets,
and reduce the cost of overheads such as transport. Collective working might generate
a substantial increase in the yields from forest management, and within a short time
the profits generated by the forest management as proposed here will increase significantly.
A potential problem with forest management is the effects it can have on the
fauna, changing the abundance of individual species, their food availability, the
distribution of microclimate or other environmental conditions and changes in
competitive relationships. These changes also could affect pollination, seed production, and seed dispersal (e.g., mahogany in Budongo forest in Uganda; Plumptre 1995), which are usually correlated with logging intensity (e.g., seed predators
in Gorupi Forest Reserve). These effects usually tend to decrease over time (e.g.,
number of species of understory birds in Kerala National Park in Uganda; Drauzoa
1998).
In the case of pc Peixoto, the impact of the management on the fauna probably
will be minimized by the low harvesting intensity, the high number of commercial
species (diluting the effect of reducing the density of a single species, such as the
exploitation of mahogany in Pará State East Amazon; Verissimo et al. 1995), and the
use of animal traction instead of mechanized log extraction. In addition, hunting
throughout the year is a common practice among most of the farmers, which might
have a much higher impact on the fauna and seed dispersal (Guariguata and Pinard
1998) than the forest management, which is restricted in space (the compartment)
and time (the cycle length of 10 years).
218
Site-Specific Alternatives to Slash-and-Burn Agriculture
F u t u re Prospects
Small-scale forest management provides an opportunity to fill a gap in land use in
the Amazon by allowing small farmers to use the forest reserves on their properties
in an economical and sustainable way. Forest management will help to maintain and
preserve these reserves, which are currently under strong pressure to be converted to
pastures and shifting cultivation.
It will be necessary to invest in farmer training to improve future yields. Additional time and work rationalization studies are needed and can be achieved by monitoring of the forest management activities involved in the forest management system. All
forest management activities must be performed by the farmers themselves and, where
possible, collectively. This avoids the costs of contracting the work to a third party.
To consolidate this proposal, some changes to forest legislation will be necessary,
and policies must be implemented to enforce and promote these changes. A specific
legislative framework covering inspection and implementation of management plans
on small properties was approved in 1998. This legislation established the use of short
cycles and animal traction by ibama agencies and provides promise for future sustained forest management by smallholders.
AC K N OWLEDGMENTS
We wish to acknowledge the support of the asb project and the Environment National Fund for equipment and field team funding.
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9
Permanent Smallholder Rubber
Agroforestry Systems in Sumatra, Indonesia
Gede Wibawa and Sinung Hendratno
Indonesian Rubber Research Institute Sungei Putih, Indonesia
Meine van Noordwijk
ICRAF Southeast Asia Nairobi, Kenya
A
lthough there is a long tradition in Southeast Asia of trading resins and
latex collected from the natural forest or secondary forests that were part
of shifting cultivation cycles, the introduction more than a century ago of
Pára rubber (Hevea brasilienses [Willd. ex Adr. Juss.] Muell Arg.) from the
Amazon to Southeast Asia formed the basis for the spontaneous and broadbased adoption of new agroforestry practices at a scale not matched elsewhere.
“The history of agriculture probably has not seen any other case where the
introduction of a single crop had such a dramatic effect on the economic condition of smallholders in vast areas, as the introduction of Hevea brasiliensis in
Indonesia” (van Gelder 1950:428). The food crop–based shifting cultivation
systems in which the fallow was of secondary importance were transformed
into systems in which the food crop that could grow in between young rubber
trees became a secondary aspect of a production system relying on rubber to
generate income. Rubber agroforestry appears to have many of the attributes
of a best-bet alternative to food crop–based slash-and-burn agriculture: They
are profitable, produce easily marketed products, and generate environmental benefits. Therefore rubber agroforests of various management intensities
have become one important focus of Alternatives to Slash and Burn’s (asb’s)
research program (Tomich et al. 1998, 2001; van Noordwijk et al. 1995,
1997). Yet the impact of this land use system—which helped attract migrants
to the forest margins—on the rate of deforestation is still debated (van Noordwijk et al. 1995; Tomich et al. 2001).
Rubber is a major export commodity supporting the Indonesian economy. More than 1 million households now depend on rubber as their main
source of income. Smallholder rubber constitutes 83 percent of the total
Indonesian rubber area (3.5 million ha) and 68 percent of total rubber pro-
Permanent Rubber Agroforestry Systems
223
duction. Smallholder rubber systems often are called jungle rubber (Gouyon et al.
1993; Williams et al. 2001), a complex agroforestry system based on production of an
economically important commodity that maintains the structure, carbon stocks, and
species richness of secondary forest vegetation (Foresta and Michon 1996). Typically,
management by smallholders is extensive and uses very few external inputs. However,
major opportunities may exist to increase the productivity of these systems by making
use of improved rubber germplasm.
All rubber agroforestry systems in Indonesia start (or started) by clearing land:
slashing, cutting, and felling the forest and burning it during the dry season. Rubber
seedlings typically are planted into an upland rice crop (for 1 or 2 years) and left to
grow along with those forest species that can regrow from stumps and the secondary
forest species that come into the plot as seeds from neighboring areas. When the rubber trees have reached a girth of about 40 cm (after 5 to 10 years, depending on site
conditions), tapping can begin and part of the vegetation is cleared to create a path
for walking from tree to tree and to promote rubber seedling growth. When the first
generation of trees becomes old and unproductive, two basic options exist for rejuvenation of the stand: cyclical and permanent agroforestry.
A cyclical rubber agroforestry system begins a new cycle with another round of
land clearing: slashing, cutting, and felling the old jungle rubber and burning it during the dry season. Cleared land is replanted with seedlings or grafted clonal rubber
trees, sometimes in combination with upland food crops (e.g., rice [Oryza sativa L.],
maize [Zea mays L.], or mung bean [Vigna radiata L.]). Leguminous cover crops are
used only in establishing a new rubber plantation on large estates. Technical, economic, and ecological aspects of these systems are well documented (Gouyon 1996;
Penot and Wibawa 1997; Wibawa and Thomas 1997).
But the cyclical system can suffer from or pose financial, agronomic, and environmental problems. For example, replanting rubber after slash-and-burn land clearing in
cyclical systems may reduce farmers’ incomes from rubber during the immature period
(5–7 years), and replanting with clonal varieties is expensive. Substantial risk of plant
damage also exists throughout the establishment period from pests (wild pigs, monkeys),
diseases (white root rot), and fire. Global environmental benefits of such agroforestry
systems in terms of biodiversity conservation and carbon stocks (chapters 2 and 4, this
volume) are limited by the recurrence of a burn after each cycle of 25 to 30 years.
An alternative method of rejuvenating old rubber agroforests in Sumatra is the
sisipan system, which culminates in a permanent rubber agroforest that more closely
resembles a natural forest in terms of the age and size distributions of trees. This permanent system is based on the management of small plots (about 1 ha in size) within
which very small parcels (about 100 m2 in size) are rejuvenated either by spontaneous
regeneration from seeds or by rubber seedlings planted in forest gaps. This type of
rejuvenation is common in Sumatra in damar (Shorea javanica Koord. & Valeton)
and fruit tree agroforests and home gardens. With this type of management, a single
field can contain rubber trees of all ages, with a subset always available for tapping.
Decisions on gap replacement are made at the tree rather than field level, thereby pro-
224
Site-Specific Alternatives to Slash-and-Burn Agriculture
viding more opportunities to introduce valuable nonrubber trees and to retain older,
productive rubber trees. We hypothesize that the prospects for biodiversity conservation and time-averaged carbon stocks are higher in permanent rubber agroforestry
systems than in cyclical systems and that the risks and investment associated with
permanent systems are better suited to smallholders with little land, labor, and capital
at their disposal.
As part of the asb research activities in Indonesia, villages in and surrounding
the benchmark areas in the lowland peneplain and piedmont zones (van Noordwijk
et al. 1995) were surveyed to better understand farmers’ interests in and constraints
to adopting the sisipan permanent agroforestry system as an alternative to the cyclical
system. Land use systems (luss) were characterized at the field, patch or gap, and tree
levels. At the lus level, the following issues were addressed: What farm and farmer
characteristics (e.g., gender, age) are associated with sisipan system adoption; how
does the economic performance of the sisipan system compare with the cyclical slashand-burn alternative; and what are the scope for and obstacles to increasing the productivity of sisipan systems? This chapter presents the materials and methods, results,
and conclusions from this study.
M AT E R I ALS AND METHODS
The survey was carried out in Jambi Province, Sumatra, in an area extending beyond
the original asb benchmark site (van Noordwijk et al. 1995, 1997; Murdiyarso et al.
2002). Jambi is one of the main rubber-producing provinces in Indonesia and represented approximately 17 percent of national smallholder rubber area (495,556 ha) in
1995 (dge 1995). From this province, seven villages in the Bungo Tebo district were
chosen to represent two main agroecological zones: the foothills (piedmont zone) and
the lowland peneplain zone. Five of the villages are in the piedmont zone (Rantau
Pandan site), and the other two are in the peneplain zone (Bungo Tebo site; see table
9.1). The survey was carried out between October 1998 and January 1999, so all
financial information refers to the period after the monetary crisis that began in the
second half of 1997.
In these villages, farmers who had implemented sisipan as part of their livelihood
strategy were chosen for interviews. Thus the survey was of an exploratory nature and
did not propose to identify the proportion of farmers who practiced sisipan or slashand-burn–based systems. The objective was to improve our understanding of how sisipan systems were practiced and to explore why farmers chose sisipan for rejuvenating
rubber agroforests. Insights for selecting larger, random samples for future studies can
be gleaned from this research. Respondents selected were those available at the time
of the interview and chosen from lists provided by village chiefs and farmer leaders.
Seventy-six farmers were involved in the study.
The interview process had two stages. The first stage consisted of interviews with
village chiefs and farm leaders. The aim was to collect secondary data on village char-
Permanent Rubber Agroforestry Systems
225
Table 9.1 Villages Surveyed and Numbers of Respondents, by Agroecological Zone
Agroecological Zone
Village
Number of Respondents
Piedmont zone
Sepungur
Lubuk
Muara Kuamang
Pintas Tuo
Embacang Gedang
Rantau Pandan
Muara Buat
9
7
11
8
10
14
17
76
Peneplain zone
Total sample size
acteristics, the number of farmers who had implemented permanent systems, and
general rubber-farming conditions. In the second stage, interviews were conducted
at the household level to collect primary data on farmer, farm household, and farm
characteristics and to obtain detailed information on the implementation of permanent systems. These structured interviews were supported by direct observation of the
respondents’ rubber agroforests.
To compare the necessary inputs and financial performance of sisipan and cyclical rubber agroforestry systems, five variations on these basic systems were identified
and analyzed: cyclical systems using locally acquired seedlings, cyclical systems using
high-productivity clonal rubber seedlings, sisipan systems using local seedlings and
standard yields, sisipan systems using low-productivity seedlings (15 percent lower
yields than those of local standard seedlings), and sisipan systems using local seedlings
with standard yields but also benefiting from offtake from fruit trees.
The net present values (npv), internal rates of return (irr), and benefit:cost (bc)
ratios were calculated for each of the five systems. In addition, for each system two
cost scenarios were calculated, one (called fully costed) that used market prices to
value all inputs used in production (land, family labor, hired labor, small farm equipment, and fertilizers) and a second (called partially costed) that used market prices to
value inputs actually purchased in the market (i.e., land, family labor, and upland rice
seeds were not included in this cost scenario because their true opportunity costs may
have been below the market price).
R E S U LTS AND DISCUSSION
C h a r ac t eristics of Farmers Interested in Permanent
R u b b e r Agroforests and Their Farms
In the study area, sisipan practices appeared to be widespread. Between one- and twothirds of the farmers had adopted sisipan on at least part of their operational holdings.
The seventy-six respondents who were managing permanent rubber agroforests at the
time of the survey had the following characteristics.
226
Site-Specific Alternatives to Slash-and-Burn Agriculture
The head of the family managing a permanent rubber agroforest was typically male
(95 percent), was a local rather than migrant farmer (75 percent), and had completed
primary school (71 percent). Twenty-eight percent of farmers were partially employed
in off-farm, nonagricultural activities (e.g., teachers, carpenters, or traders), and 17
percent had official village roles, such as village officer or Muslim scholar (ulama).
The average respondent was 41 years old (the median age was 36 years), had long
experience of rubber farming (18 years), and had known about the sisipan technique
for about 7 years. Older farmers tended to be more recent adopters of the sisipan
system, whereas younger farmers tended to have known about it for as long as they
had had rubber agroforests. This result suggests that land availability, distance to forest plots, and establishment costs may affect sisipan adoption. For example, young
farmers tended to have land further from the village than the older farmers, making
it more difficult to control pest damage in a new plantation. And, as an alternative to
rejuvenating old rubber agroforests, forest land could be opened, cleared, and planted
using the cyclical system. But forest clearing is done by young farmers, who still have
strength to do the hard work it entails, or by the rich, who can afford to hire such
services. Most new rubber agroforest land is prepared using slash-and-burn. Of the
land opened by slash-and-burn in our survey, most was forest and fallow (bush) land
(88 percent), and only 12 percent was old (cyclical system) rubber.
The average operational holding was 6.4 ha and included several land uses (table
9.2). Most farmers (61 percent) had other farm land or forest, bush, or fallow land,
suggesting that they could expand the area under production. Size of operational holding did not seem to influence sisipan adoption, which was practiced by some farmers
with very large and others with very small farms.
Eighty four percent of farmers indicated that knowledge of sisipan was passed
from father to son. The role of extension officers in influencing sisipan adoption decisions was very limited; only 4 percent of the sample reported learning about sisipan
from extension workers.
Average household size was 5.7 people. Of these, the average number of potential
family laborers (males and females between ages 15 and 55) was about 3, and the
amount of family labor used on the farm was about 2.2 people (roughly equivalent
to 660 person-days per year). Perhaps most importantly, the majority of farmers (68
percent) reported facing labor shortages. Sisipan is well adapted to labor shortages
Table 9.2 Average Area Dedicated to Particular Land Uses and Total Operational Holding
Land Uses
Average Areas (ha)
Number of Respondents
Reporting a Given Land Use
Rubber garden
Mature rubber
Immature rubber
Rice fields and other farming operations
Housing
Other land (forest, bush, and fallow)
Total operational holding
2.2
1.8
0.7
0.1
1.6
6.4
71
60
50
42
46
Permanent Rubber Agroforestry Systems
227
because little time must be devoted specifically to it. For example, farmers manage
emerging components of sisipan systems (planting or maintaining the saplings) after
tapping mature trees, while performing other tasks in the field, or during rainy days
when the opportunity cost of their time is low.
Regarding overall labor use, 54 percent of farmers depended exclusively on family
labor in rubber production, and the remainder reported using family and hired labor.
Most respondents (97 percent) agreed that hired labor was available in the village at
a daily wage rate of Rp7000 to Rp17,000 (approximately us$1–2 at the late 1998
exchange rate of us$1 = Rp7500). Wage rates varied by task, location of task, and
gender of laborer and were linked to the price of rice; the daily wage rate was generally
equivalent to the market value of 2.5 kg of rice.
The average, continuously tapped rubber area was 2.2 ha and contained approximately 525 trees/ha. This average area produced an 82.4-kg slab of rubber per week.
The dry rubber content of this slab was about 45 percent, so the average productivity
of a rubber garden was about 880 kg of dry rubber/ha/yr, or approximately 12 g of
dry rubber per tree per tapping-day. The productivity of rubber in the study areas
was 35 percent higher than the national average for smallholders (Ditjenbun 1997)
but much lower than the productivity of clonal rubber in plantations (1500 kg of dry
rubber/ha/yr) (Hendratno et al. 1997).
Sixty-nine percent of the farmers’ income was derived from rubber, with the
remainder coming from off-farm employment, rice production, and the collection
of wood and nontimber forest products (table 9.3). Because of the importance of
rubber in generating income, most farmers could not afford to slash and burn and
replant entire areas that contain low-productivity trees because doing so could interrupt income flows for up to 7 years. The sisipan system provides a continuous, though
sometimes reduced, flow of revenues from rubber tapping by introducing seedlings
while retaining older but still productive rubber and other trees. Income flows from
Table 9.3 Average Annual Income and Expenditures by Source and Use
Income and Expenditures
(thousands of 1998 Rp)a
Percentage of Total Income
or Expenditures
4819
1424
768
7011
69
20
11
100
4344
46
2028
6418
68
1
31
100
Income
Rubber
Other farm activities
Off-farm activities
Subtotal
Expenditures
Consumption (mainly food)
Education
Others (clothes, socials, etc.)
Subtotal
$1 Rp7500 in late 1998.
a
228
Site-Specific Alternatives to Slash-and-Burn Agriculture
agroforests were sustained during a sisipan phase by intensively tapping all remaining
rubber trees (and accepting the consequent reduction in their lifespans) or by selling
fruits and timber products. Farmers were aware that the growth of sisipan rubber
seedlings was very slow, but by maintaining high plant density and planting low- or
no-cost seedlings farmers could stabilize incomes at acceptable levels. As regards overall family budgets, most farmers (76 percent) reported an annual income surplus after
basic necessities were met, whereas the remaining 24 percent of farm households faced
recurring deficits; for most farmers, then, the sisipan rubber system seemed to provide
an adequate living.
Damage to seedlings by pests (mainly monkeys and wild pigs) could be substantial.
To reduce these risks farmers could plant seedlings in fenced, large-diameter stumps
or in bushy areas to hide seedlings from pests. In areas where risk of pest damage was
very high, farmers generally used low-cost (and low-productivity) local seedlings as
planting material, thereby reducing the value of unavoidable losses. Farmers wanting
to boost productivity in these high-risk areas could plant clonal rubber and protect the
seedlings with fences or live temporarily on the plot to guard seedlings.
Nonrubber trees in permanent systems also provided benefits to farm households,
and the abundance of these trees depended on the growth stage of the patch and management intensity. Farmers surveyed mentioned more than eighty valuable nonrubber tree species, forty of which could be exploited from permanent rubber agroforest
systems, and others were of less value but still retained if they did not compete with
valuable species. Three fruit species were identified by many farmers as sources of food
or income: petai (also known as parkia; Parkia speciosa Hassk.), jengkol (also known
as blackbead; Pithecellobium jiringa W. Jack]), and durian (Durio zibethinus Murray).
The number and diversity of nonrubber plants in rubber agroforests were closely related to the management choices by the farmers who weeded intensively (two to three
times per year) during the first 2 years while food crops were grown (ladang phase)
and thereafter only minimally managed the agroforest (again, via weeding). During
this period of less intensive weeding, forest regrowth from seedlings or resprouting
from stumps emerged and valuable trees (timber, fruits, and, rattan) were selected for
retention every 3 to 4 years as farmers slashed weeds and other less valuable vegetation.
This management process continued selectively cutting trees to allow light to promote
rubber seedling growth.
Fa rm e r Concerns, Economic Per formance
o f A lt e rnative Systems, and Strategies for Improving
R u b b e r Agroforest Productivit y
The survey identified five main factors that jointly affected farmers’ decisions to
adopt permanent rubber agroforestry systems (table 9.4). Note that continuity
of income flows and risk reduction were key farmer objectives met by the sisipan
system.
Permanent Rubber Agroforestry Systems
229
Table 9.4 Factors Influencing Farmers’ Decisions to Practice Sisipan, in Descending Order of
Positive Response Rates
Factor
Percentage of Respondents Indicating a
Positive Effect on Sisipan Adoption
Decision
Sisipan increases land productivity and maintains income
flows from existing rubber and other trees.
Sisipan reduces the risk of pest damage.
Sisipan can be practiced using family labor alone.
Sisipan is a simple, known management practice.
Sisipan can be practiced with little or no capital or cash.
99
74
58
56
51
As indicated earlier, economic performance indicators were calculated for two
versions of the cyclical system (the first using local seedlings and the second using
more productive clonal planting material) and three versions of the permanent system
(the first using local seedlings, the second using seedlings yielding 15 percent less than
local seedlings, and the third using local seedlings and deriving income from nonrubber trees). The results of this analysis appear in table 9.5. All calculations were done on
the basis of 1-ha parcels managed over a 30-year period and assumed a farmgate price
of dry rubber of Rp3570 per kg and daily wage rates for men and women of Rp7000
and Rp5000, respectively. Prices were derived from survey data and were assumed to
remain constant over the entire 30-year evaluation period. Three measures of ecoTable 9.5 Financial Performance Indicators for Cyclical and Permanent Agroforestry Systems,
by Productivity and System Scenario and by Cost Accounting Method
Systems and Scenarios
Measures of Financial Performance
Net Present Value
(20% discount rate;
thousands of late-1998 Rp)
Fully costed
Cyclical
Local seedlings
Improved seedlings
Permanent
Local seedlings
Low-productivity seedlings
Local seedlings and fruit
Partially costed
Cyclical
Local seedlings
Improved seedlings
Permanent
Local seedlings
Low-productivity seedlings
Local seedlings and fruit
Internal Rate
of Return (%)
Benefit:Cost
Ratio
80
250
22
21
1.02
1.03
1,300
400
3,900
33
32
50
1.09
1.03
1.27
1,800
1,500
35
24
2.80
1.29
13,800
11,400
13,800
50
50
50
8.72
7.41
8.72
230
Site-Specific Alternatives to Slash-and-Burn Agriculture
nomic performance were calculated (npv, irr, and bc ratio) all of which presented
consistent patterns; in what follows we focus on important npv results.
First, all rubber agroforestry systems evaluated generated positive economic
returns; that is, the discounted streams of benefits minus costs were positive for all
systems. Simply put, it paid to invest in rubber agroforests of any kind.
Second, the permanent systems clearly dominate the cyclical systems in terms
of npv. The cyclical system using improved seedlings (npv = Rp250,000) could
not compete with even the permanent system using low-productivity seedlings
(npv = Rp400,000). This result is more significant when one considers the continuity
of income emerging from the permanent systems but absent from the cyclical systems
(important to the results presented in table 9.5 but not specifically addressed there).
Third, including income derived from timber, bark, and fruit trees such as jengkol, petai, and durian dramatically increased the economic performance of permanent
systems (npv increased from Rp1,300,000 to Rp3,900,000).
Fourth, not surprisingly, all measures of economic performance improved if farm
land and family labor were not considered in calculating production costs. Differences
were largest for the permanent systems that used family labor more intensively.
Finally, rubber yields may vary spatially and over time. Sensitivity analysis (not
presented in table 9.5) suggested a bc ratio of 1 if rubber yields fell to 656 kg/ha/yr.
The productivity of both cyclical and permanent systems was low when local
seedlings were the source of planting materials. To increase productivity, new
planting material must be introduced. Smallholder rubber yields per tree could
be more than doubled if improved clonal material were to replace local seedlings.
The Indonesian Rubber Research Institute has recommended the planting of several rubber clones that increase rubber productivity and also provide useful timber products (Lasminingsih 1995). Economic analysis suggests that farmers would
benefit from switching to improved seedlings, but obstacles to adoption exist
(Williams et al. 2001; Joshi et al. 2002). For example, the economic returns to
investing in improved seedlings depended on farmers’ abilities to protect them
from pest damage by fencing, round-the-clock vigilance, or village-level hunting.
Although pest risks under cyclical and permanent systems cannot be compared yet,
fencing individual trees in permanent systems with bamboo shafts appears to be
effective (unpublished icraf report). In addition, improved seedlings (which are
usually grafted) grow more slowly in heavily shaded permanent systems than in
cyclical systems, but growth can be sped up if improved material is grafted directly
onto well-established local seedlings.
Although initial farmer responses to seedling grafting have been quite positive,
impediments to adoption exist. Currently, there are few reliable sources of improved
planting material (district-level markets in Muara Bungo or Rimbo Bujang dominate the market for these seedlings), and grafting skills are not widespread. Expansion of the area dedicated to improved planting material (via grafting) could promote
the development of local businesses such as rubber and other tree crop nurseries and
increase job opportunities for those skilled in grafting.
Permanent Rubber Agroforestry Systems
231
C O N C LU SION
Permanent rubber agroforestry systems occupy significant proportions of agricultural
systems in the lowland peneplain and lower piedmont zones of Sumatra, Indonesia,
where they also make substantial contributions to smallholder income. Although these
systems are becoming more broadly adopted, little is known about their economic
performance or the environmental services they generate. One traditional method
of establishing and maintaining permanent rubber agroforests is the sisipan system,
which does not use slash-and-burn practices but rather selectively removes old and less
valuable trees and replaces them with rubber seedlings. The economic performance
of permanent systems was found to be superior to the alternative cyclical systems
that do use slash-and-burn techniques. Sisipan was also found to be compatible with
smallholder characteristics in the region, especially labor shortages and lack of capital
for agricultural investments. As the extensive margin is reduced in Sumatra and forest
resources become scarcer, the sisipan system will become even more widespread.
But the productivity of sisipan systems based on local planting material remains
low, with consequences for smallholder welfare. Productivity can be improved by introducing clonal rubber germplasm or by expanding the number of products extracted
from rubber agroforests. More and more focused research is needed. Policy action to
develop more productive germplasm and facilitate its adoption by smallholders is also
needed.
AC K N OWLEDGMENTS
We acknowledge financial support provided by the Australian Centre for International Agricultural Research through the asb Programme, and the assistance of the
icraf Southeast Asia staff during field data collection.
References
DGE (Directorate General of Estate). 1995. Statistik karet. Direktorat Jendral Perkebunan,
Jakarta.
Ditjenbun (Direktorat Jenderal Perkebunan). 1997. Statistik Perkebunan Indonesia 1995–
1997. Karet, Jakarta.
Foresta, H. de, and G. Michon. 1996. Tree improvement research for agroforestry: A note of
caution. Agrofor. Forum 7(3):8–11.
Gouyon, A. 1996. Smallholder production faced with the world rubber market. Plantation,
Recherche, Develop. 3(5.):338–345.
Gouyon, A., H. de Foresta, and P. Levang. 1993. Does the jungle rubber deserve its name?
An analysis of rubber agroforestry systems in Southeast Sumatra. Agrofor. Syst. 22:181–
206.
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Hendratno, S., G. Wibawa, and C. Anwar. 1997. Evaluasi dan analisis proyek proyek pengembangan karet rakyat di Jambi. Jurnal Penelitian Karet (J. Indonesian Rubber Res. Inst.)
15(1):42–56.
Joshi, L., G. Wibawa, H.J. Beukema, S.E. Williams, and M. van Noordwijk. 2002. Technological change and biodiversity in the rubber agroecosystem. Pp. 133–157. In J. Vandermeer
(ed.) Tropical agroecosystems: New directions for research. CRC Press, Boca Raton, FL.
Lasminingsih, M. 1995. Klon klon karet harapan untuk program hti. Paper presented on
Lokakarya Nasional Pemuliaan Tanaman Karet. Medan, 28–30 November.
Murdiyarso D., M. van Noordwijk, U.R. Wasrin, T.P. Tomich, and A.N. Gillison. 2002. Environmental benefits and sustainable land-use options in the Jambi transect, Sumatra,
Indonesia. J. Vegetation Sci. 13:429–438.
Penot, E., and G. Wibawa. 1997. Complex rubber agroforestry systems in Indonesia: An alternative to low productivity of jungle rubber conserving agroforestry practices and benefits.
pp. 56–80. In Proceedings of the Symposium on Farming System Aspects of the Cultivation of Natural Rubber (Hevea brasiliensis), Beruwala, Sri Lanka, 5–8 Nov. 1996. Int.
Rubber Res. and Develop. Board, London, UK.
Tomich, T.P., M. van Noordwijk, S. Budidarsono, A. Gillison, T. Kusumanto, D. Murdiyarso,
et al. 1998. Alternatives to Slash-and-Burn in Indonesia. Summary report and synthesis
of phase II. ASB, icraf, Nairobi.
Tomich, T.P., M. van Noordwijk, S. Budidarsono, A. Gillison, T. Kusumanto, D. Murdiyarso,
et al. 2001. Agricultural intensification, deforestation and the environment: Assessing
tradeoffs in Sumatra, Indonesia. Pp. 221–244. In D. Lee and C. Barrett (eds.) Tradeoffs
or synergies? Agricultural intensification, economic development and the environment.
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van Gelder, A. 1950. Bevolkingsrubber. Pp. 427–475. In C.J. van Hall and A. Van de Koppel
(eds.) De Landbouw in de Indische Archipel. Van Hoeve, the Hague, the Netherlands.
van Noordwijk, M., T.P. Tomich, D.P. Garrity, and A.M. Fagi (eds.). 1997. Alternatives to
Slash-and-Burn Research in Indonesia. Proceedings of the workshop, Bogor, 6–9 June
1995. Agency for Agric. Res. and Develop., Jakarta.
van Noordwijk, M., T.P. Tomich, R. Winahyu, D. Murdiyarso, S. Suyanto, S. Partoharjono, et
al. (eds.). 1995. Alternatives to Slash-and-Burn in Indonesia: Summary report of phase 1.
ASB–Indonesia Rep. No. 4. ASB–Indonesia Consortium and icraf, Bogor, Indonesia.
Wibawa, G., and Thomas. 1997. Study of Hevea based intercropping system functioning. pp.
25–39. In Proceedings of the Symposium on Farming System Aspects of the Cultivation
of Natural Rubber (Hevea brasiliensis), Beruwala, Sri Lanka, 5–8 Nov. 1996. Int. Rubber
Res. and Develop. Board, United Kingdom.
Williams, S.E., M. van Noordwijk, E. Penot, J.R. Healey, F.L. Sinclair, and G. Wibawa. 2001.
On-farm evaluation of the establishment of clonal rubber in multistrata agroforests in
Jambi, Indonesia. Agrofor. Syst. 53:227–237.
10 Coffee, Pastures, and Deforestation in the
Western Brazilian Amazon
a farm-level bioeco n o m i c m o d e l
Chantal L. Carpentier
North American Commission for Environmental Cooperation Quebec,
Canada
Stephen A. Vosti and Julie Witcover
University of California Davis, California
T
ropical moist forests are disappearing every year, and much clearing is
driven by the demand for agricultural land. This conversion of forest
to agriculture carries with it costs and benefits. The costs include soil degradation, deterioration in water quality and availability, biodiversity loss, and
conflict with traditional forest dwellers. The benefits, production of food
and fiber for consumption and sale, can also be considerable for inhabitants
of forest margin areas and populations depending on agricultural exports
from these areas, but large gaps in assessments of environmental and poverty
dimensions prevent an evaluation of the overall impact of forest conversion.
Activities at many levels (e.g., the Biodiversity Convention, Kyoto Protocol,
Amazon Treaty Organization, Pilot Program to Conserve the Brazilian Rain
Forest, and national-level movement to protect extractive reserves in Brazil)
that seek to mitigate further deforestation via some kind of government
intervention respond to a scenario in which, at the private level, the benefits
of clearing land outweigh the costs of land conversion, and social costs of
deforestation are higher than the benefits.
In the past, economists paid attention mainly to external drivers of
deforestation such as distorting macro policies and Amazon settlement
subsidies (e.g., Hecht 1985; Binswanger 1987). Most of these policies
have been stopped, yet deforestation continues. This suggests that external drivers apart from policies may be at work, but more importantly, that
internal drivers—factors within the region—may play an important role.
Recent analyses of these internal drivers failed to integrate production systems effectively into either a whole-farm view or into current socioeconomic conditions of small-scale farmers in the western Brazilian Amazon
234
Site-Specific Alternatives to Slash-and-Burn Agriculture
(Vosti et al. 2002). In their review of economic models of deforestation, Kaimowitz
and Angelsen (1998) found that national models failed to account for internal
drivers.
Although some believe that improving yields on already cleared land in forest
margin areas will take pressure off the remaining forest, and promoting perennial
and agroforestry systems will alleviate some ecological damage caused by deforestation, responses by resource users to technology and policy changes are not necessarily straightforward. This chapter looks at those responses, which ultimately will
determine the impacts of forests and rural inhabitants on policy and technology
change.
In part to fill this gap, a Farm Level Bioeconomic Model (Falebem) was built
to study how various policies and technology interventions affect land use decisions of small-scale farmers in the western Brazilian Amazon. The western Brazilian
Amazon is home to much of the world’s remaining tropical moist forests and to
more than 500,000 small-scale farmers whose annual decisions to deforest (or not)
will have a large influence on the ultimate fate of the forest. For instance, an average small-scale farmer in the settlement project of Pedro Peixoto, Acre, slashed and
burned 2.46 ha of forest per year (Lewis et al. 2002), annually emitting 367 t of
carbon contained in this forest (Palm et al. 2002; Lewis et al. 2002). Using linear
programming to simulate consumption-maximizing behavior of farm households,
the Falebem incorporates farm-level objectives and constraints to production; can
be adjusted to fit the heterogeneity of land, labor, and farm household characteristics prevalent in the area; and tracks the income, soil productivity, carbon stock,
and forest depletion impacts of current and proposed technology or policy experiments.
The Falebem helps structure thinking about these issues and replaces “I think”
statements with “if–then” statements through policy experiments. It differs from
purely economic models in that it simulates biophysical processes and economic
activities based on optimization algorithms. What differentiates this bem from most
bems applied to developed countries, such as those of Shortle (1984), Ellis et al.
(1991), Dosi and Moretto (1993), and Carpentier et al. (1998), is the feedback of
soil fertility depletion and regeneration on agricultural production and deforestation.
The Falebem effectively links deforestation decisions to production decisions on the
cleared land. Also, Falebem overcomes criticisms of many linear programming models by approximating nonlinear production and damage functions with linear segments (Barbier and Bergeron 1998).
For this chapter, the model was used to predict the effect of changes in input and
product prices, particularly that of coffee (Coffea canephora Pierre ex Fröhner L.),
between 1994 and 1996 in the state of Acre. Model simulations of land use for the
1994 baseline for the settlement project of Pedro Peixoto in Acre are compared with
simulations of 1996 with more favorable coffee prices.
Coffee, Pastures, and Deforestation
235
M E T H O DS
Th e M o d el
The Falebem, a dynamic mathematical programming model written and solved in
gams (Brooke et al. 1992), was developed to model the decisions of representative
small-scale subsistence-oriented settlers in the Pedro Peixoto project in the western
Brazilian state of Acre. It simulates the typical farmer’s responses to a wide range of
policy, technology, and project interventions. The model incorporates all the important biophysical and economic factors thought to affect farmers’ decisions about land
use and deforestation (see Lewis et al. 2002, for a more detailed description of the
model).
The model assumes that farmers maximize the discounted value of their household consumption over a 15-year time horizon, but it is not a utility-maximizing
model because it values consumption but not leisure time. However, this maximization is subject to serious labor constraints. Previous work has shown that labor availability is the major factor in slowing deforestation (Lewis et al. 2002).
Although the model has a 15-year planning horizon, it is solved recursively at
5-year intervals. If one updates all the constraint values for each solution, a series of
moving 15-year farm plans are obtained that can be used to track much longer periods
of time than the initial 15-year period. This is especially useful for exploring longterm changes in land use and the sustainability aspects of different farming practices.
The results presented in this chapter are based on a 25-year period and were derived
from five recursive runs of the model for each policy experiment.
There are also minimum consumption constraints that must be met each year for
food, clothes, and farm implements. The model allocates farm income each year to
consumption and on-farm investments. When income is invested it increases future
production potential, and hence future consumption, but at the expense of current
consumption. Income is generated in the model by the production of products for
home consumption or sale. Production choices are subject to an array of resource and
technology constraints, including seasonal land, labor, and cash flow constraints. For
example, in keeping with local restrictions on markets, milk sales are constrained by
quotas, and the maximum amount of hired labor that can be acquired in any given
month is restricted to 15 worker-days. In addition to agricultural production, the
household can engage in extractive activities in the forest (e.g., harvesting Brazil nuts
[Bertholletia excelsa Humb. & Bonpl.]) and can sell household labor off farm. It can
also hire nonfamily labor to work on the farm. Because the region is only a small
producer of most products, all output prices are fixed in the model. This assumption
is less defensible for nontimber tree products because these products have limited
marketing outlets. But the model produces such small quantities that the impact on
236
Site-Specific Alternatives to Slash-and-Burn Agriculture
consumption of any price effects can reasonably be ignored. Potential general equilibrium effects on the input side, especially labor and wages, were addressed through sensitivity analyses. Because the model does not include risk, and land cannot be rented,
purchased, or sold, results must be interpreted in light of these realities: Would risk
and land markets change the land use patterns shown here? These issues are addressed
in this chapter.
The model also tracks soil fertility and soil nutrient balances, and these influence future productivity levels within the planning period of the model. Soil fertility
can be improved by adding inorganic fertilizers, by changing the cropping pattern,
by putting land into fallow, or opening new areas to production (deforesting). Soil
nutrients in the forest, fallow, and cultivated areas are tracked and linked to crop
nutrient demands and yields; this provides a link between deforestation decisions and
production decisions on the cleared land. This link is modeled by allowing farmers
to choose between growing the crops with all the nutrients needed to achieve the
average yield for a given soil type and crop or using fewer nutrients and suffering
the yield consequences depicted in figure 10.1. Choosing to produce with nutrient
deficiency (c) has a yield reduction effect (b) calculated as y – (b/c ND), where y is the
yield when nutrient requirements are met, and ND is the level of deficiency chosen by
the model. The model approximates each land use’s yield response function by dividing and linearizing the nutrient yield–response function into three sections (O 1–3
in figure 10.1) and measuring yield reductions based on the slope of the curve at the
chosen level of deficiency, ND. Agronomic and soil productivity decline and buildup,
Figure 10.1 Hypothetical crop yield response to varying soil nitrogen levels. Point b is the decrease in
crop yield expected for a given nitrogen deficiency in the soil of c; O = threshold levels of nutrients.
Coffee, Pastures, and Deforestation
237
as well as crop yield responses, were modeled using local crop and soil expert opinion
and published data.
The Falebem also keeps track of how many hectares of forest and of each cleared
land use are on the farm in any year and the age of these land uses. Using this information, the farm’s carbon stock in any year is determined. The Falebem can be used to
perform carbon policy experiments, such as mandating a minimum amount of carbon
that must be maintained in any year or allowing farmers to be paid for carbon stocks
or flows (Carpentier et al. 2000). Estimates of carbon stocks by land use are from
Lewis et al. (2002) and from chapter 2 of this volume.
Other agronomic constraints restrict land use dynamics and thus the long-term
composition of the farm. Pasture is least restricted in that it can be planted after any
land use and on all soil types. Annual and perennial crops can be planted only after
other crops, burned forest, or fallow areas. In the absence of added inputs, the number
of consecutive years crops can be planted on the same plot of land is limited by the
decline in yields that accompanies the exhaustion of nutrients left after the burn and
subsequent planting. In the model, farmers can choose to apply commercial fertilizer
or to face smaller yields. Observed and reported yields declined over the years after the
burn because most farmers do not use prohibitively expensive commercial fertilizers.
After 2 years of annual cropping, farmers reported switching to pastures, fallow, or
perennials because without adding fertilizers annual crop yields would be too low.
Economic activities and associated land uses affect soil productivity, which in turn
affects future land uses and yields. The long-term effects of these interactions are taken
into account in Falebem using a discretely dynamic modeling approach in which the
state of the economic and environmental resources at the end of year t = 1 becomes the
initial condition for decision-making in year t = 2.
More specifically, forest and other stocks are carried over from one production
year to the next to become the initial natural resource stock for the next year. This
discretely dynamic model is initiated in the first year of simulation with a set of initial
conditions describing a farm and farmer’s family characteristics in 1994 that were
derived from field surveys for a group of farmers well situated vis-à-vis markets (see
Witcover and Vosti 1996). These include characteristics such as hectares in different
land uses, forest remaining, and on-farm labor (family composition). Basically, this
model presents the farmer with the complete set of land use options and intensity levels available in the area, and some experimental ones, and then performs several “reality checks” that constrain farmer decisions, such as input availability, reversibility of
land use decisions, and profitability. Financial returns for each activity are the product
of the activity’s yield and output prices minus input costs. With all this information
in hand, the model selects, from all possible land use paths (over a 15-year period),
the one that maximizes the discounted sum of consumption that results from yearly
allocation of income to investment or consumption discounted to the present using a
9 percent discount rate.
Land use activities can be modeled at three levels of technology, V1, V2, and
V3, each with associated input and output technical coefficients. V1 is the dominant
traditional production system for small farmers in the area. It is land and labor inten-
238
Site-Specific Alternatives to Slash-and-Burn Agriculture
sive and uses limited external inputs. V3 is the recommended technology package of
the state branch of the national agricultural research agency, Empresa Brasileira de
Pesquisa Agropecuária (Embrapa). The intermediate technology level, V2, uses some
improved management and commercial inputs but not necessarily at recommended
levels. This level reflects the way small-scale farmers adopt new technology packages
incrementally, instead of whole packages at once. As the level of technology intensifies
from V1 to V3, management (controlled burning, increased weeding, spacing, control
breeding, and herd rotation) generally improves, reliance on commercial inputs (seeds,
fertilizers, pesticides, vaccines, feed supplements) increases, and the quality of these
inputs (seeds, bulls, and cows) increases. Labor may decrease or increase depending
on the activity. Generally, farmers using V3 technology apply commercial fertilizers
and pesticides, whereas those using V1 and V2 do not. The V1 technology implies use
of seeds kept from previous years, whereas V2 and V3 imply use of commercial seeds.
Perennials are grown with technology V1 or V3; that is, farmers usually adopt the
recommended technology package or keep their traditional practices. Perennials cannot be stored because they are highly perishable; they are sold in the month in which
they are harvested (in Rondônia, 20 percent of output is consumed by the family or
spoiled [Oliveira 1998]).
Data
The model was built using economic parameters collected during fieldwork, such as
input (including monthly labor) and output levels. Parameters for the model were
generated through statistical analysis of detailed farm surveys conducted in Pedro
Peixoto with eighty-one farmers in 1994 and sixty-two of the same farmers in 1996.
Prices were drawn from secondary data supplemented by fieldwork. Our fieldwork
revealed that farmers form their expectation of this year’s prices based on last year’s,
mainly harvest, prices. Because the model tries to replicate the 1994 (1993–1994) and
1996 (1995–1996) land use decisions, 1992–1993 and 1994–1995 prices are used
for all crops and livestock for the 1994 and 1996 simulations, respectively. Brazil nut
prices are an exception to this rule; 1994 and 1996 prices were used because families
can observe current prices before deciding whether to gather Brazil nuts. Together,
these factors determine financial returns to activities undertaken at different scales.
The preliminary results of the model were calibrated by groups of experts.
B AC KG ROUND DATA AND MODELING RESULTS
C h a r ac t eristics of Acre and the Pedro Peixoto
S e t t l e m ent Project
Nine percent of the state of Acre (15.25 million ha) has been deforested (chapter 12,
this volume). Most of the deforested area is under pasture (900,000 ha), followed by
Coffee, Pastures, and Deforestation
239
annual crops (108,000 ha), fallow land (64,000 ha), and banana (Musa X paradisiaca
L., 8000 ha) (ibge 1996). Cattle herd size in 1996 was 794,307 head and has now
reached 1.2 million (chapter 12, this volume). In 1996, 36 percent of these animals
were on small farms of less than 100 ha, and this number is expected to have grown
to 50 percent by 2000 (Valentim, pers. comm. 2002). Pests and insects are common
and cause sporadic damage. Because of agronomic constraints coupled with economic
viability, most cleared land eventually is planted to pasture. Most farmers use extensive
pasture systems with minimum management and thus labor, which results in substantial amounts of pasture. Valentim (1989) reports that in 1989 an estimated 70 percent
of the 600,000 ha of pasture in Acre was degraded or in the process of being degraded.
Traditional pastures can degrade quickly. However, with better management (including past and present stocking rates, quality of the initial forest burn, frequency of
pasture burning, and the quality and adaptability of the grass planted, as well as soil
improvements), the decrease in pasture carrying capacity can be reduced.
Table 10.1 summarizes land uses of the farms surveyed in Pedro Peixoto in 1994
and 1996. In 1994, farm size averaged 91.1 ha, 70 percent of which was still forested,
58 percent of their cleared land was in pasture, and more than 90 percent of farmers had some pasture. The forest, annual crop, and fallow areas decreased between
1994 and 1996; pasture areas increased, as did mixed crops and perennials, with high
growth rates but in extremely small areas. According to Fujisaka et al. (1996), after 2
years of annual crops, 64 percent of farmers in Pedro Peixoto in 1994 planted their
land to pasture, 36 percent let it go into fallow, and none planted it to perennials or
annuals.
Banana and coffee are the main perennial crops in Pedro Peixoto, although they
are grown at very limited levels. Annuals and perennials are labor intensive, few herbicides are applied, and no animal traction or mechanical implements are used. On
average, farmers had 0.37 ha of coffee in 1996 and a total of 1.3 ha of perennials,
including banana. Bananas are integrated into agroforestry systems to shade young
trees, planted in monoculture, or used in farm gardens. Although coffee is common
Table 10.1 Area in Different Land Uses and Percentage Land Use Change for Farms Sampled
in the Pedro Peixoto Project in 1994 and 1996
Land Uses
1994 (ha)
1996 (ha)
Change (%)
Forest
Annuals
Perennials
Mixed annual and perennial crops
Fallow
Pasture
Total
Number of farms surveyed
61.5
4.6
0.9
0.1
5.9
17.8
90.8
70
55.6
2.5
0.6
0.7
4.5
19.5
83.4
122
–9.5
–45.7
–33.3
600
–23.7
9.5
–8.2
Source: Field survey, 1994 and 1996.
240
Site-Specific Alternatives to Slash-and-Burn Agriculture
in the neighboring state of Rondônia, it was just beginning to appear in Acre in 1994,
when most coffee plants were too young to be productive. Coffee usually is planted in
association with corn (Zea mays L.), followed by bean (Phaseolus vulgaris L.), and has
a productive life of 5 to 9 years, depending on management practices.
The farm household modeled combines subsistence and market-oriented activities. Among the surveyed farmers, more than 90 percent keep their own seeds of
annual crops from one year to the next instead of buying certified seeds. The model
allows farm households to store grains for seeds and feed themselves. Seeds and grain
for consumption can also be bought. Similarly, extra labor can be sold off farm, and
labor can be hired on farm. Production systems were characterized by extensive land
uses with low or nonexistent external inputs. For example, out of the 124 Acre farmers
interviewed in 1996, 2 used chemical fertilizers, 15 insecticides, and 17 herbicides.
Among the major shifts in prices between the harvest years of 1994 and 1996 was
an increase of 36 percent in common (V1) livestock prices, a milk price increase of 11
percent, and a decrease in animal care of 20 percent (table 10.2). Rice (Oryza sativa
L.) prices decreased by 26 percent, whereas corn prices increased by 13 percent and
bean prices by 2 percent. Coffee prices increased by 411 percent, and banana prices increased by 123 percent. Input prices such as pesticides and fertilizers decreased
by 10 percent, and wages increased by 43 percent. Coffee yields in the model are
the expected yields given average weather for each technology level and soil type. A
medium-quality soil’s peak coffee yield is 970 kg/ha with V1 technology and 3400
kg/ha with V3 technology.
From field data collected in 1994, farms were grouped on the basis of characteristics deemed to be exogenous to farmers’ land use decisions as characterized by
the model (e.g., soil type, distance to market, and age of settlement of land). Several
groups emerged, each of which can be taken to represent a farm type. There were two
main groups: smaller, well-situated farms, and bigger farms further from the market.
The average farm and household characteristics for well-situated farms, in terms of
access to markets, were used as the model’s initial conditions. This group was dominated by soil types of medium quality, that is, with some fertility problems, mild
slopes, or rockiness. The 60-ha farm’s initial land uses are 2.5 ha of annuals, 1.5 ha of
perennials, 4 ha of fallow, 9 ha of pasture, and 43 ha of forest. There are 10,067 t of
total carbon stock over all land uses, 89 percent of it in the forest.
Ba s e l i n e Simul ation Results
The baseline explicitly includes one forestry policy that prevents small-scale farmers
from harvesting timber products from their forested land. Although technically permissible by law, the bureaucratic obstacles to obtaining official permission to sustainably harvest timber products in farmers’ legal reserves have been insurmountable in
practice and have made on-farm timber extraction difficult (see chapter 8, this volume). Another forestry law mandating that no more than half of any farm be cleared
Table 10.2 Farmgate Prices in 1994 and 1996
Prices
Farmgate Prices (in 1996 reais [R])
1994
1996
Change (%)
Commodity Prices
Rice, kg
Corn, kg
Bean, kg
Coffee, kg
Banana, bunch
Brazil nut, 18 kg
Timber, m3
Calf, per head (V1 tech.)
Cow, per head (V1 tech.)
Beef, per head (V1 tech.)
Milk, L (all technologies)
0.27
0.15
0.51
0.28
0.87
2.60
110
102
214
350
0.36
0.20
0.17
0.52
1.43
1.94
3.20
120
134
290
364
0.40
–26
13
2
411
123
23
9
31
36
4
11
1.74
1.72
2.27
1.00
2.36
11.60
0.85
24
1.21
1441
1525
37
302
5.18
7
823
15
91
1.80
2.40
2.40
0.30
2.36
10
0.65
21.60
1.08
841
1120
50
307
4.14
10
823
10
100
3
40
6
–70
0
–14
–24
–10
–11
–42
–27
35
2
–20
43
0
–33
10
Input Prices
Rice seeds, kg
Corn seeds, kg
Bean seeds, kg
Coffee seedlings, each
Grass seeds, kg (V2 tech.)
Kudzu seeds, kg (V2 tech.)
Sacks, each
Pesticides, kg
Nitrogen fertilizer, kg (V3 tech.)
Chainsaw (purchase price)
Oxen cart (purchase price)
Chainsaw operator rental rate
Fence cost, km (V1 tech.)
Animal care (R/animal unit/m, V1 tech.)
Wage rate, June
Bull, purchase price (V1 tech.)
Timber transport (R/m3)
Truck rental (round trip to market)
The price vectors labeled 1994 and 1996 are the vectors of prices judged to influence 1994 and 1996 land
uses and reflect market prices for the agricultural years 1992–1993 and 1994–1995. All prices reflect values
for average-quality products and inputs for that region; regional product quality is not high by national
standards, especially for coffee.
Source: Banco da Amazonia, 1994, 1995, 1996, semester report and farming supply store survey.
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Site-Specific Alternatives to Slash-and-Burn Agriculture
for agricultural purposes (the 50 percent rule) was excluded because this law was not
actively enforced in the 1994–1996 period.
Figure 10.2 depicts land uses (including forest, and therefore implicitly deforestation) generated by the model for a 25-year time span for this typical small-scale farm
in the settlement project of Pedro Peixoto, Acre.
There are several results from this baseline simulation. The amount of forest
retained declines over time, finally disappearing in about year 25, despite the small
but positive revenue provided by the extraction of Brazil nuts (an activity undertaken
by about 50 percent of sample farms in 1996). At the same time, cattle production
eventually occupies about 85 percent of the farm. In addition, the survey results suggest that farmers do not plant V1 pasture, so the baseline results do not include any
degraded pasture. The level of annual crop area is constant, and this activity occupies
about 8 percent of the farm throughout the 25-year time horizon. Manioc (Manihot
esculenta Crantz) takes up about 1 ha throughout the 25-year horizon (manioc is
included in the perennial category for modeling purposes because it spans more than 1
year, although it is not a perennial). Young fallow up to 4 years in age weaves into and
out of the baseline to support annual crop production, becoming more significant as
the forest disappears completely. When baseline simulations are extended to 35 years,
area in fallow continues to increase at approximately 0.2 ha every 2 years, to reach 5.5
ha in year 35. Finally, no coffee or bananas were grown under 1994 conditions (the
only pseudo-perennial is manioc). Farm incomes plateau at about year 13, at a level of
approximately R9000 per year (as all prices, in 1996 reais). The net present value of
consumption over the 25-year period is R50,688. The other farm type is characterized
Figure 10.2 Area (ha) of a typical farm in different land uses during the 25-yr time line of the baseline
simulation using 1994 prices.
Coffee, Pastures, and Deforestation
243
by farms further away from market, with 90 ha and less household labor. Vosti et al.
(chapter 17, this volume) report that deforestation rate on these farms is lower, resulting in slightly less than half the area still forested after 25 years. For this farm type too,
however, pasture is the dominant cleared land use.
Po l i c y E xperiment Simul ation Results
Some key product and input prices varied substantially between 1994 and 1996. A
baseline simulation, using the medium-quality soils and 1996 prices, was run to assess
the impact of some dramatic changes in relative prices since 1994, especially for coffee
(a 411 percent increase) and labor (a 43 percent increase).
Figure 10.3 depicts land uses for a 25-year horizon using 1996 rather than 1994
prices (with adoption unaffected with risk factors such as price volatility). Comparing
land use distributions on a farm with the baseline scenario (figure 10.2), the following
results emerge. Deforestation rates slow somewhat, primarily because of the reallocation of labor (family and hired) to the establishment and especially the maintenance
of coffee. Note that higher wages have a more significant impact on activities that
depend on hired labor, such as coffee. The impact of increased labor needs for coffee
(primarily during harvesting) is reflected in the rapid decline in deforestation after
about year 7, when the substantial coffee area established during years 1 to 6 comes
into full production and must be harvested in June, the time when new forest is usu-
Figure 10.3 Area (ha) of a typical farm in different land uses during the 25-yr time line of the policy
experiment simulation using 1996 prices.
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Site-Specific Alternatives to Slash-and-Burn Agriculture
ally cleared. That said, at year 25, forest is 12 ha and still declining, whereas pasture
increases and perennials remain stable. Land dedicated to annual crops declines, and
area in secondary fallow drops to zero. Finally, family-discounted consumption for
the 25-year period increases substantially under the 1996 price scenario to R71,305,
R20,617 more than in the baseline and mostly from coffee.
Under current economic and policy conditions, simulation results suggest that a
large tradeoff exists: Deforestation will continue until the forest is exhausted on small
farms, but incomes will rise. Results suggest that changes in relative prices such as those
occurring between 1994 and 1996 would substantially raise farm household income.
The quadrupling of coffee prices, in particular, would have a braking effect on deforestation, delaying by about 5 years the total depletion of the forest. In the simulation,
the use of cleared land is significantly affected, with more land dedicated to coffee and
less to annuals and fallow. However, the amount of land in pasture remains constant
with the baseline, and the typical farm is still dominated by pasture.
C O N C LUSION AND POLICY IMPLICATIONS
Four conclusions relevant for policy emerge from this modeling experiment. First,
although farmers face constraints, these constraints do not shield farmers from major
changes in product prices; therefore farmers are likely to respond to such large changes
as occurred between 1994 and 1996, when input prices to establish coffee plummeted
and the returns to this activity dramatically improved. Second, price changes between
1994 and 1996 led to substantial increases in farm income and a dramatic increase in
the proportion of income coming from coffee. Third although overall deforestation
was slowed by the shift in relative prices, it did not stop. In fact, if the time horizon
for the 1996 simulation were extended by 5 years or so, forest retained on the farm
would fall to zero. However, the gains in forest cover evaluated at year 25 are substantial when compared with the baseline, with 12 ha compared with none in the baseline,
primarily because labor is reallocated from deforestation activities to coffee harvesting,
activities that overlap in the annual agricultural calendar (although simulations suggest similar braking effects of total labor bottlenecks, even if in other seasons). Fourth,
and perhaps most importantly for land use policy, area in pasture did not change
much in the face of a dramatically changed set of relative prices for other commodities. Instead, adjustments in cleared area to establish coffee came at the expense of
annual crops and fallow areas.
Two policy implications arise from these results. First, although major changes
in input and product prices would be expected to affect land use practices and areas
based on revised profitability, not all land uses necessarily will be significantly affected. For example, although increases in coffee prices would be expected to cause an
increase in the area dedicated to coffee production, simulations show that this occurs
at the expense of annual and fallow land rather than pasture. In this labor-scarce
environment, farmers respond to favorable coffee prices initially by switching out of
Coffee, Pastures, and Deforestation
245
other labor-intensive activities rather than activities that use less labor per land unit
(pasture, in this case). This also means that the price shift would not be expected to
make a tremendous difference in deforestation rates. That livestock systems demand
labor throughout the calendar year (rather than labor demand peaking, as it does for
coffee, particularly at harvest time) only reinforces the propensity to stay with pasture
if possible. Policymakers should not expect, then, that in the short to medium term
(before the labor scarcity drew in more workers to the area), pricing policies aimed at
establishing labor-intensive production systems would greatly affect the area dedicated
to more extensive production systems. Because most agroforestry systems have a high
overall labor demand and peak labor demands (as opposed to labor demands spread
throughout the year), results obtained here for coffee are likely to apply for other
perennial systems or simple or complex agroforests.
These results are so because the Linear Programming model sets out to capture
a market setting in which farm households out to boost their consumption to the
highest levels possible bump up against severe labor constraints, at least seasonally:
They may have the money to buy more labor, but that labor is not available. This
characterization of smallholder objectives and circumstances is one of several offered
by Angelsen et al. (2001). Under these conditions, smallholders experiencing price
changes are limited primarily by labor availability in the changes they can make to
product mix or production technique. So, although price changes may greatly influence farm household incomes, changes in land and labor allocation across production
activities in response to these prices can be concentrated among activities that compete
seasonally for the most scarce factor: labor. This situation leaves pasture and deforestation unaffected. The good news is that the relationship is likely to be symmetric; as
coffee prices fall, deforestation probably will not increase. Poorly functioning labor
markets are an ingredient essential to both sides of this story; improvements in labor
market performance will make the links between price changes and deforestation (via
income) more direct and larger.
Second, some price changes, such as the shift in relative prices experienced
between 1994 and 1996, simply cannot be managed by policymakers at any level. In
this case, the supply and demand conditions of the international coffee market were
chiefly responsible for the dramatic increase in coffee prices, and the private sector
(with assistance for public sector research and extension) was responsible for much of
the decrease in coffee establishment costs. Policymakers can influence the profitability
of coffee production even though they cannot affect product prices by taking policy
action focused on reducing costs, improving product quality, or discovering niche
markets (e.g., organic coffee from the Amazon), but the effects (especially of the last
option) probably will not be widespread.
Finally (these insights cannot be gleaned from the model in its current form),
coffee is a perennial and as such can be managed more or less intensively—even to
the point of abandonment—for a year or more while prices find their new low and
begin to recover. A waiting period does not depend only on farmers’ price expectations because converting land from coffee to pasture is not in itself costless: There
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Site-Specific Alternatives to Slash-and-Burn Agriculture
are short-term constraints to herd expansion. Therefore it is unlikely that coffee will
be converted to pasture immediately, although that will be the end result if return to
profitability is delayed more than a couple of years. Also unlikely is any rush to convert
more forest to pasture just because coffee prices have fallen because the seasonal nature
of forest felling itself precludes hasty action, and the farmer still faces the short-term
herd expansion constraints. That said, farmers might engage in other activities that
require little investment and time commitment to cover livelihood needs and mitigate
coffee losses; these could include off-farm employment or illegal logging.
AC K N OWLEDGMENTS
The Falebem model was developed as part of the asb consortium while the authors
were at the International Food Policy Research Institute. The authors thank institute
researchers Bruno Barbier, Hans Lofgren, Andrea Cattaneo, and Peter Hazell for their
guidance in the writing of this model. We are also indebted to Tamara Gomes, Judson Valentim, Angelo Mansur Mendes, Claudenor Pinho de Sá, Alessandra Araujo,
Dennys Russell, Samuel Oliveira, and many more colleagues at Embrapa Acre and
Rondônia who provided valuable information and insight on key technical coefficients and biophysical parameters. Funding for research was provided by the InterAmerican Development Bank, the Danish Agency for Development Assistance (via
their contributions to the asb Program), the government of Switzerland, and the
government of Japan.
References
Angelsen, A., D. van Soest, D. Kaimowitz, and E. Bulte. 2001. Technological change and
deforestation: A theoretical overview. pp. 19–34. In A. Angelsen and D. Kaimowitz (eds.)
Agricultural technologies and tropical deforestation. CAB Int., Wallingford, UK.
Banco da Amazonia. 1994, 1995, and 1996. Informação trimestral sobre atividades agropecuarias. Rio Branco, Acre.
Barbier, B., and G. Bergeron. 1998. Natural resource management in the hillsides of Honduras: Bioeconomic modeling at the micro-watershed level. Environ. and Production Technol. Div. Discussion Paper 32. IFPRI, Washington, DC.
Binswanger, H. 1987. Fiscal and legal incentives with environmental effects on the Brazilian Amazon. Discussion Paper. Research Unit, Agric. and Rural Dev. Dep., Operational
Policy Staff. World Bank, Washington, DC.
Brooke, A., D. Kendrick, and A. Meeraus. 1992. GAMS: A user’s guide, Release 2.25. The
Scientific Press Ser., Boyd & Fraser Publ. Co., Danvers, MA.
Carpentier, C.L., D.D. Bosch, and S.S. Batie. 1998. Using spatial information to reduce
costs of controlling agricultural nonpoint source pollution. Agric. Resource Econ. Rev.
(April):72–84.
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Carpentier, C.L., S.A. Vosti, and J. Witcover. 2000. Small-scale farms in the western Brazilian
Amazon: Can they benefit from carbon trade? Environ. and Production Technol. Div.
Discussion Pap. no. 67. IFPRI, Washington, DC.
Dosi, C., and M. Moretto. 1993. Nonpoint-source pollution control, information asymmetry,
and the choice of time profile for environmental fees. In C.S. Russell and J.F. Shogren
(eds.) Theory, modeling and experience in the management of nonpoint-source pollution.
Kluwer Academic Publ., Boston.
Ellis, J.K., D.W. Hugues, and W.R. Butcher. 1991. Economic modeling of farm production
and conservation decision in response to alternative resource and environmental policies.
Northeast. J. Agric. Resource Econ. 20 (April):198–208.
Fujisaka, S., W. Bell, N. Thomas, L. Hurtado, and E. Crawford. 1996. Slash-and-burn agriculture, conversion to pasture, and deforestation in two Brazilian Amazon colonies. Agric.
Ecosyst. Environ. 59:115–130.
Hecht, S.B. 1985. Environment, development and politics: Capital accumulation and the
livestock sector in eastern Amazonia. World Dev. 13(6):663–684.
IBGE (Instituto Brasileiro de Geografia e Estatistica). 1996. Anuário estatístico do Acre. IBGE,
Rio de Janeiro.
Kaimowitz, D., and A. Angelsen. 1998. Economic models of tropical deforestation: A review.
CIFOR, Bogor, Indonesia.
Lewis, J., S. Vosti, J. Witcover, P.J. Ericksen, R. Guevara, and T.P. Tomich (eds.). 2002. Alternatives to Slash-and-Burn (asb) in Brazil: Summary report and synthesis of phase II.
November 2002. World Agroforestry Center (icraf), Nairobi.
Oliveira, S.J.M. 1998. Mercado de café no mundo, no Brasil e na Amazônia: Aspectos conjunturais. Circular Técnica, 38 nov. Porto Velho, Embrapa Rondônia, Brazil.
Palm, C.A., P.L. Woomer, J. Alegre, C. Castilla, K. Cordeiro, K. Hairiah, et al. 2002. Carbon
sequestration and trace gas emissions in slash-and-burn and alternative land uses in the
tropics. Alternatives to Slash-and-Burn Phase II Final Rep. ICRAF, Nairobi.
Shortle, J.S. 1984. The use of estimated pollution flows in agricultural pollution control policy:
Implications for abatement and policy instrument. Northeast. J. Agric. Resource Econ.
13(October 1984):277–285.
Valentim, J.F. 1989. Impacto ambiental da pecuária no Acre. Documento Base do Curso de
Avaliação do Impacto Ambiental da Pecuária no Acre. Embrapa–Unidade de Execução de
Pessquisa de Âmbito Estadual Rio Branco/Inst. de Meio Ambiente do Acre, Acre, Brazil.
Vosti, S.A., J. Witcover, and C.L. Carpentier. 2002. Agricultural intensification by smallholders
in the western Brazilian Amazon: From deforestation to sustainable use. IFPRI Res. Rep.
130. IFPRI, Washington, DC. Available at http://www.ifpri.org/pubs/pubs.htm#rreport
(verified 7 Dec. 2003).
Witcover, J., and S.A. Vosti. 1996. Alternatives to slash-and-burn agriculture (asb): A characterization of Brazilian benchmark sites of Pedro Peixoto and Theobroma, August/September 1994. MP-8 Working Paper US96–003. IFPRI, Washington, DC.
11 Smallholder Options for Reclaiming
and Using Imperata cylindrica L.
(Alang-Alang) Grasslands in Indonesia
Pratiknyo Purnomosidhi
ICRAF Southeast Asia Bogor, Indonesia
Kurniatun Hairiah
Brawijaya University Malang, Indonesia
Subekti Rahayu
ICRAF Southeast Asia Bogor, Indonesia
Meine van Noordwijk
ICRAF Southeast Asia Bogor, Indonesia
T
he Alternatives to Slash and Burn (asb) program in Indonesia aims to
identify options for slowing down deforestation and promoting the rehabilitation of degraded (formerly forested) areas (van Noordwijk et al. 1997).
Many previously forested areas have seen a trajectory of forest degradation
similar to that shown in figure 1.1a, with a phase of low-use degraded land
and a rehabilitation process. This macro process of degradation and rehabilitation may resemble the plot-level decline and restoration of productivity
in a shifting cultivation cycle but is driven by more complex processes of
migrating farmers, changing tenure and resource access of farmers, broaderscale landscape- or village-level control over free-ranging fires (Wibowo et al.
1997), and market-driven economic incentives. This chapter addresses technical issues associated with smallholder rehabilitation of grasslands derived from
forest degradation at the asb benchmark site in Pakuan Ratu (in the northern
part of Lampung province) in Sumatra, Indonesia (see figure 13.1 later in this
volume), which was chosen as representative of the vast area under Imperata
cylindrica and related coarse grasses in Asia (approximately 35 million ha) and
Indonesia (8.5 million ha) (Garrity et al. 1997). Although increasing the rate
of rehabilitation of these grasslands does not necessarily slow down the rate of
deforestation at the frontier, rehabilitated areas can offer an alternative attraction point for migrants.
Efforts to reclaim Imperata grassland areas and put them to intensive
agricultural use where shifting cultivation is practiced have been debated in
Reclaiming and Using Imperata cylindrica
249
Indonesia since at least the 1930s (Hagreis 1931; Danhof 1941). A common prescription was large-scale reforestation, possibly with international financial support
via projects aiming to increase carbon sequestration (Drajat 1991; Tjitrosemito and
Soerjani 1991). However, there is remarkably little evidence of economies of scale
in reforestation (Tomich et al. 1997), and smallholder agroforestry may provide a
socially, economically, and environmentally superior option.
From the history of past successful transitions of Imperata grasslands into densely
inhabited agroforestry land use mosaics (Foresta and Michon 1997; Potter 1997),
we can conclude that four conditions must be met for such reclamation to occur as a
spontaneous, farmer-led process:
• A sense of security of tenure over the trees planted, if not the land itself
• Effective village-level institutions for controlling free-ranging fires
• Local farmer knowledge of agroforestry techniques and access to germplasm
that can effectuate the transformation and address the often low fertility of
the soils (Santoso et al. 1997)
• Physical and economic access to markets for the products of the land, leading to adequate profitability
The research results reported here focus on the third of these requirements and
more specifically on technical requirements for shade-based control of Imperata in
developing agroforestry systems.
L a n d U s e Pat terns in the Research Site
One of the asb benchmark sites in Indonesia is located in Pakuan Ratu subdistrict
of northern Lampung, Sumatra, at the lower reaches of the Tulang Bawang River.
This area was chosen to represent the rehabilitation phase of land use change and
represents a situation in which conflicts over land did not (at the time of the survey)
override other concerns because the area is not (or is no longer) considered to be
state forest land. Three groups of farmers (Lampungese in villages along the rivers,
transmigrants moved by the government from forest reserves in southern and central
Lampung, and spontaneous migrant settlers) interact with large agroindustrial estates
(sugar cane [Saccharum officinarum L.], cassava [Manihot esculenta Crantz], and fastgrowing timber). However, after the “Reformasi” change in Indonesian government
in 1998 serious conflicts emerged between Lampungese and the state sugar cane plantation, leading to a de facto closure of roads, loss of off-farm labor opportunity, and
general hardship in the transmigration villages. Forest cover was lost rapidly after logging in the early 1970s, followed by government-sponsored conversion of the land to
transmigration or plantation sites. Around the transmigration villages the landscape
degraded rapidly as the initial soil fertility inherited from the forest was used, and large
areas became dominated by Imperata fallows, alternating with cassava.
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Site-Specific Alternatives to Slash-and-Burn Agriculture
Transmigration programs started in 1905 in southern Lampung (Djojoprapto
1995) and—in combination with an influx of spontaneous migrants—have transformed Lampung into the most densely populated Indonesian province outside Java
(174 people/km2 in 1993), with the lowest remaining forest cover; hardly any state
forest land outside national parks still had full forest cover in the late 1980s (van
Noordwijk et al. 1995). Northern Lampung was the last frontier in the lowland peneplain and was used in the early 1980s to resettle spontaneous migrants from Java or
Javanese born in transmigration settlements in Lampung from the fertile coffee belt
in the hills, to protect the water supply to irrigation schemes (in the Way Sekampung,
Way Seputih, and Tulang Bawang watersheds). These farmers were moved to Pakuan
Ratu, the poorest subdistrict in Lampung and, in fact, in Sumatra as a whole (except
for some of the adjacent islands), with thirty-nine of its forty-one villages classified as
poor. The asb benchmark area is largely in the Pakuan Ratu subdistrict, with Negeri
Besar as the largest and oldest Lampungese settlement on the river. However, a traveler’s report from 1920 had already commented on the degraded forests close to the
Tulang Bawang River, linked partly to the demand for railway sleepers for the Bandar
Lampung–Palembang railway construction (van Noordwijk et al. 1995).
The typical pattern in transmigration sites in the early 1980s was as follows: After
clearing the forest by slash-and-burn, transmigrant farmers planted food crops in the
first few years. When the fertility of the land declined by the fourth year, they shifted
to off-farm activities such as daily wage labor or driving on the nearby sugar cane
plantation (PG Bunga Mayang), in the remaining logging concession and forest timber company (Industrial Timber Plantation Company, or hti), or in illegal logging
operations. Only farmers who had land that could be transformed into paddy rice
(Oryza sativa L.) could make a living from agriculture (Elmhirst 1996). The opening
of cassava processing plants (PT Bumi Waras) made it worthwhile to continue farming on the acid upland soils, in what became an Imperata–cassava rotation, but cassava
prices fluctuated, partly under the influence of European Union quotas for imports of
tapioca as fodder. With declining fertility and more and more fires in the landscape,
the area that was abandoned to Imperata increased.
By the late 1980s the sugar cane plantation started an “outgrowers” scheme,
stimulating farmers to form groups (Petani Tebu Rakyat Intensifikasi) and providing
credit for plowing, fertilizer, and cane planting, to be paid back through the cane harvest in the first 3 years. Although at some stage smallholder cane under this program
almost equaled the area under sugar cane managed by the plantation company (and
thus compensated for the overcapacity of the factory given the declining productivity of the plantation itself ), relations between the plantation and farmers turned sour
(Elmhirst et al. 1998) when the results for the farmers’ fields were less than expected
(for numerous reasons, including logistics of fertilizer delivery and transport at harvest time), and farmers could not pay back their credits. After this sugar cane phase,
land was again abandoned to Imperata or reused for cassava, benefiting from good
farmgate prices and possibly from the residual fertility of fertilizer used in the sugar
cane.
Reclaiming and Using Imperata cylindrica
251
The agility of the farmers’ adaptations to changing income opportunities did not
stop there. The transmigrant and spontaneous migrant farmers continued to struggle to transform the Imperata land into a productive resource, gradually clearing it
manually (hoeing), plowing it by using draft animals (after a government program
introduced cattle to the villages) or hired tractors, or applying herbicides, if they had
the capital to do so. The farmers have tried to get tree crops started, with oil palm,
fast-growing timber species (such as Acacia mangium Willd. and Paraserianthes falcataria [L.] Nielsen), and rubber as the main options. Doing so is risky because future
markets for the timber are not clear, and marketing of oil palm to remote factories has
been erratic because it depends on a reliable road network. Rubber became a serious
option for farmers when road transport improved (especially that on the east–west
axis, complementing the north–south access via the sugar cane plantation), and a new
bridge provided contact with rubber-growing areas to the east of the benchmark area,
around Manggala. In the asb benchmark area, rubber planting gained importance
in the villages of Panaragan, Karangsakti, and Karang Mulya, spreading from the village of Negeri Ujungkarang, where the Dinas Perkebunan (tree crop advisory service)
established a nursery. Planting material is also bought from farmers in Madukoro,
Negara Ratu, or Kotabumi, but village-level nurseries are now emerging. Farmers
chose rubber because latex can give continuous income once the trees are tapped and
can be marketed through various channels, wood of the rubber trees is valuable, and
investment and maintenance costs are less than those for oil palm. Meanwhile, farmers in Batu Raja, Negara Batin, and villages further along the road to the Pakuan Ratu
subdistrict office viewed oil palm as their main way out of poverty. They chose oil
palm because it has a good market and can regrow after burning and drought, whereas
rubber and timber trees are lost in Imperata fires.
Pepper and coffee have good prospects, too, and are the preferred option for the
Lampungese farmers, who occupy the slightly better soils along the river (Van Noordwijk et al. 1996b). Transmigrant farmers chose this option only in the villages of
Gedung Nyapah and Tulung Buyut. Coffee and black pepper have a good market, and
their local price increased during the recent monetary crisis.
P rev i o u s Experiments on Sha de-Based Control
In 1992, an on-farm experiment was begun by the Biological Management of Soil
Fertility Project to plant trees in Imperata grassland as a low-cost method of shading
out the grass (van Noordwijk et al. 1992, 1997). Two tree species—the fire-tolerant
local Peltophorum dasyrrachis Kurz and a common legume Gliricidia sepium (Jacq.)
Kunth ex Walp.—were planted in Imperata grasslands strips 4 m apart. After 1 year,
the trees reduced the vigor of the Imperata but not sufficiently for reclamation. In the
second year, tree canopy development continued, but it was still not enough to eliminate the Imperata. Tree growth showed wide variability, and only in the patches where
Peltophorum grew best was Imperata controlled after 2 years. In the exceptionally dry
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Site-Specific Alternatives to Slash-and-Burn Agriculture
season of the El Niño year 1994, fires (a perennial concern; see Bagnall-Oakeley et al.,
1997) reached the plot from an adjacent area and provided a true test of fire tolerance.
All trees of both species resprouted after the fire, and the experiment continued with
food crops, pruned hedgerows, and spot applications of herbicides to control Imperata. The experiment thus showed that shade-based control of Imperata grass is not
easily achieved and raised questions about the intensity and duration of shade needed
to do so (MacDicken et al. 1997). Further work was clearly needed.
R e s e a rc h Questions
Given that farmers in the asb benchmark area had (at the time of the experiment,
before the Reformasi period) reasonably secure access to land and were located near
well-performing markets, and given the potential profitability of tree crops, we
addressed the following specific issues:
• Which techniques are used by the farmers to convert the Imperata grasslands,
and why?
• How can the developing agroforestry systems suppress Imperata regrowth and
avoid the fire risks at an intermediate age (Bagnall-Oakeley et al. 1997); more specifically, how long and intense a shade is needed for adequate control (MacDicken et al.
1997).
The second research question was split into three parts: How much light can still
penetrate to ground level in young rubber, oil palm, pepper–coffee, and timber production systems; for how many years can farmers still interplant food crops between
the tree rows in these systems; and how does a well-established Imperata stand respond
to shade of different intensities and duration.
M AT E R I AL AND METHODS
Four research activities were undertaken to address these issues: a farm household
survey of reclamation methods, field measurements of light intensity at ground level
in selected agroforestry systems, an experiment aimed at defining the intensity and
duration of shade needed for Imperata control, and in-depth interviews on the management practices in four smallholder agroforestry systems in the area.
Fa rm e r Household Survey
A survey on farmer management options for converting and using Imperata grassland
was conducted in an area extending beyond the asb benchmark area and includ-
Reclaiming and Using Imperata cylindrica
253
ing villages in the Pakuan Ratu, North Sungkai, and South Sungkai subdistricts of
North Lampung district (the district has since been subdivided and the study area
now belongs partly to Way Kanan district). The survey was carried out in July 1997
and again in August 1998 and focused on the details of various management strategies and the costs associated with each. Total sample size was fifty intensive household
interviews.
F i e l d M e asurements of Sunlight Below
Ag ro f o restry Systems
On fifty farms, selected to cover the full spectrum of land use practices and a range
of ages, light intensity and Imperata biomass were measured. On twenty locations per
plot, relative light intensity (vis-à-vis full sunlight, measured using a photosynthetically active radiation sensor) was measured halfway between trees in the plant row and
between rows. Tree diameter at 1.3 m above ground (diameter at breast height) was
also measured. For oil palm plants, height was recorded instead of stem diameter. Biomass of Imperata grass was collected from 1-m2 sampling areas. Results were averaged
over the twenty sample points for each site for the current analysis.
A rt i f i c i a l Shading Experiment
An experiment to quantify the response of well-established Imperata stands to shade
of different intensities and duration was begun at the Biological Management of Soil
Fertility Research Station (van Noordwijk et al. 1996a) in November 1995, with
four levels of artificial shade in a randomized block design with four replicates. The
experiment was monitored to measure (at monthly intervals) the decline of standing
Imperata biomass under different shade conditions and to measure Imperata’s ability
to regrow from rhizomes after a ground-level cut after 0 to 7 months at each level of
shading.
R E S E A RC H RESULTS
Fa rm e r Household Survey
Farmers reported several techniques for clearing Imperata grasslands (figure 11.1) and
selected one or more of the following depending on the availability of labor and cash
and the crop to be planted after clearing.
The techniques range from manual slashing of the grass followed by hoeing, to
application of systemic herbicides followed by plowing and sometimes preceded by
burning, to plowing with animal or mechanical traction, usually after burning the
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Site-Specific Alternatives to Slash-and-Burn Agriculture
Figure 11.1 Summary of Imperata land clearing methods and the percentage of farmers in the survey who
used the various methods.
Imperata above-ground biomass to make work easier. Before clearing by almost any
method, thatch can be manually collected from Imperata areas and used for roofing.
Cash-poor farmers (60–70 percent of respondents) rely on hoeing with family
labor and can clear only a quarter to half a hectare per family per year, in the dry season
(July–October). If labor were paid, this method would be very expensive. Land cleared
in this way generally was used for planting food crops such as upland rice (Oryza sativa
L.), maize (Zea mays L.), or soybean (Glycine max [L.] Merr.). Farmers mentioned that
they prefer shallow soil tillage to deeper plowing because this keeps the dark top 15 to
20 cm of soil (the “soil meat”) intact and avoids the iron-rich aggregates (locally called
crocos) found below that depth and brought to the surface by plowing.
Farmers who can afford it prefer to use herbicides unless they have animal draft
power available. Application rates ranged from 2 to 5 L/ha of one of the commercially
available brands of glyphosate, often mixing more than one type. Herbicide normally
was sprayed on young regrowth of Imperata 2 to 3 weeks after slashing or burning the
standing biomass; 20 to 25 mL of herbicide is diluted in 15 L of water in a knapsack
sprayer. According to the farmers, systemic herbicides remained effective for about 6
months, after which farmers commonly sprayed again, twice if the Imperata was not
dense. The first spraying covered the entire area, and the second spraying covered only
patches that remained green after 14 days; at least 5 L of herbicide was needed per
hectare to achieve adequate control. Herbicide use without tillage was the preferred
Reclaiming and Using Imperata cylindrica
255
method of Imperata clearing before planting of rubber, oil palm, or timber trees; land
dedicated to food crops needed plowing.
Farmers owning or having easy access to draft animals used them to convert Imperata grasslands. Plowing with draft animals normally is done in the dry season, when
the Imperata rhizomes brought to the surface dry up easily, but sometimes (in 10 to
15 percent of interviewed cases) plowing extends into the early rainy season, when the
soil is easier to work. Plowing in the early rains is preferred when the Imperata vegetation is not very dense and land is flat (on slopes manual hoeing is normal). Cattle were
introduced into the area in about 1985 under a government loan scheme, benefiting
transmigrants who were familiar with animal traction, rather than Lampungese farmers. Actually, farmers prefer animal drawn plows to tractors because the quality of
work is good and no subsoil is brought to the surface, and they have seen what happens in tractor plowing at the sugar cane plantation. If the Imperata stand is dense,
the early activities consist of a week of slashing, collecting, burning, and plowing per
0.25 ha or 3 to 4 days of burning and continued plowing per 0.25 ha. Normally a
second tillage operation is needed once the rhizomes brought to the soil surface have
dried off. Tractor-powered plows are used to clear Imperata land if the farmer intends
to plant sugar cane or cassava; this technique became popular in the 1990s when the
sugar cane factory started its outgrower scheme. In both Negara Jaya and Negara
Tulang Bawang villages, a local (Lampungese) farmer has bought a tractor and started
contract operations. Plowing mixes the soil to a depth of 50 cm, so most farmers
perceive that soil fertility decreases because they see crocos appear on the top layer, to
which they attribute in part the failure of the sugar cane outgrower scheme.
Of the several ways of converting Imperata grassland, which were the most cost
effective? Table 11.1 reports the results of the farm household survey of conversion
costs. The first column presents the main input used in conversion: labor, chemicals,
Table 11.1 Costs of Imperata Grassland Clearing, by Clearing Method, 1998 and 1999
Primary Input Used
Manual labora
Herbicide
Animal traction
Tractor
Details of Clearing Method
Burning–hoeing or slashing–collecting–
burning–hoeing
Herbicide only
Burning–herbicide–plowing or slashing–
herbicide–plowing
Plowing, burning–plowing, or slashing–
collecting–plowing
Plowing
Total Cost per Hectare
(Rp000)
1998
1999
740–960
1500–1680
104–260
464–696
90–225
590–935
360–540
500–800
160–200
350–400
Mostly unpaid family labor. Average wage rate of labor in the survey area was Rp5200 in 1998 and Rp6400
in 1999.
a
256
Site-Specific Alternatives to Slash-and-Burn Agriculture
animal traction, and tractors. The second column provides some details of the ranges of
activities involved in clearing Imperata grassland. The final two columns of table 11.1
present ranges of cost estimates for each general type of grassland clearing practice;
cost estimates are provided for 1998 and for 1999 separately to highlight the effects of
changes in relative prices that occurred over that time period on conversion costs.
In 1998, clearing Imperata grassland using tractor-drawn plows was cheapest
(costing Rp160,000 to Rp200,000 per hectare). Using herbicides alone to clear land
was a bit more expensive, costing Rp104,000 to Rp260,000. Using animal traction
to clear Imperata grassland cost more than twice the per-hectare rate of tractors, and
manually clearing was by far the most expensive.
In 1999, however, changes in fuel and other prices dramatically increased the
cost of tractor use (to a range of Rp350,000 to Rp400,000 per hectare), thereby making herbicide use alone the most cost-effective way of clearing Imperata grasslands.
The cost advantage of tractors and herbicides over manual clearing techniques and
those involving animal traction remained despite price changes over the 1998 to 1999
period.
A rt i f i c i al Shade Control Experiment
The shade intensity experiment showed that even if light levels are reduced to about
10 percent of full sunlight, an established Imperata stand will only gradually decline; a
55 percent shade for up to 8 months had little effect (figure 11.2). Hence shade alone
probably could not be relied on to reduce Imperata grasslands.
Regrowth after removing all above-ground biomass (figure 11.3) was more affected
by shading than standing biomass, but a 55 percent shade, which would be considered
problematic for most food crops, had no effect on the ability of Imperata rhizomes to
resprout. Only when an 88 percent shade was applied for more than 2 months, did
the ability of rhizomes to resprout decline to a negligible level. Further analysis of the
physiological backgrounds of these effects is under way.
L i g h t I ntensities Below Agroforestry Systems
These results for artificial shade were compared with results of the survey of Imperata
occurrence and light intensity under a range of agroforestry systems (figure 11.4).
A statistically significant relationship was found between light levels below the tree
canopy and Imperata biomass. Imperata biomass decreased drastically when a relative
light intensity of 10 to 20 percent was reached (figure 11.4). When more than 20
percent of sunlight reaches the ground, Imperata still has a chance in these agroforestry systems.
The various tree and plantation crops differ in the age and tree basal area they
need to achieve this control target of 10 to 20 percent. Light intensity reduces more
Figure 11.2 Above-ground biomass of artificially shaded Imperata grassland plots relative to that of unshaded control plots in the same experiment.
Figure 11.3 Regrowth of Imperata plots after a ground-level cut, made after 0–7 mo of exposure to an
artificial shade of 0–88%. The symbols distinguish the number of months of artificial shade received
before cutting.
258
Site-Specific Alternatives to Slash-and-Burn Agriculture
Figure 11.4 Relationship between Imperata biomass and relative light intensity (taking full sunlight as 1)
in a survey of smallholder agroforestry systems that include coffee and pepper systems, rubber, oil palm,
Paraserianthes falcataria, and Acacia mangium Willd. block planting.
quickly for a given stem basal area in rubber and Acacia mangium systems than in pepper agroforestry (using Gliricidia sepium and other trees as support and shade trees)
and Paraserianthes falcataria (sengon) (figure 11.5).
Sy n t h e s is: Smallholder Agroforestry Options
f o r C o n version of Imperata Grassl ands
Because high degrees of shading were shown to reduce Imperata biomass and control
regrowth, the next step was to identify agroforestry systems that could provide such
shade and that would be attractive to smallholders. Four existing systems were evaluated in discussions with farmers.
The first system was based on fast-growing timber trees that became popular in
the study area as a result of planting of Acacia mangium and Paraserianthes falcataria
by the Industrial Timber Plantation Company in the early 1990s; both the technology and part of the seedlings became used outside their plantation area. Numerous
farmers, stimulated by one of the village heads, started to spray the Imperata and
plant Paraserianthes falcataria at a distance of 2 × 2 or 2 × 2.5 m2 or at 2 × 4 m2 when
intended for intercropping with food crops (upland rice in year 1, cassava in years
2–4) for more than a year. Canopy closure of Paraserianthes is slow, so the farmers
deemed weeding or plowing between rows after harvesting the food crops necessary.
Reclaiming and Using Imperata cylindrica
259
In plantations that were 5 to 8 years old the light intensity at the soil surface still
reached 18 to 28 percent of full sunlight, and Imperata remained a problem (Tjitrosemito and Soerjani 1991). Some farmers abandoned the plantation, and secondary
vegetation regenerated with tree species such as Schima wallichii (D.C.) Korth., Dillenia sp., Peltophorum dassyrachys, shrubs such as Chromolaena odorata (L.) R.M.
King and H. Robinson, Melastoma sp. or Mimosa sp., and grasses such as Setaria sp.
replacing the Imperata. The stands remain sensitive to fire, though, and tree performance was poorer than expected. The long dry season of 1997 showed that Paraserianthes is suited only for the wetter sites at the bottom of slopes. Acacia mangium
planted at a spacing of 2 × 4 m2 (1250 trees/ha) reduced light at ground level to 10
percent of full sunlight 4 years after planting at a stem basal area of 23 m2/ha, which
is adequate for Imperata control.
The second system was based on rubber trees planted at a spacing of 3.3 × 6 m2
or 4 × 5 m2 (500 trees/ha) and took an average of 7 years before stem basal area was 10
m2/ha and light levels at ground level were reduced below 20 percent of full sunlight.
Farmers usually plant maize or cassava between the rubber tree rows in years 1 to 3.
Although cassava, which belongs to the Euphorbiaceae, the same family as rubber, is
considered capable of transferring soilborne diseases to rubber trees, farmers preferred
it as an intercrop because of its minimal maintenance needs and its ability to provide income. After year 3, however, the transition described by Bagnall-Oakeley et al.
(1997) occurred; the system provided too much shade for food crop production and
too little for Imperata control.
The third agroforestry system evaluated was smallholder oil palm, which was only
recently introduced into the benchmark site. Farmers considered oil palm a good
option because it regrew after burns and appeared less affected by drought than rubber
or sengon. Oil palm agronomists emphasize negative drought impacts on palm fruit
production up to a year after a drought, whereas rubber tapping can resume quickly if
trees survive weather or fire shocks. Farmers in the survey planted oil palm at an 8 × 9
m2 spacing (138 plants/ha), which leaves ample area for Imperata growth. Farmers
generally cultivated maize or rice between oil palm rows during the first few years. In
some instances, smallholders with little land were allowed to grow food crops between
the oil palms of richer farmers because food crops are deemed less competitive with
the oil palm than Imperata would have been. However, as is the case for rubber, the 2to 5-year period between the time food crop production ceased and the palm canopy
effectively cut off sunlight is long enough to allow Imperata to become reestablished.
Indeed, a stand of oil palm 10 m high still allowed about 15 percent of full sunlight to
penetrate to ground level; this is sufficient sunlight for Imperata growth.
Lastly, pepper (Piper nigrum L.) and coffee agroforestry systems are found on
the better soils west of the asb benchmark area in Pakuan Ratu. Farmers start these
systems by planting Gliricidia sepium or Erythrina orientalis Murray as shade and support trees at a spacing of 2 × 2 m2. Rice, maize, or other food crops are grown for 1 or
2 years, after which coffee is planted in the middle of the 4-m2 spaces between shade
trees, and pepper vines are planted at the stem base of the shade and support trees.
260
Site-Specific Alternatives to Slash-and-Burn Agriculture
Figure 11.5 Relationship between tree basal area and relative light intensity (taking full sunlight as 1) in a
survey of smallholder agroforestry systems that include coffee and pepper systems, rubber, Paraserianthes
falcataria, and Acacia mangium Willd. block planting; the line at a relative light intensity of 0.15 indicates
the target for full control (compare figure 11.4).
Fruit trees such as Parkia speciosa Hassk, Pithecellobium dulce (Roxb.) Bentham, Durio
zibethinus Murray, Lansium domesticum Corr., and Ceiba pentandra (L.) Gaertn. are
mixed between the stands, often especially as boundary markers for the field. When
these plantations are 4 years old (stem basal area 5 cm2/m2), light intensity at ground
level may still be 45 to 50 percent because the shade trees are pruned for the benefit
of the pepper and coffee. In an 8- to 10-year-old plantation (stem basal area of 10
cm2/m2) light intensity at ground level was 20 percent of full sunlight, again sufficient
for Imperata growth.
D I S C U S SION AND CONCLUSION
Imperata cylindrica (alang-alang) grasslands occupy large areas of Southeast Asia and
are viewed both as a consequence of failed rural development strategies and as an
opportunity for expanding agricultural production in areas with diminished forest
resources. However, reducing Imperata grassland area and controlling regrowth will
not be easy and may be beyond the reach of cash-poor smallholders who need immediate returns to labor.
Reclaiming and Using Imperata cylindrica
261
The first steps in controlling Imperata in the agroforestation of grasslands can be
achieved by either mechanical or chemical control, and farmers use a range of techniques, depending on their resources and current prices. Food crops are used in the
first few years of most tree crop or agroforestry systems to maintain income and provide a low-cost (from the tree crop perspective) Imperata control option. However, the
gap between the last food crop interplanting and canopy closure leads to a major risk
of Imperata regrowth and fire occurrence. Targets for shade duration and intensity as
estimated in the experiment cannot be easily reached in practice. Farmers in the study
area have been experimenting with a range of tree crops and agroforestry systems,
but results during the El Niño drought of 1997 discouraged the use of trees such as
Paraserianthes falcataria. A wider range of tree options is needed, and information on
site-by-species matching can avoid (or reduce) disappointment.
In the broader picture, results for the asb benchmark area are encouraging for the
Imperata grasslands elsewhere, on state forest land. Farmers will explore and exploit a
range of options once they have security of tenure and can develop village level rules
and controls for the use of fire. For society to reap the benefits of additional carbon
storage on these former grasslands, no specific subsidies are needed once tenure policies are right, although farmers welcome technical support in finding locally suited
trees. In the benchmark area, the International Center for Research in Agroforestry
and its partners are now engaged in this type of on-farm experimentation.
References
Bagnall-Oakeley, H., C. Conro, A. Faiz, A. Gunawan, A. Gouyon, E. Penot, et al. 1997. Imperata management strategies used in smallholder rubber-based farming systems. Agrofor.
Syst. 36:83–104.
Danhof, G.N. 1941. Tweede bijdrage tot oplossing van het alang-alang vraagstuk in de Lampongse Districten [Second contribution to the solution of the Imperata problem in the
Lampung Districts; in Dutch]. Tectona 34:67–85.
Djojoprapto, T. 1995. Perkembangan penyelenggaraan transmigrasi. pp. 51–66. In M. Utomo
and R. Ahmad (eds.) 90 tahun Kolonisasi, 45 tahun Transmigrasi: Redistribusi penduduk
di Indonesia. Penebar Swadaya, Jakarta.
Drajat, M. 1991. Alang-alang grassland and land management aspects. pp. 78–98. In M. Sambas Sabarnurdin, H. Iswantoro, and G. Adjers (eds.) Forestation of alang-alang (Imperata
cylindrica Beauv. var Koenigii Benth) grassland: Lesson from South Kalimantan. Gadjah
Mada Univ. Press, Yogyakarta, Indonesia.
Elmhirst, R.J. 1996. Soil fertility management in the context of livelihood systems among
transmigrants in North Lampung. Agrivita 19:212–220.
Elmhirst, R., Hermalia, and Yulianti. 1998. “Krismon” and “Kemarau”: A downward sustainability spiral in a north Lampung “Translok” settlement. pp. 106–121. In M. van
Noordwijk and H. De Foresta (eds.) Agroforestry in landscapes under pressure: Lampung
research planning trip, 17–21 June 1998. Rep. no. 6. ASB Indonesia, Bogor.
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smallholder agriculture and forestry reach sustainability. Agrofor. Syst. 36:105–120.
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Garrity, D.P., M. Soekardi, M. van Noordwijk, R. de la Cruz, P.S. Pathak, H.P.M. Gunasena,
et al. 1997. The Imperata grasslands of tropical Asia: Area, distribution and typology.
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MacDicken, K.G., K. Hairiah, A. Otsamo, B. Duguma, and N M. Majid. 1997. Shade-based
control of Imperata cylindrica: Tree fallow and cover crops. Agrofor. Syst. 36:131–149.
Potter, L.M. 1997. The dynamics of Imperata: Historical overview and current farmer perspectives, with special reference to South Kalimantan, Indonesia. Agrofor. Syst. 36:31–51.
Santoso, D., S. Adiningsih, E. Mutert, T. Fairhurst, and M. van Noordwijk. 1997. Site improvement and soil fertility management for reclamation of Imperata grasslands by smallholder agroforestry. Agrofor. Syst. 36:181–202.
Tjitrosemito, S., and M. Soerjani. 1991. Alang-alang grassland and land management aspects.
pp. 10–36. In M. Sambas, H. Iswantaro, and G. Adjers (eds.) Forestation of alang-alang
(Imperata cylindrica Beauv. var Koenigii Benth) grassland: Lesson from south Kalimantan.
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management of soil fertility for sustainable agriculture on acid upland soils in Lampung
(Sumatra). Agrivita 19:131–136.
van Noordwijk, M., K. Hairiah, S. Partoharjono, R.V. Labios, and D.P. Garrity. 1997. Sustainable food-crop based production systems, as alternative to Imperata grasslands? Agrofor.
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van Noordwijk, M., K. Hairiah, S.M. Sitompul, and M. Syekhfani. 1992. Rotational hedgerow intercropping Peltophorum pterocarpum = new hope for weed infested soils. Agrofor.
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iv. n at i o n a l pe r s pe c t i ve s
12 The Western Brazilian Amazon
Judson F. Valentim
Embrapa Rio Branco, Acre, Brazil
Stephen A. Vosti
University of California Davis, California
T
he Brazilian Amazon has long been viewed as empty space contributing
little to overall national economic development (Government of Brazil
1969). Federal and state governments have taken action over the past several
decades to address this issue, and partly as a consequence of those actions the
Brazilian Amazon has been the focus of national and international debate on
issues such as tropical deforestation, global climate change, biodiversity conservation, regional integration, the production and transportation of illegal
drugs, national security, and the rights of indigenous populations. Although
perhaps seemingly unrelated at first glance, these issues often are closely linked.
For example, regional integration might increase the demand for agricultural
land, which can come at a cost to forests, the biodiversity they contain, and
the carbon they store. Therefore, these issues must be examined jointly to
identify possible links. If links exist, policy action must consider them.
Moreover, these issues generate more than just debate. Indeed, deforestation and its environmental and social impacts have led to social conflict
involving Amerindians and rubber tappers displaced from forested areas on
one hand and agriculturalists and cattle ranchers on the other (Hecht 1984;
Myers 1984; Denslow 1988; Valentim 1989; Lisboa et al. 1991; Homma
1993; Smith et al. 1995; ). Some of these displacements—and other encroachments into forested lands that do not spark social conflict—are directly linked
to policy actions, and others result from more general economic trends that
may themselves be beyond the reach of policymakers. Under both sets of
circumstances policy action or policy reform may be needed. But what policy
action is called for, and what should be the targeted agents or geographic
areas? And—the question that is rarely asked—what will be the implications
of corrective policy actions for broad development objectives (Vosti and Rear-
266
National Perspectives
don 1997)? Finally, and most important for this chapter, do we have the knowledge
needed to confidently respond to these policy questions? If not, has a process capable
of identifying and filling knowledge gaps been initiated?
This chapter reviews past national priorities for the region, policy action taken to
populate and integrate the Amazon into the national economy, and the environmental and social consequences of this action. Against this backdrop, we assess past and
potential future contributions of the Alternatives to Slash and Burn (asb) Program
to promoting and guiding research and policy action in the region, with particular
emphasis on the western Amazonian states of Acre and Rondônia, and asb activities
at the benchmark sites there (Ávila 1994).
We begin by examining national development priorities from the early 1960s
to mid-1980s as they relate to the Amazon, including policies implemented by the
Brazilian government to occupy and integrate this region into national and international markets. We then focus on the direct and indirect consequences of past regional
and local policies on migration, deforestation, the expansion of agricultural activities, and their consequences for economic growth, human development, and environmental sustainability. We then look at future challenges stemming from past and
ongoing widespread land degradation and the exhaustion of extensive agricultural
frontier. These challenges are set alongside new opportunities provided by new and
better-performing markets; new technology; some marked shifts in the political climate at the local, state, and international levels; and the emergence of a new vision of
development that aims to reconcile economic growth, poverty alleviation, and natural
resource conservation in the Amazon. The final section highlights the contributions
of asb’s research and outreach activities in the western Brazilian Amazon and sets an
agenda for future asb-Brazil activities.
D EV E LOPMENT IN THE AMAZON (1960 s–1990s)
The largest tracts of the world’s remaining tropical moist rainforests are located in the
Amazon Basin, which occupies about 7.86 million km2 in nine countries and covers
about 44 percent of the South American continent (Valente 1968). About half of the
Amazon forest (3.87 million km2) is located in northern Brazil. This forest covers
more than 52 percent of Brazil’s national territory (ibge 1997), an area larger than
the whole of Western Europe (inpe 2003) (figure 12.1).
Since the early 1960s, the Amazon region has been viewed by the federal government of Brazil as a source of natural resources (e.g., forests, agricultural land, minerals) that could be used to fuel regional and national economic growth. Low population density (about 0.9 inhabitants per square kilometer in 1970) was an obstacle to
exploiting the region’s resources and integrating it into the national economy. Labor
needed to tap and transport resources was scarce, and the low population density was
perceived as a threat to national security, particularly given the production and transportation of illicit drugs in neighboring countries (Fórum Sôbre a Amazônia 1968;
The Western Brazilian Amazon
267
Figure 12.1 Map of Brazil, with the North Region highlighted (inpe 2003).
Government of Brazil, 1969, 1981; sudam 1976; Smith et al. 1995; ibge 1997;
Santana et al. 1997; Homma 1998).
But two objectives, tapping the resources of the Amazon and developing the
region, often became decoupled by policy action. There were several reasons, some of
them known before the task began and others discovered after the processes had begun.
First, huge distances separated the Amazon from major population and transportation
centers, thereby making inputs needed in the Amazon more expensive and products
from the region less valuable. Second, the Amazon was found to be a huge mosaic of
different ecosystems rather than a homogenous forested area. This latter discovery had
both positive and negative consequences. Biophysical scientists were introduced to the
world’s greatest cache of biodiversity, but development planners were faced with the
unforeseen need for expensive niche-specific projects and support programs. Third,
the biodiversity of the Amazon forest and the carbon stored in it were increasingly
viewed as belonging to groups both larger and smaller than the Brazilian federal gov-
268
National Perspectives
ernment, which held legal claim to much of this vast area. Indigenous communities
were increasingly vocal about their claims to large tracts of land and the resources on
and beneath them. Simultaneously, the international community, under the banners
of greenhouse gas emissions and biodiversity conservation, provided much advice on
what portions of the Amazon should be used and how (Myers 1984).
In the 1960s, the federal government decided to implement policies aimed at
occupying the Amazon region and integrating it with the rest of the national economy. The development process was launched with policymakers hoping that research
undertaken alongside development, and at times supported by the financiers of development activities, would provide answers needed for wise stewardship of the Amazon.
We now know that knowledge was insufficient to appropriately guide development
policy action at that time and that research could not close that gap in the dynamic
decades of the 1960s, 1970s, and 1980s.
Operation Amazon, established in 1966, set out a broad geopolitical and economic plan for the region (Government of Brazil 1969; Mahar 1979; Santana et al.
1997). In support of Operation Amazon, new policy objectives and policy instruments were created that were to supply the legal and financial means, labor, transportation networks, and electrical power needed to establish migrants and industry
in the Amazon. In addition, new regional development agencies such as the Amazon Development Agency (Superintendência de Desenvolvimento da Amazônia), the
Amazonian Duty-Free Authority (Superintendência da Zona Franca de Manaus), and
the Amazonian Regional Bank (Banco da Amazônia S.A.) were established to organize
and support development activities, often via the provision of subsidized credit to
agriculture, particularly extensive beef cattle ranching, and mining projects (Forum
Sôbre a Amazônia 1968; Government of Brazil 1969, 1981; sudam 1976; Smith et
al. 1995; ibge 1997; Santana et al. 1997; Faminow 1998).
Since the establishment of federal subsidized credit in the late 1960s, thousands of
agricultural and industrial projects have been approved and implemented in the Amazon. In the western Brazilian states of Acre and Rondônia alone, thirty-three projects
were approved from 1965 to 1996 for agricultural and industrial activities. This was
roughly 12 percent of the 392 projects implemented throughout the Amazon during
that time (Santana et al. 1997).
To support these projects, large hydroelectric dams, such as the Tucuruí Dam
in the state of Pará, were built. In addition, several highways were planned and partially constructed to provide access to the region. The Trans-Amazon highway, from
the Atlantic Coast to the Peruvian border, was to comprise about 5000 km of allweather roads but is yet to be finished. Other major highways were completed, such
as the BR-364, linking Acre and Rondônia to São Paulo and southern Brazil, and the
Belém–Brasília road, linking Pará with the rest of the country (sudam 1976; Santana
et al. 1997).
In the early 1970s, world economic and oil crises led to a severe economic
recession in Brazil. When combined with changes in agricultural technology and
consequent changes in farm structure, this generated large increases in unemploy-
The Western Brazilian Amazon
269
ment and landlessness in southern and southeastern Brazil, and consequent social
conflicts in these regions. The Federal Government saw the opportunity to solve
two problems simultaneously. Moving unemployed and especially landless people to
the Amazon region and establishing them in settlement projects there would reduce
social pressures in the southern regions of the country and increase the labor available for development in the Amazon (sudam 1976; Government of Brazil 1981;
Bunker 1985).
The process of assisting migration and colonization of landless people to meet
these dual objectives was rapid and intense. The federal government handed over millions of hectares of forested land to small- and large-scale migrants and local people
with little knowledge of the potential for these areas to support agricultural activities
of any kind. These small-scale farms (in the Brazilian context), ranging in size from 50
to 100 ha, came to be known as “dumb rectangles” because few soil, water, or watershed conditions were taken into consideration during their demarcation (Valentim
1989; Walker and Homma 1996; Wolstein et al. 1998).
C O N S E QUENCES OF THE DEVELOPMENT PROCESS
The policy-driven occupation of the Amazon has been under way for more than 30
years. Policy action, conditioned by economic forces and biophysical factors, has had
direct and indirect consequences for economic growth, human welfare, environmental
sustainability, and especially demographic change.
M i g r at i o n
From about 1965 to 1995, more than 500,000 families settled in new colonization
projects or spontaneously invaded forest areas along the highways that were opened
throughout the Amazon. In the western Brazilian Amazon, population growth was
substantial but uneven. In the state of Acre, the population grew from just over
100,000 in 1950 to nearly 500,000 by 1996. In the state of Rondônia, population
grew from 36,000 in 1950 to more than 1.2 million in 1996, a staggering increase in
46 years. As a consequence, population density in Acre and Rondônia rose from 1.4
and 0.5 people per square kilometer in 1970 to 3.2 and 5.2 people per square kilometer in 1996. Although they were initially rural populations, by 1996 almost twice
as many people lived in urban as in rural areas, as shown for Rondônia in figure 12.2
(ibge 1997).
Starting in 1970, the western Brazilian Amazon also experienced a rapid process
of urbanization. By 1996 more than 60 percent of the region’s population was already
in cities and towns, although rural–urban migration patterns differed by state. In
Acre, rural population tended to be stable between 1970 and 1996, while the urban
population grew. In Rondônia, rural population growth continued until about 1991.
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National Perspectives
Figure 12.2 Population growth in the Brazilian asb benchmark state of Rondônia between 1950 and
1996 (ibge 1996).
Upon arrival in these areas, settlers cut and burned primary forests, and the
cleared areas were put under plow for a series of agricultural activities. But hardships
awaited many settlers. Most of the newcomers were stricken by malaria, a disease that
significantly reduced their capacity to work, generated medical expenses that further
reduced already precariously low household financial resources, and was sometimes
fatal (Bartolome and Vosti 1995). Promised social services generally were lacking in
the early years of colonization: Health care facilities were built but not staffed, and
schools often were constructed, but qualified teachers were hard to find and retain. By
those measures, poverty probably increased for early settlers (Vosti et al. 1998).
D e f o re s tation
The environmental consequences of the policies pursued in the Amazon were substantial and generally negative. In the past 30 years, forest cover in the Amazon has been
substantially reduced, with consequent increases in emissions of CO2 and other greenhouse gases, loss of biodiversity, nutrient leaching, soil erosion, and land degradation
(Valentim 1989; Smith et al. 1995; Homma 1998; Wolstein et al. 1998; Embrapa
1999a; inpe 2003).
In some areas, forest conversion was particularly aggressive. For example, in
Rondônia, accelerated settlement and agricultural programs have resulted in the conversion of approximately 23 percent of that state’s forests to agriculture in the past
20 years, with annual deforestation rates reaching 2.8 percent of the total area of the
The Western Brazilian Amazon
271
state in 1995 (Fearnside 1991; Lisboa et al. 1991; inpe 2003). In Acre, migration and
forest conversion to agriculture have been less rapid, resulting in the deforestation of
approximately 9.3 percent of the total area of the state in the same period, with the
peak annual deforestation rate also reached in 1995, about 0.8 percent of total state
land, as shown in figure 12.3 (inpe 2003).
The predominant land use system in the area begins with the clearance of forests
using slash-and-burn techniques for annual crops, which can be grown without the
use of external nutrient inputs on a given plot of land for 2 to 3 years. The establishment of cultivated pastures for dual-purpose, extensive cattle ranching generally follows on plots that can no longer support annual crop production.
Most of the land clearing in the Brazilian Amazon, even in the large enterprises
was done by slash-and-burn. There was only one case of a big international company
that used herbicides to kill 10,000 ha of forests in Pará and then burned it. Bulldozers were not really used, with only a few exceptions, in the context of the Brazilian
Amazon.
There is a tendency for farms of all sizes to decrease the area remaining of forest
and increase the area under pasture over time. Other land uses (monoculture coffee [Coffea canephora Pierre ex Fröhner] or agroforestry systems) can contribute substantially to household income and absorb considerable amounts of family and hired
labor, but the amount of land usually dedicated to these other uses remains small,
relative to pasture, as shown in figure 12.4 (Dale et al. 1993; Browder 1994; Fujisaka
et al. 1996; Vosti and Witcover 1996; Vosti et al. 2002).
S o i l D e g radation
Lack of knowledge even among soil scientists of the degree of heterogeneity of Amazonian soils and their ability to support different agricultural activities, and failure on
the part of planners and policymakers to put to effective use the partial knowledge
that was available, led to the settling of thousands of farmers on land that could not
support agriculture of almost any kind, certainly not the types of agriculture settlers
were likely to pursue, given their experience in the south or northeast. As a result, soils
became degraded and unproductive after just a few years, further fueling deforestation in the region as farmers sought to add to their stocks of usable soils. Moreover,
and perhaps ironically, many farmers began to experience water scarcity in the world’s
largest and most productive watershed. The search for on-farm alternatives and supplements to annual cropping increased water needs, especially for livestock, and the
deforestation needed to clear land for and to finance the establishment of alternative
production systems may have decreased surface water supplies (Valentim 1989; Smith
et al. 1995; Serrão et al. 1996; Wolstein et al. 1998; Amaral et al. 1999, 2000b).
It is estimated that by 1997, about 55 million ha of forests in the Brazilian Amazon (14 percent of the total area) had been converted to agriculture and that roughly
one half of that deforested area (about 25 million ha) was already degraded (inpe
Figure 12.3 Deforestation in the Brazilian asb benchmark states of Acre and Rondônia between 1978
and 1997: (a) cumulative percentage of area and (b) annual rates (inpe 2003).
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273
Figure 12.4 Land uses, by farm age, in the Pedro Peixoto Settlement Project in the state of Acre, Brazil,
in 1996 (Vosti et al. 2002).
2003). The states of Rondônia and Acre have an estimated 1.5 million and 450,000
ha of degraded pasture and 540,000 and 140,000 ha in secondary fallow (capoeira),
respectively (Embrapa 1999a; inpe 2003).
E co n o m i c Grow th
Although the policies, economic forces, and biophysical factors guiding the occupation, use, and integration of the Brazilian Amazon have resulted in waves of migration
and significant deforestation, progress in economic growth has been substantial over
the past 30 years, with marked increases in gross domestic product and regional value
added.
For example, Rondônia (with 5.4 million ha of forests converted to agriculture)
became the third largest cocoa-producing and fifth largest coffee-producing state in
Brazil by 1995. And, with 70 percent of the deforested area (3.8 million ha) planted to cultivated pastures, the state now has roughly 4 million head of cattle (ibge
1997). Gross domestic product per capita in Rondônia rose from us$2025 in 1970
to us$6448 in 1996 (table 12.1), close to the national average for Brazil for that year
(ibge 1997; Faminow and Vosti 1998; undp 1999).
In Acre, economic progress over the past 25 years also has been substantial. Farmers have deforested only about 9.3 percent (1.4 million ha) of the total area, convert-
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National Perspectives
Table 12.1 Changes in Indicators of Human Welfare for Acre, Rondônia, and All Brazil,
1970–1996
Socioeconomic Indicator
Year
Acre
Rondônia
Brazil
Grammar school matriculation (% of schoolaged children registered)
1970
1980
1991
1995
1996
1970
1980
1991
1995
1996
1970
1980
1991
1995
1996
1970
1980
1991
1995
1996
36.1
48.5
59.0
74.1
74.1
47.3
55.2
65.7
70.2
70.2
1302
2343
3767
5499
5741
0.376
0.506
0.662
0.752
0.754
31.7
50.7
63.0
69.8
70.7
64.7
68.5
80.4
84.3
85.8
2025
3426
4185
5562
6448
0.474
0.611
0.725
0.782
0.820
49.2
61.2
67.8
75.7
76.8
67.0
74.7
80.6
84.4
85.3
2315
4882
5023
5986
6491
0.494
0.734
0.787
0.814
0.830
Literacy rates (%)
Per capita gross domestic product
( $ purchasing power parity)
United Nations Development Program human
development index
The human development index is a summary index that incorporates life expectancy, literacy, and
standard of living.
Sources: (1997a), (1999).
ing roughly 80 percent of the cleared areas to pastures (1.2 million ha), and now manage about 1 million head of cattle (Embrapa 1999a). Annual gross domestic product
per capita in Acre (table 12.1) rose from us$1302 in 1970 to us$5741 in 1996 (ibge
1997a; undp 1999).
H u m a n Welfare Improvements
There also have been large social benefits from the policies implemented in the last
three decades in the western Brazilian Amazon. Poverty has been reduced, school
matriculation rates have risen, incomes have increased, and nutritional status has
improved. Total primary and secondary school matriculation in Acre and Rondônia
more than doubled in 26 years, rising from 36 and 32 percent in 1970 to 74 and 71
percent in 1996, respectively. Over the same period, life expectancy at birth in both
Acre and Rondônia rose from 53 years to more than 67 years, and illiteracy rates
among adults decreased in Acre from 53 to 30 percent and in Rondônia from 35 to
14 percent. The undp human development indices for Acre and Rondônia rose from
The Western Brazilian Amazon
275
0.38 and 0.47 in 1970 to 0.75 and 0.82 in 1996, respectively, although these are still
below the value for Brazil as a whole, which was 0.83, as shown in table 12.1 (ibge
1997a; undp 1999).
N E E D F OR A NEW DEVELOPMENT PARADIGM
It is clear that over the past three decades, the western Brazilian Amazon has experienced rapid socioeconomic and environmental change. But can, or should, this process continue? We argue that it cannot and need not continue for several reasons.
First, the forested land suitable and available for conversion to agriculture
is becoming scarce. Most soils in Acre and Rondônia near roads and rivers with
known and reasonable agricultural potential have already been used or soon will
be. Remaining forested areas (some of which may have agricultural potential) are
increasingly off-limits because of local, state, federal, or international agreements,
especially concerning Amerindian and extractive reserves. Federal law since 1989
has prohibited public credit programs from extending loans to clear forests for
agricultural purposes in the Brazilian Amazon. Rondônia, in particular, has almost
exhausted its agricultural frontier and must now search for other means of increasing agricultural production. Productivity increases will be the primary source of
future agricultural growth.
Second, soil degradation is pervasive in the western Brazilian Amazon, and this
increasingly limits product choice and productivity. For example, 50 percent of the
532,000 ha of pasture land in Acre is located on soils now judged to be unsuitable
for traditional braquiarão or brizantão (Brachiaria brizantha [Hochst. ex A. Rich.]
Stapf ) pastures. These pastures either already have suffered or will soon experience
rapid decreases in carrying capacity (Valentim et al. 2000). With area for new pasture
expansion increasingly limited, improved and more intensive pasture and cattle management systems will be needed, as will investments to establish them.
Third, water resources in this humid tropical region are becoming scarce in colonization projects and urban areas. Water pollution is also becoming a problem, especially in and around urban areas (Knight 1998).
Fourth, because of a shifting geographic focus and fiscal limitations, the federal
agencies that played such broad and fundamental roles in opening up the western Brazilian Amazon and linking it to the rest of the country have substantially reduced their
activities and shifted investments in established areas (Government of Brazil 1998).
State and local governments, often working with other groups, are struggling to fill
these gaps (Vosti et al. 1998).
Therefore, with new agricultural land becoming scarce, productivity on cleared
land falling, water scarcities developing, and traditional funding sources eroding, a
new regional development paradigm is needed. And the overall environment seems
conducive to change; new economic circumstances, new technologies, and potential
policy and organizational and institutional changes combine to offer development
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National Perspectives
options that were not available even a decade ago (Almeida and Uhl 1995). The main
reasons are as follows.
First, the western Brazilian Amazon is no longer the very distant outpost it was
when development began 30 years ago. All-weather roads link most major urban centers, and recent investments in water transport have dramatically altered the potential
for regional and international trade. So markets exist today that did not 20 years ago,
and general market performance seems to be improving with economic integration
and increased competition.
Second, new and better technology is now available to support agriculture, from
production to harvesting, processing, and marketing. New technologies made available by the private and public sectors expand the product mix available to farmers and
can improve profitability, too.
Third, and perhaps most important, some areas in the western Brazilian Amazon
are experiencing broadening local support to better manage agricultural growth and
integrate it with modern, sustainable forest stewardship. In Acre, for example, a state
government of the forest was recently elected, with sustainable development driven by
both forestry and agriculture as a fundamental part of its party platform.
What specific solutions might spur sustainable development in the face of the
challenges and opportunities noted in this chapter? What can policymakers do to
promote these solutions? What role remains for research? We briefly address these
Figure 12.5 Tradeoffs between forest area and income for different farm activities as a result of a bioeconomic simulation model in a small farm holding in the Pedro Peixoto Settlement Project in 1996
(Carpentier et al. 1998). Low Tech–All, traditional practices; Low Tech–Cattle, intensified cropping but
traditional cattle pasture management; Cleared Land–Inten., intensification of all crop and cattle activities; Clrd. & Forest–Inten., intensification of all crop and cattle activities and forest management; NPV,
net present value.
The Western Brazilian Amazon
277
issues in the context of one promising land and forest use system: small-scale managed
forestry (see also chapter 8, this volume).
Past policies failed to add value to the forest and usually achieved just the opposite, generally by design. As a result, even short-term gains from low-productivity
agriculture were, and often continue to be, greater than the private financial returns to
the types of forest extraction activities that would be practiced given policy and price
conditions. Forests will continue to be cleared for agriculture until this broad profitability gap is closed. One way of doing so is to permit small-scale managed forestry,
a best-bet alternative to slash-and-burn developed by Empresa Brasileira de Pesquisa
Agropecuária (Embrapa) as part of the asb program, which has been demonstrated
under experimental conditions to be profitable, to reduce but not eliminate deforestation, and to be capable of retaining the resiliency and productivity of forest ecosystems
(figures 12.5 and 12.6).
This managed forestry technology has not been easy or cheap to develop. Years of
research on the response of forest systems to different types and intensities of logging
were needed to identify a small subset of sustainable forest management techniques.
Figure 12.6 Aspects of the Low Impact Sustainable Forest Management in Legal Reserves of the Pedro
Peixoto Colonization Project: (a) the legal reserve areas being managed, (b) wood planks extracted from
this forest area, (c) the house made with wood extracted from the managed area where the family of the
small farmer lives, and (d) a field day demonstrating the research and development results to other farmers and extension agents.
278
National Perspectives
Research was also needed to determine the farmer and market conditions under which
it was profitable to pursue these techniques when alternative uses of farmers’ time,
land, and financial resources were considered (Homma 1993; Araújo 1998; Oliveira
et al. 1998; Vosti et al. 2002; Vosti and Valentim 1998; Embrapa 1999b; Santos et al.
1999; Carpentier et al. 2000a, 2000b).
But experimental techniques are not easy to promote, refine, or replicate without
enabling policies. Promoting these managed forestry systems beyond their experimental stages will entail policy action, such as changes in legal and practical impediments
to timber management and credit programs to support investments in small-scale
implements, as well as institutional change, such as the formation of groups of smallholders that can manage and monitor forest extraction activities. Refining systems in
response to changes in farming and forest circumstances will entail new and continuing research and scientific monitoring. Replication on a broad scale will necessitate
research into the effects of doing so on market and ecosystem conditions. If broad
adoption is recommended, extension services will have to be retooled.
T H E M ULTIPLE IMPACTS OF ASB
As indicated earlier, scientific and technical knowledge to support and guide development in the western Brazilian Amazon in the 1960s was insufficient. Although some
measures were taken at that time to augment it, they were generally too small in scale
or too narrowly focused to deliver new knowledge at the necessary pace. We know
much more today about Amazonian ecosystems and the agents occupying these lands.
However, we still do not have the knowledge we need for economically and ecologically sound planning on a regional or subregional basis (Valentim 1989; Smith et al.
1995; Homma 1998), but progress in filling knowledge gaps has quickened over the
past 10 years. Multi-institutional, interdisciplinary research teams have been largely
responsible for this broader knowledge base, and asb is a leader among these teams,
especially in Acre. Of course, there were other multidisciplinary groups of researchers
working on development problems in the region, such as the Grupo de Pesquisa e
Extensão em Sistemas Agroflorestais do Acre (pesacre, a local research consortium)
and the Universidade Federal do Acre. The asb provided strong scientific and institutional leadership. In what follows, we focus on asb impacts on Embrapa, but there
were substantial spillovers to other research- and service-oriented organizations (especially pesacre and Empresa de Assistência Técnica e Extensão Rural, the agricultural
extension service).
From the outset, asb’s mandate, research methods, and research partners have had
profound effects on Embrapa and the potential for Embrapa to effectively contribute
to changing development objectives and policies in the western Brazilian Amazon. The
asb’s research mandate was to better understand biophysical and socioeconomic processes and outcomes and the links between them and—based on new knowledge—to
identify entry points for policy actions needed to achieve broad development objec-
The Western Brazilian Amazon
279
tives in the region. The specific outcomes of research on these issues are reported
elsewhere in this publication. Here, we highlight the impacts of asb in Brazil on the
focus and nature of research, on the search for and development of new technologies,
and on policy change in Embrapa Acre and Rondônia.
Th e F o c u s and Nature of Res earch
With the arrival of asb, its new research paradigm, collaborators, and financial
resources, there was a substantial shift in the focus and nature of Embrapa’s biophysical and social science and policy research at the two benchmark states (Ávila 1994).
First, biophysical research that traditionally examined single food production
activities over short periods of time was expanded to include multiproduct land use
systems practiced over much longer periods of time. And because the biophysical
consequences of agricultural and other changes are not restricted to the boundaries of
the farm, transects of land including but not restricted to farm land were studied. It
was clear that these land use systems should not be examined in isolation but needed
to be jointly analyzed at the landscape level and in the context of important on- and
off-farm variables.
Second, the ways in which much of Embrapa’s biophysical research is carried
out have also changed, in part because of collaboration with asb. In the past, most
Embrapa research was carried out in plots located on experiment stations. The degree
of farmer involvement in determining research topics or methods was limited, and
the biophysical and socioeconomic contexts in which farmers made product, technology, and resource allocation decisions were not part of researcher-led experimental
designs. For some scientific problems, such as fertilizer response trials, this de-linking
of experiments from smallholder situations is effective and efficient. For many other
problems, such as the potential for establishing legume-based pastures in farmers’
fields, it is not.
Most of asb’s biophysical research was carried out on farmers’ fields, often with
the direct participation of farmers in developing, monitoring, and managing experiments.
Where scientifically appropriate, this emphasis on farmer participation and farmbased experimentation continues at Embrapa today. For example, research conducted
in farmers’ fields rose from less than 10 percent in 1994 to approximately 60 percent in 1998 in Embrapa Acre, with consequent increases in the use of participatory
research methods and the validation of research products by farmers in their own
socioeconomic and environmental situations.
Third, Embrapa’s research traditionally focused on agronomic factors of immediate or short-term relevance to farmers. Links with asb and its national and especially
international network of research institutions expanded the geographic and temporal
foci of Embrapa research. For example, the long-term consequences of particular land
use patterns are now of central concern. In addition, identifying the impacts of land
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National Perspectives
use and land cover change on local, regional, and even international communities is
now very important in Embrapa research. The asb is chiefly responsible for Embrapa’s
new focus on international environmental externalities (e.g., CO2 emissions, changes
in above- and below-ground biodiversity).
S o c i o e conomic Research
Like biophysical researchers, social science researchers had spent little time on farmers’ fields or in farm households collecting data. The asb brought a substantial shift
toward socioeconomic field research, especially the collection and use of field data.
Efforts to develop and use secondary data, such as those containing comprehensive
product and input price series, were also expanded with asb guidance.
Perhaps the most important contribution of asb to Embrapa’s socioeconomic and
policy research was the increased priority given to predicting the impacts of different
price and technology changes and to developing the analytical tools to generate these
predictions (Vosti et al. 2001a). For example, asb and Embrapa collaborated to develop, test, and use a farm-level bioeconomic model capable of predicting the impact of
changes in policy on land use patterns, deforestation, and household income (see also
chapter 10, this volume). Simulated land uses over a 25-year period produced by this
model and based on conditions for a typical small-scale farmer whose characteristics
were derived from field research in Acre. Model simulations, under socioeconomic
and policy conditions prevalent in 1994 to 1996 and subject to the biophysical and
especially farm household labor constraints, show that forest will continue to fall in
the western Brazilian Amazon and cleared land will be allocated predominantly to
pasture (Carpentier et al. 2000a; chapter 10, this volume).
Combining information generated by model simulations can be much more
informative. Figure 12.5 summarizes results of several simulations based on different
policy and technology scenarios. Tradeoffs can be examined as we move from one
scenario to another between household income (measured in terms of net present
value of profit streams and represented by bars in figure 12.5) and the amount of forest retained on farms (measured in terms of hectares of forest remaining in year 25 of
the scenario and represented by diamonds connected by lines in figure 12.5). In the
scenarios examined here, increasing the scope of agricultural intensification (moving
from left to right, beginning with no intensification on cleared or forested land to
a scenario that permitted intensification of all activities on cleared lands, the third
scenario) increases household income and decreases forest cover. Note that only when
agricultural and forestry activities are intensified (final scenario in figure 12.5) do both
income and forest cover increase (Carpentier et al. 2000b). Absolute levels of farm
household income may seem high at first glance. Readers are reminded that figures
reported represent the present discounted values of income streams earned over the
25-year time horizon of the farm household model. General equilibrium effects are
not taken into consideration, nor is risk included explicitly into the model, except in
the case of edible bean (Phaseolus vulgaris L.) production.
The Western Brazilian Amazon
281
At a much higher level of spatial and economic aggregation, asb also developed
an economy-wide model capable of predicting the impact of changes in macroeconomic policy and region-wide changes in agricultural technology on deforestation in
the Amazon. This model, the only one of its kind in Brazil, predicts, for example, that
in response to a major devaluation of the Brazilian currency, in the Amazon region
taken as a whole the area dedicated to coffee would double, extractive activities would
experience a boom, production of consumer staples would decrease substantially, but
logging would only be slightly affected (Cattaneo 1999; chapter 7, this volume).
B i o ph y s i cal Research
The asb collaboration has also modified the focus of and methods for Embrapa’s
technology development activities. Historically, Embrapa’s research had focused on
economic practices undertaken on cleared land and on traditional agricultural activities. Under the economic premise that adding value to the forest is fundamental to
saving it, the search for new technologies has been expanded to include those that can
be practiced on forested lands.
In addition, research has shifted somewhat from agricultural practices imported
to the region from other areas in Brazil, such as upland rice (Oryza sativa L.) and bean
production, to those involving native species, primarily woody perennials. Examples
of these are agroforestry systems such as that of the Projeto Reca with mixtures of tree
species such as peach palm (Bactris gasipaes Kunth), cupuaçú or theobroma (Theobroma grandiflorum [Willd. ex Spreng. K. Schum.]), and Brazil nut (Bertholetia excelsa
Humb. & Bonpl.) (figure 12.7). Another is the cultivation of pimenta longa (Piper
hispidinervum C.DC.), a native bush containing an essential oil (Safrol) that is used
in cosmetics production (as a fixing agent of fragrances) and as a synergistic agent in
the production of domestic insecticides. Embrapa has domesticated this species and
developed the agricultural and agroindustrial production systems. Research on these
emerging products focuses not only on their sustainable cultivation but also on postharvest processing and marketing issues.
Finally, given the demonstrated attractiveness of dual-purpose (milk, beef ) cattle
ranching to local smallholders, special efforts are under way to make these systems
more agronomically sustainable and to limit the need for and incentives to expanding
new pasture lands. For example, in the Ramal da Enco farmers’ association in Acre,
research on the use of solar-charged, battery-powered electric fences for managing
pastures and cattle herds is under way. Preliminary results suggest that pasture carrying capacity can be increased and pasture life extended by using these fences, which
are inexpensive to establish and maintain (Vaz and Valentim 2001). To take another
example, new legumes such as perennial peanut (Arachis pintoi Krap. & Greg.) and
tropical kudzu (Pueraria phaseoloides [Roxb.] Benth.) are being recommended for the
establishment of grass–legume pastures to increase the profitability and sustainability
of cattle production systems in the western Brazilian Amazon (Valentim and Carneiro
2001; Valentim et al. 2001), as shown in figure 12.8.
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National Perspectives
Figure 12.7 The simple agroforestry system of the Projeto Reca in Rondônia, which includes peach palm,
cupuaçú, and Brazil nut trees.
E m b r a pa’s Role in Regional Policy Dialogue
In part as a result of asb research, Embrapa’s position in local, state, regional, and
national policy debates has been strengthened, allowing it to offer more concrete policy advice on a broader array of issues and to help avoid costly policy mistakes. In most
cases, the mechanisms for Embrapa input into policymaking predate asb, but it was
the asb program that brought policy implications to the forefront in research design
and also sought to extract policy-relevant lessons from all research projects. Moreover,
the predictive power of the household and economy-wide models developed by asb
has provided Embrapa with greater voice and credibility in policy debates. The following are examples of the types of policy debates to which Embrapa is contributing:
Land use zoning was undertaken during the early period of modern occupation in
Acre, and the resulting land use potential recommendations are 87 percent of the area
for crops, 12 percent for pastures, and less than 1 percent for forest plantations. Less
than 0.5 percent of the land was considered to have no agricultural potential. At that
time, much of the state’s land was deemed suitable for nearly any type of agricultural
pursuit, at any scale. An Embrapa reevaluation of land use potential (carried out in
part with asb assistance) revealed a very different suggested set of land use options,
this time highlighting the limits to traditional large-scale agricultural activities and the
major role that small-scale agriculturalists, agroforestry, and forestry activities should
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283
Figure 12.8 Photographs (clockwise) of dairy cattle grazing a protein bank of perennial peanut (cv. Belmonte); dairy cattle grazing guineagrass (Panicum maximum Jacq.) cv. Massai, a new grass developed
by Embrapa based on selection of ecotypes introduced from Africa; beef cattle grazing guineagrass cv.
Tanzania, also a new grass developed by Embrapa based on selection of ecotypes introduced from Africa;
and grass–legume pastures consisting of Tanzania grass and tropical kudzu.
play (Amaral et al. 2000a) (figure 12.9). This updated land use assessment is one of
the cornerstones of state development planning and policy today.
A separate set of Embrapa-led land use zoning exercises has helped identify where
subsoil impediments to drainage are causing the death of brizantão-based pastures
over very broad areas (Valentim et al. 2000). Research is under way to identify replacement grasses.
Embrapa is routinely asked to provide suggestions for targeting subsidized agricultural credit in the region. Based on the results of collaborative forest ecology and
farm household economic research, Embrapa has proposed that farmers or farmer
cooperatives preparing plans to implement small-scale managed forestry schemes be
eligible for special credit from a fund managed by the Amazonian Regional Bank.
In May 1999, the federal government of Brazil and the state government of Acre
organized a workshop involving government and nongovernment organizations and
representatives of the private sector to discuss a positive agenda for the Brazilian Amazon aimed at addressing growth, poverty, and environmental issues together. Embrapa
was asked to provide the scientific and technical basis on which regional and state-level
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National Perspectives
Figure 12.9 Land use recommendations for Acre in 1999, focusing on small-scale agriculture, agroforestry, and small-scale forestry, based on work of Embrapa and asb (Amaral et al. 2000a).
policies would be developed. Research results, methods, and experiences provided by
asb collaboration greatly assisted Embrapa in this task. The most important proposals
to emerge from this workshop were to
• Gradually decrease deforestation rates in Acre.
• Establish a targeted amount of cleared land, initially set at 14 percent of
total state area, to be reached by the year 2020.
• Establish policy disincentives to forest conversion for agricultural purposes
and policy incentives to reclaim degraded land and increase the efficient
and sustainable use of forests.
Although it attracts less attention now than in the past, the formal colonization
process in the region is still ongoing, though at a much slower rate than in earlier
decades. So the problems of where and how to settle smallholders and what sorts of
support are needed to increase the chances of success remain. Embrapa (supported by
asb research results and research tools) is changing the way colonization projects are
conceived and implemented.
For example, a settlement project recently approved for joint implementation
in the Seringal São Salvador by Embrapa Acre, Instituto Nacional de Colonização e
Reforma Agrária Acre (National Colonization Institute), pesacre, the municipality
The Western Brazilian Amazon
285
of Mancio Lima, sos Amazonia (an environmental organization), and the Brazilian
Institute for the Environment and Natural Resources envisions land distribution and
land and forest use patterns quite different from those implemented under traditional
colonization schemes. In traditional colonization schemes, land allocation to farmers was done without much thought given to the potential and limits of the natural
resource base (forests, soils, water) or to the socioeconomic circumstances of migrant
families, and the legal reserve areas were established within individual plots and left to
farmers to manage.
The current approach to settling smallholders pays much more attention to assessments of the natural resources done beforehand to determine land use potential and
constraints, the possibility that some lands may not be suitable for settlement purposes
and therefore should be set aside for conservation, the socioeconomic circumstances
of candidate families, farmer participation in colonization planning and implementation phases, the potential for locating legal reserves to ensure that continuous blocks
of forest remain in or around colonization projects, and the management of these
legal reserves to sustainably produce timber and nontimber forest products. This new
approach reduces settlement costs and limits deforestation to no more than 30 percent
of the total colonization project area (as opposed to the 50 percent allowed in the
traditional schemes).
Embrapa also played an important role in providing scientific and technical support to the federal government’s decision in November 1999 to prohibit establishment
of new settlement projects in forest areas of the Brazilian Amazon.
Finally, Embrapa input, some of which was based directly on asb research
results and research tools, has provided a sounder basis for establishing price policy
at state and regional levels. For example, policymakers in Acre were contemplating a subsidy for upland rice and bean production, alleging that it would reduce
deforestation. The asb–Embrapa research results based specifically on simulations
of the bioeconomic model demonstrated that such a price policy would not reduce
deforestation, although it would improve smallholder incomes. The choice was left
to policymakers, but with the predicted impacts of the proposed policy change more
clearly articulated.
O rg a n i z ational and Institutional Impacts of ASB
Collaborative Embrapa and asb research provided and promoted the establishment
of links with the international research community and consequently provided access
to new individuals and institutions, new views, and new tools. In part as a result of
Embrapa’s support to asb, there was a marked change in the profile and training of
Embrapa’s research staff. New specialists in the fields of forestry, economics, soil classification, and soil fertility were recruited and retained, and the level of research staff
training rose considerably: The proportion of staff holding Ph.D. degrees rose from 6
to 19 percent between 1995 and 1999.
286
National Perspectives
At the same time, laboratory infrastructure was significantly increased and
improved. Soil fertility and physics laboratories that before 1995 had limited capacity
and low levels of reliability are now certified by a national quality control program and
analyzed more than 20,000 soil samples in 1999. Laboratories for food technology,
seed analysis, seed certification and processing, animal nutrition, and plant analysis
were recently constructed, and technical staff to run them were hired and trained.
although these and other efforts to expand and improve laboratory capacity were only
partially funded by asb, asb was central in helping identify them as priorities.
Improving and increasing computer services within Embrapa was also a high priority, to which asb contributed significantly. In 1994, Embrapa Acre had only six
microcomputers and one specialist in this field. By 1999, there were seventy-four
microcomputers and a large staff to support them. Training in computer and software
use (some of which was undertaken or financed directly by asb) has resulted in the
presence of a cadre of research and support staff that is highly computer literate and
consequently much more productive.
F U T U R E COLL ABORATIVE RESEARCH WITH ASB
Future collaborative research involving Embrapa, asb, and other organizations will
focus on plot-level, farm-level, and landscape-level issues, always overlaying biophysical and socioeconomic factors in generating scientific contributions to help promote
sustainable economic growth, increase incomes, and improve living conditions of
small-scale farmers and conserve the natural resource base. At all levels, the search for
new combinations of policies, technologies, and institutional arrangements to meet
development objectives will continue.
Plot-level research will focus on identifying the links between land use and changes in above- and below-ground biodiversity. Establishing these links will help researchers identify the private benefits of biodiversity (i.e., those affecting farm profits) and
develop policies to use these benefits as entry points for enhancing biodiversity conservation.
At farm level, research will expand the set of products and land use activities for
which complete biophysical and socioeconomic information is available and incorporate this new information into predictive models. In addition, the focus of research
will expand beyond settlement project areas to include extractive reserves, where small
numbers of households are responsible for the stewardship of very large tracts of forest
land, and large-scale farms, where small numbers of economic agents make decisions
on large tracts of cleared and forested land.
At landscape level, land use mosaics within and across farms that are financially
attractive and have beneficial environmental characteristics will be identified, and policies for promoting their establishment and maintenance will be explored.
Finally, at all levels research will endeavor to generate predictive capacity by
developing models that will allow researchers and policymakers to assess a priori the
The Western Brazilian Amazon
287
impacts on environmental sustainability, economic growth, and poverty alleviation of
alternative policy interventions or combinations of them.
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13 The Forest Margins of Sumatra, Indonesia
Soetjipto Partohardjono, Djuber Pasaribu, and Achmad M. Fagi
Center for Research in Food Crops Agency for Agricultural Research
and Development Bogor, Indonesia
I
ndonesia still has large forest areas, but they are rapidly being converted to
other land uses. Transformation from primary to secondary forest is caused
largely by timber extraction, and traditional shifting cultivation systems play
a smaller role. Subsequent transformation of secondary and logged-over forest types generally is based on slash-and-burn practices by large-scale farmers
and smallholders for a variety of reasons. Migrants convert part of the forest
to temporary cropland either in government-sponsored schemes or spontaneously. Such land can evolve into alang-alang (Imperata cylindrica [L.]) grasslands or into permanent tree-based production systems (agroforests).
Slash-and-burn is both a land-clearing technique and a land use system.
It is inaccurate to equate slash-and-burn agriculture only with permanent forest conversion and unsustainable land use. The technique is attractive because
fire is the cheapest, most effective way to clear land (Ketterings et al. 1999).
The Alternatives to Slash and Burn (asb) characterization data (van Noordwijk et al. 1995, 1998; Tomich et al. 1998) suggest that in Jambi (Sumatra),
most slash-and-burn is used for replacing old jungle rubber, rather than for
conversion of primary forest. Traditional shifting cultivation of food crops,
practiced for generations by local people in Sumatra, was sustainable as long
as population densities were low enough to allow long fallow rotations. Traditional shifting cultivation has been disappearing as rural population densities increase, but slash-and-burn is used for land clearing by almost all those
(public and private, large- and small-scale) who contribute to forest conversion, sometimes in systems that are unsustainable but often in systems that
apparently are sustainable for the foreseeable future.
Agroforests begin with slash-and-burn clearing and intercropping of
upland food crops, but the primary objective is the establishment of tree
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National Perspectives
crops such as rubber and various fruit and timber species. This system accommodates
natural regeneration. As a result, agroforests replicate some elements of natural forest
structure and ecology (Michon and de Foresta 1995). In the asb global project, the
island of Sumatra was chosen to represent the lowland humid tropical forest zone in
Southeast Asia.
In this chapter we give an overview of the results in phase 1 and 2 of the asb Project in Indonesia, with a brief historical background of the forest conversion process,
discussing the categorization of forest lands in Indonesia and describing the benchmark areas in Jambi and Lampung, before we discuss the main asb hypothesis on the
relationships between intensification of land use and the developmental and environmental consequences this may have.
H I S TO R ICAL BACKGROUND
Since the beginning of the twentieth century, population density in Sumatra has
increased by migration from Java, both spontaneous and government sponsored. A
clear gradient in population density occurs from the south (Lampung province) to
the middle (Jambi, Riau provinces) of the island. Although most land in Sumatra is
considered to be government “forest land,” a substantial part of this land is no longer under forest cover, and the amount of “forest damage” is correlated with population density at the provincial level, with Riau and Jambi provinces at the lower end
of the spectrum and Lampung at the higher end. Because many smallholder farmers practicing slash-and-burn appear to do so because they lack feasible livelihood
options, the development of sustainable, labor-intensive land use practices that are
viable alternatives to slash-and-burn could discourage deforestation.
The major part of the island of Sumatra was still under forest cover in 1932
(Van Steenis 1935). Forest conversion by that time had taken place mainly in coastal
zones (especially in Aceh, West Sumatra, Bengkulu and Lampung provinces), close
to the major rivers in the eastern peneplain (especially the Musi River in south
Sumatra and the Batanghari River in Jambi), and areas involved in the tobacco
(Nicotiana tabacum L.) and rubber (Hevea brasiliensis [Willd. Ex A. Juss.] Muell.Arg.) plantation booms in the late nineteenth and early twentieth centuries in north
Sumatra. Forest conversion by 1982 had affected most of the remaining forest in
Lampung and south Sumatra but not in Jambi (MacKinnon 1982).
This changed with the completion of the Trans-Sumatra highway and associated transmigration projects in the early 1980s. The asb benchmark areas in Jambi
are thus located in an area where forest conversion along the major rivers took place
before the 1930s but that otherwise remained mostly under forest cover at least
until the early 1980s. The north Lampung benchmark area abuts one of the few
forest patches left in the Lampung–south Sumatra part of the eastern peneplain.
The Forest Margins of Sumatra
293
I N D O N E SIAN FOREST L ANDS
In the 1980s, “Agreed Forest Use Categories” were established on all state forest land
in Indonesia. Under this system, forest land is categorized as follows:
• National parks and conservation forests: These are areas in which nature conservation gets priority.
• Protection forests: This class is defined mainly on the basis of slope and protects
water supplies for downstream sites.
• Limited production forests: Only collection of nontimber forest products is
allowed in this category, which is intended to provide a buffer zone around conservation or protection forests.
• Production forests: Here the Indonesian Selective Logging System is supposed
to be followed. Under this system, only a few large-diameter trees are harvested per
hectare, followed by a 30-year regrowth period before the next logging operation, to
secure sustained harvest with little loss of biodiversity. In practice few (if any) logging
concessions have met this target. Forest damage in the concessions is much larger than
anticipated because of a combination of logging of more trees than allowed (using
inefficient techniques that unnecessarily damage the remaining forest) and the use
of forest land for other purposes by large-scale forest squatters following the logging
roads. Production forest can be divided into limited production forests with stricter
regulation on timber use and nonconvertible production forests.
• Convertible production forests: These are forests officially targeted for conversion to other land use, including industrial timber estates (hutan tanaman industri,
hti), transmigration projects, and plantations of oil palm (Elaeis guineensis Jacq.),
sugar cane (Saccharum officinarum L.), and other crops. The total areas in the different
categories are shown in table 13.1.
Because any conversion of primary forest entails a significant decline in biodiversity, conservation reserves always have an important potential role in biodiversity conservation. In Sumatra, efforts to conserve large national parks tend to concentrate on
mountain areas (such as Kerinci Seblat National Park and the Gunung Leuser Park),
while little of the rich lowland forests has been protected effectively. Allowing some
use of highland park areas while protecting more of the lowlands probably would
increase conservation efficiency while allowing the same number of people to achieve
a similar level of livelihood (van Noordwijk et al. 1995). For Sumatra as a whole, 6.6
percent of the original forest is protected in reserves; this equates to 16 percent of the
forest that remained in 1982 (MacKinnon 1982). The montane or submontane forests have a better protection status than average, and the mangrove and swamp forest
are most endangered.
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National Perspectives
Table 13.1 Areas in the Different Categories of Forest Landa in Indonesia, April 1999
Category
Area (million ha)
Percentage
Park and reservation forests
Protection forests
Limited production forests
Nonconvertible production forests
Convertible production forests
Total
20.62
33.92
23.17
35.32
8.08
121.11
17.02
28.01
19.13
29.16
6.67
100
This refers to state forest land rather than to the actual vegetation.
Source: Santoso (1999).
a
Forest classification may have little bearing on the situation on the ground because
there is often confusion over the exact location of boundaries. Both protection and
production forest categories show the same relationship between forest damage and
population density in Sumatra (van Noordwijk et al. 1995). Only the national parks
are well protected.
L A N D U SE IN THE ASB BENCHMARK SITES
The asb Indonesia consortium has focused on benchmark areas in the forest margins
of Jambi in the central part of Sumatra and the deforested and degraded lands with
higher population densities found in the southern part of the island, close to Java,
with its high population densities. Figure 13.1 shows the main ecological zones of
Sumatra and the benchmark areas.
Ja m b i
Two sites in Jambi province were chosen for detailed characterization by the asb Project. The Bungo Tebo site is a dissected peneplain of acid tuffaceous sediments, and the
elevation is generally less than 100 m above sea level. The Rantau Pandan site is 100
to 500 m above sea level and represents the piedmont zone, which was formed mainly
by granite and andesitic lava. Soils in Bungo Tebo are predominantly ultisols, deep,
well drained, very acid, and of low fertility. Soils in Rantau Pandan are more varied
and complex—ranging from shallow to very deep, moderate to fine texture, and well
to moderately excessive drained—but they are also very acid and have low soil fertility.
Both Jambi sites average seven to nine wet months (more than 200 mm rainfall) and
less than 2 dry months (100 mm rainfall) per year, with annual rainfall of 2100 to
3000 mm. Forestry and the rubber-processing industry (crumb rubber) contributed
99 percent of the exports from the province in 1993. In the rubber industry, small-
The Forest Margins of Sumatra
295
Figure 13.1 Agroecological zones of Sumatra and with asb benchmark sites indicated (van Noordwijk
et al. 1995).
holder rubber plays a crucial role. The total area of rubber cultivation in Jambi in 1993
was 502,642 ha, of which only 3447 ha was planted with high-yielding varieties under
intensive management; the rest was jungle rubber (rubber agroforests). About 64 percent of the land in Jambi is categorized as state forest land. However, forest status often
was declared long after local communities had settled there. In practice, a large part of
the forest land is used for rubber agroforests and other forms of agriculture.
After the completion of the Trans-Sumatra highway in the 1980s, Jambi became
a popular migrant destination. The asb studies indicate that more than 25 percent of
spontaneous migrants came between 5 and 15 years ago, and almost 40 percent came
less than 5 years ago; more than 80 percent of spontaneous migrants came from Java,
and less than 20 percent came from other parts of Sumatra.
Almost every smallholder household interviewed in the asb surveys in Jambi is
engaged in agriculture. Less than 10 percent of households and spontaneous migrants
engage in nonagricultural activities. This is in strong contrast to transmigrants.
Although agricultural activities are the main occupation of transmigrants, 75 percent of these households reported nonagricultural work (in trading, services, and paid
labor). Most household heads did not complete primary school; the figure exceeded
70 percent for each site and was as high as 95 percent for the sample of local people
in Bungo Tebo.
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National Perspectives
Lampung
The peneplain of northern Lampung, Sumatra, was chosen to represent the landscape
degradation that can follow forest conversion if intensive food crop production is
pursued on these soils. Of the benchmark sites, only the Pakuan Ratu subdistrict in
north Lampung has no forest left, except for an industrial timber plantation or hti
(production forest). All other forest remnants have been converted into agricultural
areas or are too small to be included in the statistics.
The spontaneous movement of people between Java and Lampung, and additional efforts by the government during various periods in the twentieth century, are key
to understanding its landscape dynamics. Government-sponsored transmigrants generally have found the lowland peneplain soils unsuitable for their crop-based systems.
Only in depression and valleys, where paddy fields could be created, has agriculture
become a major source of their livelihood. Otherwise off-farm labor has had to provide the income that the remaining population of the area had; a substantial number
of transmigrants left the area in the first few years. This exodus may have accelerated
as conditions worsened because of drought and the national financial crisis; eleven out
of thirty households interviewed in 1993 had left the village when a repeat survey was
done in 1998 (Elmhirst et al. 1998).
Some migrants settled of their own accord, despite the hardships in the area,
including the second generation of the government-sponsored transmigrants, for
whom there is no land in the village. Spontaneous migrants tend to use agricultural
systems intermediate between the local system and the Javanese food crop–based system, with a greater emphasis on tree crops.
The indigenous Lampung people, who live along the rivers, still have their semipermanent food crop production on flooded riverbanks, but two decades ago they
stopped the extensive shifting cultivation of the lowland peneplain. Along the rivers,
they still have old jungle rubber gardens on the margin of Sumatra’s rubber domain.
Recently there has been renewed interest in rubber production, but as a whole the
indigenous Lampungese now aim to secure their livelihoods outside agriculture (Elmhirst 1997; Elmhirst et al. 1998).
The research site of Krui is on the west coast of Lampung province (across the
mountainous Bukit Barisan range), where a narrow coastal strip has had a long history of settlement but little immigration over the last century. Here an extraordinary
form of agroforestry was developed by local farmers about a century ago, the Shorea
javanica–based damar agroforests (De Foresta et al. 2000). International organizations and national partners led by asb formed the Krui team’ that helped in obtaining
government recognition for the value of this land use system as property rights (Fay
et al. 1998). This work culminated in 1998 in the signing by the minister of forestry
of a decree creating a special class within state forest land, Kawasan Dengan Tijuana
Istimewa (“Zone with Distinct Purpose”) granting the local community tree tenure in
The Forest Margins of Sumatra
297
perpetuity and the right to fully manage state forest land, preventing outsiders from
gaining access to that land.
A S B H y p otheses for Indonesia
The key hypothesis underlying phases I and II of the asb project in Indonesia is that
intensifying land use as an alternative to slash-and-burn can simultaneously reduce
deforestation and poverty (van Noordwijk et al. 2001). In phase I, the research program was designed to characterize selected benchmark sites and identify and prioritize research following the asb global guidelines. In phase II, the research program
was designed to better understand how the Indonesian government and donor agencies could balance global environmental objectives with economic development and
poverty reduction. Although conversion of primary forest has the major effect on
biodiversity and carbon stocks, the resulting land uses also matter a great deal for the
supply of these global public goods. Measurements of differences in environmental
consequences of the various land uses provide the basis for quantifying major tradeoffs
involved in land use change.
The asb surveyed the five main agricultural land uses in the Jambi benchmark
areas:
• Wet rice fields (sawah). Except for local farmers in Bungo Tebo (who reported
none), households typically have one wet rice (Oryza sativa L.) or paddy field. The
average size of wet rice plots is 0.31 ha for the sample of transmigrants and 0.68 ha for
spontaneous migrants in Bungo Tebo, compared with 0.84 ha for the sample of local
people in Rantau Pandan.
• Upland fields (ladang). This category includes both the shifting cultivation
rotation of food crops followed by fallow, and upland fields that will be—or already
have been—planted with perennials such as rubber. Local people and transmigrants
both average about one plot per household. Spontaneous migrants have more upland
plots (1.6 per household), and their upland fields are bigger (1.6 ha on average, compared to less than 1 ha for other groups).
• Perennial plots including agroforests (kebun). As just noted, perennial plots also
begin with intercropping of upland food crops, but the primary objective is establishment of tree crops such as rubber agroforests (the main land use for these sites), various fruit species, and (recently, in Rantau Pandan) cinnamon (Cinnamomum burmanii [Nees] Bl.). Local people in Bungo Tebo typically have two perennial plots (mainly
rubber) per household, with plots averaging 3.6 ha each. Spontaneous migrants at
this site have somewhat fewer plots (1.8 per household), but their plots are bigger on
average (4.3 ha per plot). Transmigrants reported an average of 1.4 plots per household and an average size of only 1.8 ha per plot. Surprisingly, data from the sample of
local people in Rantau Pandan yielded averages similar to those of the transmigrants
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National Perspectives
in Bungo Tebo. This probably reflects underreporting of plots located on state forest
land.
• Bush fallow (belukar). Bush fallow comprises two categories. Semak—land covered by grasses, shrubs, and small trees—is the first fallow stage. The second stage,
belukar tua, often resembles secondary forest; land is covered by larger trees and may
even include old rubber trees that no longer are productive. In Rantau Pandan, sample
households reported an average of 1.7 bush fallow plots with an average size of 1.5
ha, whereas in Bungo Tebo the number of plots per household is somewhat lower
(1.2–1.3 plots) but the average plot size is larger (1.6–2.8 ha).
• Home gardens (pekarangan). Home gardens, comprising a variety of annuals
and perennials used for many purposes, are cultivated intensively by transmigrants
and spontaneous migrants but are less used by local people.
The asb study of land use change in the 1982 to 1996 period showed that jungle
rubber is the predominant farming system in the Jambi area. In a 1982 vegetation
map, large areas were indicated as “mosaics of rubber and shrub” or “mosaics of rubber
and forest.” On 1992 and 1994 satellite maps, however, the major part of the rubber
complex is indicated as “old secondary forest.” Whether this change is a true maturation of the jungle rubber system or a result of the coarser scale of the 1986 map is not
clear. Farmers said that jungle rubber is inherited from generation to generation and
seldom rejuvenated because of limited access to better planting material, loss of potential income while waiting for the new plantation to become productive, and wild pigs
disturbing plants (Hadi et al. 1997). Farmers replace jungle rubber only after production has become very low and when they need land for their food crops. Plots of rubber, cinnamon (traded as cassiavera), or both range from 0.5 to 4 ha per household.
Since 1999, a pilot project from the Department of Forestry, Hutan Rakyat
(“community forest”), has been carried out in the community’s bush fallow. About 50
ha of this belukar was given to families to be cultivated with durian (Durio zibethinus
Murr.), cinnamon, surian (Toona sinensis [A. Juss.] Roem), and sengon (Paraserianthes
falcataria [L.] I. Nielsen) as agroforests. Planting material also came from the project,
which recommended a slash-and-mulch system without burning. It is a first step in
the government’s recognition of the role of local people in managing the forest. If this
project succeeds, it may be a good basis for future programs.
No agricultural land use consistently harvests products without putting management efforts into maintenance of the system, so all judgments of sustainability
depend on a specified management regime and on farmers’ efforts to overcome obstacles. Land-clearing techniques play an important role. The effects of improper landclearing methods are observed even 8 to 10 years after the land has been cleared, and
especially when the overall soil fertility has drastically declined. Improved understanding of people’s interactions with forests is fundamental to development of effective
options for sustainable management for forested lands. The asb’s research project in
Indonesia has assessed which land use options are agronomically sustainable (Weise
1998a, 1998b; chapter 6, this volume).
The Forest Margins of Sumatra
299
A set of field-level criteria and indicators was used to evaluate the sustainability
of a range of land use systems that can follow forest conversion (van Noordwijk et al.
2001). Natural forest can be used as a starting point for all land use types. Synthesis
of sustainability indicators showed that most land use systems considered have one or
more aspects that need attention, but most of these stay within the range of solvable
problems at the farm level. The various tree crop systems appear to be freely convertible to each other, but extensive rubber agroforests will change in character once the
seedbank of original natural vegetation is depleted and the site is out of reach of seed
dispersal. The cassava–Imperata cycle has a number of associated issues, such as maintaining a nutrient balance, which are so serious that they probably cannot be resolved
at the farm level within the current constraints (Weise 1998a, 1998b; chapter 6, this
volume).
A S B ’s R e search Activities and Major
R e s e a rc h F indings
Major findings in phases I and II of asb activities are as follows:
• No surveyed households practiced shifting cultivation in the classic sense (van
Noordwijk et al. 1995).
• All households, whether local farmers, government-sponsored transmigrants,
or spontaneous migrants, use slash-and-burn methods for land clearing (van Noordwijk et al. 1995).
• The most common land use system in the Jambi benchmark site is clearance of
logged-over or secondary forest or old jungle rubber to plant upland rice mixed with
rubber trees; in the second year upland rice or other food crops may be grown, but the
emphasis is on the tree crops.
• Most of the existing rubber agroforests in Jambi are old and have low productivity. To get sufficient income, a large area is needed. Currently, land for rubber
expansion is very limited; most of the forested land that is seen as potential areas for
rubber expansion by local people is already distributed by the government to projects
and therefore is off limits.
• The most common land use system in the north Lampung benchmark site is
clearance of secondary (or logged-over) forest or shrub fallow vegetation to plant food
crops or sugar cane. Recently, however, interest is growing in converting the land to
better-adapted and more profitable tree crops in the form of rubber, oil palm, or fastgrowing timber species. Such tree-based systems can accommodate short-term needs
for food production.
• Vertebrate pests (wild pigs and monkeys in the forest margins, rats on the
degraded lands) are perceived as major constraints in cultivating food crops. Wild
pigs are also a threat to young rubber plants and deter farmers from investing in more
expensive higher-yielding rubber planting material.
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National Perspectives
• Soil fertility constraints are most obvious on the peneplain sites where transmigrant farmers have attempted continuous food crop production. Aluminum toxicity,
phosphorus deficiency, and rapid depletion of soil organic matter means that continuous food crop production is not possible without substantial inputs of fertilizers.
Many of the current high-yielding crop varieties also need lime.
• North Lampung has more frequent, more pronounced dry seasons than the
rest of Sumatra. These are a limitation for several tree crops, including hybrid coconut
(Cocos nucifera L.) and various fruit trees. These dry periods also entail a fire risk and
tend to maintain Imperata grasslands.
• Logging concessions in Jambi have affected large areas of primary forest in the
piedmont and the peneplain zone; logging roads encourage an inflow of spontaneous
migrants who usually plant rubber. Thus, rubber expansion may prevent the regeneration of logged-over forests and speed up permanent forest conversion.
• The transmigration program can have two results: Where villages are successful, they attract a spontaneous influx of people from Java. Where they do not succeed,
they became a source of spontaneous migrants, who either search for more fertile land
in the forest margins or go to urban areas.
• Land tenure in the transmigration areas is recognized officially, whereas that in
the local villages is based mainly on customary law (adat); land disputes are common
where the two tenure systems overlap.
• Conflict over forest land use occurs when current regulations and policies are
declared after settlers have occupied the forest or when new settlers occupy forest land
where such regulations are not effectively implemented.
• As much as 59 percent of the above-ground carbon stocks were removed by
forest fire, and about 97 percent of unburned trees were removed from the plots.
Changes in soil carbon stocks were small (Murdiyarso et al. 1997).
• The methane oxidation capacity of upland soils under trees (which partly offsets methane emissions in other land uses, such as paddy rice fields) declines with soil
compaction (Murdiyarso et al. 1997; chapter 3, this volume).
• Nitrous oxide emissions appear to be related to the temporary abundance of
soil mineral nitrogen or the amount of nitrogen cycling through the system (Davidson
et al. 2000). At certain times during the year and during the land use cycle fluxes from
forests are higher than those from other land uses and vice versa. No consistent relationship between land use and net emissions of nitrous oxide over a system’s lifespan
has yet been found (Tomich et al. 1998; Davidson et al. 2000).
• Alternative land uses at the forest margins differ in their potential for conservation of above-ground biodiversity, with a range of alternatives falling between the
extremes of the smallholder’s complex agroforests and large-scale plantation monoculture.
• All tree-based alternatives appear to be agronomically sustainable.
• Because of the currency collapse in 1997, profitability of many tree-based
systems has increased substantially, which boosts incentives for forest conversion by
smallholders and large-scale operators alike.
The Forest Margins of Sumatra
301
• There may be tradeoffs between potential profitability and above-ground biodiversity in tree-based production systems, but this must be verified.
• Potential profitability of some tree-based alternatives for smallholders (such as
rubber agroforestry with higher-yielding rubber varieties) appears to be comparable to
large-scale oil palm estates, but this also must be verified.
• Smallholders must address some important institutional questions to enable
widespread adoption of profitable agroforestry alternatives.
L E S S O N S LEARNED
Forest-derived land uses differ significantly in their ability to substitute for specific
functions of natural forests (De Jong et al. 2001). Because of the multiple objectives
of production and environmental services of forests, deforestation must be viewed as
a multidimensional phenomenon. Sometimes this policy problem can be simplified
with tradeoff analysis.
The Sumatra case shows that agroforestry solutions help alleviate poverty but
that they may speed up rather than slow down forest conversion as their profitability
attracts migrant farmers and thus reduces biodiversity (Tomich et al. 2001).
The rapid spread of rubber as a smallholder crop in Sumatra since the beginning of the twentieth century and of smallholder oil palm in the late 1990s have
contributed to large-scale forest conversion, to the point that there is very little
lowland primary forest left. The logging concessions, especially those of the 1960s
to 1980s, followed by an inflow of spontaneous settlers with rubber-based agriculture, have completed the conversion. Murdiyarso et al. (2002) show that the labor
absorption of rubber agroforests can be high (providing a decent living to population densities of the order of sixty people per square kilometer), similar to that of
oil palm, indicating that rubber agroforests so far are our best bet for integrating
biodiversity and profitability of land use. If possible, however, segregating land into
full protection status with more intensive agriculture in the remaining land might
be superior (Van Schaik and van Noordwijk 2002). The returns to labor for logging
in the presence of roads are so high that labor-intensive agroforestry as such can
never compete with forest destruction, and a combination of social or governmentbased rules for protecting forests and labor-intensive, profitable land use systems
is a prerequisite for forest protection (van Noordwijk et al. 1995; Tomich et al.
2001). Efforts to develop land use alternatives and policy options to pursue global
environmental objectives (biodiversity conservation and carbon sequestration) are
futile without consideration of agronomic sustainability and environmental services
at other scales, objectives of farmers and policymakers at various levels, and weaknesses in markets and other institutions that influence the adoptability of land use
alternatives by smallholders.
Tenure, institutions, trade policies, and macroeconomic shocks affect a household’s livelihood options and thereby either reduce or intensify further deforestation.
302
National Perspectives
This policy and institutional environment also has a powerful effect on the natural
resource management decisions made by people at the forest margins.
Ongoing collaboration, contact, and presence of national and international
members of the research team are essential for real impact on policy and technology
options. Building effective multidisciplinary teams to study complexities of land use
change is feasible but involves high costs.
F U T U R E RESEARCH NEEDS
Scientists active in the asb Indonesia team identified future research needs:
• Examine a wider range of tree-based best bets regarding their environmental,
agronomic, and economic impacts and feasibility of adoption (Williams et al. 2001).
• Gain a better understanding about the relationships between above-ground
and below-ground biodiversity, production sustainability, and potential profitability
(Murdiyarso et al. 2002).
• Expand the assessments of sustainability from plot-level agronomic issues to
include environmental externalities at the landscape level, including watershed functions.
• Complete the landscape transect by expanding the present focus on the peneplains and piedmont agroecological zones to include the montane zone and coastal
swamps.
• Study more intensively the underlying causes of fires, policy issues, and technological alternatives to alleviate such catastrophic fires and smoke problems as happened in 1997 and 1998.
• Analyze how macroeconomic shocks affect land use change, environmental services, poverty, and household food security.
• Verify the potential environmental, social, and economic benefits of a smallholder-based development strategy as an alternative to large-scale plantation monoculture.
C O N C LUSION
Indonesia still has large forest areas, and conversion to other land uses is rapid. The
transformation from primary to secondary forest is caused largely by timber extraction, with traditional shifting cultivation playing a smaller role.
Although a part of the deforestation resulting from slash-and-burn is linked to the
poverty of people living at the forest margins, the conditions necessary for increased
productivity of agroforestry and other land use systems to reduce poverty and reduce
deforestation are not sufficiently well understood.
The Forest Margins of Sumatra
303
The asb’s study of the present land use systems has revealed that all tree-based
alternatives to slash-and-burn appear to be agronomically sustainable.
In developing alternative land uses and policy options that address global environmental objectives (biodiversity conservation and carbon sequestration), agronomic sustainability, and other environmental services, we must continue to consider the objectives of farmers and policymakers at various levels and weaknesses in
markets and other institutions that influence the adoptability of land use alternatives
by smallholders.
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the slash-and-burn cultivator in north Lampung and Bungo Tebo. pp. 191–229. In M.
Van Noordwijk, T.P. Tomich, D.P. Garrity, and A.M. Fagi (eds.) Alternatives to Slash-andBurn research in Indonesia, Rep. no 6. ASB–Indonesia.
Ketterings, Q.M., T. Wibowo, M. Van Noordwijk, and E. Penot. 1999. Farmers’ perceptions
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and carbon balance in slash-and-burn practices. pp. 35–58. In M. Van Noordwijk, T.P.
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Environmental benefits and sustainable land-use options in the Jambi transect, Sumatra,
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14 The Forest Margins of Cameroon
James Gockowski
IITA Humid Forest Research Station M’Balmayo, Cameroon
Jean Tonyé
IRAD Yaoundé, Cameroon
Chimere Diaw
CIFOR Humid Forest Research Station M’Balmayo, Cameroon
Stefan Hauser
IITA Humid Forest Research Station M’Balmayo, Cameroon
Jean Kotto-Same and Rosaline Njomgang
IRAD Yaoundé, Cameroon
Appolinaire Moukam
IRAD Deceased
Dieudonné Nwaga
Université de Yaoundé I Yaoundé, Cameroon
Téophile Tiki-Manga
IRAD Yaoundé, Cameroon
Jerome Tondoh
Université d’Abobo-Adjame Cameroon
Zac Tschondeau
World Agroforestry Centre-Cameroon Yaoundé, Cameroon
Stephan Weise
IITA Humid Forest Research Station M’Balmayo, Cameroon
Louis Zapfack
Université de Yaoundé I Yaoundé, Cameroon
T
he Congo Basin encompasses the world’s second largest contiguous rainforest after the Amazon and includes six countries: Congo–Brazzaville,
Congo–Kinshasa, Gabon, Central African Republic, Equatorial Guinea, and
Cameroon. Deforestation rates for the Congo Basin were estimated to be
1.14 million ha/yr (0.6 percent/yr) (fao 1997), compared with 1.08 million ha/yr (1.0 percent/yr) for Indonesia and 2.55 million ha/yr (0.5 percent/
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National Perspectives
yr) for Brazil. Unlike Brazil and Indonesia, where large-scale agricultural operations
play an important role, much of the deforestation in the Congo Basin is attributed
to smallholder agriculturalists using extensive slash-and-burn techniques. Thus rural
population density plays a significant role in determining the extent of closed-canopy
forest and the stock of woody biomass in a given area, but the relationship is far from
linear and depends on a complex assortment of factors. The low productivity of slashand-burn agriculture, in combination with rapid population growth, results in the
continual extension of the forest margins, with a highly fragmented boundary in the
Congo Basin, as shown in figure 14.1.
An Alternatives to Slash and Burn (asb) benchmark site in Cameroon was chosen to represent the Congo Basin (figure 14.2). Cameroon’s forest resources, one of
the country’s greatest riches, have played and continue to play a significant role in
its economic growth and development. In the 1950s, 1960s, and 1970s, conversion
Figure 14.1 Satellite photo of the Congo rainforest region showing the risk of deforestation (the lighter
the color, the higher the risk), with a close-up of the Cameroon benchmark site. Note the fragmentation
of the forest margins (Ericksen and Fernandes 1998).
The Forest Margins of Cameroon
307
Figure 14.2 The asb forest margin benchmark area in southern Cameroon showing the Yaoundé,
M’Balmayo, and Ebolowa blocks. Shaded area is the humid tropical zone of West and Central Africa.
Most of the West African zone is deforested.
of approximately 500,000 ha of moist forests to smallholder coffee (Coffea spp.) and
cocoa (Theobroma cacao L.) agroforests resulted in equitable economic growth, averaging 3 to 4 percent. In more recent years, timber exploitation has overtaken coffee
and cocoa production as the most important economic activity in the moist forests.
Cameroon is now the leading African exporter of tropical timber, with more than
$270 million in annual export sales.
One of the most rapid changes affecting the agricultural sector throughout the
Congo Basin has been the tremendous growth in urban populations. Both Douala
and Yaoundé have grown at annual rates of more than 6 percent in the years since
independence, which means that the number of urban consumers is doubling roughly
every 12 years. The most important single market in the benchmark site is Yaoundé,
with more than a million inhabitants. The largest food commodity markets in terms
of value are plantain (Musa paradisiaca L.), cassava (Manihot esculenta), and cocoyam
(Xanthosoma sagittifolium [L.] Schott). Approximately 80 percent of the total tonnage
sold in Cameroon of these three crops is produced in the humid forest zone (Ministry
of Agriculture [minagri] survey statistics, 1984–1990).
The rate of deforestation in Cameroon is estimated by fao (1997) at 0.6 percent,
with about 108,000 ha of closed-canopy forest lost annually. About half of the annual
clearing is for agricultural purposes, the remaining largely for logging (Ekoko 1995),
although shifting cultivators follow logging roads, making this distinction hard to
quantify. Across the benchmark site, 25 percent of the total land area was estimated to
be in some agricultural use (including fallow fields) in 1994 (Gockowski et al. 1998).
308
National Perspectives
A poor nation, Cameroon has little choice but to develop its forest resources.
From the standpoint of government policy, the critical question is whether Cameroon’s tropical forests will be turned into sustainable agricultural and forestry production systems or “mined” into a state of degraded vegetation. The benchmark site in
Cameroon spans a resource use and population density gradient and also encompasses
significant variation in market access, soils, and climate. This site allowed the asb
Project to explore the opportunities for and constraints to income generation, sustainable land use, and environmental protection in the area and in the end to assess which
land use systems are the most promising and what policies must be in place to ensure
their adoption.
B E N C H MARK SITE CHARACTERIZ ATION
The benchmark site in southern Cameroon was divided into three blocks that were
distinguished according to intensity of resource use and population density as follows: the Yaoundé block, with 30 to 90 people per square kilometer; the M’Balmayo
block, with 10 to 30 people per square kilometer; and the Ebolowa block, with up
to 10 people per square kilometer (figure 14.2). At the southern end is the Ebolowa
block, with low population density and large tracts of intact primary forest (59 percent of land cover). Cocoa is the primary source of farm income, with food crops
grown mainly to meet subsistence needs. There is still significant reliance on natural
resource–based activities, such as bushmeat hunting and gathering of nontimber forest products. Local agricultural markets are comparatively small, agricultural input
markets are underdeveloped, and road infrastructure is poor and not maintained. At
the northern end is the Yaoundé block, with most of the land in some phase of an
agricultural cycle; only 4 percent of land remains covered by primary forest. Proximity
to the Yaoundé market, better-developed market institutions, and rural infrastructure
has led to a process of agricultural intensification, diversification, and commercialization.
N at u r a l Ecosystems
The dense, humid forests comprising the benchmark area are classified as GuineoCongolian forests (iucn 1992), which are subdivided into four categories (table 14.1).
This distinction is important in terms of biodiversity richness. The climax vegetation
in the benchmark site is the dense semideciduous forests characteristic of the Yaoundé
block, extending south into the M’Balmayo block, and the dense, humid Congolese
forest in the southern reaches of the M’Balmayo block, extending to the Ebolowa
block. In addition, there are small pockets along the western border of the Ebolowa
and M’Balmayo blocks that are characterized by the biologically diverse, moist, evergreen Atlantic forest. The highest biodiversity is found in the Barren forests of these
The Forest Margins of Cameroon
309
Table 14.1 Extent of Humid Forest Ecosystems in Cameroon and Their Main Characteristics
Guineo-Congolian Forests
Area
(million ha)
Submontane forest
0.377
Dense, humid evergreen
Atlantic forest, including
Barren forests
5.400
Dense, humid Cameroon–
Congo forest
8.100
Dense, humid
semideciduous forest
4.000
Total
Main Characteristics
Lies between 800 and 2200 m in elevation, increasing
diversity of epiphytic flora with elevation, Prunus
africana found at higher elevations. Biology of
ecosystem not well known compared with lowland
and Afromontane forest systems.
Very high floristic diversity with marked endemism,
with affinities to Atlantic South American forests.
Center of diversity of genera Cola, Diospyros, Garcinia,
and Dorstenia. Gregarious associations of
Caesalpinaceae characterize the Barren forest subtype.
Intermediate in floristic diversity between the Atlantic
forest and the semideciduous forest, flora affinities
with Congo basin forests. Important ecosystem for
large primates and elephants.
Often fragmented, subject to fire during the dry
season, particularly rich in commercial timber species
although less biologically diverse than other tropical
forest types. Close to the savanna zone.
17.877
Source: IUCN (1992).
Atlantic forests, with many of the plants being endemic. More than 200 plant species
have been counted in a 1000-m2 transect, which purportedly represents higher plant
diversity than any other forest in Africa or Southeast Asia and is greater than that of
most South American forests (Garland 1989). The Barren forest is a center of genetic
diversity for important genera such as Cola spp., Diospyros spp. (ebony), and Garcinia
spp. (which includes the bitter cola). The Cameroon–Congo and the semideciduous
forests, which are widespread in the southeast of the country, have a much lower rate
of plant endemism than Barren forests.
C l i m at e and Soils
Rainfall in the benchmark site is typical of equatorial rainforest climates with no pronounced dry season. Annual precipitation ranges from 1350 to 1900 mm and has a
bimodal rainfall distribution. There is increasing precipitation from the north to the
south.
The red and red-yellow soils in the benchmark area fall mainly into the broad soil
classes of acrisols (ultisols) and ferrasols (oxisols). Three soil profile classes—Yaoundé
(Rhodic Kandiudults, pH 5.2, 35 percent clay), M’Balmayo (Typic Kandiudults,
310
National Perspectives
pH 6.5, 25 percent clay), and Ebolowa (Epiaquic Kandiudults, pH 4.8, 42 percent
clay)—form a north–south fertility gradient, with lower fertility in the southern part
of the benchmark area (Gockowski et al. 1998). Though generally acidic and infertile,
these soils are suitable for cocoa, coffee, oil palm (Elaeis guineensis Jacq.), and rubber
(Hevea brasiliensis [A. Juss.] Muell.-Arg.) production if clay content is high enough
(more than 20 percent).
L A N D U SE SYSTEMS
Farms in the benchmark site are small and fragmented (Gockowski and Baker 1996)
The average number of annual crop fields per household is slightly more than four;
62 percent of the households in the Yaoundé block had five to eight distinct field
types, compared with only 28 and 44 percent in the M’Balmayo and Ebolowa blocks,
respectively (Gockowski et al. 1998). The mean annual land cover in productive agricultural land use, not including the fallow vegetation, was 2.6 ha per household in the
Yaoundé block, 2.4 ha in the M’Balmayo block, and 3.6 ha in the Ebolowa block.
Nine land use systems were evaluated by the asb Cameroon team (table 14.2).
These systems included two food crop systems, four variants of the widespread cocoa
agroforests, two variants of hybrid oil palm plantations, and community-managed forests. With the exception of community-based forest management, all systems began
with slash-and-burn of the primary forest, secondary forest fallows (10–15 years), or
short-duration Chromolaena odorata (L.) RM King and H. Robinson fallows (2–4
years). The environmental parameters measured were carbon stocks, plant diversity,
Table 14.2 The Nine Predominant Land Use Systems in the Cameroon Benchmark Site
Meta–Land Use System (Cameroon land use system)
Fallow Type and Duration (yr)
Crop–Fallow Rotations
Mixed peanut–cassava
Mixed melon–plantain–cassava
Chromolaena (4)
Secondary (9–23)
Complex Cacao Agroforests
Extensive cacao and tree fruits
Extensive cacao, no fruit harvests
Intensive cacao and tree fruits
Intensive cacao, no fruit harvests
Secondary (9–23)
Secondary (9–23)
Chromolaena (4)
Chromolaena (4)
Simple Agroforests
Extensive oil palm
Intensive oil palm
Forest
Community-managed forest
Secondary (9–23)
Chromolaena (4)
The Forest Margins of Cameroon
311
and soil fauna diversity; the results are detailed in chapters 2, 4, and 5, respectively,
and in Gillison (2000). Agronomic sustainability issues are presented in chapter 6 and
the socioeconomic aspects and farmer concerns in chapter 17.
F o o d C rop–Fallow Rotations
Mixed peanut (Arachis hypogea L.)–cassava production is the most important food
crop system in the benchmark site. It largely guarantees household food security and
in areas with market access generates marketable surpluses. The two dominant crops
are peanut and cassava. Other crops interplanted in lower densities include cocoyam,
maize (Zea mays L.), leafy vegetables (Solanum scabrum Miller, Corchorus olitorius L.),
and plantain. The crops are normally planted after slashing and burning a 4-year
Chromolaena odorata fallow and are grown for 2 years before reverting back to the
Chromolaena fallow. Women manage this system, which is typically planted twice: in
March–April and again in August–September, given the bimodal rainfall distribution.
Surplus revenues tend to be controlled by women.
The mixed melon (Cucumeropsis mannii Naudin)–plantain (Musa × paradisiaca)–
cassava cropping system that follows long fallows is the third most common land use
system (70 percent of households) after the peanut–cassava and cocoa agroforests. Melon, plantains, maize, and cocoyams are planted after slashing and burning of 9- to 23year-old secondary forest fallows and grown for 2 years, after which they are put back
into another secondary forest fallow. Although both male and female labor is used,
the cash income from this field tends to be controlled by men. This land use system
became a major commercial alternative for cocoa farmers when cocoa prices collapsed
in 1989. Together these systems account for an estimated 75 percent of all cropland in
the benchmark area (Gockowski et al. 1998).
C o coa Agroforests
The second most important system and the largest source of household agricultural
revenues are the cocoa complex agroforests, or jungle cocoa. Men mainly manage
these systems, although in certain instances widows also manage such systems. They
cover 3.8 percent of total land area in the benchmark site and represent 48 percent of
total agricultural land use. An estimated 75 percent of households in the benchmark
site have these systems, with the mean area per household estimated at 1.3 ha (Gockowski et al. 1998).
Cocoa is established after slashing and burning of a primary forest, a long-term
secondary forest fallow, or even a short-term Chromolaena fallow. There are four variations on this land use system, based on the level of crop intensification and the duration of the preceding fallow. It begins with a food intercropping of plantain, cocoyam,
and melon in the first 3 years. Cocoa is grown for about 25 years. Sometimes jungle
312
National Perspectives
cocoa is established through gap and understory plantings in forests without the food
cropping stage. Descriptions of cocoa agroforests can be found in Duguma et al.
(2001) and Gockowski and Dury (1999).
E x t e n s i ve Cocoa Systems
Extensive cocoa systems, jungle cocoa, are characteristic of the less populated areas
and usually are established in primary forest or old secondary fallows. Cocoa is grown
under the shade of taller trees that include fruit trees such as avocado (Persea americana Miller), mango (Mangifera indica L.), African plum (Dacryodes edulis [G. Don f.]
H.J. Lam), and mandarin oranges (Citrus spp.). These fruit trees provide substantial
income in areas that have good market access. The two major pest constraints for
cocoa production in southern Cameroon are cocoa blackpod disease (caused by Phytophthora megakarya Brasier and Griffin) and capsids (plant-sucking insects belonging
to Miradeae family). Without pesticides these pathogens typically reduce yields by
more than 50 percent. Fungicide use is about half of that used of the intensive cocoa
systems, and there is no insect control. Many producers with more intensive systems
shifted to these more extensive types when cocoa prices collapsed in 1989.
I n t e n s i ve Cocoa Systems
Intensive cocoa systems are characterized by higher levels of management, fungicides,
and insecticides. They tend to be in areas of more pronounced land pressures and are
associated with good market access. The system often is established after 4 years of a
Chromolaena fallow and intercropped with peanut, maize, leafy vegetables, plantains,
and cocoyams during the first 3 years of establishment. Although fruit trees are almost
always a component of cocoa agroforests, it is only in areas with easy market access
that they assume commercial importance because of their bulky nature and low valueto-weight ratio.
O i l Pa l m Pl antations
Palm oil has always been the most consumed edible oil in Cameroon. In rural areas
of the humid forest zone, most households are self-sufficient, relying on production
from the semidomesticated Dura variety of oil palm. The bulk of production for the
urban market comes from large-scale parastatal plantations (Cameroon Development Corporation, Palmol, and Société Camerounaise de Palmeraies) producing the
tenera hybrid (a cross between the Dura and Piscifera varieties). However, as urban
populations have increased, small-scale producers have also adopted industrial-type
plantation monoculture of the hybrid tenera variety in recent years. Oil palm trailed
cocoa, coffee, plantains, cassava, cocoyams, and dessert bananas, as measured by total
The Forest Margins of Cameroon
313
producer revenues (minagri, unpublished survey data, 1984–1990). The tenera oil
palm plantations are grown as a monoculture at a planting density of 143 trees per
hectare. Forested land or Chromolaena fallow is converted with intercropping of plantain, cocoyam, and melon during the first 2 years of oil palm establishment. There is
a 7-year establishment phase and a 25-year rotation.
C o m m u n i t y-Based Forests
It is currently illegal for a farmer to cut down and sell timber growing on his land even
if he has legal title to the land; however, he may harvest it for his own construction
purposes.
Commercial rights to timber belong to the state, with the exception of timber cut
for the landholder’s own use. The minimal economic incentives faced by farmers for
maintaining timber species on the landscape do not provide a competitive alternative
to slash-and-burn agricultural use. The 1994 forestry law has established a statutory
framework through which a village can gain communal commercial rights to timber
in community forests of 5000 ha. This tenure permits a community to legally harvest
and sell timber. Another concept of the community forest is found in the community’s dependence on the common property resources in forested land. The forest and
local institutions governing the exploitation of its natural resources (wild fruits, honey,
building materials, rattan, fish, game, and medicinal plants) are the defining parameters of this alternative concept.
O t h e r Sy stems
There are several other important land use systems that were not evaluated. These
include livestock, shaded robusta coffee (Coffea canephora Pierre ex. Fröhner) systems, large-scale industrial plantations of oil palm and rubber, horticultural cropping
systems, and various inland valley systems. The livestock sector is not well developed
in the benchmark site. Cattle grazing is practically nonexistent because of tsetse fly
(Glossina spp.) infestation, so there are essentially no planted pastures. Goats (Capra
hircus L.), tropical sheep (Ovis aries L.), swine, and poultry are raised in a free-range,
extensive fashion. Although robusta coffee systems are important in the Congo Basin,
this system is very limited in extent in the Cameroon benchmark area. Industrialscale plantations of rubber and oil palm are found around Mount Cameroon in the
Southwest Province and along the coast in the South Province but were not included
in the study largely because they are not expanding their operations and are no longer
a driving force of deforestation. Input-intensive monocultures of horticultural crops
and maize for the fresh market are encountered in the Yaoundé block. The horticultural commodities tend to be high value compared with staple food crops and have
replaced cocoa as the most important source of revenues in many villages close to
Yaoundé.
314
National Perspectives
M A R K E TS AND INSTITUTIONS
Institutions and infrastructure are in general much better developed in the Yaoundé
block, where population densities are higher. Remote sensing estimates indicate a
rural road density in Yaoundé that is three times the density in the Ambam area of the
Ebolowa block. Institutional development is also more evolved in the Yaoundé block,
where traditional customary land tenure systems are evolving gradually toward individualistic, legally recognized land ownership characterized by cadastral surveys and
an increased incidence of land titling (iita, unpublished data, 1997).
Among the important institutional differences is the development in the Yaoundé
block of a fairly competitive marketing system for both outputs and inputs. Farmers
in this area generally have easy access to purchased inputs, which are heavily applied
to cocoa agroforests (fungicides and insecticides) and horticultural fields (fungicides,
insecticides, and fertilizers). In the rest of the benchmark site, farmers can spend more
than a full day in acquiring inputs.
M AC RO ECONOMICS
Sectoral and macroeconomic policy reforms since the late 1980s have had important
impacts on slash-and-burn agricultural systems. Most of these reforms occurred in the
cocoa and coffee sectors, with the state disengaging and liquidating the national marketing boards for these crops during this period. At the same time, fertilizer and pesticide subsidies (ranging from 60 to 100 percent) were removed. Most of these reforms
were driven through as part of a structural adjustment package with the World Bank
and the International Monetary Fund in an effort to help the Cameroon government
diminish internal and external deficits. Unfortunately, these reforms took place in
the context of and, indeed, were necessitated by an overvalued Central African franc
(fcfa) and depressed world commodity markets. As a result, cocoa and coffee producers in Cameroon faced historically low producer prices and, in response, neglected
their agroforests and shifted resources into the production of plantain, cocoyams, and
horticultural crops to make up for the declining profitability of coffee and cocoa.
This put significant additional pressure on the forest margins as new forest lands were
cleared and brought into annual food crop production (Gockowski et al. 2001).
T R A D E OFFS BET WEEN GLO BAL ENVIRONMENTAL
B E N E F I TS, AGRONOMIC SU STAINABILIT Y,
A N D P ROFITABILIT Y
From an environmental perspective only the community forest system retains the bulk
of the biodiversity and carbon stocks, whereas the tree-based systems lose about 60
The Forest Margins of Cameroon
315
percent of the carbon and the crop–short fallow systems lose 95 percent of the carbon
(chapter 2, this volume). The tree-based systems, including both intensive and extensive cacao systems, and long-term fallows retain high levels of biodiversity, although
the high values in the intensive cacao system include many weedy species (chapter 4,
this volume). Given the mosaic of fallow fields on the landscape needed to support the
long rotation, biodiversity probably is not greatly threatened by this system. The treebased systems still serve as a rich form of nontimber forest products, including game,
fuel, and medicines (Kotto-Same et al. 2000). The short-term fallow systems and oil
palm plantations are depauperate in comparison.
In summary, the cacao and long fallow systems have the highest global environmental benefits. Likewise the agronomic sustainability of these systems is high,
although pest concerns can threaten the cacao production (chapter 6, this volume).
Although negative environmental concerns are associated with most land use systems
in the forest margins because they have much less biodiversity and carbon storage than
the forest, the starting point of a particular land conversion process has enormous
importance in whether there will be gains or losses in terms of global environmental benefits. The rehabilitation of degraded short fallow–crop rotation systems with
perennial systems will increase the current carbon stocks and biodiversity levels and is
a clear objective of the asb Program.
Adoption
No matter how positive the parameters for agronomic sustainability or the environment may be, small-scale farmers are likely to adopt such systems only if they improve
farmer livelihoods without entailing an extraordinary amount of risk. Endeavors to
promote the systems with environmental benefits and sustainability must specifically
consider the profitability, labor needs, food security, and equity biases. Additionally,
livelihoods in the forest margins of Cameroon are sustained by a complex set of productive and social activities conducted in the context of a risk-reducing kinship network of social relationships. Some land use systems entail high institutional costs and
support services, which can limit adoption. Some of these issues and constraints to
adoption are discussed later in this chapter (table 14.3); details are provided in KottoSame et al. (2000), Gockowski et al. (2001), and chapter 17.
P ro f i ta b ilit y
Profitability is arguably the most important criterion for adoption in a commercialized agricultural economy. In land surplus economies, adoption potential is more
appropriately measured by the financial returns to labor than by returns to land. On
this basis, intensive cocoa with fruit and oil palm from forest fallow were considered as
high profit, the extensive and intensive cocoa systems with fruit as medium profit, and
316
National Perspectives
Table 14.3 Ordinal Ranking of Land Use Systems by Adoption Criteria
Rank
Adoption Criteria
Social Profitability
(return/ha)
Financial Profitability
(return to labor, $/d)
Labor Intensity
(lowest to highest)
Household Food
Security (kcal/ha)
1
Intensive cocoa with
fruit
Oil palm in forest
fallow
Extensive cocoa
without fruit
2
Oil palm in forest
fallow
Intensive cocoa with
fruit
Intercropped food
in long fallow
3
Intensive cocoa
without fruit
Extensive cocoa
with fruit
Oil palm in short
fallow
Intercropped food
in short fallow
Extensive cocoa
without fruit
Intercropped food
in long fallow
Extensive cocoa with
fruit
Intensive cocoa
without fruit
Oil palm in short
fallow
Intercropped food in
short fallow
Intercropped food in
long fallow
Extensive cocoa
without fruit
Extensive cocoa
with fruit
Oil palm in short
fallow
Oil palm in long
fallow
Intensive cocoa
without fruit
Intensive cocoa with
fruit
Intercropped food
in short fallow
Intercropped food
in short fallow
rotation
Intercropped food
in long fallow
rotation
Intensive cocoa with
fruit
Extensive cocoa
with fruit
Oil palm in short
fallow
Intensive cocoa
without fruit
Oil palm in long
fallow
Extensive cocoa
without fruit
4
5
6
7
8
Source: Kotto-Same et al. (2000).
the mixed groundnut, oil palm from short fallow, melon and plantain, and extensive
cocoa without fruit systems as low profit. However, this static view of profitability
masks the volatility that characterizes agricultural and world commodity markets. The
recent episode of low cocoa prices (1988–1996) had a significant impact on the profitability of the sector, with prices received being halved.
Labor
Labor intensity is an important determinant of adoption in areas with labor scarcity and
poorly developed labor markets. The most labor-extensive systems are the Cucumeropsis–
plantain field and the extensive cocoa systems, whereas the mixed groundnut field and
the intensive cocoa systems used two to three times the labor (table 14.4). The oil palm
systems were intermediate between the two types of cocoa systems.
F o o d S e curit y
The capacity of land use systems to contribute to food security is a concern of both
household and national decision makers. In areas where rural food markets do not
The Forest Margins of Cameroon
317
Table 14.4 Labor Needs and Food Entitlements for the Alternative Land Use Systems
System
Scale (ha)
Food Entitlements During Productive
Stage
Labor
Protein
Establishment Operating Calories
Micronutrients
(000 kcal/ (kg/ha/yr)
Phase
Phase
(d/ha/yr)
(d/ha/yr) ha/yr)
SF, food intercrop
LF, food intercrop
SF, intensive cocoa
with fruit
SF, intensive cocoa
without fruit
FOR, extensive
cocoa with fruit
FOR, extensive
cocoa without fruit
SF, oil palm
FOR, oil palm
Community-based
forest
0.25
0.25
1.3
NA
NA
148
115
44
97
3803
780
1463
1.3
135
95
1.3
136
1.3
1
1
5000
54.8
10.9
19.8
Yes
Yes
Yes
762
11
Yes
46
1143
15
Yes
123
43
442
6.2
No
209
196
71
73
762
442
11
6.2
Yes
Yes
SF, short fallow; LF, long fallow; FOR, agroforest.
Source: Adapted from Kotto-Same et al. (2000).
exist or function properly, most households rely on their own production. The mixed
food crop field is the household granary and is planted throughout the benchmark
area. This is also true for the Cucumeropsis–plantain field, although in some areas this
system is planted for commercial reasons. In terms of calorie and protein supply, the
mixed groundnut field was the highest of all the systems and the cocoa system with
fruits was high largely because of the significant contribution of avocado and African
plum, with high fat contents (table 14.4). Palm oil is an important component of the
diet in Cameroon, a fact that is recognized by government trade policy prohibiting oil
palm exports during the dry season, when production declines, to ensure urban supply at low prices. Oil palm is also the major source of cooking oil in the Congo Basin,
and many producers cite meeting household oil demand as a factor in their adoption
decision.
M a rk e ts
In a liberalized economy, the functioning of market institutions is a key determinant
to adoption of intensive production systems. Cameroon producers are still adapting
to the new economic reality of liberalized input markets that came about in the early
1990s. In the densely populated areas of the benchmark area and the Congo Basin,
318
National Perspectives
markets and communication infrastructure tend to be better developed, resulting in
more commercially oriented and diversified agriculture. Better functioning, more
competitive markets in conjunction with better infrastructure result in significantly
lower marketing margins and, consequently, higher producer prices and lower input
prices. Still a major handicap for producers throughout the benchmark area is the near
nonexistence of capital markets in rural areas. When an unexpected financial crisis
arrives (e.g., illness, death), liquid assets that might have been set aside for purchasing
agrochemicals are spent, and production suffers.
The market institutional needs (inputs, outputs, labor, and capital) of the intensive cocoa systems are the most dependent on the reliable supply of agrochemicals.
Intensive cocoa systems with fruit trees also presume good access to urban fruit markets. The oil palm systems depend on fertilizer inputs and the multiplication and distribution of hybrid palm varieties. Oil palm production also entails further transformation, ranging from artisanal methods necessitating almost no capital investment,
small-scale oil presses with intermediate levels of capital investment, and large-scale
industrial processing with high capital needs.
L a n d Te nure
Land tenure is still largely by customary right, although there has been an evolution
toward more individualistic ownership patterns and away from communal control of
land in the high population areas. There is a much higher incidence of official land
disputes in these areas. However, there is little official titling of land, in part because of
the high transaction costs of doing so (estimated at more than $500 at current prices).
Land tenure and property rights raise issues for systems requiring access to new forest
lands for planting perennial tree crops. In certain parts of the benchmark area, this
land remains in the domain of the larger family clan, and use is negotiated within the
clan unit. These issues do not affect the planting of perennial systems on existing fallow lands for which customary tenure rights at the household level are robust.
E x t e n s i on Services
The move toward intensification necessitates a viable and dynamic research and extension system capable of responding to farmers’ demands and generating appropriate
solutions. Intensive knowledge generation and diffusion is perhaps most critical for
the oil palm systems because the production of commercial hybrid oil palm is just
being introduced at the household level. A World Bank–sponsored training and visit
extension program in Cameroon (and in many other African countries) is intended
to reinvigorate a moribund extension service, although there are serious questions
about the success of this type of extension system. The encouraging development of
local farmer groups, farmer federations, and grassroots nongovernment organizations
The Forest Margins of Cameroon
319
(ngos) throughout southern Cameroon offers an additional avenue for combining
the knowledge generated by agricultural research and rural development.
E qu i t y
There are two major types of equity issues surrounding these alternative land use systems. The first is that of an increasing concentration of wealth and land holding. This
is a concern mainly for oil palm systems, where economies of scale in both production
and transformation seem to exist. In the long run, there is a question as to whether
smallholder production, which typically relies on family labor, can remain competitive with large-scale plantations. To the extent that these systems are also meeting
subsistence needs, the issue of economies of scale is less likely to impede the continued
adoption of these systems.
The other equity issue is the intrahousehold distribution of returns. Women
manage only mixed groundnut fields, and there is significant risk that women might
not receive their share if an expansion of the other land use systems were to occur.
Any strategy therefore should focus attention on improving cropping systems and
crops that are traditionally grown and marketed by women. Such improvements
could deflect the pressure to clear more forested land as populations grow and would
increase women’s revenues and social prestige. In the perennial tree crop systems, the
labor divisions must be further studied and, if possible, innovations developed to
ensure that women also benefit. Indications are that women receive a more equitable
share of fruit tree revenues than is the case for the cocoa component in the fruit–cocoa
agroforests found in the Yaoundé block (Dury 1999).
E X PE C T ED TRENDS IN L AND USE, IMPACTS,
A N D R E S EARCH NEEDS
F o o d C rop and Fallow Systems
Despite the negative environmental aspects and lack of agronomic sustainability of the
short-fallow, mixed food cropping system, efforts to replace this slash-and-burn system
are likely to fail given its central role in the social fabric of village life and the underdeveloped rural food markets of the Congo Basin. A significant proportion of the food
crops in the urban markets comes from this field system and generates an important
portion of women’s income. Increased demand for food from the urban areas indicates
that this system will increase in the future; therefore efforts should focus on improving
the productivity and sustainability of this system. To do so, soil degradation and crop
protection urgently need to be addressed. Crop breeding should focus on increasing
varietal tolerance to pests, diseases, and the many mineral deficiencies that characterize the soils of the basin. The introduction of improved varieties should be combined
320
National Perspectives
with integrated soil fertility management that combines the use of organic materials,
including improved fallow species, with the strategic use of fertilizers, particularly in
areas with developed input markets and good rural roads.
The long fallow food cropping system, although higher in carbon and biodiversity, requires land-abundant households, which limits its extent and adoption in areas
where population pressures are high. In areas where land is still abundant and populations are low, market infrastructure and institutional development are poor and hence
profitability is low. Low profitability could be ameliorated by an increase in agricultural
research targeting the three principal crops—melon, cocoyam, and plantain—which
have been largely neglected by agricultural research to date. Given the current population growth rate of 2.9 percent and the fact that plantains are the most important
commercial food crop in the humid forest zone, this system probably will continue to
increase in area. However, increasing population in rural areas and demand for food
from the urban sector are likely to lead to a decline in the fallow period of this system
and the eventual shift to the short-fallow food system. This shift would have high
environmental costs, with increased loss of biodiversity and carbon.
There is the Pandora’s box issue of increasing land and labor productivity in the
two food crop systems and whether this would lead to an expansion in this land use
type and increase deforestation (Angelsen and Kaimowitz 2001). This valid concern
may be assuaged by broad-based productivity increases in land use systems. Achieving this difficult task will entail a balanced agenda involving multi-institutional collaboration on the research and development of the major components of the Congo
Basin farming systems. The Pandora’s box issue also is a function of the size of output
markets and the elasticity of demand. If they were small, as is likely, then an increase
in productivity of these systems probably would deflect pressure to clear new forest. Both of the crop–fallow rotational systems are likely to remain important across
the Congo Basin and should be the focus of land-saving and labor-neutral or laborsaving interventions. Abating the environmental loss associated with extensive slashand-burn systems will entail both alternative perennial systems capable of sustaining
rural livelihoods and more productive slash-and-burn systems. The latter would permit farmers to convert land currently in these crop–fallow systems to what are arguably more agronomically sustainable perennial tree crop systems.
C ac ao - Based Systems
The intensive cocoa system with fruit trees planted to short fallow is among the most
profitable of the systems; in addition, its high carbon stocks and biodiversity make it
a desirable land use alternative at the forest margins. Elevated productivity of this system will depend on an increase in labor and pesticide input. Institutional constraints
in many areas of the Congo Basin, such as the unavailability of inputs and scarce
labor availability, are likely to limit the extent of this particular land use system. The
fruit tree component contributes significantly to the profitability of this system, but
The Forest Margins of Cameroon
321
because of the low value-to-weight ratio of fruit, it results in increasing transportation
costs with distance to market. The underdeveloped road infrastructure of the Congo
Basin will also constrain the development of this multistrata complex agroforestry
system. The most extensive extrapolation domains for this particular system are likely
to lie in the more densely populated, humid forest areas of West Africa (Ghana, Côte
d’Ivoire, Nigeria, and Togo), where cocoa is already a significant cash crop and market
institutions are more robust. Extensive cocoa systems with fruit trees planted in forest
land are moderately profitable, but the institutional and labor constraints attached to
cocoa production are less than those of the intensive cocoa systems. However, urban
market access will limit the extent of this system.
Rather than the preferred expansion of these cocoa systems at the expense of
degraded lands, the area in cocoa probably declined between 1990 and 1996 as farmers abandoned production in the face of low world and national prices. Most of these
plantations were old and had low productivity. Labor was reduced in both extensive and intensive cocoa systems and was largely reallocated to long fallow–intercrop
rotations focused on the production of melon, plantain, and cocoyams. There was a
negative environmental impact (loss of biodiversity and carbon stocks) as this annual
cropping system replaced secondary forest. The decline in cocoa profitability and the
reduced foreign exchange earnings during this period had major repercussions on economic growth and probably led to a higher incidence of poverty in the humid forest
zone. Despite the decline, cocoa still remains the dominant land use system and the
major source of household revenues.
An overvalued fcfa also can affect farmer returns. If the fcfa is overvalued by
50 percent, the producer’s return to labor would be lower in the cocoa system than
the slash-and-burn systems. Before the devaluation in 1994, the overvalued fcfa was
a source of heavy implicit taxation for producers of tradable commodities such as oil
palm and cocoa. Overall, the effect of the overvalued fcfa was to favor food production systems over export crops such as coffee, cocoa, and oil palm.
Given current and expected supply and demand conditions in world cocoa markets, it is likely that cocoa prices will remain robust in the foreseeable future, which
should ease the negative trend seen in recent years. The higher prices of 1997 and
1998 (550–650 fcfa vs. 350 fcfa in 1996) increased farmer incentives and, subsequently, input use in cocoa systems. Input markets, which have been liberalized since
1992, are better developed today than they were 5 years ago, reinforcing the trend
toward more intensive cocoa systems. A large proportion of this increase probably will
come from a shift from extensive to intensive production systems. Whether there will
be significant new conversion to either extensive or intensive cocoa production is difficult to predict. Indications from the robusta coffee sector in Cameroon and the cocoa
sector of Côte d’Ivoire are that there is likely to be some expansion in new planting
area (Akiyami 1988; Gockowski 1994).
The impact on the environment of an increase in new plantings will depend on
whether these systems are targeted to degraded short-fallow land or forested land.
Given the choice, the producer normally will choose the latter in an effort to capture
322
National Perspectives
the forest rent (Ruf 1998). Policy incentives should be targeted toward the creation
of perennial crop systems in degraded lands. This strategy should be accompanied by
an increase in the productivity of food cropping systems to compensate for a reduction in the area of the food crop fallow system. To encourage the intensification of
cocoa production, policies to promote the agricultural input supply sector should be
considered.
One of the major problems in the Cameroon cocoa sector is the low level of plant
resistance to cocoa blackpod disease, caused by Phytophthora spp. The efforts under
way at Institut de Recherche Agricole pour le Développement (irad) to evaluate, test,
and disseminate resistant varieties, working with the increasingly vital grassroots farmer organizations, must be strongly supported. The ecological relationships between
biodiversity, management practices, and productivity are an area for future research,
especially in the species-rich cocoa agroforests. Specifically, interactions between entomopathogenic fungi, plant functional attributes, ant and termite mosaics, applications
of copper fungicides, and the population dynamics of Phytoptera spp. are important
for strategic research.
O i l Pa l m
The oil palm system planted on forest land is the most profitable of all land use systems; carbon stocks are similar to those of the other tree-based systems, but there is
little doubt about the lack of plant and faunal diversity in these monoculture systems.
The overall contribution to the rural economy of smallholder oil palm production
from 1986 to 1990 was still minor, with the exception of the area around Edea-EsekaMakak in the westernmost portion of the benchmark area. Whether the small producer movement, which has been fairly robust in recent years, continues will depend on
several critical institutional issues. Postharvest processing must normally occur within
48 hours of harvest. There are likely to be scale economies in both time and space,
which will warrant some type of collective action in the processing phase. If smallholder systems are to expand significantly, improvements in the distribution and supply of these hybrid plants will also be needed. Currently there are only two suppliers:
the national research institute and parastatal industrial oil palm plantations charging
200 to 250 fcfa per germinated seed and wielding significant market power. The ability of small producers to compete with large-scale producers in the face of economies
of scale in production and processing is questionable in the long run. Economies of
scale could outweigh the advantage of the lower opportunity cost of family labor, driving producer prices and profits too low. Mitigating in favor of the expansion of the
smallholder sector is the perception by producers that unlike cocoa, palm oil and its
multiple products (oil, wine, and building materials) can also be used to meet direct
household needs in consumption. As for cocoa and coffee, the net environmental
impact of an expansion of oil palm systems will depend on whether they are planted
in short fallow or forest land. The most likely candidate is for farmers to choose the
The Forest Margins of Cameroon
323
latter, again because of the fertility rent they capture. When planted to forested land,
these systems tend to decrease the total carbon and biodiversity in the landscape.
C o m m u n i t y-Based Forests
Communal management of forest lands for commercial timber production and other
purposes received positive scores on all environmental and sustainability accounts,
although the sustainable commercial harvest of tropical timbers has proved to be an
elusive goal for many timber companies. The impact of sustainable logging practices on biodiversity also remains a question. The financial incentives attached to the
commercial harvest of timber could deter the practice of slash-and-burn agriculture.
However, there are numerous institutional and regulatory issues that a community
must resolve before it can obtain legal community tenure to timber. As currently written, the state-imposed regulatory framework requires more than twenty procedures
to obtain community tenure. There are also many collective action problems associated with distribution of benefits, sanctions, and free-ridership. Overcoming these
obstacles is a necessary condition if slash-and-burn farming communities are to limit
their agricultural activities to areas outside the community forest.
L A N D U S E SHIFTS, POLICY, AND ACTION
The framework developed for promoting alternative land use systems that are best
bets in terms of minimizing the tradeoffs between the environment and livelihoods
is based on existing systems. It encompasses the notion that households’ needs in the
humid forest zone typically are met through the integration of multiple crops and
tree-based systems, complemented by an array of activities including monocropping,
hunting, and gathering of nontimber forest products, providing a food, cash, and
social basket (figure 14.3). Current land use is shaped by household structure and
preferences, land and natural resource configurations, and the institutional makeup of
property and access rights in the rural landscape. It is unlikely that policy or technological innovation, however radical, would drastically alter those patterns and trends.
To improve the performance of expanding land uses and lift the obstacles to the development of other promising systems, our best option is to mimic farmers’ integrative
strategies while improving individual components of the system. We have called this
approach an improved mosaic within a strategy of integrated landscape management.
It is within that realm that technological innovation and improvements can be targeted for research, development, and policy efforts. A summary of the anticipated
benefits and losses associated with expected land use shifts is provided in table 14.5.
In areas of low population density, policies and practices should be geared toward
sustainable use and conservation of forested land to improve rural livelihoods and
environmental values. Policy-led intensification at the household level should focus on
324
National Perspectives
Figure 14.3 Household (hh) food, cash, and social basket as provided by the landscape mosaic of forest
and land use systems (Kotto-Same et al. 2000).
the two major components of farming systems: perennial crop agroforests and slashand-burn food crop production systems. Policies to encourage agricultural intensification are needed to overcome the divergence between the farmer’s valuation of forest
woody biomass resource as a fertility input and the societal value of a forest (timber
revenues, environmental values, and intrinsic value). For primary production alternatives to develop their full potential and create positive spinoffs for the overall development–conservation nexus in the forest, a host of interconnected initiatives must be
taken simultaneously or at least in a close sequence. Research indicates that revenue
increase for nontimber forest products is not consistent with resource preservation
unless the pace of species domestication is accelerated and information is adequately
disseminated to farmers (Ndoye and Kaimowitz 2000). Cocoa plantations would fit
naturally with endeavors related to the marketing and domestication of nontimber
forest products . Market mechanisms such as eco-ok labeling and the fair trade
movement are attempting market corrections for coffee and cocoa produced in an
environmentally benign fashion, albeit on a small scale and largely without the support of large donors. These efforts should be expanded for increasing revenues in these
systems.
The development of postharvest systems and periurban enterprises is also necessary to reduce postharvest losses and to benefit from the added value of small-scale
rural businesses and the proximity of expanding urban markets. Such enterprises
could generate rural wealth while deflecting some of the anthropic pressure on land
Table 14.5 Summary of Beneficiaries, Benefits, and Risks or Losses Associated with the
Expansion of Different Land Use Alternatives
Oil Palm Systems
Context and assumptions:
Strong spread of oil palm systems in the benchmark area.
Dominant smallholder monocrop system based on the industrial Société Camerounaise de Palmeraies
model (oil palm associated with food crops in the first 3 yr, followed by monocropping).
Beneficiaries
Benefits
Risks and Losses
Farm s
Social elites
Palm oil industry
Government
Urban consumers
Regional consumers
Increased revenues from sales
(men mainly) and artisanal
processing (women included)
Increased revenues, prestige, and
money
Greater profits (privatization in
process), steady supply at
favorable prices
Increased tax revenues
Mitigation of the monocrop Soca
model
Better supply of oil palm
products and byproducts
Urban bias through seasonal
quotas on exports (hidden tax)
Reduced women’s influence on
decisions.
Loss of common property forest
lands.
Concentration risk against
capital-poor s.
Producers’ dependency on the
industry (tied loans for inputs).
Rural producers’ loss of market
advantages and revenues during
low season.
Some loss in environmental
benefits.
Options: Develop and promote improved varieties; mitigate environmental, concentration, and gender
biases through mosaic. Develop small-scale processing. Maintain seasonal quotas for resource
preservation.
Cocoa Systems
Context and assumptions:
Likely to remain stable in present conditions, following structural adjustment programs that cut
subsidies and state services. Recent increase in world and producer market prices for cocoa might
result in a renewal of the activity but not in its dramatic upscaling throughout the landscape.
Increase in the quantity and quality of cocoa production could result from appropriate policies and
the availability of affordable technologies to control pests, particularly blackpod fungal disease.
Beneficiaries
Benefits
Risks and Losses
Farm s
Farmer organizations
Government
International cocoa sector
and chocolate industry
Global consumers
Increased revenues
New occupational niche in
marketing sector
Fiscal benefits and rents
Biggest profit from the sector’s
growth
No control on world prices;
producer is mainly a price-taker.
Intensification might induce bias
against poor farmers.
Information and position in
regulatory bodies still weak.
Lower benefits than desirable
under present international terms
of trade.
Further conditions: Fair international share of the cost of environmental conservation. Internal
policies supporting plantation renewal and the strengthening of farmer organizations. Increased
representation of farmers in regulatory bodies.
Table 14.5 (Continued)
Community Forestry: Scenario 1
Context and assumptions:
No change in present policy orientations.
Weak implication of traditional tenure institutions.
1994 Forestry Reform includes provisions for granting concessions to communities represented by
legal entities taken from a pool of farmer organizations, which acquired legal status through the 1990,
1992, and 1993 laws on associations, common interest groups, and economic interest groups. These
organizations can play a strong proactive role in conservation and development. However, they do not
have the community mandates required in matters of tenure and devolution. Anthropological
institutions, such as lineages, clans, and village councils, which are not considered by the reform,
retain these functions.
Beneficiaries
Position and Power
Benefits
Potential Risks and
Losses
Communities
Medium: little
information, can
participate but only
through legal entities
Strong: main beneficiary of
information asymmetries
Small tax and loggingrelated revenues
Loss of forest and
forest-related revenues;
risks of social
destructuration.
Conflicts harmful to
influence in
community.
Common initiative
groups as a potential
vehicle of vested
interests.
Low returns from forest
exploitation, loss of
agricultural lands,
weakening of
traditional authority.
Nonsustainable
logging, small size of
s (5000 ha).
Loss of environmental
and economic benefits.
Local elites
Farmer
organizations
Farm s and
lineages
National and
international
logging interests
National public
interests
Government
Global
consumers
Rent capture of
logging-related revenues
and taxes
Intermediate: can be
recognized as legal entity;
low information and legal
limits to economic benefits
Weak: family institutions
not recognized as
legitimate stakeholders
Strong bargaining position;
have the technical and
financial capacity to fulfill
inventory and logging
requirements in s
Intermediate: limited
influence through s
and other private and
public bodies
Strong: retain main
decision-making power for
recognition, design, and
monitoring of s
Quick profit
Low-cost logging in
s
Loss of long-run fiscal
revenues, negotiation
failure.
Loss of global
environment benefits,
nonsustainable
consumer benefits.
Table 14.5 (Continued)
Community Forestry: Scenario 2
Context and assumptions:
Adoption of reform at implementation stage.
Empowerment of customary tenure institutions.
Flexible adaptation of criteria related to size of s.
Adaptive management plan that takes into account the relationship between forest and agricultural
cycles.
Beneficiaries
Position and Power
Benefits
Communities
Strong: can participate
through all institutions
and organizations
Balanced revenues from
agriculture, small-scale
logging, gathering and
domestication of
nontimber forest
products, use of other
natural resources; tax
revenues from logging
Local elites
Intermediate: benefit from
information but not
institutional asymmetries
Strong: can participate and
play a proactive role
Farmer
organizations
Farm s and
lineages
National and
international
logging interests
Strong: family institutions
recognized as stakeholders
Intermediate: have the
technical and financial
capacity to invest s, but
this influence is
subordinated to larger
community interests
National public
interests
Intermediate: some
influence through s
and other civil interests
Strong: main supervision
power in recognition,
design, and monitoring of
s
Intermediate: through
donors and international
agencies
Government
Global
consumers
Potential Risks and
Losses
Reinforced collective
action for poverty
alleviation and forestrelated alternatives
Increased welfare
More local
accountability and
economic discipline of
logging; sustainable
logging based on
genuine stakeholder
negotiation
Forest conservation and
increased availability of
forest-related products
Long-term economic
and environmental
benefits and fiscal
revenues
Gain of global
environment benefits at
sustainable consumer
prices
Higher short-term
transaction costs.
Loss of short-term tax
revenues.
328
National Perspectives
Table 14.5 (Continued)
Improved Food Crop and Long Fallow or Forest Fields
Context and assumptions:
Significant labor constraints restrict the possibility of a large portfolio of food crops and forest fields
per . Under present technological conditions, a large-scale spread of these systems is likely to
happen only with the multiplication of farm s, as a consequence of demographic growth.
These two types of fields are complementary within agricultural cycles.
Their improvement depends on research and technological innovation (e.g., short-fallow and
multistrata systems, integrated pest management, plant health management).
Beneficiaries
Benefits
Risks and Losses
Women for food
crops
Men for forest fields
Farm s in
general
National and
regional consumers
Increased revenues
from increase in
marketed surplus
Increase in farm
food security
Increased food
supplies and
improved regional
food security
Lack of marketing infrastructure and difficult market
access limit farmer incentives to intensify.
Small market size and inelastic demand lead to
decrease in farm prices and fall in farm revenues.
Increased profitability of extensive long-fallow systems
leads to an increase in resources allocated to this land
use system, increasing its relative extent and depleting
forest resources.
Enhanced rural technologies and increased
profitability of slash-and-burn farming along forest
margins lead to influx of rural migrants.
Marketing infrastructure remains underdeveloped.
HH, household; CF, community forest; NGO, nongovernment organization.
Source: Kotto-Same et al. (2000).
and forest. Oil palm systems are a natural candidate for these postharvest enterprises
because small-scale palm oil processing technology can be readily made available to
farmers at a large scale. The deflection feature of these off-farm alternatives cannot
be neglected as we try to mitigate the negative environmental impacts of any single
technological option.
In areas of high population pressure, annual crop systems must be made more
productive and sustainable. If this can be achieved, then it may be possible to put
aside land for specialized perennial systems (e.g., cocoa–fruit agroforests) and to protect pockets of forest to increase carbon stocks and maintain biodiversity across the
landscape. One policy instrument that the Cameroon government could consider is
to target new planting subsidies of both cocoa and oil palm systems to degraded short
fallow–crop rotational systems. Under these conditions, carbon would be sequestered,
and, at least in the case of shaded cocoa, biodiversity in the landscape would increase.
Farmers normally will choose to establish their plantations in long bush and forest
fallows when this type of land is disposable, to capture the fertility rent (Ruf 1998).
Since the Kyoto conference on global warming, discussion of carbon emissions trading between nations has focused some attention on perennial tree crop systems in the
tropics as a possible sink for carbon sequestration. A strong economic argument for
The Forest Margins of Cameroon
329
subsidizing production from agroforests can be made on the basis of the range of outputs that are not valued by markets (biodiversity, carbon sequestration, and watershed
functions). There is, of course, a major caveat: Perennial tree crop systems generate net
environmental benefits only when they replace degraded short-fallow lands.
A necessary element for policy-led intensification is strong local and national
institutions. A viable and dynamic research and extension system capable of responding to farmers’ demands and generating and disseminating appropriate solutions is
paramount. The overall capacity of the public sector in Cameroon was significantly
weakened by the across-the-board salary reduction that the government implemented
as part of its structural adjustment program. Without support for institutional development, the significant gains achieved in environmental and forestry policies since the
mid-1990s will remain little more than paper policies. Public sector capacity to provide a continuous stream of technology consistent with resource endowments generally is most effective when the political environment has encouraged the development
of farmer organizations (Binswanger and Ruttan 1978).
Changes in the institutional makeup of the research, development, and conservation sectors in Cameroon and Central Africa offer a great opportunity for the emergence
of a broad-based alliance. The decentralization reforms of the early 1990s have created
a favorable environment for community-based collective action. Thousands of grassroots organizations have acquired legal status and have formed large federations and
confederations of farmers. These organizations have started numerous initiatives and
are seeking collaboration with research institutions and ngos. These grassroots initiatives are a potentially important vehicle for accomplishing the bottom-up institutional
change so desperately needed to effect agricultural intensification in the Congo Basin.
In collaboration with the Consultive Group on International Agricultural Research
ngo committee, International Institute for Tropical Agriculture, irad, International
Center for Research in Agroforestry, and Center for International Forestry Research
have initiated talks with two dozen ngos and farmer federations about a platform of
action on common research and development priorities. This alliance could shape the
orientation of land use systems in a manner coherent with asb’s objectives and results
and develop an influence at both the community and state levels of decision making.
Given the global environmental services that would result from the adoption of best
bets, it must be stressed that the level of policy action or lobbying needed goes beyond
national states to include the contribution of global interests to the environmental,
economic, and social alternatives inherent to the asb program. This also will require
appropriate intervention at the appropriate level.
S U M M A RY AND CONCLUSION
In Cameroon, smallholder slash-and-burn agriculture is the major source of deforestation. Any proposed approach for addressing deforestation must start with agriculture. We argue for a proactive, policy-led effort to intensify both perennial and food
330
National Perspectives
crop systems to deflect further advance of the forest margin at the household level.
Any technology or policy innovation that increases the productivity of farming in
the humid forest region runs the risk that additional land and labor resources will be
allocated to that particular activity, increasing deforestation. Therefore, at the regional
and national level, policies should strive to limit rural migration to the forest frontier.
So far, in the Cameroon benchmark area, customary tenure institutions have been
sufficiently robust to prevent large-scale in-migration (Diaw 1997).
Such has not been universally the case, as in the large-scale rural-to-rural migration to the forested lowlands of the Littoral and Southwest Province from the densely
populated western highlands (Dongmo 1981). More research is needed to understand
the factors affecting migration so that better-informed policies can be devised.
At the national level, policymakers are concerned about food security issues and
maintaining adequate food supplies in urban areas. Interregional trade liberalization
should be encouraged, particularly across agroecological zones, to address these concerns. The countries of West and Central Africa might be better off concentrating
food production in savanna areas, which potentially have higher production at fewer
environmental costs than the humid zone, while promoting diversified perennial tree
crop systems to generate foreign exchange in the humid forest zone. The areas in the
world agronomically able to successfully produce cocoa, coffee, rubber, oil palm, and
other tree crops are limited compared with the areas that can grow maize (Zea mays
L.), wheat (Triticum aestivum L.), rice (Oryza sativa L.), and other staple grains. However, a large portion of the population of the Congo Basin lives in urban centers with
extremely poor links to these potentially productive savanna areas. Developing transport corridors could significantly reduce the intensification pressures around urban
centers in the humid forest zone and increase urban food supply.
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15 The Peruvian Amazon
development impe r at i ve s
and challenges
Douglas White
CIAT Pucallpa, Peru
Manuel Arca
INIA Lima, Peru
Julio Alegre
World Agroforestry Centre Lima, Peru
David Yanggen
Centro Internacional de la Papa Quito, Ecuador
Ricardo Labarta
World Agroforestry Centre Pucallpa–Ucayali, Peru
John C. Weber
Corvallis, Oregon
Carmen Sotelo-Montes
World Agroforestry Centre Lima, Peru
Héctor Vidaurre
World Agroforestry Centre Lima, Peru
T
he Amazon region occupies parts of seven sovereign nations and is
highly heterogeneous both biophysically and socioeconomically. The
Amazon of Peru is especially heterogeneous. For example, the forests in the
tropical Andes, a region in the western section of the Amazon, by virtue of
the nearby mountains, contain more biodiversity than those in other Amazon
regions. Exceptionally large numbers of endemic plants (up to 20,000) have
been identified in these forests, which are now considered a strong hotspot
candidate for conservation support (Myers et al. 2000). The varied topography (200–2000 m above sea level) and the wide range of annual rainfall
(1100–5000 mm/yr) provide conditions for very large numbers of different
species to thrive.
Alongside this biophysical heterogeneity is a broad array of socioeconomic and policy contexts. Multiple decision-making domains coexist in
The Peruvian Amazon 333
the region and sometimes overlap. For example, national administrative divisions
(e.g., municipalities) exist alongside the domains occupied and managed by indigenous populations that have their own decision-making processes. The combined
biophysical, socioeconomic, and policy heterogeneity lead not only to very different
resource use strategies and patterns by economic agents but also to a wide range of
environmental consequences. Therefore predicting the effects of policy changes on
land use patterns is complicated, and foreseeing related effects on the environment
is even more so.
Despite this multidimensional and interrelated context, developing the Peruvian
Amazon is imperative to the long-term growth of the country. Indeed, the region is
undergoing rapid change from increasing economic activity such as timber extraction, slash-and-burn agriculture, livestock production, mineral extraction, and fishing. Although a small human population now lives in the Peruvian Amazon (only
about 2.2 million people, or 9 percent of the country’s population), typical economic
activities are predictably land-extensive and may have severe consequences for plant
and animal biodiversity and the environment in general.
Nearly 60 percent of Peru’s national territory is in the Amazon region. Since
the 1980s, government policies such as tax breaks, subsidies, and road building
have attempted to speed development in this region as part of a national response
to general economic malaise and a growing population (Bedoya Garland 1987). By
some accounts, the economic gains associated with these policy actions have been
meager (Hecht 1993); by other accounts the gains have been more significant.
There is general agreement that the environmental effects have been large and
negative.
Yet systematic empirical assessments of the effects of land use change on economic
growth and the environment are largely absent. As a result, huge gaps in knowledge
limit the efficacy of policy initiatives. To fill some of these knowledge gaps, the Alternatives to Slash and Burn (asb) consortium in Peru undertakes, coordinates, and
integrates many research activities in the region. National and international partners
conduct both biophysical and socioeconomic research to understand why and how the
region is being transformed. Most importantly, lessons are distilled from this research
to guide and promote future development activities in the region.
Specific research themes of scientists in the asb consortium in Peru focus on soil
and nutrient management, farmer participatory research, environmental–economic
tradeoffs, tree genetic resource management, and improved germplasm of tree and
agricultural crops. Research also seeks to improve our understanding of the magnitudes and mechanics of pressing local and global environmental issues, including soil
degradation, greenhouse gas emissions, and biodiversity loss.
The two central objectives of asb research are to have impact at field level and
to generate knowledge, management strategies, and policy options that can be useful
outside the Peruvian Amazon. A mix of scientific and other research products, including capacity strengthening, are produced to meet these two objectives.
334
National Perspectives
U N D E R STANDING THE AMAZON: HETEROGENEIT Y
A N D C HANGING PAT TERNS OF RESOURCE USE
With the hope of earning a better living, settlers migrate to and about the Amazon
(Townsend 1983; Aramburú 1984; Barham and Coomes 1995). Yet after forested
land is cleared for agricultural use, soil fertility and associated bountiful harvests are
short-lived (Nye and Greenland 1960). To maintain production levels, farmers are
compelled to cut more forest (Ruthenberg 1976). Therefore there is an apparent tradeoff between preserving the environment and providing basic human needs. At the
crux of the environment–economic tradeoff is the fallow period, where vegetative
regrowth of 2 to 15 years becomes the nutrient supply for the next agricultural cycle.
Although purchased inputs, especially fertilizers, can increase and sustain yields, they
are prohibitively expensive for small-scale farmers. Moreover, extensive production
techniques are more cost-effective because a hectare of land can cost less than a 50-kg
bag of fertilizer (Holland 1999; White et al. 2001). Therefore land use options must
be developed with special regard to their financial feasibility and the resource constraints (land, labor, and capital) farmers face.
The Amazon region of Peru is markedly different from the rest of the country.
Cooler sierra (mountain) and drier coastal regions are distinct agroecosystems to the
hot and humid tropical forests of the Amazon. National policies must be tailored to
specific regions of the country. The Peruvian Amazon poses the greatest challenges to
policymakers. First, a majority of the national policymakers have little knowledge of
this isolated region. Second, the Amazon remains disconnected from the rest of the
country, especially the seat of political power and decision making in Lima. Therefore
effective policy implementation is difficult and costly in the Amazon. In part because
of complexity and costs associated with promoting development, the overall development objectives associated with the region have been pared back.
Despite the lackluster performance of organized settlement programs undertaken
when the region was envisioned as a breadbasket (Nelson 1973), Peru continues to
formally promote development in the Amazon. In the 1990s, the Peruvian government instituted a series of regional tax relief measures and fuel subsidies. The government also began permitting large tracts of Amazon forest to be logged by national and
foreign companies. Other natural resources, such as oil and gas, are being prospected
and extracted. Unofficial settlements commonly follow logging or mineral access roads
and often encroach into national forests and indigenous community lands. More generally, though, the potential effects of such national policies and settlements on longterm forest cover, the well-being of indigenous communities, or the economic welfare
of the region are not known.
The physical characteristics of the Amazon region are diverse, much like its famed
plant communities and animal populations. Topography and soils differ throughout the
region, ranging from fertile alluvial soils on riverbanks to nutrient-deficient, acidic soils
in the upland areas (Sanchez 1976; Denevan 1984; Padoch and de Jong 1992). There-
The Peruvian Amazon 335
fore broad generalizations regarding resource endowments or the suitability of agriculture cannot be made. To adequately capture a broad array of biophysical characteristics
and understand their roles in determining land use, asb activities take place at two sites:
a main benchmark area near Pucallpa and a second smaller site near Yurimaguas.
Pucallpa is located in the Department of Ucayali (figure 15.1), which borders
Acre, Brazil, to the east. The department corresponds to an area 80 percent the size
of El Salvador but has about 5 percent of that country’s population. Settlement of the
Pucallpa area began in the 1940s after construction of a road linking the Ucayali River, a major Amazon tributary, and the capital city of Lima. The current cropping and
ranching activity on any given piece of land typically is associated with the number of
years since the forest was originally cleared (Fujisaka and White 1998; Labarta 1998;
Smith et al. 1999). For example, the amount of area remaining in forest on farms is
inversely related to the time since it was first settled. In the more recently settled areas,
59 percent of the rural holdings remain forested, whereas in more mature settlements,
forest coverage decreases to 40 percent. Cattle ranches, which tend to dominate the
oldest settlements, have an average of 19 percent of their land in forest. Conversely,
the land area dedicated to pastures generally increases according to the age of the
settlement. The recent settlers have about 10 percent of their holdings in pasture,
compared with 19 percent on older farms. Cattle ranches have 66 percent of their land
in pasture (Smith et al. 1999). The stocking rate on traditional pastures is approximately 0.6 animal units (aus) per hectare. Land values are low, ranging from us$10
to us$200/ha depending on the quality of road access (Fujisaka and White 1998).
Political instability in the region in the 1990s caused cattle herds to decrease markedly. More than a third of the regional cattle herd was sold or stolen between 1990 and
1995 (Fujisaka and White 1998). The ensuing situation of low stocking rates in the
region has led to an oversupply of pasture plant biomass given the size of the regional
cattle herd. In some cases, pastures are so overgrown that they become flammable and
often permit fire to spread into the surrounding forest (White et al. 2001).
The Pucallpa region has bimodal rainfall pattern, with wet months of February
to May and September to November and dry months of June to August and December to January. As in many humid tropical regions, soil infertility is a major factor
affecting the production potential of agricultural systems (Nye and Greenland 1960;
Ruthenberg 1976). The basic soil constraints are low cation exchange capacity, soil
acidity, high aluminum saturation, and low nutrient stocks (particularly phosphorus,
nitrogen, and calcium). Soils include more favorable alluvial but less common riverine areas, where pH is about 7.7 and available phosphorus is 15 ppm, and the more
common well-drained upland areas of acidic (pH 4.4), low-phosphorus (2 ppm) soils
(Loker 1993). Invasive weeds are another factor influencing land use decisions, as
discussed later in this chapter.
The Pucallpa site offers two important research advantages. First, the ranges of
some key characteristics (e.g., rainfall amounts and patterns, and soil types) are quite
similar to those of other broad regions in the Amazon, including the asb research site
in Acre, Brazil (iica 1995). Thus, research outcomes can be compared with, and may
Figure 15.1 Landsat image showing the boundaries of the Pucallpa research site.
The Peruvian Amazon 337
Figure 15.2 Population growth in Yurimaguas and Pucallpa from 1960 to 1995 (inei 1997).
be applicable to, larger swaths of the Amazon basin. Second, approximately 50 years
of occupation by a steadily growing human population has led to a wide range of
deforestation patterns and land uses in this small area (17,000 km2, or 2 percent of the
Peruvian Amazon). Although only about 10 percent of the Peruvian Amazon was estimated to be deforested as of 1995, approximately 25 percent of forests in the Pucallpa
region had been cleared by then (iiap 1999). Therefore the Pucallpa experience may
offer an important window through which to view, understand, and help manage
future deforestation and land use patterns in other areas of the Peruvian Amazon.
The second site, Yurimaguas, adds geographic breadth and a longer-term research
context. The Yurimaguas site was home to the North Carolina State/TropSoils Collaborative Research Support Program, where experimental agronomic data have been
collected for nearly 30 years. It also provides an interesting comparison with Pucallpa
Table 15.1 Area in Different Land Use Systems, Length of Fallow Period, and Residence Time
of Migrants on Farms in Two Peru Research Sites
Average farm size, ha
Primary forest, ha
Fallow, ha
Annual crops, ha
Perennials, ha
Pasture, ha
Average fallow period
Migrants who arrived before 1960
Source: site characterization survey (Labarta 1998).
Yurimaguas
Pucallpa
23.6
8.5
9.4
1.9
0.8
3.1
3.6 yr
45%
28.7
9.5
8.2
1.6
2.3
7.1
3.2 yr
25%
338
National Perspectives
regarding migration in the Amazon. In 1971, Yurimaguas had approximately 20,000
residents, and within 14 years the population doubled. As of 2000, there were about
55,000 inhabitants in Yurimaguas, half of whom were living in rural areas. In contrast,
Pucallpa has grown at a much faster rate since 1971 (figure 15.2), and the population
has doubled in less than 10 years. Implications of the growing population are seen in
the rapidly changing land uses around urban centers. In part because of better market
access, land use systems in Pucallpa have shorter fallow periods, and larger areas of
cleared land are dedicated to perennial crops and pasture (table 15.1).
B I O PH Y SICAL RESEARCH
The biophysical component examines how different land uses are associated with
changes in biodiversity, carbon stocks, and greenhouse gas emissions. The asb also
seeks to identify geographic patterns of genetic variation in tree species. The ultimate
objective is to provide practical policy guidance for improved land management.
A b ove - Ground and Below-Ground Biodiversit y
Slash-and-burn creates spatially diverse sets of land uses that can complicate traditional methods of vegetation classification and limit their usefulness for characterizing above-ground plant biodiversity. Two different approaches were used to assess
the effects of land use on above-ground biodiversity. Gillison and Alegre (2000)
used a plant functional attributes approach to measure the diversity of plants (chapter 4, this volume). Fujisaka et al. (2000) used an ecological approach, combined
with an ethnographic component that addressed farmers’ understanding of and
preferences for different plants, including weeds. A third study of below-ground
animal biodiversity examined soil macrofauna in different land uses and their links
to soil quality.
For the species richness and plant functional types approach, twenty-one 40- by
5-m transects were used to sample a range of land use types and chronosequences in
Yurimaguas. The highest species and functional type richness were recorded in a forest logged 40 years previously, 20-year abandoned gardens, and 2-year successional
fallows dominated by plants from the Asteraceae or the daisy family. Multistrata agroforests showed moderate degrees of species and plant functional attribute richness,
and improved pastures were least rich, with only four plant species and functional
types (Gillison and Alegre 2000). Initial analysis of the data revealed close associations between plant-based classifications, land use type, and vegetation succession
but generally weak correlations between these same classifications and soil physical
and chemical characteristics. The most significant correlations of soil attributes arose
between vegetation structure, plant functional attributes, and ratios of richness of
plant species to functional types.
The Peruvian Amazon 339
Fujisaka et al. (2000) examined the sequence of interactions between farmers and
ecosystems to examine how farmers manage biodiversity. In samples taken across a
chronosequence in Pucallpa, 235 plant species were recorded in the forest, of which
143 were not found in any successive land use. Plants not existing in the forest colonized both cropland fields and fallow areas. In total, 595 species were identified across
the land uses. Changes in plant communities generally reflected the replacement of
shade-tolerant plants and plants for which seeds are dispersed by bats, other mammals, ants, and larger birds. Pioneer plants were those adapted to conditions of more
direct sunlight and produced larger numbers of small seeds dispersed by smaller birds
or the wind. Each form of land use contained 7 to 25 percent of the original forest
species plus thirteen to sixty-six new plant species adapted to that land use.
As field conditions changed over time, different sets of more competitive weeds
emerged. In response, farmers adapted agricultural product mix and management
strategies, relegated weed-infested plots to fallow, and cleared more forest. Farmers
were most concerned about Rottboellia cochinchinensis (Lour.) Clayton in fields after
fallow and Imperata brasiliensis Trin., both of which serve as indicators of soil degradation. Farmers identified useful species across treatments, but counts of these species
were very low, suggesting high levels of human intervention in the forest and heavy
pressure on such species in all land uses. Although fallowed areas regained some of
the original forest-like plant species, valuable shade-tolerant, slow-growing hardwood
trees did not reappear in fallow areas, perhaps because of their short duration. Perhaps
because many settlers were new to the region, they did not use indicator species to
identify fertile forest areas or signal decreased soil productivity after cropping (Fujisaka et al. 2000).
The below-ground soil macrofauna diversity was significantly affected by land
use in Yurimaguas (table 15.2). As intensity of land use increased, macrofauna numbers decreased significantly. The number of taxonomic units identified in a traditional
tree-based fallow area (thirty) was nearly twice that of low-input annual cropping system with a legume-based cover crop fallow (sixteen). By this measure, the multistrata
agroforestry system contained the most biodiversity. However, more detailed analysis
revealed that 95 percent of the total biomass of the multistrata system (55.7 g/m2)
corresponded to the exotic earthworm species Pontoscolex corethrurus Muller (Alegre
et al. 2001). Thus even though this agroforestry system helped conserve (or rebuild)
below-ground biodiversity, the emerging composition was quite different from that of
the original forest. Research into the functional consequences for agricultural productivity and other ecosystem functions of this shift in the composition of below-ground
biodiversity is under way.
C a r b o n S tocks
Scientists from the Instituto Nacional de Investigación Agraria (inia), Universidad
Nacional del Ucayali (unu), Tropical Soil Biology and Fertility Programme (tsbf),
340
National Perspectives
Table 15.2 Taxonomic Richness, Mean Abundance, and Biomass of Macroinvertebrates in
Different Land Use Systems in Yurimaguas, Peru
Land Use System
Shifting
High-Input Low-Input Multistrata Peach
Secondary
Agriculture Cropping
Cropping Agroforestry Palm
Forest
Plantation Fallow
Number of taxonomic 22
unitsa
Population density/m2a 151
Biomass (g/m2)a,b
21.8
16
16
31
22
30
171
22.4
175
23.3
557
55.9
115
35.5
806
42.9
Land use systems are defined as follows:
Shifting agriculture: 1-yr annual cropping alternated with a 7-yr fallow.
High-input cropping: mechanized maize–soybean continuous rotational cropping over 7 yr with high nutrient
input from fertilizers and lime.
Low-input cropping: 2-yr rotational cycle of annual crops with fallow of tropical kudzu (Pueraria phaseoloides).
Multistrata agroforestry: a diversified production system with timber, pole, and fruit trees (tornillo, Cedrelinga
catenaeformis D. Ducke; coffee, Coffea canephora Pierre ex Fröhner; bolaina blanca, Colubrina glandulosa; peach
palm, Bactris gasipaes Kunth; araza, Eugenia stipitata McVaugh; and Inga edulis Mart.), annual crops in the
first 2 yr, followed by a Centrosema macrocarpum Benth. understory, forming different strata in the system.
Peach palm plantation: peach palm planted at 5 by 5 m with a Centrosema macrocarpum Benth. understory.
Secondary forest fallow: maintenance of a secondary forest fallow, 7 yr old in 1985.
a
Includes earthworms, termites, ants, Coleoptera, Arachnida, Myriapodes, and others.
b
Fresh weight.
Source: Alegre et al (2001).
and International Centre for Research in Agroforestry (icraf) evaluated the aboveand below-ground carbon stocks in land use chronosequences near Pucallpa and
Yurimaguas. The evaluation was accomplished using the procedural guidelines developed by the tsbf for asb (chapter 2, this volume). This report includes only the
above-ground carbon stocks, not the time-averaged carbon stocks for the entire rotation as reported in chapter 2.
The above-ground carbon stocks for natural forests in the Yurimaguas area were
almost twice those of the forests in Pucallpa (table 15.3). This difference in forest
biomass could be a result of the higher rainfall and less disturbance of the forest from
a lower population density in Yurimaguas. Not surprisingly, when forest is converted
to agricultural uses, above-ground carbon is reduced; in fact, the 15-year-old fallows
in each location attained about 70 percent of the biomass of the primary forest. The
natural fallows had carbon accumulation rates as high as 10 t C/ha/yr (table 15.3), as
high as or higher than those reported in chapter 2. Among the managed, tree-based
systems, the carbon content ranged from 41 t C/ha for oil palm (Elaeis guineenisis
Jacq.) plantations to 74 t C/ha for rubber (Hevea brasiliensis [A. Juss.]) plantations
(Pucallpa), whereas that of multistrata agroforestry system in Yurimaguas was intermediate at 59 t C/ha. Rubber plantations and multistrata systems have a permanent
understory of tropical kudzu (Pueraria phaseoloides [Roxb.]), which increased the carbon stocks by 2 to 5 t C/ha (Alegre et al. 2002; Palm et al. 2002).
Table 15.3 Above-Ground Carbon Stocks of Different Land Use Systems in Yurimaguas and
Pucallpa, Peru
Site and Land Use
Above-Ground Carbon (t/ha)a
Yurimaguas
Forest
Moderately logged (40 yr)
Fallow
15 yr
5 yr
3 yr
Agricultural crops
Rice
Pasture
Degraded (30 yr)
Improved (w/Brachiaria)
Agroforestry
Multistrata b
294
185
44
19
17
2
5
59
Pucallpa
Forest
Primary (untouched)
Residual (logged)
Fallow
15 yr
3 yr
Agricultural crops
Maize
Cassava
Plantain
Pasture
Degraded
Perennial crops
Rubber (30 yr) with kudzu
Oil palm with grasses
162
123
126
21
8
3
16
3
74
41
Includes standing trees and dead and fallen logs.
Peach palm (Bactris gasipaes Kunth), tornillo (Cedrelinga catenaeformis D. Ducke), Inga edulis Mart., bolaina
blanca (Colubrina glandulosa Perkins), and coffee (Coffea arabica L.) with cover crop of Centrosema macrocarpum
Benth.
Source: Alegre et al. (2002).
a
b
342
National Perspectives
The amount of carbon in annual cropping systems is very low (3–17 t C/ha). The
upland rice (Oryza sativa L.) system in Yurimaguas showed carbon stocks similar to
those of the biennial plantain system in Pucallpa, but much of that was the carbon still
held in the remaining unburned logs from the clearing. Pastures contained the lowest
quantities of carbon. Of note, as with the forests, carbon stocks were greater in similar
land use systems in Yurimaguas than in Pucallpa. This is probably a result of the lower
levels of agricultural intensification and higher rainfall in Yurimaguas (Fujisaka et al.
1998; Alegre et al. 2002).
G re e n h ouse Gas Emissions
In addition to net carbon emissions, deforestation and resulting land use can lead to
the release of other greenhouse gases, including methane (CH4) and nitrous oxide
(N2O). Although tropical soils can provide sinks for atmospheric CH4, they are also
reputed to be a major source of N2O gases (Keller et al. 1997). Evidence suggests
that the CH4 sink strength of well-drained upland tropical soils diminishes as the
intensity of land use increases. Early analyses of tropical forest conversion to pasture
indicated a large positive flux (4.18 µg/cm2/h) of N2O into the atmosphere (Luizao
et al. 1989). More recent studies suggest that such emission increases are temporary
and that the rates may eventually decrease to less than those of the nearby undisturbed
forest (Keller and Reiners 1994; Erickson and Keller 1997). Because few studies on
trace gas emissions in the tropics have been undertaken in areas other than natural
forests and pastures, a goal of asb was to sample and compare fluxes from the full
spectrum of land uses ranging from natural forests to degraded pastures (see chapter
3, this volume).
A strategy of intensive sampling of N2O and CH4 fluxes in fewer, well-characterized locations was adopted for sites in Peru and Indonesia. Similar land use categories
were and continue to be monitored in both Pucallpa and Yurimaguas, representing the
entire range of land uses from forest to pasture.
In Yurimaguas, monthly measurements were taken over the course of 2 years,
1997 to 1999, in a long-term experiment comparing different land uses (Palm et al.
2002). Five of the six land use systems were established 13 years previously by slashing and burning of a 10-year-old shifting cultivation forest fallow. In 1985, a portion
of the 10-year fallow was slashed and burned and the following five treatments were
installed: traditional shifting agriculture system, high-input cropping with fertilization and liming, low-input cropping, a multistrata agroforestry system, and a peach
palm (Bactris gasipaes Kunth) plantation (table 15.2). These five treatments were all
compared with the original forest fallow that was 23 years old at the time gas measurements were taken.
Average monthly N2O fluxes ranged from 0.6 to 0.9 kg N/ha/yr in the tree-based
systems, were almost twice as high in the low-input cropping system, and reached 2.3
kg N/ha/yr in the high-input cropping system. The fluxes in the nonfertilized systems
The Peruvian Amazon 343
(tree-based and low-input cropping) are similar to those on the acid, infertile soils in
the Indonesia asb site in Jambi (chapter 3, this volume)
Methane fluxes also showed differences across treatments, with the high-input
cropping system actually switching to a net source of CH4 of +1.3 kg C/ha/yr (Palm et
al. 2002). All of the other systems maintained a net CH4 sink, showing decreasing sink
strength with increasing land use intensity (e.g., –2.6 kg C/ha/yr in the 23-year-old
forest fallow and –1.6 kg C/ha/yr in the low-input cropping). The differences in CH4
flux are related primarily to increased soil bulk density and corresponding increased
water-filled pore space. These methane consumption rates are similar to those reported from the Jambi site in Indonesia (chapter 3, this volume).
These preliminary results demonstrate that agroforestry systems maintain CH4
sink and have low N2O emissions, and as land use intensification increases, CH4 sink
strength decreases and N2O emissions increase if nitrogen fertilization and tillage are
practiced.
An analysis of the net global warming potential (gwp), which includes the net
radiative forcing effects of CO2, N2O, and CH4, of the different land use systems in
Yurimaguas indicated that the CO2 released from the vegetation as a result of biomass
burning from deforestation (75 mol C/m2/yr; dashed line in figure 15.3; Palm et al.
2004) exceeded any subsequent emissions of CO2, N2O, and CH4 from the soils. Carbon dioxide emissions from the decomposition of soil organic matter after deforestation, 0 to 8 mol C/m2/yr, were as high as or higher than the combined gwp of N2O
and CH4 fluxes, despite the higher net radiative forcing values for the latter two gases,
21 for CH4 and 310 for N2O (Watson et al. 2000). The gwp from CH4 production in
Figure 15.3 Sources of the net global warming potential (gwp) over a 25-yr period for the different land
use systems in Yurimaguas in the Peruvian Amazon. The dashed line represents the gwp resulting from
deforestation and biomass burning (adapted from Palm et al. 2004).
344
National Perspectives
the high-input cropping system or consumption in the other systems were undetectable in comparison to the gwp from CO2.
The establishment of tree-based systems reduced the initial gwp as a result of
deforestation by 11 to 35 percent (figure 15.3); this decrease resulted from carbon
sequestered in the vegetation. In contrast, establishment of the two cropping systems
increased the initial gwp by more than 20 percent through losses of soil carbon and,
in the case of the high-input cropping system, higher N2O losses and net CH4 production. Efforts to mitigate this dominating effect of the release of CO2 from the
slash-and-burn process should focus on reducing rates of deforestation or establishing
tree-based land use systems that sequester more carbon in the vegetation and soil than
annual cropping systems and pasture.
G e n e t i c Variation in Tree Species and Its Role
i n P ro m oting Sustainable Land Use
The asb research program on tree domestication takes discoveries regarding spatial
and temporal variation within tree species and uses them to promote on-farm productive diversity and improved tree germplasm. Farmers in the lowland jungle of the
Peruvian Amazon depend on more than 250 agroforestry tree species for construction
material, fenceposts, firewood, charcoal, fibers, resins, fruits, medicines, and service
functions such as soil conservation and shade (Sotelo Montes and Weber 1997). These
trees contribute significantly to the income and food security of resource-poor farmers
(Labarta and Weber 1998) and provide environmental services at local, national, and
global levels.
It is widely known that deforestation and logging decrease the abundance of tree
species around many rural communities in the tropics (Pearce and Brown 1994). As
a result, these communities have fewer natural resource options for economic development in the future. Less widely recognized but equally important is that genetic
variation within tree species may also be decreasing around rural communities (Ledig
1992). If this continues unchecked, communities may have even fewer opportunities for sustainable economic development in the future because reduced variation
within tree populations is likely to decrease production stability and yield over time.
Therefore it is imperative that domestication projects focus not only on increasing the
number of valuable tree species on farm but also on managing the genetic resources of
these species (O’Neill et al. 2001).
Intraspecific genetic variation in tree species is fundamental for the improvement
of agroforestry systems. Through appropriate selection strategies, significant improvements can be made in timber tree form, fruit quality, and other commercially important traits (Simons et al. 1994). The presence of intraspecific genetic variation not
only creates opportunities for selection but also provides an adaptive buffering capacity to changing user needs and environmental pressures.
One challenge for asb was to quickly and cheaply identify the most productive
germplasm for different agroforestry systems. Farmers consistently cite the lack of
The Peruvian Amazon 345
high-quality tree germplasm as a major obstacle to diversifying and expanding their
agroforestry practices, and traditional tree improvement methods are too slow and
expensive to meet their needs (Simons 1996). Nontraditional approaches involving
farmers as collaborators in the research and development process are needed (Weber
et al. 2001), and asb has taken steps to develop and implement them. An example
follows.
In the Pucallpa region, farmers want more productive germplasm of bolaina blanca (Guazuma crinita Mart.), capirona (Calycophyllum spruceanum Benth.), and other
timber trees (Sotelo Montes and Weber 1997). In 1996, researchers and farming communities worked together to collect seed from eleven natural populations of bolaina
blanca and capirona and established on-farm provenance trials in 1998. These were
the first genetics trials of native tree species in the Peruvian Amazon. The principal
objective of the trials was to identify the most promising provenances as seed sources
for reforestation in different environmental conditions in the Peruvian Amazon. The
trials were established on farms in the Aguaytía watershed (near Pucallpa), which is
representative of many watersheds in the western Amazon Basin. Farmers participate
in the evaluation of growth and other characteristics and provide useful information
about their selection criteria for tree germplasm.
Preliminary results of the on-farm provenance trials illustrate the potential gains
in productivity that farmers can realize from an early selection of provenances of fastgrowing timber trees (Sotelo Montes et al. 2000). In both bolaina blanca and capirona
there was significant variation in average height between provenances in the nursery and after 6 and 12 months in the field (p < .001). In the case of bolaina blanca,
after 12 months in the field the local provenance from the Aguaytía watershed (Von
Humboldt) was 13 percent taller than the average height of the other provenances
combined (p < .05). Capirona did not grow as rapidly as bolaina blanca during the
first few years.
Traditional studies of variation in provenance trials provide essential information
about the adaptive and commercial value of germplasm from different regions (Morgenstern 1996), but they cannot fully quantify the underlying diversity and genetic
constitution of tree populations. Molecular methods can provide this information
and are being used to complement traditional approaches. Molecular methods provide insights into the origin of tree populations, and the relationships between these
populations—essential information for management of tree genetic resources. For
example, molecular techniques were used to identify diverse populations of capirona
for cultivation and for in-situ and on-farm conservation in the Peruvian Amazon
(Russell et al. 1999).
Accelerating the delivery of high-quality tree germplasm to farmers is the second
principal objective of participatory tree domestication. A traditional forestry approach
involves many steps: species selection trials, provenance trials to identify the best seed
sources of each species, progeny tests to identify the best mother trees within each
selected site, collection of seeds or vegetative material from the best mother trees to
establish seedling or clonal seed orchards, and finally the production of high-quality
seed for dissemination. Using this slow and costly process, government and nongov-
346
National Perspectives
ernment organizations cannot meet the growing demand for high-quality germplasm,
particularly when formal institutions and networks break down.
Involving farmers in germplasm selection, production, and dissemination can
accelerate delivery of high-quality germplasm. On-farm genetics trials, like the provenance trials just mentioned, can be transformed directly into seed orchards. Farmers
with on-farm genetics trials are being organized into networks for the production and
commercialization of high-quality seed, seedlings, and timber. These seed orchards are
a new form of small business enterprise in Peru and also serve as ex situ conservation
sites.
Provisional guidelines were determined for seed transfer within the region based
on geographic patterns of genetic similarity between populations. In general, one
should try to match the environment conditions of the seed source with those of
the plantation. This entails characterizing the environmental conditions of potential
plantation sites and seed sources. In the absence of such characterization data, seeds
should be collected from trees that grow near the plantation site and have desirable
phenotypic characteristics. Using seeds from geographically distant regions should be
avoided unless there is evidence from genetic trials that such seedlots are adapted to
local environmental conditions.
S O C I O E CONOMIC RESEARCH
Farmers in the Amazon, like their counterparts worldwide, face many agronomic and
marketing challenges: Yields are uncertain, market prices typically are low and can
fluctuate wildly, and transportation to major markets is expensive. In the case of the
Peruvian Amazon, however, transportation costs are much higher than those faced
by agriculturalists in other areas; to reach international markets, products must be
transported down one of the longest rivers or over some of the highest mountains
in the world. Such conditions make farming (and hence farmers) uncompetitive in
all but local markets for most of their products, and these markets suffer from severe
seasonal gluts. Political and social instability also complicate production and marketing activities, putting farmers in the region at a further competitive disadvantage
even compared with their Amazonian counterparts in Brazil and Bolivia. For example,
unrest in the late 1980s led to a severe decline in livestock herd sizes in the Pucallpa
region (Fujisaka and White 1998). Contributing to the slow and ongoing recovery is
the drastic reduction of agricultural support programs (e.g., product price subsidies
and subsidized credit) in the 1990s (Hopkins 1998; Yanggen 2000a).
In an effort to improve smallholder welfare in the region, numerous land use
alternatives have been developed, ranging from improved traditional annual cropping
systems to new multistrata agroforestry systems. Though agronomically suited to the
region, improvements in income and food security based on these new systems have
been limited by several factors, some of which are beyond the reach of any policymaker.
For example, in 1999 perennial crops such as coffee (Coffea spp.), palm oil, and cocoa
The Peruvian Amazon 347
(Theobroma cacao L.) suffered price declines ranging from 25 to 50 percent. Despite a
large set of well-funded activities to promote exotic Amazonian fruits and forest products (Clay and Clement 1993; Toledo 1994), citrus and achiote (Bixa orellana L.) have
failed commercially. Consequently, farmers near Pucallpa continue to sell citrus and
other perennial tree crops at low prices in local markets. Despite these failures, new
projects that encourage the production of other Amazonian agricultural goods, such
as camu-camu (Myrciaria dubia [Kunth] McVaugh) and uña de gato (Uncaria tomentosa [Willd.] DC), are under way. Although these products provide an opportunity to
diversify production, demand for these specialty products is uncertain.
The asb socioeconomic research also addressed the issue of how government policies could best promote sustainable production systems, improve smallholder welfare,
and reduce the impact of agriculture on deforestation (Yanggen 2000b). More specifically, the research analyzed how changes in Peruvian agricultural policies, including
those of structural adjustment in the 1990s, affected use of cleared land and forest
cover. Analysis based on a 1998 household survey revealed that upon provision of
subsidized agricultural credit and guaranteed minimum prices for agricultural products in the latter half of the 1980s, 94 percent of farmers increased production (predominantly of rice and maize [Zea mays L.]), 90 percent of farmers hired more labor,
but only 11 percent of farmers increased capital input use. These government policies
led farmers to increase output by hiring more labor for slash-and-burn production
of annual crops. A sharp increase in forest clearing resulted; 75 percent of farmers
reported clearing more primary forest for agricultural use. When subsidized credit and
guaranteed prices were eliminated in the context of structural adjustment, production levels and deforestation sharply declined in the region around Pucallpa (Yanggen
2000a). Satellite images confirmed this decrease in deforestation rates over a broader
area (iiap 1999).
The econometric component of this research analyzed the dynamics of agriculture’s impact on deforestation at three levels: how economic and policy incentives and
other factors (e.g., biophysical conditions) affect farmer decisions concerning choice
of production technology, product mix, and the amount of land cultivated and how
these decisions, in turn, affect rates of deforestation. (figure 15.4).
The regression model results showed a clear evolution of land use patterns. Annual crop production was most strongly associated with early frontier development and
led to deforestation at the forest margin. Pasture and cattle tended to occupy land previously used for annual cropping, and also displaced secondary forest fallows. These
results confirm those of Fujisaka and White (1998) and Smith et al. (1999). Area
dedicated to perennial tree crops stagnated over the period covered by the sample,
primarily because the profitability of these activities was undermined by steep declines
in product prices.
Regression results also confirm the key role of labor as a constraining factor of
production. Farmers with above-average amounts of family labor produced more of
all the principal outputs: annual crops, perennial tree crop products, and livestock
products. Greater overall labor availability (both hired labor and family labor) led to
348
National Perspectives
Figure 15.4 Causal relationships between socioeconomics and technology leading to deforestation.
greater amounts of primary and secondary forest clearing. Farm households engaged
in above-average amounts of off-farm employment activities reported significantly
lower annual and perennial crop production. Clearly, reducing labor availability can
reduce the pressure on forests.
These models also capture the key role of financial capital in determining product mix, technology choice, and deforestation. The use of credit was positively correlated with the use of purchased inputs and hired labor. Credit was negatively correlated with labor- and capital-saving technologies, such as kudzu-improved fallows
and Brachiaria-improved pastures. Although the impacts of these specific inputs and
technologies on deforestation were not uniform, it is clear that access to credit played
a key role in determining the farmers’ decisions regarding scale of operation and
product mix, and these decisions did affect deforestation.
This research distinguished between the clearing of primary and secondary forests. Primary forests are areas that have never been felled (but often selectively logged);
vegetative regrowth on fallow land becomes secondary forests. A common perception
is that once primary forest deforestation has occurred, the forest (and all the services it
provides) is lost forever. However, research by the Food and Agriculture Organization
(fao 1996) estimated that in 1990 there existed 165 million ha of secondary forest in
Latin America; hence, the potential exists for recouping at least some of the forest services via increases in area in secondary fallow. In the Pucallpa area, farmers maintain
nearly equivalent areas of secondary and primary forest, 30 and 31 percent of the average operational holding, respectively (Yanggen 2000a). Econometric analysis showed
that use of kudzu-improved fallows, purchased inputs (e.g., fertilizer, improved seed,
and herbicides), and alluvial soils increased the amount of secondary forest cleared on
farms but decreased the amount of primary forest cleared. Increases in land productivity in these cases seemed to mitigate declines in soil fertility linked to annual crop production, thereby enabling farmers to reuse secondary forest fallows, which decreased
the need to clear primary forest (Yanggen and Reardon 2001).
The Peruvian Amazon 349
A central conclusion of this research is that the production of annual crops using
shifting slash-and-burn agriculture is a key driver of deforestation in the Pucallpa
research area. Greater labor availability increased these extensive production systems
and deforestation. One general policy objective, then, is to reduce the labor available for shifting annual crop production. One option is to promote off-farm income
opportunities that siphon labor away from annual cropping and other agricultural
activities. Development of a nonagricultural economic sector therefore may be key to
removing pressures on forests. This implies the need for a broad-based development
strategy including other sectors such as industry, tourism, and other services. In addition, research and policy initiatives must promote more sustainable annual cropping
practices. The use of productivity-enhancing inputs such as improved seeds, fertilizer,
and pesticides intensified land use and reduced clearing of primary and secondary
forests in our sample of farmers from the Pucallpa area. However, given low product prices and poor transportation infrastructure, agricultural research must redouble
efforts to identify product and technology packages that are affordable to and profitable for smallholders.
One option is to intensify pasture production systems. Indeed, kudzu-improved
fallows and Brachiaria-improved pastures have been widely adopted by farmers because
they increase returns to the labor. However, these systems use less labor per hectare,
thereby freeing labor for deforestation and other uses; analysis revealed that the adoption of kudzu-improved fallows increased secondary forest clearing, and the adoption
of Brachiaria-improved pastures increased clearing of all types of forests (Yanggen
2000b). The challenge is to identify production practices that both increase returns
to labor and decrease pressure on primary and secondary forests. Labor-intensive production of high-value perennial crops can do this by absorbing labor while still providing high returns to labor. Agroforestry techniques that incorporate trees with highvalue products into pastures and fallow areas have the potential to do this. Therefore,
integrating perennial tree crops into production systems should be a research priority.
In addition, on-farm processing of agricultural products into oils, preserves, flour, and
other products can dramatically lower the transportation costs relative to unit value of
output, and refined products also tend to suffer less price turbulence than do primary
products. Finally, policies that promote forest-based processing can help promote sustainable production of nontimber forest products.
This research proposed a series of strategies to encourage more intensive and sustainable agricultural production practices. However, this research also pointed out
that if new practices or crops were sufficiently profitable, farmers would invest in
labor-saving equipment or simply hire more labor to expand production and would
do so at the expense of forests. Thus more intensive forms of cultivation may promote
deforestation. Therefore there is a need to complement the promotion of intensive
cropping systems with policies that restrict access to forests. Options such as reductions in new road construction and enforceable regulations limiting the clearing of
primary forest merit consideration.
Recent geographic information system analysis by the International Center for
Tropical Agriculture (ciat) used high-detail images to identify the asb Pucallpa
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National Perspectives
benchmark area of the Aguaytía watershed while identifying and coding land uses.
Complementary research by the Instituto de Investigacion de la Amazonia Peruana
(iiap) delineated and estimated the rates of deforestation from 1955 to 1995. This
work has served as an input to policy planning (e.g., road construction and agricultural development projects) according to environmental and economic criteria (iiap
1999).
C A PAC I T Y STRENGTHENING, ASB IMPACT,
A N D F U TURE RESEARCH PRIORITIES
In 1998, national and international organizations working in Pucallpa held a workshop on participatory planning by objective to define research priorities. Using the
logical framework method, participating organizations selected biodiversity research,
research on and development of markets for Amazonian products, and the refinement
and application of farmer participatory research methods as priority issues. The establishment of a Training and Information Center also was deemed necessary.
The 1998 workshop yielded quick results for asb and its collaborators. National
research partners and universities began to include agroforestry in their research portfolios and curricula and also began to refine and replicate research methods, such
as tree domestication processes and the measuring of carbon stocks in production
systems. Training in tree domestication and genetic resource management has motivated inia, the Instituto Nacional de los Recursos Naturales, and the Reforestation
Committees to include similar projects in their research portfolios, thereby expanding the overall impact of asb research in Peru. In addition, the government of Peru
is incorporating recommendations regarding tree genetic resource management in its
new national forestry laws.
The asb collaborators are involved in participatory, farm-based research on the
management of pastures and secondary forests. Tropileche, a research consortium
involving ciat, iiap, and the Instituto Veterinario de Investigaciones Tropicales y
de Altura (ivita) aims to improve pasture quality and productivity for milk and beef
(dual-purpose) cattle production systems (Holmann 1999; White et al. 2001). The
Secondary Forest Project collaborates with institutions in Peru (Centre for International Forestry Research [cifor], inia, Universidad Nacional Agraria la Molina),
Brazil (Empresa Brasileira de Pesquisa Agropecuária), and Nicaragua to characterize
secondary forest use, examine the biophysical dynamics of secondary fallow systems,
and identify management options for enriching and otherwise improving secondary
fallows (Smith et al. 2001).
Planned future research and outreach efforts include expanding efforts to distill practical policy messages from field-based research results, with special attention
paid to policies likely to affect smallholder land use decisions and welfare. Examples
include more careful assessments of the affects of policy changes on smallholders; help
in prioritizing spending on agricultural research and extension, and greater efforts
The Peruvian Amazon 351
to identify and transfer to Peru relevant policy lessons learned from other asb sites,
especially Brazil.
AC K N OWLEDGMENTS
We are indebted to the three international centers involved in asb activities in Latin
America—ciat, cifor, and the World Agroforestry Center (icraf)—and for pioneering research on tropical soils and agronomy begun by North Carolina State University.
We are also indebted to our asb partner organizations: inia, Cámara Nacional
Forestal, Comité de Reforestación de Ucayali, Instituto Nacional de los Recursos Naturales, iiap, ivita, Dirección Regional de Agricultura–Ucayali, Universidad Nacional
Agraria la Molina, Universidad Nacional de la Amazonía Peruana, unu, Consorcio de
Desarrollo Sostenible del Ucayali, and Desarrollo Participativo Amazónico.
The authors are grateful for the helpful comments from Polly Ericksen, Sam Fujisaka, Jessa Lewis, and an anonymous reviewer. The asb Peru team appreciates the
financial support from the governments of Spain (Agencia Española de Cooperación
Internacional), Canada (International Development Research Centre), the Netherlands (dml/bd), Norway, the United States (Agency for International Development),
England (Department for International Development), Denmark (Danish International Development Agency), the European Union, the Interamerican Development
Bank, and the International Tropical Timber Organization.
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16 Northern Thailand
Ch anging Smallho l d e r L a n d
Use Pat terns
Plodprasop Suraswadi
Ministry of Agriculture and Cooperatives Bangkok, Thailand
David E. Thomas
World Agroforestry Centre Chiang Mai, Thailand
Komon Pragtong
Ministry of Agriculture and Cooperatives Bangkok, Thailand
Pornchai Preechapanya
Ministry of Agriculture and Cooperatives Chiang Mai, Thailand
Horst Weyerhaeuser
World Agroforestry Centre Kunming, Yunnan, China
T
he Alternatives to Slash and Burn (asb) research program in northern Thailand seeks to understand land use change in the mountainous
mainland Southeast Asia (mmsea) ecoregion and to develop technologies
and policies that can improve land use management and human welfare in
the region. The mmsea includes the large region of hill and mountain terrain that joins the Himalayan mountains in southwestern China and extends
through northern portions of Myanmar, Thailand, and Laos, to Vietnam in
the east (figure 16.1). Several major river systems flow through or have headwaters in this region, also long known for its diverse ethnic composition and
complex mosaic patterns of traditional land use that include shifting cultivation. Because this region also includes most of what remains of mainland
Southeast Asia’s rapidly dwindling forest resources, it is the focus of increasing
environmental concern related to the use and management of surface water
and biodiversity and to global climate change.
Improving natural resource management, reducing rural poverty, and
understanding the important role of socioeconomic context in which resource
use decisions are made are key asb objectives. More specifically, given strong
and growing concern over watersheds and river systems that support major
lowland populations, their rice bowl production areas, and urban and industrial centers, asb chose watersheds as its unit of observation in establishing
356
National Perspectives
Figure 16.1 Mountainous mainland Southeast Asia and the asb Thailand benchmark site.
an analytical framework. Moreover, special focus is given to land use in upper tributaries, where many poor minority communities have benefited least from the rapid
economic development that has characterized Thailand and the region. We also seek
to incorporate into our analysis relevant lessons from the Asian economic crisis and
constitutional and governance issues emerging in Thai society and the wider region.
This chapter focuses on changes in patterns of land use in mountainous landscapes of northern Thailand, with particular attention to changing land uses of mountain minority communities and the effects of these changes on environmental services
emerging from watersheds. The next two sections describe changes in land use in the
study area, discuss some of the factors influencing land use change, and identify some of
the environmental consequences of these changes. Then we examine selected projectspecific responses to factors influencing changes in forest and land use, describe promising technological and institutional innovations, and provide details of asb’s research,
capacity strengthening, and outreach agendas in Thailand.
Northern Thailand 357
C H A N G I NG L AND USE PAT TERNS IN MOUNTAIN
WAT E R S HEDS
The asb Thailand research strategy began with a review of policy concerns and issues
associated with changing patterns of land use in northern Thailand, with emphasis on
upper watershed areas (Thomas 1996). We also reviewed the literature and ongoing
research to identify strategic knowledge gaps and to guide the selection of an appropriate benchmark site and program development. Based on these reviews, the 4000-km2
Mae Chaem watershed was selected as the primary asb benchmark site. The asb’s
secondary focus in Thailand has been on one ridge of the Mae Taeng watershed where
the Sam Mun Highland Development Project was conducted over the period 1987
to 1994.
Because most land in upper watershed areas is officially classified as reserved or
protected forest, our first task was to identify types of forest resource user groups and
examine their uses of forested land for timber and other purposes and then to assess
the effects of user practices on watershed degradation.
D e f o re s tation
Thailand entered its era of rapid economic growth in 1960 with the launching of
its first national 5-year economic and social development plan. Although much economic development has been achieved, one cost has been the loss of more than half of
Thailand’s natural forest resources, resulting in growing concern about loss of biodiversity and contributions to global climate change. Table 16.1 summarizes changes in
proportions of land under forest, agriculture, and other uses over the period 1960 to
1998, for the nation as a whole and for northern Thailand.
Table 16.1 Changes in Percentage Land Cover in Thailand and Northern Thailand, 1960–1998
Land Cover
Forest cover
Farm land
Other nonforest
Proportion of Total Area (%)
National
Northern Thailand
National
Northern Thailand
National
Northern Thailand
1960
1970
1980
1990
1998
54.0
68.8
20.0
11.0
26.0
20.2
46.0
67.3
29.0
17.0
25.0
15.7
32.0
53.9
37.1
24.5
30.9
21.6
27.3
46.4
41.2
28.0
31.5
25.6
25.3
43.1
41.5
27.5
33.2
29.4
Sources: Adapted from Charuppat (1998) (Royal Forest Department), Center for Agricultural Statistics
(1994), and Center for Agricultural Information (1998).
358
National Perspectives
Although dramatic decreases in forest cover began later in northern Thailand
than in much of the rest of the country, major losses occurred at both levels in
the 1970s. Rates of loss appear to have begun to decline recently, but percentage
losses in forest cover are still above the national average. Moreover, although most
remaining forest is in the north, losses there are already greater than in other areas of
the mmsea. There are three principal proximate causes of deforestation in northern
Thailand: conversion of forests to agriculture, logging, and traditional farming practiced in forested areas.
• Conversion of Forests to Agriculture. Conversion of forest after 1960 throughout Thailand was associated primarily with expansion of land for agriculture, as seen
in table 16.1, both to feed the growing population and to produce export crops to provide foreign exchange for the rapidly growing economy. Conversion to agriculture was
facilitated by heavy logging and, in the late 1970s, by policies promoting agricultural
expansion. Policies to address political and national security issues further encouraged
forest clearing (Pragtong and Thomas 1990). As agriculture began to expand into
increasingly marginal sites, overall population growth rates began to decline, the economy underwent structural adjustments that favored the industrial and service sectors,
and urban and suburban growth began to accelerate. Forest conversion then became
increasingly associated with cities, industry, housing, resorts, and, more recently, land
speculation (Thomas 1996, 1997).
• Logging of Natural Forest. Logging helped fuel economic growth initially, but
the combination of huge concession areas overlapping with protected forest areas and
local communities, high official and unofficial harvest rates, low replanting rates, settlement and cultivation of logged areas, and slow expansion of plantation forests made
such contributions to economic growth unsustainable (Pragtong and Thomas 1990).
Although logging concessions were stopped in 1989, illegal logging is still a problem in
reserved forest and protected areas. Forest department policy now emphasizes forest conservation rather than timber production and the strict enforcement of established rules.
• Traditional Agriculture within the Forest. In the mountains of northern Thailand, various ethnic minorities have long lived as farmers in the forest (Kunstadter
et al. 1978). A web of interrelated issues is associated with their land use practices,
including opium production, shifting cultivation, rural poverty, and the impact of
land use practices on protected forest areas and on the environmental services these
forests provide (Rerkasem and Rerkasem 1994; tdri 1994; Thomas 1996; Kaosaard 2000). The 1997 distribution of mountain ethnic minority populations living
in the midlands and highlands (above 600 m a.s.l.) is presented in table 16.2 for the
nation as a whole, the northern region, Chiang Mai province, and the asb benchmark
site (Mae Chaem). Although national proportions of mountain ethnic minorities are
quite low, they often make up more than half of the population in northern upper
watershed areas.
The grouping of communities into highland, midland, and lowland categories
corresponds to the altitude zones in which they have been most prevalent and the
Northern Thailand 359
Table 16.2 Distribution of Mountain Ethnic Populations, by Ethnic Group and Geographic
Area, 1997
Groups
Nation
Northern Thailand
Chiang Mai
Mae Chaem
With Highland Agricultural Traditions
H’mong
Lahu
Akha
Yao
Lisu
Subtotal
126,300
85,845
56,616
48,357
33,365
350,483
119,768
84,262
56,157
42,561
31,040
333,788
19,011
32,583
5,486
353
13,201
70,634
4,814
—
—
—
431
5,245
353,574
38,823
17,637
13,674
125
423,833
310,909
40,302
16,225
10,567
125
378,128
111,667
—
5,473
21
—
117,161
29,197
—
1,451
—
—
30,648
Mountain minoritiesa
Proportion of total
774,316
100%
711,916
92%
187,795
24%
35,893
5%
Total population
Mountain minorities
60,816,227
1%
12,091,337
6%
1,573,757
12%
67,912
53%
With Midland Agricultural Traditions
Karen
Htin
Lua
Khamu
Mlabri
Subtotal
Mountain minorities are defined as members of the ethnic groups listed in this table.
Source: Adapted from Hilltribe Welfare Division (1998).
a
types of agroecosystem management practices they have traditionally used (Preechapanya 2001). (Highland peak areas, a strategically important but small altitude zone
not densely inhabited by humans, are excluded from the analysis presented here.)
Although such groupings are based on traditional distinctions widely applicable across
the mmsea ecoregion, altitude zones are approximate, geographic domains of ethnic
groups’ overlap, and conditions change and traditions adapt over time. Table 16.3
presents estimates for the asb benchmark site of the distribution of ethnic groups
across altitude zones (top portion of table 16.3; rows sum to 100 percent) and ethnic
distributions within each zone (bottom portion of table 16.3, columns sum to 100
percent) as of 1997. Note that 27 percent of highland tradition populations (H’mong
and Lisu) are now located in midland and lowland zones, whereas 42 percent of midland tradition populations (Karen and Lua) are located in the highland zone (usually
near its lower boundary), where they outnumber traditional highland groups by a
factor of four.
From an environmental viewpoint, the most important distinction between traditional groups is their agroecosystem management (Thomas 1996). Attention usually
has focused on shifting cultivation, or swidden components of their systems: Highland groups are associated with pioneer swidden agriculture, midland groups with
360
National Perspectives
Table 16.3 Distribution of Ethnic Groups in the site, by Altitude Zone, 1997
Population
H’mong and Lisu
Karen and Lua
Thai
Total
6,192
42,900
18,820
67,912
Population
H’mong and Lisu
Karen and Lua
Thai
Total
6,192
42,900
18,820
67,912
Distribution of Ethnic Groups Across Zones (%)
Highlands
Midlands
Lowlands
73
42
—
33
12
47
3
32
15
11
97
35
Ethnic Composition of Altitude Zones (%)
Highlands
Midlands
Lowlands
20
80
—
3
94
3
4
19
77
Source: Unpublished International Center for Research in Agroforestry and Ministry of Interior data.
established swidden agriculture, and lowland groups with northern Thai swidden
agriculture (Sheng 1979). There has never been a basis for official recognition of forest fallow fields as a component of agricultural land holdings, and clearing of fields in
a shifting cultivation system is officially viewed as forest destruction. Critics of these
official views claim that when a new field is cleared—especially under established or
rotational swidden agriculture—an old field is returned to fallow, resulting in no net
deforestation. Although remote sensing can provide estimates of the proportion of an
area that is cleared of forest at a given time, little is known about the impact on forest
ecosystems of changing swidden agriculture practices.
Wat e r s hed Degradation
Many believe that groups practicing agriculture of different types in different altitude
zones are damaging the watersheds they cultivate (Rerkasem and Rerkasem 1994;
tdri 1994; Thomas 1996; Tangtham 1999; Kaosa-ard 2000). Two primary concerns
are reductions in the quantity and quality of watershed services and increased conflict
over watershed services. Although these concerns are most urgent in northern Thailand, they are relevant throughout mmsea, including portions of the Hong (Red),
Mekong, Salween, Irawaddy, Yangtze, and Xi Jiang (Pearl) river systems (Kaosa-ard et
al. 1995; cmu 1996; Revenga et al. 1998; Tangtham 1999).
Reductions in the Quality and Quantity of Watershed Services
The mountains of northern Thailand are the headlands of the Chao Phraya river
system, which nourishes Thailand’s key rice (Oryza sativa L.) production areas in the
Northern Thailand 361
central plains and the vast urban–industrial complex around Bangkok. Concern about
deterioration of watershed services began in the 1960s when a group from the Kasetsart University Faculty of Forestry began research at three small highland subcatchments at Doi Pui. Findings through 1980 from a detailed set of studies suggest that the
effects of swidden agriculture on stream flow, soil erosion, and water pollution were
negative but modest, especially when compared with the effects on the same environmental parameters of more intensive forms of agriculture and the road construction
and other activities associated with the human settlements that accompanied agricultural intensification (Chunkao et al. 1974, 1981; Lapudomlert et al. 1974; Prachoom
et al. 1974; Aksornkoae et al. 1977; Chunkao 1983). Several follow-up studies have
been undertaken (e.g., Royal Forest Department 1993; Vincent et al. 1995; Kaosa-ard
2000), but there is still insufficient socioeconomic and environmental information for
comprehensive land use planning (Kaosa-ard 1996; Tangtham 1999). In particular,
almost nothing is known about the effects of changes in product mix or production
technology in mountain mosaic land use patterns on the quantity or quality of watershed services on-site or downstream or of the effects of such changes on the human
welfare; both are key research questions for asb.
Conflict Between Resource User Groups
Growing environmental awareness combined with increasing demands for water by
agriculture, cities, and industry are focusing attention on land use in upper watersheds
(Hirsch 1997). Increasing competition for water resources among a growing range
of stakeholders, combined with shortages of key data and limited access to existing
knowledge, are fueling debate, conflict, and confrontation (Kaosa-ard 2000). Various schools of thought are developing, some of which appear to reject most scientific
analysis, whereas others seem unable to integrate local knowledge regarding watershed management practices, water rights, and water use into policy debates. In order
for water scarcity to prompt innovation, conservation, and efficiency, established and
agreed-upon criteria for measuring and valuing resource stocks and flows are needed
(Kaosa-ard 1996). Valuation and other measures should be developed using both
traditional and contemporary tools and concepts. Organizations and institutions
to manage disputes at various levels also must be strengthened. Meanwhile, because
action programs must proceed with less-than-ideal knowledge, tools, and institutions,
mechanisms must be developed to systematically distill lessons learned from ongoing
successes and failures into future action programs.
D E T E R M INANTS, EFFECTS, AND SPATIAL PAT TERNS
O F L A N D USE
Three sets of factors contribute to land use and land cover change in northern Thailand: incentives and pressures for land use change, responses to these incentives and
362
National Perspectives
pressures by traditional mountain land use systems, and the spatial distribution of
these responses.
I n c e n t i ves and Pressures for Land Use Change
Six interrelated factors influence incentives and pressures for land use change.
Demographic Change
High population growth rates of mountain ethnic minority communities combined
with migration to these areas from neighboring countries have increased the pressure
of population on land (Rerkasem and Rerkasem 1994). In recent decades Thailand has
been a safe haven and an economic magnet for many people in neighboring countries.
Because many ethnic minority communities in the midlands and highlands are still
being integrated into the formal Thai administration system, they are included only
in recent demographic data. Table 16.2 presents estimates from the Hilltribe Welfare Division (1998) of mountain minority populations living above 600 m a.s.l. in
1997 at the benchmark, provincial, regional, and national levels. Although the mountain minority population represents only about 1 percent of the national population,
almost all (92 percent) mountain minority members live in the northern region, and
in the Mae Chaem site ethnic minorities represent more than half (64 percent) of the
resident population.
Moreover, some mountain minority populations are the fastest-growing segment
of the Thai population. Compared with estimates from the same source in 1972 (Kunstadter et al. 1978), highland groups have experienced population increases of nearly
10 percent per year, whereas midland groups have experienced growth rates of only
about 2 and 3 percent in the north and in Chiang Mai province, respectively. This
compares with an average annual growth rate of total population of approximately 2
percent in Chiang Mai and northern Thailand since 1972.
Agricultural Change
Expansion of area dedicated to agriculture and changes in product mix have been
brought about by opium crop replacement projects in the highlands and by the expansion of now–land-constrained lowland agroindustry (tdri 1994). Work in northern
Thailand on replacement of opium with intensive commercial crops was pioneered
largely by projects under the king’s patronage, followed by a set of public and private projects in various northern areas. Although some highland production activities
(e.g., cabbages [Brassica spp.], barley [Hordeum vulgare L.], ginger [Zingiber officinale
Roscoe], and some fruit crops) are now conducted through private channels, Royal
Northern Thailand 363
Project centers specializing in fruits, vegetables, or ornamental plants are under the
umbrella of the Royal Project Foundation, and some products are marketed under
their own Doi Kham brand name (for details see Royal Project Foundation 2002).
In addition to these project-motivated changes in product mix, expanding Thai
agroindustry is being displaced in urbanizing lowland areas and is pushing field crop
and horticultural production onto hillsides and into mountain valleys in the midland zone. Examples of products produced in these new areas include soybean (Glycine max [L.] Merr.), maize (Zea mays L.), potato (Solanum tuberosum L.), longan
(Dimocarpus longan Lour.), mango (Mangifera indica L.), and lychee (Litchi chinensis Sonn.). Although these efforts often have the blessing of rural development and
poverty reduction programs, success in achieving these program objectives has varied
substantially spatially and over time and has been hampered generally by the high
investment requirements, higher agricultural risk, and lower profitability characteristic of agriculture in marginal areas, especially when pursued under highly fluctuating
economic conditions.
Government Policy Incentives
Forest policy has resulted in the establishment of forest reserves, national parks, wildlife sanctuaries, and protected watershed forests that preclude formal recognition of
private land ownership claims in most mountain areas. The importance of reserved
and protected areas to populations living above 600 m a.s.l. is suggested in table 16.4.
In some areas, land has been degazetted from reserved or protected status when local
communities have demonstrated long-term residency and met other requirements.
In all midland and highland areas, though, the absence of property rights may affect
incentives to invest in more sustainable land management and agricultural activities.
Note that the asb benchmark site (Mae Chaem) is well placed to study issues asso-
Table 16.4 Spatial Distribution of Populations Living Above 600 m Above Sea Level, by
Geographic Area and Land Status, 1997
Land Category
National
Northern
Thailand
Chiang Mai
Mae Chaem
Reserved forest
National parks
Wildlife sanctuaries
No-hunting areas
Degazetted areas
Planned reserves
Military lands
Total
611,400
39,421
40,600
2,001
283,878
8,322
5,500
991,122
589,279
37,877
30,900
1,957
250,104
8,322
—
918,439
174,224
15,742
6,755
1,895
46,689
8,322
—
253,672
30,794
311
—
—
3,309
4,615
—
39,029
Source: Adapted from Hilltribe Welfare Division (1998).
364
National Perspectives
ciated with communities living in reserved forest, planned reserves and parks, and
degazetted areas.
The perceived importance of watershed issues has prompted another set of policies
directly related to land use in the mountainous areas of northern Thailand. A watershed classification system was developed and implemented throughout the country,
initially under the aegis of the National Research Council and subsequently under the
Ministry of Science, Technology, and Environment. Five watershed classes were identified using 1:50,000 scale topographic maps, and land use regulations were developed
for each class; land use was most restricted in Class 1 areas and least restricted in Class
5 areas (Chunkao 1996).
Table 16.5 presents the spatial distribution of watershed classes nationally, for the
northern region, for the Ping Basin, and for the asb site located in the Ping Basin.
Although proportions of land in classes with severe restrictions appear modest at
national level, this proportion increases rapidly as one moves upstream. For example,
although only 26 percent of the nation’s land falls into Class 1 and Class 2 (the most
limiting land use restriction categories), the proportion in these classes is twice that for
the northern region and the Ping and climbs to about 90 percent in the Mae Chaem
watershed, a major tributary of the Ping River.
But hydrologic services are not the only concern in mountainous areas. Illegal
logging, production, and processing of narcotics and national security all contribute
to the felt need for government policy action in midland and highland areas, and
the sources of policy action are becoming more diverse. For example, whereas in the
past rural poverty programs in the mountains have been conducted largely through
the Public Welfare Department, in the contexts of special projects, or by missionaries
(Renard et al. 1988), since constitutional reform was enacted in 1997 rural development decision making has been shifting to elected local governments. Various new
provisions that shift responsibility and authority for watershed management from
national to local policymakers, including a community forestry law, are now being
considered by Parliament.
Table 16.5 Distribution of Land by Watershed Class at National and Subnational Levels
Geographic Area
Thailand
North
Ping Basin
Mae Chaem ( site)
Overall
Highlands
Midlands
Lowlands
Distribution of Land by Watershed Classification (%)
Class 1
Class 2
Class 3
Class 4
Class 5
18.1
32.6
38.3
8.3
15.0
14.2
7.7
10.8
9.6
15.8
9.5
8.9
49.0
31.8
28.3
63.9
82.6
54.7
17.7
25.0
14.5
32.4
41.9
8.7
2.9
10.2
28.2
1.8
0.0
2.7
6.0
0.7
—
—
6.1
Area covered by water are not included in this table, so rows do not sum to 100%.
Sources: Chunkao (1996), International Center for Research in Agroforestry unpublished data.
Northern Thailand 365
Infrastructure Development, Market Access, and Public Services
Programs to eradicate opium production and to promote national security have
increased efforts to expand road infrastructure in mountain regions. Expanded road
networks have had direct and indirect negative environmental effects; road construction and roads themselves disrupt ecosystems, and improved access to forests can fuel
illicit logging and forest extraction operations. On the other hand, roads have brought
market access for alternative cash crop production to many remote areas. Expansion
of public services is another public policy objective, including registration of minority
communities, the provision of improved education and health services, and increased
access to electricity and mass media, all of which increase opportunities to integrate
these communities into national society.
Urbanization, Industrialization, and Tourism
Tourism, resorts, and recreational facilities are bringing new claims, pressures, and
opportunities to mountain areas (Dearden 1996). Urbanization and industrialization
have also begun affecting various aspects of life and decision making in mountainous
areas. For example, land in these areas is coming to be valued as a tradable commodity
and a store of wealth rather than simply an input into an agricultural production process (Thomas 1996). The consequences of this shift for land values, land use, poverty,
and environmental services are not known.
Environmentalism
Rapid growth of environmental awareness has been associated with both a populist
element calling for more local control over natural resource management and a more
ecocentric element that believes local communities should be excluded from protected
areas for the longer-term benefit of larger society. Although these two factions were
allies during the early emergence of the environmental movement into the national
public policy arena, they have since split into camps that often oppose each other
(Thomas 1997). Tension between these elements is substantial and growing and occasionally breaks out into open conflict.
E f f e c ts of Incentives and Pressures on Traditional
M o u n ta i n Land Use Systems
The effects of these incentives and pressures on the natural resource base and on
human welfare are conditioned by the traditional land use systems developed for specific altitude zones and by ethnic groups that practice them. Three general categories
366
National Perspectives
of traditional systems have evolved in the mountain ecosystems of northern Thailand:
highland, midland, and lowland. These systems reflect the natural forest types that
exist in the area—which are strongly associated with altitude, as modified by geology,
aspect, fire, and other factors—and the cultural diversity of the region (Grandstaff
1976; Kunstadter et al. 1978; Schmidt-Vogt 1999). Table 16.6 presents some of the
basic features of these three altitude-specific zones, as of about 1960, that are important for understanding the distribution of resources, people, and activities in northern
Thailand and other parts of the mmsea.
Traditional highland land use systems are generally characterized as pioneer systems and are practiced by mobile villages using long cropping cycles and very long
“abandoned” forest fallow cycles that are viable only in areas with small populations with access to extensive areas (Grandstaff 1976; Kunstadter et al. 1978; Sheng
1979).
Traditional midland land use systems are associated with more established villages and systematic, short cropping cycles, long rotational forest fallow systems that
often include paddy rice land where topography and water allow, and systematic
management of landscape components including areas kept under permanent forest
cover (Grandstaff 1976; Kunstadter et al. 1978; Chammarik and Santasombat 1993;
Thomas et al. 2000). Some of these managed forest parcels include miang or jungle
tea production, where Camellia sinensis L. is planted as an understory tree in hill evergreen forest. Leaves are steamed and sold with or without fermentation for chewing as
a traditional stimulant. Livestock also grazes in these midland systems (Preechapanya
1996, 2001).
Traditional lowland land use systems have focused largely on irrigated paddy rice
production and home gardens (Preechapanya 2001), sometimes with supplemental
short-fallow cropping practiced on nearby slopes.
Table 16.6 General Features of Traditional Land Use Systems, by Altitude Zone and Natural
Forest Type
Zone Label
Altitude Range
(m a.s.l.)
Natural Forest
Ethnic
Groups
Traditional Agricultural
Practices
Highlands
1000–1800
Hill evergreen and
coniferous
Midlands
1000–1200
600–1000
H’mong, Lisu,
Akha, other
Thai, Karen
Lua, Karen
Lowlands
600
Pioneer shifting cultivation
(perhaps with opium)
Jungle tea (in some areas)
Paddy (limited) and
rotational long-fallow
shifting cultivation
Paddy, gardens (perhaps
with short-fallow shifting
cultivation)
Mixed deciduous
Dry deciduous and
swamp
Thai
Source: Adapted from International Center for Research in Agroforestry and Royal Forest Department
unpublished data.
Northern Thailand 367
As indicated earlier, over the past 30 years or more, the incentives and pressures
for change have altered product mix and production technology within and across the
traditional altitude zones, with consequences for producers, consumers, and the environment (Chammarik and Santasombat 1993; Rerkasem and Rerkasem 1994; tdri
1994; Thong-ngam et al. 1996; Kaosa-ard 2000; Thomas et al. 2000, 2002; Thomas
2001). Table 16.7 (and the following text) summarizes these changes.
• Highlands. Pioneer shifting cultivation and opium production have been largely replaced by commercial vegetable production that is now pushing from the highlands down into the midlands (tdri 1994). There is growing downstream concern
about impacts on stream flow, erosion, and pesticide water pollution.
• Midlands. Pressures from population growth, expanding lowland and highland systems, and government policy have reduced land availability, often resulting in
much shorter forest fallow cycles and some conversion to permanent fields. In some
cases, sacred tree groves are being threatened.
• Lowlands. Field crop production systems, and in some cases orchards, have
moved from lowland areas into forested watersheds above rice paddies and are pushing
up into the midland zone.
S pat i a l Distribution of Land Use Change
Neither the factors influencing land use change nor the changes themselves are distributed uniformly within or between altitude zones. Estimates of the proportions of
Table 16.7 Changes in Land Use and Their Consequences, by Altitude Zone
Zone Label
Altitude Range
(m.a.s.l.)
New Land Uses
Producer and
Consumer Issues
Environmental Issues
Highland
1000–1800
Commercial
horticulture,
grasslands, forest
plantations
Jungle tea (in some
areas)
Paddy (limited) and
short-rotation
shifting cultivation,
permanent upland
fields
Paddy, gardens,
upland field crops,
orchards
Crop markets, land
security
Deforestation,
reduced stream flow,
water pollution
Crop markets, land
security
Food security, land
security, crop
markets
Less forest buffer
Deforestation,
reduced stream flow,
water pollution
Crop markets,
irrigation water,
land security
Deforestation,
reduced stream flow,
water pollution
1000–1200
Midlands
Lowlands
600–1000
600
Source: Adapted from International Center for Research in Agroforestry and Royal Forest Department
unpublished data.
368
National Perspectives
Table 16.8 Distribution of Land Cover Type, by Geographic Area, 1990
Geographic Area
Proportion of Total Area (%)
Thailand
Northern Thailand
Mae Chaem ( )
Highlands
Midlands
Lowlands
Forest
Agriculture
Nonforest
27.3
46.4
79.4
81.5
74.8
85.4
41.2
28.0
1.5
0.4
1.6
7.5
31.5
25.6
19.0
18.1
23.7
7.1
Sources: Adapted from Charuppat (1998) (Royal Forest Department) and unpublished International
Center for Research in Agroforestry data.
land in forest, agriculture, and other nonforest categories at national, regional, and site
levels are presented in table 16.8. As one moves from the nation to the watershed level,
forest cover increases (e.g., from 27 to 46 to 79 percent) and area dedicated to agriculture decreases (e.g., from 41 to 28 to 1.5 percent). Within Mae Chaem, roughly similar patterns occur among altitude zones that comprise the site. One must be cautious
in interpreting such data, however, because issues of measurement error loom large,
especially for midland and highland land systems; boundaries of components of these
systems are located using remote sensing techniques that have difficulty distinguishing
between some system components, such as between fallow and forest cover.
Table 16.9 Subdistricts of the Mae Chaem Benchmark Watershed, by Altitude Zone
Subdistrict Labels
Ban Chan
Chaem Luang
Pang Hin Fon
Mae Daet
Mae Suk
Mae Na Chon
Ban Tub
Kong Khaek
Ta Pha
Chang Koeng
Total
Total Area
(ha)
18,504
24,851
24,167
16,453
68,200
72,545
40,647
36,918
10,672
19,961
332,918
Altitude Zones
(percentage of total land)
Land Use Features
Highlands
Midlands
Lowlands
92
84
75
70
60
45
36
18
25
22
51
8
15
25
31
38
51
53
61
45
52
41
—
—
—
—
3
3
11
21
30
26
7
High-value horticulture
Med-SC, veg., park
Short-SC, veg., park
Med-SC, veg., park
Med-SC, veg.
Short-SC, veg., park
Short-SC, veg., park
Fixed fields, park
Fixed fields, park
Town, fixed fields, park
Med-SC, medium-cycle, shifting cultivation; veg., vegetable crop production; park, parkland; short-SC, shortcycle shifting cultivation.
Sources: Adapted from unpublished Royal Forest Department, International Center for Research in Agroforestry, and Care-Thailand data and unpublished Ministry of Interior data.
Northern Thailand 369
Policy domains can also influence spatial patterns of land use. For example, the
4000-km2 Mae Chaem watershed can be disaggregated into administrative subdistricts, or tambons, ten of which make up about 90 percent of the watershed. These
subdistricts are increasingly important decision-making units for natural resource
management, especially since the 1997 constitution changes that delegated power and
responsibility for many such decisions to local authorities. Table 16.9 indicates the
relative size of these subdistricts, how their land is distributed between altitude zones,
and a few major features of land use within their domains. Differences within altitude
ranges across subdistricts are explained by natural factors such as geology and geography and by policy decisions related to road access, current and past project activities,
and government programs.
E F F O RTS TO ADAPT TO CHANGING CONDITIONS
In response to these incentives, pressures, and resulting patterns of change, innovative farmers and pilot projects have been seeking ways to improve livelihoods while
reducing pressure on forests and protected watersheds. Some of these are local efforts
by individual households or local leaders, and others are facilitated or promoted by
projects executed at various scales by government agencies or nongovernment organizations (ngos) (tdri 1994; Thomas 1996; Kaosa-ard 2000). ASB Thailand seeks to
learn from, build on, and support such efforts. In addition to the continuing efforts of
the Royal Project Foundation, several projects are providing useful insights regarding
organized efforts to influence land use change.
Sa m M u n Project
One particularly noteworthy project is the 1987 to 1994 Sam Mun Highland Development Project (hereafter called the Sam Mun Project), an interagency project led by
the Royal Forest Department in collaboration with the Office of the Narcotics Control
Board, with funding assistance from the United Nations Drug Control Program and
the Ford Foundation (Limchoowong 1994; Thomas 1997). The 2000-km2 project
area is located in the midland and highland zones of a ridge of mountains beginning
northwest of Chiang Mai City and extends to the Myanmar border. This area, like
some of the ridges in the asb Thailand benchmark watershed, was once an important opium production area; opium poppies occupied more than 800 ha in 1989.
Although one of the last internationally supported projects focusing on opium crop
substitution, it is generally recognized as the most effective and the most integrated in
its approach. Its Thai leaders made serious efforts to learn from previous projects, and
even academics usually very critical of forestry policies and projects have recognized
the value of their approach (Ganjanapan 1997:208).
370
National Perspectives
To paraphrase a former project director, the Sam Mun Project focused on strengthening the capacity of community organizations so they could be self-reliant in managing their communities, food supplies, and natural resources (soil, water, and forest) in a
manner that was appropriate to their lifestyles and values, ensured community stability,
and developed their community and environment in response to local needs and government policies, including reductions in opium production (Limchoowong 1994:11).
The project assumed that people and forests could live in harmony and emphasized food
self-sufficiency, income generation, reduced use of chemicals in agriculture, reduced
swidden agriculture, increased forest protection, initiation of watershed management
networks, and the development of tools for local land use planning. Many of the methods and tools pioneered by this project, such as participatory land use planning (plp,
explained later in this chapter) (Tan-kim-yong et al. 1994) and three-dimensional village land use models, are now being used and further adapted by projects in Thailand
and neighboring countries. In addition to promoting important changes in land use
in the project area (e.g., area under shifting cultivation was reduced by more than 80
percent and forest cover more than doubled; Tan-kim-yong et al. 1994), the project
also helped communities gain access to health and education services, citizenship, and
infrastructure improvements needed to implement their development plans. Finally, as
regards opium production, the project was highly successful; area dedicated to opium
decreased by about 90 percent from 1989 to 1994 (figure 16.2).
Q u e e n S irikit Forest Development Project
( Suan Pah Sirikit )
Building on previous smaller-scale efforts, this interagency project in the Mae
Chaem watershed has been conducted under the patronage of H.M. the Queen of
Figure 16.2 Opium-growing area in the Sam Mun Highland Development Project, by year (Limchoowong 1994).
Northern Thailand 371
Thailand since 1996 (Suan Pah Sirikit Project 2000). The Royal Forest Department
has a leading role in implementation through its ten watershed management units
in the area. The project philosophy is that people can live in harmony with the forest through community participation in conservation and forest resource development. Collaboration between villagers and government agencies in developing and
implementing local land use plans is viewed as essential to improving livelihoods
in ways that protect watershed headlands. Initial work began in response to rapid
deforestation after the end of a foreign-funded project in the late 1980s that, despite
major reductions in opium production and some useful innovations, had no lasting
positive impact on watershed management. The Suan Pah Sirikit project has built
on promising innovations and adapted several participatory methods and tools used
in the Sam Mun Project, along with experience from various Royal Projects and
other sources.
C a re -Th a il and Integrated Natural Resources
C o n s e rvation Project
The Integrated Natural Resources Conservation Project sought to conserve watersheds in the northern provinces of Chiang Mai (Mae Chaem district) and Mae
Hong Son that had been degraded by illegal logging, forest fires, and agricultural
expansion. From 1994 to 1999 the project worked with local communities to promote sustainable agriculture and the improved management of fragile watershed
forests. Project components included agroforestry, soil and water conservation,
paddy rice and fish pond development, and nonfarm income-generating activities.
Project partners included the Royal Forest Department, agencies of the Ministry of
Agriculture and Cooperatives, and the local governments. They also worked closely
with Chiang Mai University to study and implement approaches for promoting
community participation in sustainable land use. The project provided valuable
assistance during establishment of the asb Thailand benchmark site, and asb is
a partner in the implementation of their follow-on project focusing on strengthening local institutions associated with natural resource management launched in
2000.
O t h e r D evelopment and Conservation Projects
The asb Thailand is also seeking to learn from the experience of previous projects,
including the Thai–German Highland Development Project, the Thai–Australian
Highland Development Project, and the Thai–U.S. Agency for International Development Mae Chaem Development Project, and from other current efforts being conducted by Thai ngos, local groups, and government agencies.
372
National Perspectives
P RO M I S ING AGRICULTURAL INNOVATIONS
Drawing on experience of these projects, including numerous examples of ideas and
adaptations that came directly from farmers, among the most promising technical
approaches to improving livelihoods while reducing pressure on forest or watersheds
are those that focused on decreasing the area dedicated to upland rice production and
those that increased trees on the landscape.
M e e t i n g Food Securit y Needs with Less Area
D e d i c at ed to Rice Producti on
Three approaches have been proposed for meeting food needs while decreasing the
total area dedicated to food production, all of which presume that agricultural intensification will reduce pressure on forests.
Expanding Paddy Rice Production
Preliminary findings suggest that expansion of irrigated paddy rice land, in the small
niches where terrain and water resources allow, can greatly reduce land dedicated to
upland rice production. Given the higher productivity per hectare of paddy rice compared with upland rice, every hectare of paddy rice added can reduce by 10–20 ha the
amount of upland rice area needed to meet food needs, depending on paddy yields
and the length of the swidden fallow cycle. The response by farmers to paddy rice
incentives provided by the Sam Mun Project was substantial (Limchoowong 1994),
especially during the initial phase of the project (figure 16.3).
Figure 16.3 Paddy rice area in the Sam Mun Highland Development Project, by year (Limchoowong
1994).
Northern Thailand 373
Preliminary data from a range of sites in the asb benchmark watershed (Thomas
et al. 2002) indicate that paddy rice production is much more profitable than upland
rice production (in short fallow or permanent field systems), primarily because of high
labor needs for weeding, the cost of chemical inputs, and the low productivity and
higher variability of upland fields. Experiments have also been launched under asb
using new rice varieties to explore the possibility and potential impacts of doublecropping of rice in midland paddies.
Permanent Field Upland Rice Production
In areas in the Suan Pah Sirikit Project where terrain or water availability does not allow
sufficient expansion of paddy to meet local food needs, some farmers have developed a
crop rotation system for permanent upland fields in which upland rice is rotated with
soybean every third year. This has allowed farmers to reduce substantially the total area
needed for upland rice production and has also provided a new source of income from
the sale of soybeans. Land taken out of upland rice is converted to permanent community-protected forest. Farmers who have used this system for up to 10 years report
no decline in yields. Because of the need for purchased inputs (at least fertilizer and
herbicides), however, profitability is lower than in medium- to long-cycle forest fallow
systems. Although forest fallows as short as 5 years can be sustainable without chemical inputs (Wangpakapattanawong 2001), yields are much lower than those in 10-year
cycles (Thomas et al. 2002), which are now increasingly rare. Moreover, low soybean
prices have caused many farmers to switch to maize as their main cash crop; it is not
yet clear whether or how this substitution will affect sustainability or farmer incomes.
The asb Thailand is conducting agronomic and economic studies of this system.
Permanent Fields of High-Value Commercial Vegetables
This approach involves meeting food security needs by generating cash income and is
particularly suited to highland areas where the climate supports production of temperate zone vegetables. One example of this approach is the Ban Chan subdistrict of Mae
Chaem, where a project of the Royal Project Foundation has been operating for many
years (Royal Project Staff 1999). There, many villagers are producing high-value specialty vegetables that are marketed largely through the Royal Project. These intensive
systems use much less land than shifting cultivation, and although profits can be quite
high, crops suffer from periodic severe damage caused by pests and weather shocks.
Drastic price fluctuations also affect profits. Many villagers are responding to these
factors by diversifying their production into two or more crops (B. Ekasingh, unpublished data 1999), in some cases including fruit trees. Land use change in this area is
being studied in depth (Peters 2000), where traditional forms of shifting cultivation
are now quite rare and land ownership has largely been privatized. These and other
374
National Perspectives
cash crop systems with various degrees of diversification are also components of land
use patterns found in other areas of the watershed (Thomas et al. 2002).
But vegetable production can damage the environment. For example, highland
cabbage production has come under strong criticism because of planting on steep
slopes (and consequent soil erosion) and the heavy application of pesticides (and consequent water pollution) (Tangtham 1999). Projects are trying to introduce soil conservation practices and alternative pest management strategies, but with little success
so far (Royal Project Foundation 2002).
I m p rov i ng Livelihoods Through Agroforestry
There have been three major approaches to increasing the number of trees on midland
and highland landscapes.
Simple Agroforestry
This approach has centered on inducing farmers to plant fruit trees in fields, following approaches pioneered by the Royal Project. In the highlands, temperate zone
fruits such as Japanese apricot (Prunus mume Siebold & Zuccarini), Japanese plum
(Prunus salicina Lindley), Asian pear (Pyrus pyrifolia [N.L. Burman]), and persimmon
(Diospyros spp.) were introduced. In the midlands, subtropical fruits such as lychee
were introduced. Results of efforts to encourage fruit tree production in the Sam Mun
Project are presented in figure 16.4. These data probably understate the full impact
of agroforestry inducement efforts because many trees were also planted in areas that
Figure 16.4 Area in fruit trees in the Sam Mun Highland Project, by year (Limchoowong 1994). Temperates refers to temperate zone fruits (e.g., plums, apricots, pears).
Northern Thailand 375
were not included in agroforestry area tallies, such as around houses and along field
boundaries. Note that the gains were largest during the initial phase of the project;
further planting has continued after the end of the project. A preliminary asb study
of fruit tree agroforestry in Sam Mun Project areas reports a substantial range of strategies and planting configurations (Withrow-Robinson et al. 1998; Withrow-Robinson
2000).
Complex Agroforests
The primary example of an indigenous complex agroforest in northern Thailand is the
miang or jungle tea plantations embedded in hill evergreen forest (described in Preechapanya 1996, 2001). Although changing consumption patterns especially among
young consumers have decreased demand, prices for miang tea appear to have recovered from the low levels of the early 1990s, and many producers now claim that their
biggest problems are finding hired labor and fuelwood needed to process the tea. The
Sam Mun Project had some success in helping Karen producers manage debt and
obtain higher product prices.
An interesting variant of this system with potentially large implications for development projects has been observed among farmers in an area adjacent to the Sam
Mun Project area (Castillo 1990). There, farmers have gradually transformed miang
complex agroforests by substituting fruit trees and seed crops for many or most of the
forest and tea trees. During this process farmers are careful to maintain a very complex
structure that mimics the complexity of the original tea forest system (Tanpanich
1997).
Community-Managed Forests
This approach seeks to expand the area of permanent forest that local communities
protect and manage as components of their overall mosaic agroforestry landscapes
(Thomas et al. 2000, 2002; Thomas 2001). Efforts build on traditional concepts
and beliefs of midland groups (in particular) to find ways to maintain traditionally
conserved forest areas (Chammarik and Santasombat 1993), convert forest fallow in
fragile areas to permanent forest, or reforest degraded areas by planting trees or protecting areas where natural regeneration is occurring. In the context of the Sam Mun
Project, the forest department reforested 4855 ha using standard planting techniques.
Villagers responded by using these techniques to recover 242 ha but chose to protect
the natural regeneration of nearly 60,000 additional hectares (Limchoowong 1994).
The keys to the success of this approach were reaching a clear mutual agreement on
land use plans and establishing active community participation in controlling access,
use, fires, and other factors. Although the project was initially successful, researchers
and others are concerned that communities that switch from shifting cultivation to
376
National Perspectives
permanent forest cover will lose access to important natural products they obtained
from forest fallow fields during intermediate stages of regeneration (Thomas et al.
2002). Natural products are a strategically important livelihood component for many
mountain households (Nawichai 2000; Preechapanya 2001).
A fourth type of innovation quietly developed primarily by local farmers themselves is just beginning to emerge. Various examples of reduced-fallow upland rice
systems that use improved fallow management to maintain higher yields are being
documented and explored (Rerkasem et al. 2002).
P RO M I S ING INSTITUTIONAL INNOVATIONS
Although technological advances can help induce land use change, institutional
changes are also needed. Three important examples follow.
Land Use Planning
Pilot experiments have shown that it is possible to reach mutually acceptable land use
agreements between villagers and agency officials using participatory methods (Kaosaard 2000). Pioneering efforts under the Sam Mun Project developed the now widely
accepted approach known as participatory land use planning (plp). In the words of
its chief architect, “plp can be defined as an operational tool or process which creates
conditions of frequent communication and analytical discussions, hence strengthening local organizations by generating common understandings and shared rights and
responsibilities among project partners, who carry out activities that lead to the solving
of local forest management problems and other related community problems” (Tankim-yong et al. 1994:6). The conceptual framework of plp focuses on identifying and
resolving conflicts associated with natural resource management and development.
Establishing a broad set of objectives and setting in place institutions to achieve them
entails changes in the roles and responsibilities of stakeholders, both of which can
emerge as parties come to understand each others’ positions. Open access to information for all participants, involvement of a third party as moderator or facilitator, and
the presence of long-term community workers were all essential ingredients to success.
One overarching objective was to help upland villagers become active participants in
watershed forest protection rather than unwilling subjects of government control.
Once basic agreements were reached, villagers articulated their own sets of rules,
penalties for violation, and mechanisms for enforcement. Local penalties often included fines substantially higher than those imposed by lowland law, and communities
subsequently proved their willingness and ability to enforce their rules. When outsiders challenged village rules and their right to enforce them, local leaders sought assistance from project staff or local authorities.
Various tools were used to help facilitate this process and to document mutual
agreements that were reached. Particularly useful tools include scale contour maps and
Northern Thailand 377
scale three-dimensional models of the local landscape, which served as a centerpiece
for discussions and negotiations and as a clear and accessible record of changes in land
use zones and forest use rights that were established through mutual agreement. This
approach and its tools are being adapted and refined by various projects, including
those conducted by asb pilot project partners in Mae Chaem (Thomas et al. 2000,
2002).
Watershed Management Networks
With increased levels of upstream–downstream conflict over water use and quality
being encountered in many areas, projects and organizations are promoting watershed management networks. Projects have experimented with local, multivillage and
multi–ethnic group watershed management networks to coordinate land use management across areas that sometimes comprise several subwatersheds. Building on earlier
work, the Sam Mun Project facilitated the establishment of watershed networks and
encouraged groups to formulate their own rules, penalties, and enforcement mechanisms (Limchoowong 1994). The approach was basically an application of the plp
process at a broader scale and involved communities already familiar with plp at
village level. A recent study suggests that watershed management networks can be
institutionally sustainable even after project establishment funds and guidance are
withdrawn (Kaosa-ard 2000).
Constitutional and Legal Reform
Under the 1997 constitution and related legal reforms, opportunities are emerging
that may allow arrangements such as those being formulated and mapped using plp
to gain formal recognition. Examples include the constitutional provision for local
participation in natural resource management, a set of laws and programs to strengthen elected local governments, and community forestry legislation now under consideration by Parliament. Yet practical issues of implementation remain unresolved. For
example, it is not clear how to strengthen embryonic subdistrict governments often
found in poor mountain ethnic minority areas, nor have effective and efficient methods been discovered for agencies such as the forest department to interact with the
thousands of local government entities in these areas.
A S B I N THAIL AND
As we have seen, land use in northern Thailand is in transition. Although this transition has had some negative environmental consequences and conflicts between stakeholders are becoming more numerous and intense, a growing body of experience suggests that the ongoing land use transition can generate environmental and welfare
378
National Perspectives
benefits and that policy has a role in managing the direction and pace of change.
However, effective and efficient natural resource management is hampered by gaps
in knowledge and insufficient methods and tools. The Royal Forest Department has
given a mandate to asb Thailand to assist in addressing these issues.
To facilitate asb collaboration, the Royal Forest Department has officially established the Northern Mountain Area Agroforestry Systems Research and Development
Project, an open-ended project with a national steering committee and administrative
support. The project facilitates interdisciplinary, multi-institutional research by the
asb Thailand Consortium in subject areas of mutual interest in Thailand, collaboration with international researchers, and information exchange (Thomas 2002). The
asb Thailand seeks to build on existing knowledge and experience, to strengthen
ongoing research and development efforts by identifying and filling strategic gaps
in knowledge, and to undertake pilot project testing to improve policies and expand
adoption of promising approaches. Particular emphasis is on landscape agroforestry
in upper tributary watershed areas (Thomas 2001). Key partners in the Mae Chaem
watershed include the Suan Pah Sirikit Project and the Collaborative Natural Resources Management Project launched by Care-Thailand and the Raks Thai Foundation.
The asb Thailand consortium expects to make major contributions in five areas.
M e a s u ri ng and Predicting the Costs, Benefits,
a n d Tr a deoffs of Land Use Change
One of the key weaknesses of pilot efforts to improve land use technologies has been
the lack of data on their effects on local livelihoods or environmental services (watershed services, biodiversity, and climate change). These data are essential for measuring the tradeoffs between these societal objectives and for assessing the prospects for
longer-term sustainability. Moreover, this information is critical for formulating and
justifying changes in land use and forestry policies. Therefore, the first stage of asb
Thailand’s research activities has focused on providing such data by completing the
asb matrix for important and emerging land use systems in northern Thailand (Buddhaboon 2000; Gillison and Liswanti 2000; Thomas et al. 2002).
A d d re s s ing Policy Issues at the Landscape Scale
The second major asb research activity focuses on scaling up these analyses to levels
that are ecologically, economically, and politically relevant for mountain areas of northern Thailand. At this more aggregate level, broader land use mosaic patterns become
relevant, and the socioeconomic and biophysical interactions that occur at that level
become parts of the research agenda. One study of two villages in the Sam Mun Project
found that although villagers perceived substantial improvement in forest components
of their landscape over the past decade, water and wild animals have become more
Northern Thailand 379
scarce, prompting farmer concerns regarding future food and economic security (Kaosa-ard 2000). Access to natural products was a factor that interacted with various forms
of social capital in shaping the response to and impact of the Asian economic crisis on
mountain households and communities in Mae Chaem (Geran 2001).
Expanding on pioneering work (Ekasingh et al. 1996), studies in several subwatersheds of the asb site with different land use mosaics are being conducted. One of
the next major tasks will be to identify suitable criteria for assessing livelihood and
environmental impacts and potential carrying capacities of major types of land use
mosaics. These criteria must be associated with standards that accurately reflect management goals and indicators that can be used to assess current status and progress
toward meeting those goals. We also seek to understand the socioeconomic, biophysical, and political factors that influence the establishment and maintenance of major
land use mosaics (Thomas et al. 2002). A geographic information system (gis) for
the asb Thailand benchmark watershed is in place (Thomas et al. 2000). Future work
will use this system to develop and validate analytical models capable of predicting the
effects of policy and technology changes on the adoption and performance of alternative land use mosaics in agroforestry landscapes.
I n f o rm at ion Systems to Support Land Use Pl anning,
Wat e r s h ed Net works, and Local Governance
The third major area of activity is to develop and test methods to support local institutions, government agencies, and ngos involved in the development and implementation of land use plans and watershed management networks (Kaosa-ard 2000). Particular emphasis is placed on establishing criteria for use in negotiating, establishing, and
monitoring local land use agreements developed using plp; developing and disseminating simple tools based on science and local knowledge to measure effects of land
use change on watershed functions at local level for use in resolving local disputes and
documenting local conditions; and developing information systems to monitor compliance and provide transparency and accountability in enforcing land use agreements
and to monitor welfare and environmental conditions. Pilot efforts have developed a
simplified gis node in Mae Chaem to link plp land use maps with asb’s gis system
in Chiang Mai to support ongoing local planning activities and to monitor compliance with existing local land use agreements in upper watershed areas. An expanding
number of local pilot watershed management networks in Mae Chaem are also using
basic tools to monitor watershed functions (Thomas et al. 2000, 2002).
M ov i n g Beyond the Benchmark Site
In collaboration with the Royal Forest Department and other organizations and agencies, asb Thailand will provide technical support for the formulation and implemen-
380
National Perspectives
tation of larger-scale pilot activities beyond the benchmark site. The primary objective
of this activity is to improve the capacity of the forest department and related natural
resource management groups and institutions to design, implement, and assess the
impacts of programs throughout Thailand.
I n t e rn ational Research Coll aboration
a n d I n f ormation Exchange
The final major area of asb activity aims to facilitate information exchange and collaboration with groups conducting related work in neighboring countries of mmsea
and at other asb sites (Thomas 2001, 2002). Our vision is to help strengthen Thailand’s ability to function as a peer-to-peer node, both contributing to and benefiting
from the emerging global web of scientific infrastructure aimed at addressing rural
poverty, land use, and environmental issues. The Royal Forest Department is working
closely with the International Center for Research in Agroforestry and asb Thailand
to further develop and strengthen specific partnerships and activities to accomplish
this goal.
C O N C LUSION
Land use in upper tributary watersheds in northern Thailand is in transition. Ecological and cultural diversity in these mountainous areas have led to the development
over many years of altitude zone–specific traditional land use systems that comprise
both permanent and shifting agriculture practices alongside and within forests. An
array of local, regional, national, and international factors have combined recently to
put pressure on these traditional systems and landscapes. In response, land uses are
changing, and the poor in these areas may not be prepared to manage or benefit from
these changes. Indeed, little is known about how to improve traditional systems and
practices in the zones for which they were developed, and perhaps more important,
we cannot predict the environmental and human welfare consequences of agricultural
activities suited for one zone but being practiced in another. In addition, there is growing concern about the downstream environmental and other consequences of land use
change in upland landscapes. Although some pilot development projects are demonstrating the effectiveness of participatory approaches to improved land use management in these areas and the environmental and welfare benefits of certain types of land
use change that can emerge, there is still inadequate knowledge to assess the feasibility
and implications of efforts to replicate or scale up these approaches. Mechanisms to
monitor and assess their longer-term impacts and effectiveness over large areas are
not in place. Finally, the role of government and civil society at all levels in managing land use transitions in the mountainous areas must be reviewed and refined. The
asb’s research, capacity strengthening, and outreach activities in Thailand address
these issues.
Northern Thailand 381
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v. c ro s s - s i t e co m pa r i s o n s
a n d co n c lu s i o n s
17 Land Use Systems at the Margins
of Tropical Moist Forest
addressing smallh o l d e r co n c e r n s
in cameroon, indo n e s i a , a n d b r a z i l
Stephen A. Vosti
University of California Davis, California
James Gockowski
International Institute for Tropical Agriculture Yaoundé, Cameroon
Thomas P. Tomich
World Agroforestry Centre Nairobi, Kenya
A
primary objective of Alternatives to Slash and Burn (asb) research is
to identify new combinations of policies, technologies, and institutions
capable of simultaneously promoting three fundamental development objectives: poverty reduction, economic growth, and environmental sustainability
(Vosti and Reardon 1997; Tomich et al. 1998b; World Bank 2001). To be
successful in this effort, we must first understand why the currently predominant land use systems (luss) are more attractive to smallholders than existing alternatives. We must then measure the environmental and other consequences of each lus. Then, if currently predominant luss are judged to be
unsatisfactory with respect to one or more of the three objectives, alternative
luss must be identified or developed. Finally, policymakers will need guidance regarding how to promote alternative luss: which policy instruments
and institutional mechanisms should be used, how much policy action probably will be needed, and for how long this action will be needed to achieve
and sustain desired changes.
Research aiming to address these issues must focus on the concerns of
resource users, that is, farmers or farm managers charged with allocating scarce
resources to best achieve household or firm objectives (Vosti and Witcover
1996; Reardon and Vosti 1997). Therefore, for a subset of the asb metalus, this chapter shifts the focus from environmental and agronomic issues
to economic issues and the incentives and constraints faced by agriculturalists
who manage and depend on the lus for household food security, livelihoods,
and profit.
The next section defines farmers’ concerns more precisely and describes
how the performance of specific luss with respect to farmers’ concerns was
388
Cross-Site Comparisons and Conclusions
systematically measured across all asb sites. We then report assessments of lus performance and labor needs and examine market-related impediments to the adoption
of existing and alternative luss at asb benchmark sites in Cameroon, Indonesia, and
Brazil. The next section makes cross-site comparisons of luss and broader issues that
influence lus choice. The final section forecasts lus adoption trends for each benchmark site.
M E T H O DS
D e f i n i n g Land Use Systems
Ranges of Land Use Systems
Deforestation is a primary concern at all benchmark sites, so for analytical purposes
natural forest was considered the point of departure for all land uses. Grasslands,
short fallow–cultivation systems, and pastures were included as reference points at
the opposite ecological extreme. In between, a range of luss representative of systems
at each site were selected: extraction of forest products; complex multistrata agroforestry; simple tree crop systems, including but not limited to monoculture; fallow–
cultivation systems, which include the textbook version of shifting cultivation or slashand-burn agriculture; continuous annual cropping systems, which may be monocultures or mixed cropping; and cattle production systems. This array of luss covers a
gradient of meta–land uses often used by biophysical scientists to describe varying
levels of disturbance of forest for purposes of agriculture (nrc 1993; Ruthenberg
1980; Angelsen and Kaimowitz 2001).
Spatial Issues
The spatial scale at which luss are practiced can vary across systems and, for given systems, over time and across farmers or firms. To deal with this important issue, for each
system at each site the observed (or projected) scale of general operation was identified and used in evaluating system performance and resource needs. For example, at
one extreme, the short-fallow food cropping system in Cameroon was evaluated at an
operational scale of 0.25 ha, whereas community-based managed forestry in Indonesia
was evaluated at an operational scale of 35,000 ha. However, to allow for cross-system
and cross-site comparisons, all reporting is done on a per hectare basis.
Temporal Issues
Finally, luss vary in terms of their active growing periods, the number of times particular components of luss can be repeated on a given piece of land, and the necessary
Land Use Systems at the Margins of Tropical Moist Forest
389
fallow periods. In order to correctly compare the performances and requirements of different luss, these temporal issues had to be considered explicitly and adjustments made
to ensure that performances were measured over the same time horizons. For example,
to compare a coffee production system with a 20-year cycle to a swidden agricultural system with a 10-year cycle, the latter’s performance must be measured and appropriately
discounted because given the choice between volumetrically identical harvests at two
different points in time, farmers will always choose the earlier of the two cycles.
M e a s u ri ng Farmers’ Concerns
A set of three socioeconomic parameters were used to assess luss from the smallholders’ perspective: financial profitability, labor needs, and household food security
(Tomich et al. 1998a, 1998b; Vosti et al. 2000). The results in this chapter rely heavily
on Gockowski et al. (2001), Tomich et al. (2001), and Vosti et al. (2001b).
Financial Profitability
Land use systems that generate inadequate profits will not be attractive to farmers.
Financial profitability considers all establishment costs, and all cost and benefit streams
associated with the production activities of each lus, over the lifetime of each system.
It then discounts these cost and benefit streams to arrive at summary measures (e.g.,
net present value [npv], used in this analysis) that can be used to compare luss across
and especially within benchmark sites. Private prices, those actually faced by farm
households, are used in most npv calculations presented here. Summary measures
of financial profitability can be expressed in many ways; we express them in terms of
two inputs critical to small-scale agriculturalists: returns to land and labor, reported in
1996 U.S. dollars. Returns to land represent the present discounted value of the net
profits from land dedicated to a specific lus, that is, the per hectare return a farmer
would expect to earn from land allocated to a particular lus, taking into account the
stream of costs and benefits over time and valuing family labor used in that system at
the market wage. Returns to labor represent the daily wage for family labor input to
a system, that is, the average, daily wage that each family member involved in a given
lus could expect to earn from participating in it if all profits were distributed to family members as wages. Returns to labor that exceed the market wage suggest that an
lus will be attractive to family members or would justify hiring labor to operate it.
For these asb sites it is important to point out that the costs and benefits of commercial logging operations that clear forest for agriculture are not included in the calculations of the returns to the lus at some sites because the one-time value of timber
extracted as a byproduct of land clearing often exceeds the value of the derived land use
and would obscure differences in profitability between the derived land uses. Moreover,
in most cases smallholders do not reap the full benefits of timber extraction.
390
Cross-Site Comparisons and Conclusions
Labor Needs
In labor-scarce rural economies or where labor markets are underdeveloped, labor
needs are an important determinant of lus attractiveness. The luss that continually
entail more labor input than a typical rural household can provide or hire may not be
attractive, especially if these systems provide low returns to labor. Of primary concern
for asb was the labor input needed to maintain a given lus once established, so the
adopted measure of lus labor needs was the time-averaged labor input (measured in
person-days) during the operational phase. Moreover, competition for family labor
between traditional cropping systems and alternative luss can exist; if this competition was likely to be substantial, labor need numbers appearing in the tables in this
chapter were set in boldface type. Labor needs for establishing some luss can also be
very high and therefore reduce system overall attractiveness; data on labor needed for
lus establishment are available but are not presented here.
Household Food Security
Even if an lus is financially profitable and feasible given household labor constraints
and labor market conditions, it may be too risky either in terms of variability in food
yields or as a source of income to exchange for food. To identify luss for which
increased food security risk might be an issue, we adopted an indicator based on Sen’s
(1982) concept of risk of food entitlement failure that encompasses trade-based and
production-based entitlements to food. A system of indicators identifies the key paths
households adopting a particular lus would use to gain access to food: Is food derived
from one’s own production, is food purchased with the proceeds of the production
and sale of nonfood commodities or wage labor, or is access to food accomplished via
some combination of the two paths? Once paths are identified, cross-lus comparisons
of food access can be made.
Po l i c y Distortions, Institutional Issues,
a n d M a rket Imper fections
Although the aforementioned measures of the farmer concerns capture a great deal of
the relative attractiveness of the different luss, they must be supplemented by assessments of distortions of incentives arising from national policies and assessments of the
institutional setting, especially as regards markets for land, labor, capital, and commodities. For all these cases, trade and marketing policies affect prices received and
paid by smallholders (often negatively) compared with what they would receive under
free trade. These policy distortions of incentives are examined in detail in Gockowski
et al. (2001) for Cameroon and Tomich et al. (1998b) for Indonesia. Assessment of
Land Use Systems at the Margins of Tropical Moist Forest
391
the institutional setting is critical in developing countries for two reasons. First, markets are notoriously imperfect in rural areas and therefore can limit the robustness of
standard quantitative assessments; for example, if capital markets routinely fail and
credit is needed to establish some luss, our estimates of returns to land and labor for
these luss may be overstated. Second, because of structural adjustment policies and
changing world trade regulations, national policymakers are less able to use blunt trade
policies and therefore must rely increasingly on investments in institutions and organizations to promote development objectives (World Bank 2001). Consequently, cashpoor policymakers need guidance in setting institutional or organizational investment
priorities, which can include support to fledgling organizations created to compensate
for market failures.
As a first step in identifying luss that were likely to suffer from market imperfections,
experts familiar with rural institutions at each benchmark site evaluated luss in regard
to their dependence on input supply, output, labor, and capital markets and the ability
of local and regional markets to meet the challenges posed by the potential expansion of
given luss. What emerged was a series of market-specific flags (linked, respectively, to the
markets just listed and abbreviated as I, O, LB, and K in tables 7.1 through 7.3) indicating
that large problems with particular markets were likely to exist. Less important but still
significant market-related problems are identified using lowercase letters.
Cross-LUS Comparisons Using Policy Analysis Matrix
The policy analysis matrix (pam) technique, originally developed by Monke and
Pearson (1989), is the basis for calculating lus financial profitability and comparing
multiyear lus budgets. We augment the pam with lus-specific labor needs, indicators for food security, and institutional concerns. The matrix framework used here to
evaluate luss specifies lus trajectories, including technology, land area, and time line
associated with each system (matrix rows); defines indicators corresponding to different farmer concerns (matrix columns); and presents measurements of how well each
selected lus addressed each of the farmers’ concerns (matrix cells). It should be noted
that the matrices for each site take as given the agricultural and other policies in place
at the time the analysis was performed and the socioeconomic conditions prevalent at
the time and place of analysis (Vosti et al. 2000).
R E S U LTS FROM ASB BENCHMARK SITES
In this section we present evidence on the financial profitability, labor needs, and
market-related obstacles to adoption of selected luss at the three benchmark sites. For
each site, we begin with a brief description of luss, present research results in pam
form, and discuss the implications of these results.
392
Cross-Site Comparisons and Conclusions
C a m e ro on
Land Use Systems
Eight luss were evaluated and compared in the Cameroon benchmark area; two dominant slash-and-burn systems (listed first) involving crop–fallow rotations that together
account for approximately 75 percent of all annual and biennial cropland (Gockowski
et al. 1998) and six alternative perennial-based systems practiced at different levels of
intensity and frequency and are described more thoroughly in chapter 14.
• Intercropped food field planted after a short (4-year) Chromolaena odorata (L.)
R.M. King and H. Robinson fallow (abbreviated as “SF–annual food crop”). This
semicommercial system is the most common lus in the forest zone of Cameroon, is
agronomically and commercially managed by women, and provides the bulk of the
food consumed by households practicing it.
• Intercropped food field planted in a long fallow (“LF–forest crop field”). This
lus, comprising melonseed (Cucumeropsis mannii Naudin), plantain (Musa spp.),
maize (Zea mays L.), and cocoyam (Xanthosoma sagittifolium Schott), all cultivated in
a 15-year fallow field, became a major commercial alternative for cocoa farmers when
cocoa prices collapsed in 1989.
• Intensive cocoa with mixed fruit tree shade canopy planted after a short (4-year)
Chromolaena fallow (“SF–intensive cacao w/fruit”). This cacao-based system includes
avocado (Persea americana Miller), mango (Mangifera indica L.), African plum (Dacryodes edulis [G. Don] H.J. Lam), and mandarin orange (Citrus reticulata Blanco), all
of which can provide significant secondary revenues when location permits access to
urban markets (Duguma et al. 2001).
• Intensive cocoa with shade canopy planted after a short (4-year) Chromolaena
fallow (“SF–intensive cocoa w/o fruit”). This is essentially the same lus as the shortfallow intensive cacao with fruit, except that fruit trees are not a commercial component because of limited market access.
• Extensive cocoa with mixed fruit tree shade canopy planted to forest land or
long fallow (“FOR–extensive cocoa w/fruit”). This system represents the extensive
cocoa production systems more characteristic of the less populated areas of the benchmark site that enjoy good market access.
• Extensive cocoa with shade canopy planted to forest land or long fallow (“FOR–
extensive cocoa w/o fruit”). This is essentially the same lus as extensive cocoa with
fruit except that fruit trees are not a commercial component.
• Improved Tenera hybrid oil palm (Elaeis guineensis Jacq.) system planted after a
short (4-year) Chromolaena fallow (“SF–oil palm”). In this lus, oil palm is established
in a 4-year Chromolaena odorata fallow with intercropped groundnuts, maize, leafy
vegetables, and cocoyams during the first year; after the food crops are harvested a
monoculture oil palm of the hybrid Tenera remains.
Land Use Systems at the Margins of Tropical Moist Forest
393
• Improved Tenera hybrid oil palm system planted to forested land or long fallow
(“FOR–oil palm”). As in the case of short-fallow –oil palm, hybrid Tenera oil palm is
produced in a monoculture. In this case, however, forested land is converted.
Land Use System Evaluation and Performance
Financial Profitability: Returns to Land
The more lucrative perennial crop systems tended to strongly dominate the two slashand-burn systems (table 17.1, column 3). The npvs per hectare were $283 and $623
for the traditional long- and short-fallow intercropped food systems, respectively, compared with $1409 and $1471 for the intensive cocoa and mixed fruit tree system and
the hybrid oil palm system in forested land, respectively. Among the perennial crop
systems, the extensive cocoa system was least profitable at $424 per hectare. Because
per hectare profitability is measured on an annual basis and includes the fallow period,
annual profitability of the slash-and-burn systems is significantly lower.
Financial Profitability: Returns to Labor
The highest returns to labor were found in the oil palm system planted in forested
land ($2.44 per person-day) and in the intensive cocoa system with fruit trees ($2.36
per person-day). (See table 17.1). Returns to labor in intensive cocoa with no fruit
($1.95 per person-day) and in the extensive cocoa with fruit ($2.13 per person-day)
were similar to the official minimum wage ($2.17 per person-day for unskilled manual labor). Returns tended to lie below the official minimum wage for the short-fallow
annual food crop system ($1.79 per person-day), the long-fallow forest crop field
system ($1.70 per person-day), the extensive cocoa system without fruit ($1.63 per
person-day), and the short-fallow oil palm system ($1.81 per person-day). Although
the absolute differences in labor returns do not seem to be very substantial, the difference between the highest and the lowest return is about 40 percent.
This static view of financial profitability masks price volatility that characterizes
agricultural and world commodity markets. For example, in 1997 the average farmgate price per kilogram of cacao in southern Cameroon varied from 600 to 700 Central African francs (fcfa), whereas in 1996 producers received 350 to 400 fcfa per
ton. At 400 fcfa per ton of cocoa, the return to labor for the short-fallow intensive
cocoa system with fruit fell to $1.58 from $2.36 per person-day.
Labor Needs
Person-days of labor needed to operate a hectare of each selected lus, once they are
established, are presented in table 17.1. The systems using the least labor are the
extensive cocoa without fruit (43 person-days/ha/yr) and the long-fallow forest crop
field (44 person-days/ha/yr). The labor needs of the crop–fallow system are averaged
over the entire rotation and therefore are artificially low in table 17.1. If one were to
consider only the cropping phase, it would take 731 person-days of labor per hectare
Table 17.1 Land Use System Performance and Resource Inputs at the Cameroon Site
Land Use
System
Financial Profitability a
SF–annual
food crop
LF–forest
crop field
SF–intensive
cocoa w/fruit
SF–intensive
cocoa w/o
fruit
FOR–
extensive
cocoa w/fruit
FOR–
extensive
cocoa w/o
fruit
SF–oil palm
FOR–oil
palm
Labor
Needs
Household
Food
Security
Institutional
Issues
Scale of
Returns to Returns to
Operation Land
Labor
(ha)
( $/ha) (wage setting
0)
( $/person-day)
Market
Operational Food
Phase
Entitlement Imperfectionsc
(person-day/ Paths b
ha/yr)
0.25
623
1.79
115
op, ex
lb
0.25
283
1.70
44
op, ex
o, lb
1.30
1409
2.36
97
op, ex
I, o, lb, K
1.30
889
1.95
95
op, ex
I, o, lb, K
1.30
943
2.13
46
op, ex
i, o, k
1.30
424
1.63
43
ex only
i, o, k
1.00
1.00
736
1471
1.81
2.44
71
73
op, ex
op, ex
I, O, lb, K
I, O, lb, K
A discount rate of 10% was used, and the opportunity cost of household labor was set at $1.21 per day. The
local currency unit (f ) was converted at rate of 1 $ 577 f . Each proposed system’s socioeconomic
indicators are based on optimistic yield parameters. Sensitivity analyses to establish lower ranges of profitability
figures and to check robustness of results to observed swings in relative output prices and a range of discount
rates are ongoing.
b
For food security, “own production (op)” and “exchange (ex)” reflect whether the system generates food for
own consumption or income that could be used to buy food; combined food entitlement paths are common.
c
For institutional issues, letters indicate market imperfections judged to constrain adoption (with uppercase indicating a serious problem and lowercase indicating a more minor difficulty), as follows: i, input markets;
o, output markets; lb, labor markets; k, capital markets.
Source: Data derived from Gockowski et al. (2001).
a
Land Use Systems at the Margins of Tropical Moist Forest
395
to cultivate the long-fallow field crop, which helps to explain the small size (2500 m2)
of the cultivated plots. The short-fallow annual food crop system and the intensive
cocoa with fruit made the most intensive use of labor (115, which includes the 6 years
of fallow, and 97 person-days/ha/yr, respectively). The extensive cocoa systems were
the least labor demanding, at roughly half the labor needs of the intensive systems, and
the oil palm systems were intermediate between the two types of cocoa-based lus.
Household Food and Health Security
In many areas of the Congo basin, rural food markets either do not exist or, if they
do, are often periodic, and access is limited by transportation costs. As a consequence,
most households at this site rely on own production to meet food needs. Household
food security usually is not a major concern because of stable rainfall patterns and the
safety net provided by extended kinship groups. In essence, the short-fallow annual
food crop lus provides the bulk of food consumed in the household and usually is
planted with subsistence objectives paramount and commercial objectives only secondary (Gockowski and Ndoumbé 1999). The same subsistence objective is largely
true of the long-fallow forest crop field. With one exception, that of extensive cocoa
without fruit, all luss at the Cameroon benchmark site contributed directly (via own
production) and indirectly (via production sales) to meeting food needs.
Institutional Issues: Market Imperfections
The performance of input, output, labor, and credit markets exhibit wide geographic
variation within the benchmark site, and luss vary in terms of purchased input intensity. That said, some consistent patterns regarding institutional obstacles to adoption
emerged (table 17.1). The intensive cocoa systems are the most dependent on the reliable supply of agrochemicals. Intensive cocoa systems with fruit trees presume good
access to urban fruit markets. In areas where access to market is difficult, the profitability of these systems will consequently decline. Labor market imperfections affected
all intensive cropping systems.
Of note is that the oil palm systems face several market-related obstacles to broad
adoption. First, the performance of these luss depends on the multiplication and
distribution of hybrid palm varieties. Current capacity in Cameroon for producing
pregerminated hybrid oil palm seed is low and in the hands of only a few suppliers,
so prices are high ($0.42 per seed). By the time the seedling has spent a year in the
nursery, farmers can expect to spend up to $400/ha on planting material alone. Second, three levels of postharvest processing technologies are commonly used: artisanal
methods requiring almost no capital investment, small-scale manual and motorized
turnscrew presses with some capital investment, and large-scale industrial processing
with high capital investment. As operational scale increases, market development and
market access become more critical. Third, export restrictions on palm oil during the
dry season period drive down producer prices.
An additional constraint is that poorly maintained rural road networks in Central
Africa contribute to high marketing margins that can lower farmgate prices in areas
396
Cross-Site Comparisons and Conclusions
distant from markets (e.g., low-value, bulky fruits from cocoa agroforests) to the point
that these enterprises are no longer commercially viable. The high costs of marketing
in Central Africa reduce its competitiveness in world markets, with negative implications for consumer and producer welfare and the adoption of agroforest-based luss.
I N D O N ESIA
Land Use Systems Evaluated
The eight Sumatran land use systems examined in this section are presented here.
For an overview of luss, the driving forces that promote and sustain them, and their
environmental consequences, see van Noordwijk et al. (1995), Tomich et al. (1998b),
and Tomich et al. (2001).
• Natural forest. These forests, though generally not pristine, have been undisturbed for at least 100 years and are not currently used for economic purposes. They
serve as the reference point for assessing alternative luss, although they no longer are
common in the benchmark sites in Sumatra.
• Community-based forest management. This lus is practiced on 10,000- to
35,000-ha blocks of common forest land managed by indigenous smallholders.
• Commercial logging. Concessions of 35,000 ha or more are logged for timber
using a system based on a 20- to 25-year cycle that is generally practiced but probably
does not meet sustainable logging criteria.
• Rubber agroforests. This is the dominant smallholder lus and is an integral
part of an indigenous landscape mosaic. One- to five-hectare plots of forest or existing
rubber (Hevea brasiliensis) agroforest are cleared, and the land is planted to upland rice
(Oryza sativa L.) and unselected rubber seedlings, with natural regeneration of forest
species.
• Rubber agroforests with improved planting material. This is an experimental
lus based on traditional rubber agroforests but with the introduction of rubber clones
with higher yield potential. One- to five-hectare plots were planted to upland rice and
rubber clones, with regeneration of natural forest species.
• Oil palm monoculture. Practiced on estates of 35,000 ha or more, plantation
oil palm is grown with substantial use of purchased inputs and wage labor, in close
association with processing plants.
• Upland rice–bush fallow rotation. This shifting cultivation lus was once practiced by most smallholders on 1- to 2-ha plots on community land as part of an indigenous landscape mosaic but is now almost nonexistent. The version of this lus examined here consists of 1 year of upland rice followed by a short bush fallow of 5 years.
• Continuous cassava degrading to Imperata grasslands. Aside from irrigated rice
production, continuous annual cropping is rare in Sumatra except in transmigration
settlement sites. Estimates for continuous cassava (Manihot esculenta Crantz) mono-
Land Use Systems at the Margins of Tropical Moist Forest
397
culture degrading to Imperata cylindrica L. are reported here for comparison with
other asb sites. Smallholders cultivated 1- to 2-ha plots of monocrop cassava with
little use of purchased inputs.
Land Use System Evaluation and Performance
Financial Profitability: Returns to Land and Labor
For the food crop systems, the upland rice and bush fallow rotation stands out as being
unprofitable (negative us$62/ha), which helps explain its disappearance in most of
Sumatra’s peneplains. Cassava, on the other hand, may be among the most profitable of the technically feasible continuous food crop alternatives for the peneplains
(us$60/ha), but its longer-run sustainability warrants further study (van Noordwijk
et al. 1997b; chapter 6, this volume).
Returns to labor are highest for community-based forest management (extraction
of nontimber forest products (ntfps; us$4.77/d), but these high returns depend on
the ability of existing local communities to regulate access and exclude outsiders. The
low returns to land, us$5/ha, suggest that ntfp extraction is not a feasible alternative
for large numbers of people because there is not enough land for everyone to practice this extensive livelihood strategy. These results should be interpreted with care
because not all extractive activities were accounted for, which may bias profitability
estimates downward. In particular, timber extraction (currently illegal and hence not
reported) is likely to be significant, and tenure insecurity on State Land might have
biased reported offtake of ntfps. On the other hand, long-run profitability may be
overstated because of unsustainable harvesting.
Several profitability estimates for commercial logging can be calculated, depending on the degree of compliance with government regulations. However, companies
circumvent regulations on timber extraction, and most typically are vertically integrated firms producing products such as plywood for the export market. Therefore,
the best profitability estimate for commercial logging is $1080/ha, valued at social
prices that reflect world prices of forestry products.
Oil palm is widely viewed as the most profitable alternative for Sumatra’s peneplains, and Indonesia’s oil palm producers have the lowest unit costs in the world.
Thus, it is no surprise that large-scale oil palm monoculture is among the most profitable alternatives in terms of returns to land and returns to labor, both of which are
indicators of firm-level profitability, because the official wages for plantation workers
are well below our estimates of returns to labor.
The two contrasting rubber agroforest systems produce a wide range of results. It
is encouraging that returns to labor are almost identical to the market wage ($1.67 per
person-day) for rubber agroforests planted with seedlings. Although these smallholders are the lowest-cost producers of natural rubber in the world (Barlow et al. 1994),
returns to land at private prices are not much higher than for upland rice with a long
bush fallow rotation and are well below those of oil palm monoculture.
398
Cross-Site Comparisons and Conclusions
Perhaps the most striking result in table 17.2 is the returns to land for rubber
agroforests planted with PB 260 clones, which exceed those of large-scale oil palm
monoculture (us$878 vs. us$114/ha). This system also produces attractive returns to
labor. These are based on projections from farmer-managed trials and therefore should
be interpreted with caution. However, these results support the idea that potential
profitability of rubber agroforests planted with clonal material (and other smallholder
agroforests planted with appropriate, higher-yielding germplasm) may be comparable
to large-scale oil palm plantation monoculture.
Labor Requirements
For the rubber and oil palm systems evaluated, total time-averaged labor needs are
similar, ranging between 108 and 150 person-days/ha/yr. Harvesting labor is the biggest component in these systems. Because of lack of pronounced seasonality in much
of Sumatra, harvesting of rubber and oil palm can go on roughly 10 months a year.
The two extractive activities—community-based forest management and commercial
logging—fall at the opposite extreme, with less than 1 person-day per hectare per year.
Neither of these extractive activities nor the upland rice–bush fallow rotations, using
31 person-days/ha/yr, can provide many employment opportunities.
Household Food Security
A wide range of household food entitlement paths were identified for Sumatra,
from complete dependence on wage labor (commercial logging) to complete selfsufficiency in food production (upland rice production). The norm for Sumatran
smallholders falls between these extremes, with some production for household
food consumption supplementing income earned from sale of export commodities
such as rubber.
Institutional Issues: Market Imperfections
input supply markets
Markets for planting material are the greatest barrier to adoption of profitable alternatives by smallholders, as indicated by I in the final column of table 17.2 for clonal
rubber and oil palm. For example, the Treecrops Advisory Service, almost the sole
provider of rubber budwood, has focused its efforts on supplying planting materials to settlement project participants in the past and has largely ignored the much
larger number of nonparticipants (Tomich 1991). The private nursery industry has
only begun to develop in a few areas of Sumatra. For public and private sources
alike, there are serious problems of reliability of quality of planting material, which
is difficult to assess until several years after planting. Current delivery pathways for
improved planting material and the information needed to use it seem inadequate,
but direct government intervention to supply germplasm may be neither feasible nor
desirable.
op, ex
98–104
60
1- to 2-ha plots within
settlement project/1 ha
ex
op
108
15–25
o, K
I, o, K
—
O, K
—
I, k
NA
o
Market
Imperfectionsc
Institutional Issues
NA, not applicable.
a
A discount rate of 15% was used, and the opportunity cost of household labor was set at $1.67 per day. The local currency unit (Indonesian rupiah) was converted at rate of 1 $
Rp2400 (June 1997). Sensitivity analyses to establish lower ranges of profitability figures and to check robustness of results to observed swings in relative output prices and a range
of discount rates are ongoing.
b
For food security, “own production (op)” and “exchange (ex)” reflect whether the generates food for own consumption or income that could be used to buy food; combined
food entitlement paths are common.
c
For institutional issues, letters indicate market imperfections judged to constrain adoption (with uppercase indicating a serious problem and lowercase indicating a more minor
difficulty), as follows: i, input markets; o, output markets; lb, labor markets; k, capital markets.
d
Social prices were used in the case of commercial logging (see text).
Source: Data are derived from Tomich et al. (1998b, 2001).
1.78
4.74
1.47
114
(62)
35,000-ha estate
1- to 2-ha plots
Wages
ex
ex
31
111
150
0.78
1.67
2.25
1080d
0.70
878
NA
op, ex
0
0.2–0.4
0
4.77
0
5
Natural forest
Community-based
forest management
Commercial logging
Rubber agroforest
Rubber agroforest w/
clonal planting material
Oil palm monoculture
Upland rice–long bush
fallow rotation
Continuous cassava
degrading to Imperata
Food Entitlement
Paths b
Time-Averaged
Labor Input
(person-day/ha/yr)
Returns to Labor
( $/d,
at private prices)
Returns to Land
( $/ha,
at private prices)
Household Food Security
Labor Requirements
Profitability a
25-ha fragment
35,000-ha common
forest
35,000-ha concession
1- to 5-ha plots
1- to 5-ha plots
Scale of Operation (ha)
Land Use System
Table 17.2 Land Use System Performance and Resource Inputs at the Sumatra Site
400
Cross-Site Comparisons and Conclusions
output m arkets
Government restrictions on marketing and international trade are the greatest barriers
to development of smallholder timber-based alternatives and also hinder communitybased forest management. Export promotion and job creation were the official rationale
for these restrictions, but the main results were rent seeking and inefficiency. In 1998,
the Indonesian government agreed to begin deregulation of timber exports, to abolish joint marketing associations that functioned as cartels, and to end export quotas
and numerous other restrictive marketing arrangements. As export taxes are gradually
reduced, private firms should be free to trade timber, but local restrictions on timber
trade continue to be significant barriers.
Previous restrictive marketing practices also damaged most timber companies’
marketing capacity by inhibiting development of marketing networks that could
respond to buyers’ needs. The situation is particularly bad for rattan because the
export ban on raw rattan destroyed overseas markets and induced importers to seek
alternate supplies.
In a largely ineffective quest to stabilize cooking oil prices, oil palm also has been
subject to export taxes (set at 60 percent through the end of 1998) and at times to
export bans that seriously depressed farmgate prices (Tomich and Mawardi 1995). For
oil palm and cassava there also are some concerns about the structure and performance
of local markets that are needed to link smallholders with processors. However, competitive market links seem to be emerging.
Local markets for natural rubber have functioned for a century or more. Although
there are some imperfections affecting quality (e.g., difficulty of assessing dry rubber
content), these markets transmit world price changes to the farmgate rapidly, and
marketing margins reflect transport and other costs. Markets for natural rubber have
been subject to few distortions from national policy, but at times the international
buffer stock has depressed prices.
l abor ma rkets
Although the complete analysis also included skilled labor, the summary analysis presented here focuses on unskilled labor. Instead of hiring permanent skilled workers,
smallholders may be more likely to develop certain technical skills themselves. So the
relevant barrier is the acquisition of technical information rather than the market for
skilled labor. Although labor markets in Sumatra fall short of the theoretical ideal,
recent empirical studies (Suyanto et al. 1998a, 1998b) indicate that labor markets
work reasonably well. It is worth noting that casual markets for skilled labor (e.g.,
chainsaw operators) also are emerging.
capital markets
Capital market problems are second only to planting material supply as a barrier to
adoption resulting from market imperfections. Although no long-term institutional
credit is available in rural Sumatra, household savings, which financed investments in
existing smallholder agroforestry systems such as rubber agroforests, often are under-
Land Use Systems at the Margins of Tropical Moist Forest
401
estimated, and farmers are able to receive credit from informal sources (relatives,
moneylenders). However, recent economic hardships may be straining these resources.
Capital market imperfections may constrain smallholders’ fertilizer purchases for cassava production and use of clonal rubber planting material and certainly are a barrier
to the establishment of smallholder oil palm. Whether smallholder timber extraction
is constrained by capital market imperfections depends in part on development of
contract markets for chainsaw services and log transport.
BRAZIL
Land Use Systems Evaluated
Eight luss were evaluated at the asb benchmark site in the western Brazilian Amazon
(Souza and Homma 1993; Ávila 1994). Details of the luss can be found in Vosti et al.
(2002), Fujisaka et al. (1996), Lewis et al. (2002), and Witcover et al. (1996b).
• Natural forest. Limited stocks of marketable products and limited smallholder knowledge regarding forest products generally combine to dramatically limit the
number of sustainably harvested products extracted by smallholders from forests in
this region. Currently, Brazil nut (Bertholletia excelsa Humb. & Bonpl.) extraction is
the only major ntfp activity undertaken sustainably in forested areas.
• Managed forestry. This experimental lus permits low-impact extraction of up
to 13 m3 of timber from selected tree species per hectare per year, a rate and method
judged by local foresters as conservatively sustainable over a 10-year cycle for a 40-ha
tract; a different 4-ha plot is used for extraction each year (chapter 8, this volume).
This lus involves labor for felling, on-farm transport, and sawing of planks, explicitly
accounted for here.
• Coffee–bandarra. This is a smallholder coffee (Coffea canephora Pierre ex Fröhner) production system averaging about 2 ha in which native bandarra (Schizolobium
amazonica Huber ex Ducke), a quick-growing, native tree valued for its timber, is
allowed to emerge, with some thinning to avoid excess shade. This lus and the following are in initial stages of on-farm experimentation.
• Coffee–rubber. Similar to coffee and bandarra in scale, this lus contains rubber trees planted among coffee trees; regeneration of native species is suppressed.
• Traditional pasture. Low-productivity, mixed cattle production systems, and
the pastures needed to support them are the dominant lus at the Brazil benchmark
site. Traditional cattle breeds and grass-based pastures are most prominent, and the
use of purchased inputs generally is limited to those needed to allow the marketing
of beef and milk. Scale of operation can vary between 20 and 250 ha for smallholders. Large farm enterprises can practice this lus on large scales, sometimes exceeding
50,000 ha.
402
Cross-Site Comparisons and Conclusions
• Improved pasture. Similar in scale to the traditional cattle–pasture system, the
improved cattle–pasture lus comprises more productive breeds of cattle, uses substantial amounts of fencing for pasture management, and makes much more intensive
use of purchased inputs for livestock management. Beef and milk offtake increase
substantially (Faminow et al. 1997; Vosti et al. 2001a).
• Annual–fallow. This lus, constructed to provide a cross-site comparison, represents a swidden agriculture system that is rarely found in settlement areas at the
benchmark site. Approximately 2 ha of forest is felled and burned, followed by 3 years
of crop production (2 years of rice, bean (Phaseolus vulgaris L.), and maize (Zea mays
L.) production followed by 1 year of maize and cassava production), after which the
land is put to fallow for about 7 years. This cycle is repeated twice to fit into the 20year time horizon to allow cross-lus comparisons.
• Improved fallow. This system models that of experimental sites in the region
and begins by felling approximately 2 ha of forest, followed by 2 years of annual crop
production (rice, bean, and maize) after which land is place in a legume-based fallow
for 2 years. The production cycle is repeated for lus comparability.
Land Use System Evaluation and Performance
Financial Profitability: Returns to Land
The returns to land range from a low of –$17/ha for the annual crop–fallow system to
a high of $2056/ha for the experimental improved fallow system. The least profitable
luss (forest, –$2/ha and annual–fallow, –$17/ha) no longer exist in isolation from
other luss. Indeed, the former is practiced only if the opportunity cost of labor is far
below the market wage. The most common land use (traditional cattle and pasture)
generated only $2/ha, but the more intensive version of this lus (improved cattle and
pasture) boosted returns to land to $710/ha. The small-scale managed forest scheme
dramatically increased returns to land over the forest-based alternative (Brazil nut
extraction, forest) to $416/ha. The coffee-based luss generated impressive returns to
land: $1955/ha for coffee–bandarra and $872/ha for coffee–rubber. Finally, the highest returns to land (but not to labor) were found in the improved fallow system.
Returns to Labor
In this labor-scarce environment, returns to labor would outweigh returns to land in
farmers’ decisions to adopt. Returns to labor estimates: ranged from $1 per personday in the extractive forest activities to $22 in the improved livestock–pasture system
(table 17.3). Systems at or below the average rural daily wage for unskilled labor of
approximately $6.25 probably would not attract farmers, although imperfections in
the labor market, seasonality of labor demand, and heterogeneity of labor type within
a household make this less than a hard-and-fast rule. Indeed, the annual–fallow system
that is no longer practiced yields slightly lower returns than working for wages. Traditional pasture–livestock production systems, the most prevalent in the study area,
Land Use Systems at the Margins of Tropical Moist Forest
403
yield slightly better returns than working for wages; the more labor-intensive systems
yielded even more, with the higher of the two coffee-based systems (coffee–bandarra)
bringing in about twice the wage and the improved pasture–livestock and managed
forestry bringing in nearly three times as much as the traditional livestock system.
Farmers more interested in returns to labor than to land would select improved
pasture–livestock systems, whereas those more concerned with per hectare asset value
(including improvements in the form of established production systems) might prefer
systems scoring high on both counts, such as managed forest, improved fallow, and
coffee–bandarra.
Labor Requirements
An lus with high returns to labor may simply be out of reach of small farmers in
the area, given current labor scarcity and imperfectly functioning labor markets. The
coffee–rubber system demands the most labor by far to operate, nearly 60 person-days/
ha/yr. At the other end of the spectrum sits the low-level forest extraction systems in
Acre, which take only about 1 person-day/ha/yr to manage. The system currently forming the end of the land use trajectory, traditional pasture, uses the least labor of any system other than the forest systems, approximately 11 person-days/ha, but its intensified
version (improved pasture) needs just slightly more than this. Clustered at one-and-ahalf to just over two times the labor needs of these systems are two other intensified
systems (coffee–bandarra and improved fallow) and the annual–fallow lus.
Household Food Security
Forest extraction, small-scale managed forestry, and the two coffee-based systems share
the characteristic that once established, they produce no food (table 17.3). To meet
food needs, households adopting these luss will depend on markets for food and on
product markets for Brazil nuts, timber, coffee, or rubber. The two cattle-based systems and the two food crop–based systems produce food and provide cash to exchange
for food; the proportion of exchange to own production probably will be greater for
cattle-based systems.
Institutional Issues: Market Imperfections
The market for Brazil nuts has been functioning reasonably well for decades, and
collecting nuts takes almost no skill or capital investment, so there are no flags in the
market imperfections column for the forest lus (table 17.3). All other luss presented
obstacles to adoption linked to market imperfections.
output markets
Although markets for sawn timber have existed in the region for more than two decades,
small-scale agriculturalists generally have not participated in it, either individually or
in groups. Therefore, product quality and volume issues loom large for these new market entrants. Coffee markets have also existed for some time and continue to develop
thanks to policy-induced expansion of area in coffee, especially in Rondônia (e.g., free
Table 17.3 Land Use System Performance and Resource Inputs at the Brazil Benchmark Site
Land Use
System
Scale of
Operation Financial
Profitability a
(ha)
Labor
Needsb
Returns Returns
to Land to Labor
( $/ha) ( $/
personday)
Forest (AC)e
Managed
forestry (AC)
Coffee–bandarra
(RO)
Coffee–rubber
(RO)
Traditional
pasture (AC)
Improved
pasture (AC)
Annual–fallow
(AC)
Improved fallow
(AC)
TimeAveraged
Labor
Input
(person-day/
ha/yr)
1
1.22
Household
Food
Securityc
Institutional
Issuesd
Food
Entitlement
Path
(operational
phase)
Market
Imperfections
ex
ex
—
i, lb, k, o
30
40
–2
416
1
20
2
1955
13
27
ex
i, o, lb, k
2
872
9
59
ex
i, o, LB, k
40
2
7
11
ex, op
i, o
40
710
22
13
ex, op
i, lb, k
2.5
–17
6
23
ex, op
lb
2.5
2056
17
21
ex, op
LB
A discount rate of 9% was used, and the opportunity cost of household labor was set at $6.25 per day. Prices
are based on 1996 averages and expressed in December 1996 $: $1 R1.04. Each proposed system’s
socioeconomic indicators are based on optimistic yield parameters. Sensitivity analyses to establish lower ranges
of profitability figures and to check robustness of results to observed swings in relative output prices and a
range of discount rates are ongoing. For example, for managed forestry, a less optimistic offtake of 10 m3/ha/
yr would mean returns to land and labor of R252/ha and R13.50, respectively, and only slightly less labor
(1.2 person-day/ha/yr).
b
For labor needs, a boldface number indicates competition for labor with other agricultural activities for a
typical household.
c
For food security, “own production (op)” and “exchange (ex)” reflect whether the generates food for
own consumption or income that could be used to buy food; combined food entitlement paths are common.
d
For institutional issues, letters indicate market imperfections judged to constrain adoption (with uppercase indicating a serious problem and lowercase indicating a more minor difficulty), as follows: i, input
markets; o, output markets; lb, labor markets; k, capital markets.
e
“AC” and “RO” refer, respectively, to the Brazilian states of Acre and Rondônia, where measurements on
specific s were taken.
Sources: Data derived from Vosti et al. (2001b) and Oliveira (2000b).
a
Land Use Systems at the Margins of Tropical Moist Forest
405
technical assistance and subsidized planting materials). Sufficient processing capacity
for fluid milk exists in the region, but membership in a dairy cooperative (not available to all) is generally necessary to access this capacity.
l abor markets
Imperfections in the labor market were considered a factor in adoption in all intensified systems, particularly the improved fallow. Seasonal shortages in unskilled labor
especially hampered coffee-based production systems, and shortages of skilled labor
probably would occur if more intensive luss were adopted.
input markets
All of the more intensive systems also relied more heavily on purchased inputs, especially the improved cattle–pasture system. While markets for these inputs are developing, the private sector continues to focus on medium- and large-scale producers. Most
systems needed at least periodic soil nutrient enhancements (e.g., chemical fertilizers);
markets for these inputs are just emerging, and suppliers face staggering transportation costs. It is noteworthy that the market prices of purchased inputs generally do
not include the costs of training to effectively use them; for example, cattle vaccines
are readily available, but many smallholders do not know how and when to use them.
Therefore returns to luss that depend heavily on such inputs may be overstated.
capital markets and risk
All nonforest luss entailed greater capital input (with the exception of the improved
fallow system) and hence dependence on capital markets. In this frontier area, no
informal systems of production credit are locally available; there are no established private banks or money lenders that provide investment capital for agriculture. The only
formal sources of credit are the regional and federal banks that provide smallholder
credit at subsidized rates, but nonprice rationing (allocation of credit based on something other than the cost of credit, that is, the interest rate paid by farmers) of capital
effectively excludes most smallholders from routine borrowing. Moreover, all luss
entail some production and price risk. To date, there are few institutional mechanisms
for managing these risks. Therefore, luss that entail large outlays for establishment
or purchased inputs for operation (e.g., improved pasture–cattle) may be perceived as
more risky to smallholders and therefore less likely to be adopted by them (Vosti et al.
2002; Faminow et al. 1999).
All this said, as in the Cameroon case, market performance in the Brazilian benchmark site varies with distance to main roads and major cities. In hinterland areas transportation costs are high and vary enormously seasonally, so food, information, inputs,
and products are much more expensive than in closer-lying areas, especially during
the rainy season. More important for market performance, intermediaries capable of
reducing overall costs and seasonal swings in costs generally are not in place in remote
areas. Finally, small-scale farmers are much more likely to suffer from market imperfections than are their larger-scale counterparts because the latter can invest in private
forms of transportation and communication.
406
Cross-Site Comparisons and Conclusions
C RO S S - SITE COMPARISONS OF L AND USE SYSTEMS
A N D B ROADER ISSUES
In this section, we briefly examine the socioeconomic and policy elements of the asb
matrices for Cameroon, Indonesia, and Brazil side by side and then highlight crosssite similarities and differences in a set of broader issues that lie behind the matrices
but affect land use choices.
C o m pa ri ng ASB Matrices
Comparing the lus evaluation matrices for the three asb benchmark sites reveals some
interesting parallels and some differences. First, at the benchmark sites in Brazil and
Cameroon, tapping the forest for anything but timber products generated very low
returns to labor. This was not the case in Indonesia, where people involved in the sustainable offtake of ntfps could expect to earn well above the market wage. The longterm success of this lus makes it worthy of attention and support, but the sustainability
of this lus requires that extraction not be intensified. Moreover, spatially expanding this
lus within Indonesia is questionable, and the mechanism for replicating this lus in
other sites is unexplored. Second, using the market wage (at each site) as our guide, swidden agriculture is at best marginally profitable and will continue to exist only in areas
where food markets fail or the cultural significance surrounding its practice is strong
(e.g., Cameroon). Third, certain smallholder tree-based luss can increase returns to
land and labor, but market-related impediments to adoption exist at all sites. Fourth,
large agricultural enterprises (in Brazil and Indonesia today, perhaps in Cameroon in the
future) may have comparative advantages in some aspects of production or (more likely)
processing, but room for smallholder participation in many aspects of production surely
exists; policy action should promote, not constrain, this participation.
B roa d S ocioeconomic Issues
Market Imperfections
There was wide variation in the performance of markets across asb sites: Indonesian
labor and commodity markets and customary land tenure institutions worked well,
but capital markets did not; even food markets, usually the first set of markets to
develop, failed at certain locations in the Cameroon site, and the Brazil site occupied
an intermediate position, with some markets functioning well (e.g., food from southern Brazil was commonly consumed in rural areas of the Amazon) and others (e.g.,
formal credit markets) performing poorly.
At all benchmark sites, institutions and infrastructure tend to be much better
where population densities are higher. In these areas, farmers have better access to
Land Use Systems at the Margins of Tropical Moist Forest
407
competitive markets system for purchased outputs and inputs, including hired labor.
Moreover, traditional land tenure institutions in Cameroon and Indonesia seem to
be evolving gradually toward individualistic land ownership, which in Cameroon is
characterized by cadastral surveys and an increased incidence of land titling (iita,
unpublished data 1997). This trend can facilitate the development of land markets,
which may be fundamental to lus change in these areas.
However, several important caveats to this general trend in market development should be noted. First, better functioning capital markets do not generally
spontaneously emerge alongside improved markets for products or other agricultural inputs, and informal credit systems that have developed (in Cameroon and
Indonesia) often are not able to finance major changes in luss. Government action
to date has failed to fill this important gap in investment capital; smallholder investments favoring noncapital inputs have been the result. Second, market development
is never geographically uniform: Periurban areas generally benefit first, and some
outlying areas may never benefit at all. Governments have a role in improving and
extending the benefits of market development to all. Finally, the existence of wellperforming markets is a necessary but not sufficient condition for market access;
some socioeconomic groups clearly have preferential access to certain markets in
each of the asb benchmark sites (e.g., large-scale ranching operations in Brazil).
Governments have a clear role in making market access more uniform across socioeconomic groups, too.
Food Markets and Cultural Roles
When food markets fail to develop, smallholder households can become locked into
luss that generate very low returns to labor (e.g., less than the market wage in Brazil
and Cameroon). Policy action such as rice price stabilization in Indonesia reduced
risks of specialization in export commodities and permitted households the flexibility
to invest in more lucrative luss. At the same time, underdeveloped food markets only
partially explain the persistence of the subsistence mixed food crop field in southern
Cameroon, where gender plays fundamental roles in food security.
Poverty
Poverty continues to persist widely at the Cameroon site but has been substantially reduced at the Brazil and Indonesia sites, in part because of the success of the
luss that remaining smallholders have chosen to practice and the abandonment
of agriculture by those who could not establish such systems. At all sites, however,
although some farmers may have risen above abject poverty, many may still be unable
to meet high establishment costs associated with some luss; that is, although they
may have escaped welfare poverty, they still may be investment poor (Reardon and
Vosti 1995).
408
Cross-Site Comparisons and Conclusions
Scope for Policy Action
Dramatic differences were identified across the benchmark sites in the power and
responsibilities of policymakers and the policy instruments and resources available to
carry out their mandated tasks. For example, at the Brazil benchmark site a complicated patchwork (with gaps and overlaps) of responsibilities for maintaining rural roads
has emerged, and no clear system of resource generation and disbursement has developed to match these responsibilities. Consequently, even vital transportation arteries
can fall into disrepair. In Cameroon, the downturn in primary commodity markets for
coffee, cocoa, cotton, and oil in the late 1980s plunged the country into a deep recession during which per capita incomes declined by more than 50 percent from 1986
to 1993. Accompanying the downturn was a shift in policy objectives and a drastic
fall in public investments in vital sectors such as transportation, public health, education, and agricultural research and extension, all of which can influence lus choice
at the forest margin. Another factor influencing land use change in Cameroon and
most of West Africa has been the rapid urbanization since the 1970s that has increased
demand for staple food crops relative to the demand for perennial export crops. This
switch has consequent environmental impacts because the luss associated with the
tree-based systems provide many more environmental services than those associated
with food crop systems.
As regards the management of forests, in all three benchmark sites management of
public forests (e.g., parks, preservation areas, indigenous areas) is extremely difficult,
primarily because of the vast areas involved and the lack of resources to do the job
and also because local communities surrounding these areas often exploit the natural
resources of the forest to invest and to survive. Under these circumstances, curtailing
access to forests is expensive and can increase poverty.
Finally, and perhaps most important as regards policy action, at all benchmark
sites, most of the fundamental economic factors driving lus adoption were beyond
the scope of local, regional, and sometimes even national policymakers. For example,
in Cameroon the prices of coffee, cocoa, oil, and timber are of fundamental importance and are set in international markets. A similar situation exists in Indonesia for
rubber, timber, and palm oil. In Brazil, farmgate prices of cattle products and food are
set thousands of miles from the asb benchmark site. All these prices, and the incentives and disincentives they pose to the adoption of particular luss, are largely beyond
the reach of national and subnational policymakers (chapter 7, this volume), so the
scope for policy action is narrowed.
Forests and Economic Growth
The relative importance of forests in meeting national growth objectives varied widely
across asb countries. Cameroon’s forest resources, one of the country’s greatest riches,
Land Use Systems at the Margins of Tropical Moist Forest
409
have played and continue to play a significant role in its economic growth and development. In the 1950s, 1960s, and 1970s conversion of approximately 500,000 ha of
moist forests to smallholder coffee and cocoa agroforests resulted in equitable broadbased economic growth averaging 3 to 4 percent. In more recent years, timber exploitation has overtaken coffee and cocoa production as the most important economic
activity in the moist forests. Cameroon is now the leading African exporter of tropical
timbers, with more than $270 million in annual export sales. It is a poor nation, and
at this stage in its economic development Cameroon has little choice but to develop
its forest resources. From the standpoint of government policy, the critical question is
whether Cameroon’s tropical forests will be converted into sustainable agricultural and
forestry production systems or mined into a state of degraded vegetation.
By contrast, Brazil is an industrialized country with a highly diversified economy.
It is also in the globally unique situation of having two remaining agricultural frontiers: large savanna areas and huge forest areas. Is converting the Amazon to agriculture necessary to achieve national growth objectives? Probably not. Would converting
the Amazon to agriculture contribute to national growth objectives? Probably so, but
not without large environmental costs. Perhaps the more relevant question is whether
converting the Amazon to agricultural is necessary to meet regional (i.e., Amazonian) growth objectives (Soares 1997). To this question the answer probably is “yes,”
although this objective probably would be better achieved by promoting intensive
non–forest-based luss in areas with low rainfall and more pronounced and extended
dry periods within the Amazon basin.
Indonesia probably occupies an intermediate position on this issue, despite
macroeconomic upheaval in the late 1990s. Indonesia had experienced rapid economic growth, poverty reduction, and structural transformation from the early 1970s
through the mid-1990s. The financial and monetary crisis of the late 1990s probably
will be a temporary setback to absolute declines since the early 1990s in the labor force
dependent on agriculture and the resulting decline in pressure on the natural resource
base. However, as in Brazil (which crossed this turning point much earlier), there is
great regional variation in these patterns, and although agriculture and forestry will
play a declining role in the overall economy, they loom large in many regions.
C O N C LU SION
L a n d U s e System Trends
Against this backdrop of lus performance and inputs and the institutional and other
issues that underlie lus choice and guide policy action, we now look forward at each
benchmark site and predict trends in land use.
What will be the likely paths of lus adoption in the three benchmark sites over
the next two decades? Although changes in policy and economic factors could alter
lus adoption patterns, the following scenarios are likely to play out.
410
Cross-Site Comparisons and Conclusions
At all asb sites, traditional swidden agriculture has or will soon disappear because
of population pressure and low rates of return to labor. What replaces swidden agriculture varies across sites.
In Cameroon, the slash-and-burn annual cropping short fallow system is likely
to increase in area in rough proportion to the increase in rural and urban population.
However, in the absence of productivity-enhancing technical change, this system is
increasingly unsustainable because of its shortened fallow. In locales with good market
access, opportunities for commercial surplus production would be expected to lead
to a proportionally greater expansion of these short-fallow systems than in areas with
poor market access. Under current and foreseeable market conditions, the cocoa and
oil palm perennial crop systems are the most profitable of the systems examined. Currently cocoa is not widely produced in the Congo basin but could be an important
lus, especially when the economies of Southeast Asian competitors such as Indonesia
and Malaysia resume rapid economic growth and structural transformation. Moreover, input markets, liberalized since 1992, are better developed today. These factors
will combine to increase the financial profitability of cocoa and increase the amount
of land dedicated to intensive cocoa systems, a large proportion of which probably will
come from a shift from extensive to intensive production systems. Whether there will
be significant new land conversion to either extensive or intensive cocoa production
is difficult to predict. Evidence indicates that West African smallholder producers of
perennial export crops are price responsive, suggesting that some expansion in new
planting area will occur if currently high world cocoa prices are maintained (Akiyami
1988; Gockowski 1994). If new plantings substitute for short-fallow land uses, net
environmental gains are expected. On the other hand, if new planting occurs at the
expense of secondary and primary forest, environmental losses will result. Given the
choice, the producer normally will choose the latter in an effort to capture forest rents
(Ruf 1995).
In Indonesia, large-scale oil palm plantations probably will continue to expand
if government development strategies continue to discriminate against the emergence
of independent smallholder oil palm producers. These strategies emphasized Nucleus
Estate/Smallholder schemes that required marketing of tree products through project
channels to repay credit. In addition, in some areas local authorities have attempted to
prevent development of free markets in palm oil, which has retarded development of
market outlets for independent smallholders.
In Brazil, several trends are likely. First, given labor scarcity, seasonality in production activities, and market imperfections (especially for capital and emerging cultivated tropical products), cattle production will continue to dominate the landscape
(Faminow 1998; Faminow and Vosti 1998; chapter 10, this volume). Cattle production systems, especially pasture management, will become more intensive, primarily
in response to increasing pressure on soils and market access needs. Technological
change in pasture management (e.g., solar-charged, battery-powered electric fences;
see Melado 2003) are expected to facilitate this trend. Coffee and other tree-based
systems will continue to be adopted and will occupy small amounts of farm land but
Land Use Systems at the Margins of Tropical Moist Forest
411
large amounts of household labor. With sufficient technical assistance and capital, and
with effective and efficient monitoring, small-scale managed forestry could become
an important lus (chapter 8, this volume), with very broad environmental impact.
Finally, given scale economies in managing some existing luss (e.g., cattle production) and some emerging luss (e.g., managed forestry), it is likely that small-scale
agricultural holdings will be consolidated.
Estimates of returns to land and labor presented in this chapter indicate that from
a purely private perspective, returns to forest conversion are high at all benchmark
sites. If no action is taken to identify workable options either to shift incentives for
conversion or restrict access to the remaining natural forests, these rainforests will continue to disappear. Small-scale managed forestry (in Brazil), improved rubber agroforests (in Indonesia), and forest-based cocoa agroforests with fruit (in Cameroon) are
all good candidates for increasing the returns to environmentally benign activities at
these sites (and perhaps more broadly). But among these, only managed forestry shifts
incentives for conversion.
AC K N OWLEDGMENTS
We are indebted to collaborators at all three asb benchmark sites for suggestions,
insights, and clarifications and to the InterAmerican Development Bank, Asian Development Bank, Ford Foundation, Danish Agency for Development Assistance, United
Nations Development Program Global Environment Facility, Australian Centre for
International Agricultural Research, U.S. Agency for International Development,
Rockefeller Foundation, and Center for Natural Resources Policy Analysis, University
of California at Davis, for financial support.
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18 Balancing Agricultural Development
and Environmental Objectives
ass essing tradeoff s i n t h e
humid tropics
Thomas P. Tomich
World Agroforestry Centre Nairobi, Kenya
Andrea Cattaneo
Economic Research Service, USDA Washington, DC
Simon Chater
Green Ink Publishing Services Ltd. Buckfastleigh, Devon, United Kingdom
Helmut J. Geist
Université Catholique Louvain Louvain-la-Neuve, Belgium
James Gockowski
IITA Humid Forest Station Yaoundé, Cameroon
David Kaimowitz
Center for International Forestry Research Bogor, Indonesia
Eric F. Lambin
Université Catholique Louvain Louvain-la-Neuve, Belgium
Jessa Lewis
Consultant La Jolla, California
Ousseynou Ndoye
Center for International Forestry Research Yaoundé, Cameroon
Cheryl A. Palm
The Earth Institute of Columbia University New York
Fred Stolle
Université Catholique Louvain Louvain-la-Neuve, Belgium
William D. Sunderlin
Center for International Forestry Research Bogor, Indonesia
Judson F. Valentim
Embrapa Acre Rio Branco, Brazil
Meine van Noordwijk
World Agroforestry Centre Indonesia Bogor, Indonesia
Stephen A. Vosti
University of California Davis
416
Cross-Site Comparisons and Conclusions
M A N Y C ONCERNS, CONFLICTING INTERESTS
This volume so far has presented numerous issues, opportunities, and concerns from
specific national and thematic perspectives on tropical forests and deforestation. This
chapter attempts to pull these together through analysis of tradeoffs across those various perspectives. And, indeed, everyone in the world seems to want something from
tropical forests. Forest dwellers want to continue aspects of their traditional way of life
based on hunting and gathering while improving the welfare of themselves and their
families. They are losing their land to migrant smallholders, who clear small amounts
of forest to earn a living by raising crops and livestock. Both these groups tend to lose
out to larger, more powerful interests—ranchers, plantation owners, large-scale farmers, or logging concerns—whose aim is to convert large areas of forest into big money.
Outside the forests is the international community, who want to see forests preserved
for the carbon they store, which would otherwise contribute to global warming, for
the wealth of biological diversity they harbor, and for the many other ecosystem services they provide.
Deforestation continues because converting forests to other uses is almost always
profitable for the individual, household, or firm that engages in it. However, society
as a whole bears the costs of lost biodiversity, global warming, smoke pollution, and
the degradation of water resources. Every year the world loses about 13 million ha of
tropical forest, an area more than three times the size of Belgium. None of the land
use systems that replace this natural forest can match it in terms of biodiversity richness and carbon storage. However, the land use systems that replace the forest vary
greatly in the degree to which they combine at least some environmental benefits with
their contributions to economic growth and poor peoples’ livelihoods. Therefore it is
always worth asking what will replace forest (and for how long), both under the current mix of policies, institutions, and technologies and compared with possible alternatives, some of which may leave forests largely intact. In other words, what can and
should be done to secure the best balance between the conflicting interests of different
groups, including some who are poor and experience chronic hunger?
F O RC E S DRIVING TROPICA L DEFORESTATION
Most often, blame for tropical deforestation falls exclusively on specific groups, such
as smallholders practicing shifting cultivation or large companies growing plantation
crops or raising cattle. Few studies have attempted to gain an overall picture of forest
uses and users by evaluating and comparing the evidence from a large set of locations.
A review by Geist and Lambin (2002) has provided a framework for analyzing
and classifying the causes of deforestation. They examined and compared the factors
at work in 152 cases of tropical deforestation in Africa, Asia, and Latin America. They
distinguish between the proximate causes of deforestation—human activities on the
Balancing Development and Environmental Objectives
417
ground at local level—and the larger driving forces that underlie these activities. This is
an improvement on previous thinking because it recognizes that the people in the front
line of deforestation—those wielding the chainsaws or driving the bulldozers—do not
make their decisions in a vacuum but are strongly influenced by macroeconomic and
social factors operating at the national, regional, or global levels, factors over which they
have little control.
In their analytical framework, four broad clusters of proximate causes (agricultural expansion, wood extraction, infrastructure development, and other factors) are
linked to five clusters of underlying causes (demographic, economic, technological,
policy and institutional, and cultural). In each case, the clusters are subdivided into
more specific factors (figure 18.1). For example, agricultural expansion may take the
form of permanent cultivation, shifting cultivation, cattle ranching, or colonization.
A mix of causes normally is at work when deforestation occurs. The review goes
on to identify what it calls causal synergies: associations of proximate and underlying causes that help to explain deforestation more convincingly than previous singlefactor explanations. Together with other recent research, the review by Geist and
Lambin tells us much about the real causes of tropical deforestation.
Although agricultural expansion was found to be at least one of the factors in
96 percent of the cases, shifting cultivation of food crops by smallholders, so often
thought to be a major cause, was in fact a minor contributor to deforestation. Other
forms of agricultural expansion, such as permanent cropping and cattle ranching,
appear equally or more significant in most regions, although the agroecological and
policy factors influencing this cause of forest loss vary widely across regions—with
very different pathways identified for the Amazon, the Congo Basin, and Southeast
Asia—and even within regions across countries.
Far more influential than shifting cultivation, or indeed any of the proximate
causes of deforestation, are the macroeconomic forces that create the incentives to
which individuals respond. Often, these forces manifest themselves as shocks that
destabilize the lives of poor people; for example, an increase in urban unemployment
may trigger reverse migration into the countryside. These shocks punctuate longer
periods in which social and economic trends bring about more gradual changes in the
opportunities available to poor rural people, such as the steady growth of the international timber trade or of demand for livestock products and the steadily expanding
ecological and economic footprint of distant city markets. The economic integration
of forest margins and the continual development of product and labor markets that
accompany this process are factors at work in almost all cases.
Strongly associated with the influence of macroeconomic forces is the building of
roads. Often paid for by logging companies or through international aid, new roads
open up forest areas first for wood extraction and then for the expansion of agriculture. New migrants colonize roadsides and use roads to obtain inputs and deliver their
produce to markets. By linking forested areas to the broader economy, roads lower
costs and increase returns of conversion and thereby heighten the sensitivity of these
areas to changes in macroeconomic conditions.
Figure 18.1 Causes of deforestation: Five broad clusters of underlying driving forces underpin the proximate causes of tropical deforestation (Geist and Lambin 2002).
Balancing Development and Environmental Objectives
419
The findings of Geist and Lambin confirm those of the location-specific studies
conducted by Alternatives to Slash and Burn (asb) and by colleagues at the Center
for International Forestry Research (cifor) in tropical forests of Southeast Asia, the
western Amazon, and the Congo Basin, as shown in the following examples.
B r a z i l : How Macroeconomic Factors and Roads
C o m b i n e to Influence Deforestation
Logging, cropping, and ranching (not necessarily in that order) often are identified as the proximate causes of deforestation in the Brazilian Amazon. However, the
underlying macroeconomic factors influencing these land uses, some of which can be
addressed by policy change, are not often explored and have become more important
as new roads have linked activities in the Amazon with other parts of the Brazilian
economy.
For example, asb researchers modeled the effects of various macroeconomic
changes on the region’s development (chapter 7, this volume; Cattaneo 2003). They
found that a 40 percent devaluation of the Brazilian real against the U.S. dollar would
lead to increases in deforestation of 6 percent in the short term and 20 percent in the
long term, with an increase in logging of 16 to 20 percent. The production of annual
crops and livestock would expand rapidly to fill the shortfall in national demand for
foodstuffs as other regions switched to export crops. Building more roads—planned
under a government development strategy for the region—would reduce transport
costs by 20 percent, driving an increase in deforestation of 15 to 40 percent as the
returns to cultivating arable land rose.
C a m e ro o n: How Macroeconomic Shocks Affect
Fa rm e r s’ Actions
Cameroon is the only asb case study country in which shifting cultivation appears
as a significant proximate cause of deforestation (chapter 14, this volume). Yet even
here, macroeconomic policies and economic shocks drive change. Cameroon provides
a textbook case of how economic signals alter the attractiveness of different cropping systems to small-scale farmers, with major implications for deforestation rates
(Mertens et al. 2000; Ndoye and Kaimowitz 2000; Sunderlin et al. 2000; Gockowski
et al. 2001). From 1977 to 1985 Cameroon enjoyed an export-led boom based on oil,
coffee, and cocoa. Migrants from the countryside flocked to take up jobs in the cities,
while the rural population switched from subsistence farming to growing tree crops
for cash. This boom period was followed by an abrupt decline in the second half of the
1980s as the country’s oil ran out and the international prices of all three of its export
commodities slumped. In 1989 shrinking export revenues forced the government to
stop subsidizing agricultural inputs and to halve the prices of coffee and cocoa offered
420
Cross-Site Comparisons and Conclusions
to farmers. These measures were followed, in the early 1990s, by imposed structural
adjustment measures that resulted in draconian cuts in public sector employment and
wages. Finally, Cameroon’s currency was devalued in 1994.
The crisis had a dramatic effect on Cameroon’s rural areas. Satellite imagery shows
that in 1986 to 1996, annual deforestation had doubled over its 1973 to 1986 level
in areas close to the capital city and quadrupled in more remote, thickly forested areas
(Sunderlin et al. 2000). As the crisis deepened, rural–urban migration first slowed and
then went into reverse as impoverished city dwellers returned to the countryside to
take up farming. The population of rural villages grew by only 1.6 percent in the 1976
to 1987 period, but by 24 percent in 1987 to 1997 (Sunderlin and Pokam 2002).
Most of the returnees put their efforts into growing food crops to ensure family food
security and also produced some food for the market.
Existing farmers also grew more food crops while maintaining or expanding their
area in tree crops in the hope that high prices would return. The switch to food
crops, which was more pronounced in remote, thickly forested areas, greatly accelerated deforestation because food crops tended to be established on newly cleared land
rather than on old plantations (Sunderlin et al. 2000).
Four other factors in the larger economy drove the expansion of food cropping:
Demand for food crops rose as food imports declined during the crisis, the phasing
out of subsidies for inputs forced farmers to cultivate larger areas to meet production
goals, some flexibility in gender division of labor allowed an increase in labor inputs,
and logging, which clears the way for food and cash crops, accelerated after the 1993
currency devaluation.
The Cameroon case reveals how the effects of macroeconomic forces are mediated
by the responses of thousands of small-scale farmers. But it also shows that these forces
affect the pace, location, and proximate causes of deforestation rather than whether it
happens at all. In other words, changes in macroeconomic conditions can replace one
cause of deforestation with another.
I n d o n e s ia: How Multiple Actors Jostle for
P ro f i ta ble Opportunities
Forest conversion in Sumatra, Kalimantan (Indonesian Borneo), Sulawesi, and other
“Outer Islands” of Indonesia involves a range of actors and objectives. Local smallholders, migrants, loggers, large-scale tree crop estates (including industrial timber
plantations), and government-sponsored resettlement schemes (called transmigration)
all play a role in forest conversion. A large volume of literature exists documenting
aspects of land use, cover change, and forest conversion in Indonesia, but much of the
data in these documents is unreliable or extremely difficult to interpret beyond the
scale of case studies. So although smallholders often receive much of the blame for
forest conversion, it is very difficult to place accurate numbers on areas converted by
the various agents responsible for deforestation in Indonesia.
Balancing Development and Environmental Objectives
421
The island of Sumatra was chosen to represent the lowland humid forest zone of
Asia for the global asb project (Tomich and van Noordwijk 1996; Tomich et al. 1998b;
Murdiyarso et al. 2002; chapter 13, this volume). Most of the asb work in Sumatra has
concentrated on benchmark sites in Jambi and Lampung provinces, both of which are
located in Sumatra’s broad peneplain agroecological zone. The peneplains have been
the focus of government-sponsored transmigration schemes, large-scale logging, and
various large-scale public and private land development projects since the 1970s.
As with Indonesia as a whole, there are too many holes and inconsistencies in
the data to distinguish with any precision the impacts of the various actors, large and
small, on deforestation in Sumatra. However, three broad conclusions can be inferred
from an overview of the literature (Lewis and Tomich 2002), drawing particularly
on extensive reviews of available evidence conducted by Dick (1991) and Holmes
(2000) and cross-checked by asb researchers using a geographic information system.
Specifically, for the period 1980 to 1998, approximately one-quarter of total deforestation in Sumatra can be attributed to large-scale estates, and a roughly equal share
can be attributed with some confidence to smallholder activity, although the available statistics probably skew this overall percentage downward. However, about half
of Sumatran deforestation remains largely unattributable for that period, representing the actions and interactions of smallholders (both local and migrant), large-scale
tree crop and industrial timber estates, medium-scale absentee investors in tree crop
plantations, illegal encroachment on “protected” forest and clear-cutting of large-scale
timber concessions, and periodic fires.
Dick (1991) and Holmes (2000) both concluded that deforestation resulting
from individual actions of small-scale farmers was the most difficult category to assess
for large areas. Moreover, the term shifting cultivator has been consistently criticized as
being both misleading and inaccurate as a category of smallholder activity. This is particularly true in the case of Sumatra, where the textbook version of traditional shifting
cultivation (annual crop rotations with bush fallow) had nearly disappeared by the
1990s (Tomich and van Noordwijk 1996). This is consistent with asb researchers’
estimate of very low returns to labor in shifting cultivation and attractive returns to
tree crop–based systems (table 18.3 later in this chapter).
Three groups of smallholders were studied in detail in asb research in Sumatra:
local people, spontaneous migrants, and government-sponsored transmigrants. The
general features of the livelihood strategies of these three groups are remarkably similar. Although food crops are produced after initial forest conversion, food production
per se does not appear to be the primary objective. Hence, food production insecurity
was not a major driving force in Sumatra in the 1990s. And although poverty clearly
plays a role as a driving force, for reasons elaborated in this chapter, it is clear that certain measures to raise income run the risk of increasing deforestation. Thus, poverty
alone is too simplistic an explanation, and numerous push and pull factors affecting
migration must be considered.
Although shifting cultivation has largely disappeared in Sumatra, all households,
whether local farmers, government-sponsored transmigrants, or spontaneous migrants,
422
Cross-Site Comparisons and Conclusions
use slash-and-burn for land clearing. When slash-and-burn is used by smallholders in
Sumatra’s peneplains, it often is to clear and replant old rubber agroforests (“jungle
rubber”). With increasing pressure on land, however, a method of “internal rejuvenation” by gap replanting appears to have become an attractive alternative to the slashand-burn of rotational rubber systems (chapter 9, this volume). Migrants (mainly
from Java) have been quick to adopt rubber-based systems similar to those developed
and used by the indigenous Sumatran population since early in the twentieth century.
The rapid spread of rubber as a smallholder crop in Sumatra since the beginning of the
twentieth century has been a major force behind forest conversion.
Thus, deforestation caused by slash-and-burn by Sumatran smallholders has been
driven in large part by profitable income-generating opportunities, specifically production of tree crops. Some of main lessons from Sumatra for the global asb project are that some tree crop–based systems are economically attractive alternatives to
extensive food crop–based systems, and these alternatives to slash-and-burn help to
alleviate poverty. But, as pointed out by Angelsen (1999), these profitable alternatives
also can speed up rather than slow down the rate of natural forest conversion because
they attract an inflow of migrants seeking a share of the economic benefits of these
systems.
It is revealing that Lampung Province is sometimes described as “North Java,”
indicating its role as a focal point for migration from densely populated Java. The
movement of people between Java and Lampung, and additional efforts by government during various periods in the twentieth century, are key to understanding the
landscape dynamics. Only a minority of residents of Lampung can claim Lampungese
decent.
Macroeconomic forces fundamentally affect households’ livelihood options and
thereby reduce (or intensify) forces that push migrants to forest margins; macroeconomic, trade, and sectoral policies also affect resource management decisions once
they get there. In times of rapid economic growth and industrialization, migration to
urban and industrial areas has been a major escape route from rural poverty. A number
of these migratory forces reversed during the Southeast Asian monetary crisis in the
late 1990s. Beginning in August 1997, Indonesia had one of the greatest real exchange
rate depreciations experienced by any country in the last half century. Simulations by
asb researchers using partial equilibrium models of financial returns to various land
uses suggest that profitability of many tree-based systems (which produce commodities for export) increased substantially because of that exchange rate collapse, which
would boost incentives for conversion of forests to tree crops by both smallholders
and large-scale operators (Tomich et al. 1998b:101–102). A survey of more than 1000
households in the “Outer Islands” (Sunderlin et al. 2001) found that these farmers
did significantly increase conversion of forest to tree crops during the monetary crisis.
(Nevertheless, sample households felt worse off during the crisis, despite income from
export crops.)
Jambi Province became a popular destination for migrants (more than 80 percent of whom are from Java) later than Lampung and only after completion of the
Balancing Development and Environmental Objectives
423
Trans-Sumatra Highway in the 1980s. Secondary roads built by logging companies,
transmigration projects, and other large-scale actors contributed to forest conversion
by making forest access easier for migrants. But construction of main roads such as
the Trans-Sumatra Highway and other infrastructure investments probably had even
more powerful effects on people’s access to forest resources and the marketing links
that condition land use choices. To examine the complex issue of the two-stage deforestation process in which smallholders “encroach” on logged-over forest, a sample of
9477 data points was drawn from lowland forest logged in Jambi in the 1980s using
a 1-km grid and, following Chomitz and Gray (1996), a multivariate econometric
model was used to control for biophysical differences and estimate effects of distances
to main roads and rivers on probability of conversion to rubber agroforests and other
uses. Site characteristics (soil and topography) were highly significant, indicating that
smallholders are selective in their choice of sites. This model indicated that conversion of logged forest was much more likely within 10 km of main (asphalted) roads
(Chomitz et al. 1999).
Deforestation by Sumatran smallholders also is driven by their desire to establish
claims over land. Planting tree crops such as rubber is a well-established mechanism
for securing informal land tenure in Sumatra. Where communal forest land has to
be cleared before it can be claimed by individual families, this tenure arrangement
accelerates forest conversion. Within smallholder communities, slash-and-burn followed by tree planting is the chief means to establish private claims over (formerly)
communal land (Otsuka et al. 2001; Suyanto et al. 2001). This is one reason for
the existence of extensively managed jungle rubber. In addition to direct effects on
conversion, appropriation of large tracts of land for public and private projects can
have important effects on smallholders’ perception of their tenure security. Even the
expectation of new projects can accelerate forest conversion as a preemptive strategy
to retain control of land.
As emphasized earlier, smallholders are not the only actors converting forest,
nor are they the only group using slash-and-burn in Sumatra. Forest concessionaires,
industrial timber estates, tree crop plantations, and transmigration projects all have
played a role too. Large-scale operators also use slash-and-burn because it is the cheapest method to clear land. Logging concessions, especially of the 1960s to 1980s, followed by an inflow of spontaneous settlers attracted by opportunities in rubber and
other perennial-based agriculture, have completed the process to the point that there
is hardly any lowland primary forest left.
Po p u l at i on Pressure from Within and Outside
t h e F o re st Margins
Deforestation has often been attributed to population growth per se—the growth
resulting from location-specific human fertility. But the Geist and Lambin review,
like the Cameroon and Indonesia case studies, shows that migration is a far more
424
Cross-Site Comparisons and Conclusions
important factor: People move, as they have always done, to where the opportunities
exist. But institutional and policy-related factors also can be significant underlying
causes of deforestation via their effects on population movements. This category of
policy-induced causes of deforestation includes colonization in Brazil, transmigration
in Indonesia, and other government-sponsored resettlement schemes as well as public
investment in transportation infrastructure, subsidies for farming, and policies and
institutions affecting property rights, resource access, and land tenure.
At all asb benchmark sites, managing interregional migration will be key to future
land use patterns. Any technology or policy innovation that increases the productivity
and profitability of farming in the humid forest region runs the risk that additional
land and labor resources will be attracted to that particular activity and bring increasing deforestation. So far, in Cameroon, customary tenure institutions have been sufficiently robust to prevent large-scale interregional migration (Diaw 1997). However,
traditional institutions are changing (rapidly in some cases) and cannot be relied on to
solely (and peacefully) manage future population movements. Policy action to address
these issues is exceptionally difficult.
T H E A S B MATRIX: LINING UP THE FACTS IN WAYS
U S E F U L TO POLICYMAKERS
Policymakers need accurate, objective information regarding the private and social
costs and benefits of alternative land use systems on which to base their inevitably
controversial decisions. To help them weigh the difficult choices they must make, asb
researchers developed a tool known as the asb matrix (Tomich et al. 1998b; see also
chapter 1).
In the asb matrix, natural forest and the land use systems that replace it are
scored against different criteria reflecting the objectives of different interest groups. To
enable results to be compared across sites, the systems specific to each site are grouped
according to broad categories, ranging from agroforests to grasslands and pastures.
The criteria may be fine-tuned for specific locations, but the matrix always comprises
indicators for the following:
• Two major global environmental concerns: carbon storage and biodiversity
• Agronomic sustainability, assessed according to a range of soil, nutrient,
and pest trends
• Policy objectives: economic growth and employment opportunities
• Smallholders’ concerns: returns to their labor and land, their workload,
food security for their family, and startup costs of new systems or techniques
• Policy and institutional barriers to adoption by smallholders, including the
availability of credit and improved technology, and access to and the performance of input and product markets
Balancing Development and Environmental Objectives
425
Over the past 10 years, asb researchers filled in this matrix for representative
benchmark sites across the humid tropics. (See tables 18.1, 18.2, and 18.3 for simplified matrices emphasizing quantitative indictors for asb study sites in three countries; full sets of quantitative and qualitative indicators and complete explanations
are available for Brazil in Vosti et al. 2001b and Lewis et al. 2002, for Cameroon in
Kotto-Same et al. 2000 and Gockowski et al. 2001; and for Indonesia in Tomich et
al. 1998b, 2001.) The social, political, and economic factors at work at these sites
vary greatly, as does their current resource endowment, from the densely populated
lowlands of the Indonesian island of Sumatra, through a region of varying population
density and access to markets south of Yaoundé in Cameroon, to the remote forests
of Acre state in the far west of the Brazilian Amazon, where settlement by small-scale
farmers is recent and forest is still plentiful. At each site, asb researchers have evaluated land use systems both as they are currently practiced and in the alternative forms
that could be possible through policy, institutional, and technological innovations. A
key question addressed was whether the intensification of land use through technological innovation could reduce both poverty and deforestation.
U n d e r s tanding the Tradeoff s
The asb matrix allows researchers, policymakers, environmentalists, and others to
identify and discuss tradeoffs between the various objectives of different interest
groups and to discuss ways of promoting land use systems that seem likely to benefit
all groups but were not broadly adopted. The studies in Indonesia and Cameroon
have revealed the feasibility of a middle path of development involving smallholder
agroforests and community forest management for timber and other products. In Brazil, small-scale managed forestry poses the same potential benefits. Such a path could
deliver an attractive balance between environmental benefits and equitable economic
growth. Could is the operative word, however, because whether this balance is struck
in practice depends on the ability of these countries to deliver the necessary policy
and institutional innovations (see Tomich and Lewis 2001a, 2001b; Vosti et al. 2002,
2003).
Take the examples of Sumatran rubber agroforests and their cocoa and fruit
counterparts in Cameroon. These systems offer levels of biodiversity that, though
not as high as those found in natural forest, are nevertheless far higher than those in
monocrop tree plantations or annual cropping systems (chapter 4, this volume). Like
any tree-based system, they also offer substantial levels of carbon storage (chapter 2,
this volume). It is also interesting to note that there are several tree-based systems in
Cameroon with similar levels of carbon storage but drastically different profitability
and hence attractiveness to farmers (table 18.2 and figure 18.2); this example clearly
illustrates the value of the asb matrix. Crucially, technological innovations have the
potential to increase the yields of the key commodities in these systems, thereby raising
farmers’ incomes substantially, to levels that either outperform or at least compete well
with almost all other systems. However, to realize this potential it will be vital to find
148
148
56
56
3
3
7
3–6
80
NM
27
16
10
NM
34
26
0
0
0.5
–0.5
0 to –1
0 to –1
0 to –0.5
0 to –0.5
Soil
Structure
0
0
–0.5
–0.5
–0.5
–0.5
0 to –0.5
0 to !0.5
Nutrient
Export
0
0
–0.5
–0.5
–0.5
–0.5
–0.5
–0.5
to –1
to –1
to –1
to –1
Crop
Protection
–2
416
1955
872
2
710
!17
2056
Returns
to Land
(private prices,
R/ha)
1
1.22
27
59
11
13
23
21
1
20
13
9
7
22
6
17
NA
$
$
$
$, consumption
$, consumption
$, consumption
$, consumption
Entitlement
Path
(operational
phase)
$/Person-Day
(private
prices)
Labor
(person-day/
ha/yr)
Above-Ground
Plants (no. species
per standard plot)
Above-Ground
t C/ha
(time-averaged)d
Household
Food Securityc
Returns
to Laborb
Potential
Profitability b
Plot-Level Production
Sustainability
Biodiversity
Carbon Storage
Smallholders’ Concerns and
Adoptability by Smallholders
Labor
Inputs
National Policymakers’
Concerns
Agronomic Sustainabilitya
Global Environmental Concerns
NA, not applicable; NM, not measured.
a
For agronomic sustainability, 0 indicates no difficulty, –0.5 indicates some difficulty, –1 indicates major difficulty.
b
Prices are based on 1996 averages and expressed in December 1996 reais ( $ R1.04), discounted at 9% per annum.
c
For food security, “consumption” and “$” reflect whether the technology generates food for own consumption or income that can be used to buy food, respectively.
d
Indicates time-averaged above-ground carbon (see chapter 2, this volume).
Sources: Adapted from Vosti et al. (2001b), Gillison (2000a), and chapters 2, 6, and 17, this volume.
Forests
Managed forestry
Coffee–bandarra
Coffee–rubber
Traditional pasture
Improved pasture
Annual–fallow
Improved fallow
Land Use System
Table 18.1 The Summary Matrix for the Brazil Benchmark Site
0
0
–0.5 to –1 –0.5
–0.5
–0.5
0
–1
–0.5
0
–1
–1
0
–0.5
–1
–1
0
–1
NM
722–1458
424–943
889–1409
283
623
NM
93
65
107
44
115
—
1.81–2.44
1.63–2.13
1.95–2.36
1.70
1.79
$/Person-Day
Nutrient Crop
Returns
Labor
Export
Protection to Land
(person-days/ (private
prices)
(private prices, ha/yr)
$/ha)
Returns
to Laborb
$
$,
$,
$,
$,
$,
consumption
consumption
consumption
consumption
consumption
Entitlement
Path
(operational
phase)
Household
Food Securityc
Smallholders’ Concerns and
Adoptability by Smallholders
NM, not measured.
a
For agronomic sustainability, 0 indicates no difficulty, –0.5 indicates some difficulty, –1 indicates major difficulty.
b
Prices are based on the averages of the different establishment systems, from forest or fallow, for oil palm and whether fruits are sold in the cocoa systems and are expressed in Central
African francs ( $ 577 f ), discounted at 10% per annum.
c
For food security, “consumption” and “$” reflect whether the technology generates food for own consumption or income that can be used to buy food, respectively.
d
Indicates time-averaged above-ground carbon (see chapter 2, this volume).
Sources: Adapted from Gockowski et al. (2001), Kotto-Same et al. (2000), Gillison (2000a), and chapters 2, 6, and 17, this volume.
76
NM
63
63
53
63
Above-Ground
Above-Ground
Soil
t C/ha
Plants (no. species Structure
(time-averaged)d per standard plot)
Labor
Inputs
Potential
Profitability b
Plot-Level Production
Sustainability
Carbon Storage
Biodiversity
National Policymakers’
Concerns
Agronomic Sustainabilitya
Global Environmental Concerns
Forest
211
Oil palm
61
Extensive cocoa
61
Intensive cocoa
61
Food crop–long fallow
63
Food crop–short fallow
4
Land Use System
Table 18.2 The Summary Matrix for the Cameroon Benchmark Site
120
100
90
90
60
25
45
15
306
120
94
79
66
62
37
2
–0.5
–0.5
–1.0
–0.5
0
0
–0.5
0
0
Nutrient
Export
0
0
–0.5
0
–0.5
0
0
Soil
Structure
–0.5
0
–0.5
0
–0.5
–0.5
0
0
Crop
Protection
60
114
–62
1080e
0.70
878
0
5
Returns
to Land
(private prices,
$/ha)
98–104
108
15–25
31
111
150
0
0.2–0.4
1.78
4.74
1.47
0.78
1.67
2.25
0
4.77
$, consumption
$
Consumption
$
$
$
NA
$, consumption
Entitlement
Path
(operational
phase)
$/Person-Day
(private
prices)
Labor
(person-d/
ha/yr)
Above-Ground
Plants (no. species
per standard plot)
Above-Ground
t C/ha
(time-averaged)d
Household
Food Securityc
Returns
to Laborb
Potential
Profitability b
Plot-Level Production
Sustainability
Biodiversity
Carbon Storage
Smallholders’ Concerns and
Adoptability by Smallholders
Labor
Inputs
National Policymakers’
Concerns
Agronomic Sustainabilitya
Global Environmental Concerns
NA, not applicable.
a
For agronomic sustainability, 0 indicates no difficulty, –0.5 indicates some difficulty, –1 indicates major difficulty.
b
Output prices are based on 10-yr (1988–1997) averages and expressed in U.S. dollars in 1997 ( $ Rp2400 in 1997), discounted at 20% per annum.
c
For food security, “consumption” and “$” reflect whether the technology generates food for own consumption or income that can be used to buy food, respectively.
d
Time-averaged carbon from Tomich et al. (1998b) and chapter 2.
e
Social prices, rather than private prices, were used for logging (see chapter 17, this volume).
Sources: Adapted from Tomich et al. (1998b, 2001), Gillison (2000a), and chapters 2, 6, and 17, this volume.
Forest
Community-based
forest management
Commercial logging
Rubber agroforest
Rubber agroforest with
clonal planting material
Oil palm
Upland rice–bush
fallow
Continuous cassava–
Imperata
Land Use System
Table 18.3 The Summary Matrix for the Indonesian Benchmark Sites
Balancing Development and Environmental Objectives
429
Figure 18.2 Financial profitability of the different land use systems in Cameroon and the above-ground
time-averaged carbon stocks. Adapted from table 2.2 and chapter 17.
ways of delivering improved planting material, the key input needed. Other obstacles
to more widespread adoption of these agroforestry systems are the higher labor inputs
compared with other systems (tables 18.1, 18.2, 18.3), the costs of establishment, and
the number of years farmers must wait for positive cash flow (table 18.4).
In contrast, the Brazilian Amazon presents much starker tradeoffs between global
environmental benefits and the returns to smallholders’ labor. Here the most commonly practiced pasture–livestock system, which occupies most converted forest land,
is reasonably profitable and provides the best fit for the situations and needs of smallholders but entails huge carbon emissions and biodiversity loss. Systems that are preferable to this one from an environmental point of view, such as coffee combined with
bandarra (Schizolobium amazonicum Huber ex Ducke), a fast-growing timber tree, can
pay better but have prohibitively high labor costs and are riskier for farmers. An alternative, “improved” pasture–livestock system, in which farmers are expressing interest,
offers even higher returns to land and labor but only slightly improves biodiversity and
carbon storage. In other words, the land use alternatives that are attractive privately are
those most at odds with global environmental interests. Only a radical overhaul of the
incentives (or disincentives) facing land users—including smallholders—is likely to
change land use patterns.
Just how radical would the overhaul have to be? Depending on the policy instrument chosen, it would have to be very radical—even for a small effect—according to
asb research (Vosti et al. 2002). Consider, for example, the gathering of Brazil nuts
430
Cross-Site Comparisons and Conclusions
Table 18.4 Establishment Costs and Years to Positive Cash Flow for the Different Land Use
Systems for the Benchmark Sites in Indonesia and Cameroon
Meta–Land Use
Establishment Costsa ($/ha)
Years to Positive Cash Flow
Sumatra
Cameroon
Sumatra
Cameroon
NA
352
NA
NA
NA
2
NA
NA
117–1119
869–3350
1188–1304
1200
7–10
10
7–8
5
NA
NA
NA
NA
Never
2
NA
NA
Forest
Managed
Logged
Tree Crop–Based
Complex
Simple
Crops–Fallow
Short fallow
Annual crops
NA, not applicable.
a
A calculated using private (financial) prices and discount rates of 10% for Cameroon and 20% for Indonesia.
Sources: Tomich et al. (1998b) and Kotto-Same et al. (2000).
(Bertholletia excelsa Humb. & Bonpl.) from the natural forest, one of the most environmentally benign uses of the Amazon’s forests. Settlers in Brazil’s Acre state clear
forest gradually over the years, with pasture for cattle becoming the dominant land
use. In addition, approximately 50 percent of farm families in the asb study sample
harvested nuts from the part of their farms that remained forested. Using a specially
developed bioeconomic model, asb researchers explored how labor, capital, and land
would be allocated to different on-farm activities over a 25-year period under different price and market scenarios. When the model was used to examine the effects
of changes in the farmgate price of Brazil nuts, researchers found that doubling the
farmgate price of nuts would not decrease and might even increase the rate of deforestation because farmers probably would reinvest the extra cash they earned in clearing
forest faster. This would be a sensible response from the farmers’ perspective because,
even at the higher Brazil nut price, cattle production would remain by far the more
profitable activity. Only in the unlikely event that prices quadrupled over their current level might the rate of deforestation slow, but even then the braking effect would
be slight and the modest saving in forest probably would be short-lived. At current
prices offered to smallholders, Brazil nut harvesting pays well below the going rate for
wage labor. The researchers concluded that subsidizing the price of Brazil nuts would
not, by itself, be an effective policy measure for conserving forests, and even if it were
effective, the highly charged political issue of paying for the subsidy looms large. Carpentier et al. (chapter 10) found a similar result with coffee systems in the Brazilian
Amazon; policy-induced expansion of smallholder coffee production slowed but did
not halt deforestation.
Balancing Development and Environmental Objectives
431
Research by asb scientists of the Empresa Brasileira de Pesquisa Agropecuária
(Embrapa) on the pasture–livestock system in the western Amazon of Brazil shows
that, with a combination of legumes to enrich pastures and solar-powered electric
fences to control the pattern of grazing by their cattle, smallholders could double milk
production per cow, triple the carrying capacity of their land, and earn substantially
higher profits. And because this pasture system is sustainable without annual burning
to control weeds, seasonal smoke pollution would be reduced (see Tomich and Lewis
2002).
So why have these practices not been widely adopted already? First, most smallholders cannot get access to the necessary credit, seeds, or hired labor and are too far
from markets to be able to sell the increased milk supplies. Second, aiming for these
higher profits entails increased risk, in part because of the higher initial investment
costs and the increased dependence on product and input markets. But even if these
barriers were eliminated, widespread adoption of such improvements probably would
increase—not decrease—the pressure on neighboring forests for two reasons. First,
established smallholders probably would use increased profits to clear more forest for
agriculture. Second, the greater profitability of the improved system would make the
agricultural frontier more attractive to new settlers. Thus under the present mix of
policies and institutions, and the incentives they create, the forests in Brazil’s western
Amazon will continue to fall whether the smallholder succeeds or fails, although the
pace of forest conversion and the prevalence of poverty will vary depending on which
of the two scenarios plays out.
A case in Lampung Province in southwest Sumatra provides a more encouraging example in which policy action has ensured the continuation of productive and
sustainable agroforestry. The Krui people of the area grow rice (Oryza sativa L.) in
permanent irrigated plots as their staple crop, whereas in the uplands they cultivate a
succession of crops, building to a climax that mimics mature natural forest. The tallgrowing timber species they plant include the damar tree (Shorea javanica Koord. &
Valeton), a source of valuable resin that provides a steady flow of income over the long
term. The Krui system is able to deliver broad-based growth in which the poor can
participate. Combining environmental and economic benefits, the Krui system offers
advantages over many other systems that replace or exploit natural forest.
In 1991 the Krui system came under threat. The Suharto government, which
had a long history of appropriating traditionally managed land and reallocating it to
public or private ownership, declared large areas of the Krui agroforests to be State
Forest Land, a classification that would allow logging followed by conversion to oil
palm plantations. A forestry company was awarded the right to harvest an estimated
3 million trees—trees that had been planted by the local people.
The Krui stopped planting damar and other tree species, saying that they would
not resume until they were certain they would be able to reap the benefits of their
work. A consortium of research institutions, nongovernment organization (ngos),
and universities was able to provide support to these local communities through convincing scientific evidence on the social and environmental benefits of the Krui system
432
Cross-Site Comparisons and Conclusions
precisely when it was needed. The scientific evidence helped to legitimize the Krui
system in the eyes of professional foresters and refute arguments by vested interests
intent on taking the land. The consortium conveyed requests to the government from
village leaders for dialogue on the status of their land, arranged field visits for key
government officials, and organized a workshop to present research results and discuss
the tenure issue. The activities of the consortium were reported in detail to the Minister for Forestry, who signed a new decree in 1998 reversing the official position. This
historic decree declared the Krui system to be a unique form of forest use, recognized
the legitimacy of community-managed agroforests in Lampung Province, and restored
the rights of the Krui to harvest and market timber and other products from the trees
they plant. The decree is a powerful instrument for restoring social justice and promoting sustainable development. In the short term it benefits at least 7000 families
in the 32,000 ha of reclassified Krui lands. This principle of local management could
be extended to benefit hundreds of thousands of rural Indonesians in similar areas.
Although it would not work everywhere, Indonesian ngos have identified at least fifty
other communities across the archipelago that have developed production systems
comparable to the Krui case that would be ripe for replication of this approach to
reform.
Th e Ba l ancing Act
Based on these results and others presented in this publication, what can be done to
balance the objectives of forest conservation and poverty reduction in these tricky
settings? Some assert that the best opportunities for meeting both objectives lie in
the harvest of various products from community-managed forests. In practice, such
extensive systems require low population densities plus effective mechanisms for keeping other groups out if they are to prove sustainable. Where forests are converted,
agroforests often represent the next best option for conserving biodiversity and storing carbon while also providing attractive livelihood opportunities for smallholders.
However, for both economic and ecological reasons, no single land use system should
predominate at the expense of all others. Mixes of land uses increase biodiversity at a
landscape level, if not within individual systems, and also can enhance economic and
ecological resilience. A mixed landscape mosaic is an especially attractive option in
cases such as Brazil, where no single system (with the exception of the experimental
small-scale managed forestry system) offers a reasonable compromise between profitability and environmental objectives.
Where the productivity of the natural resource base has already sunk to very low
levels, concentrating development efforts on the simultaneous environmental and
economic restoration of degraded landscapes is an option well worth exploring. The
precise mix of interventions needed—hence the benefits and costs of restoration—
varies from place to place. In Cameroon, improved cocoa (Theobroma cacao L.) and
fruit tree systems could be a win–win proposition in place of unsustainably short-
Balancing Development and Environmental Objectives
433
fallow rotations (chapter 14, this volume). In Indonesia, millions of hectares of Imperata grasslands are the obvious starting point (chapter 11, this volume; Garrity 1997),
as are the millions of hectares of degraded pastures in Brazil. The direction of change
in land use systems determines the environmental consequences. For example, if farmers replace unsustainable cassava production with an improved rubber agroforest, they
help restore habitats and carbon stocks. But if such a system replaces natural forest,
the environment loses.
Intensification of land use through technological change is a two-edged sword.
It has great potential to increase the productivity and sustainability of existing forestderived systems, thereby raising incomes. By the same token, however, these higher
incomes attract more landless people to the agricultural frontier in search of a better
living. Therefore technological innovation to intensify land use may not be enough
to stop deforestation. Indeed, it often can accelerate it (see Angelsen 1999; Angelsen
and Kaimowitz 2001a). If both objectives are to be met, policy measures intended to
encourage intensification must be accompanied by measures to protect those forest
areas that harbor globally significant biodiversity.
R E S E A RC H INNOVATIONS AND NEW DIRECTIONS
FOR ASB
Numerous methodological and organizational innovations were necessary to analyze
these tradeoffs between the concerns of poor households, national development objectives, and global environmental concerns. In its early phases, asb focused on understanding and ultimately quantifying these contrasting perspectives. Standardized
methods were used across sites to assess the environmental and agronomic sustainability of the various land use alternatives found on farms in each benchmark site, and
participatory methods were used in the same sites to understand household problems,
opportunities, and constraints. Similarly, consultations with local and national policymakers provided insights about their perceptions of problems, opportunities, and constraints. In this way, participatory research and policy consultations guided the iterative process necessary to identify and develop policy, institutional, and technological
options that are workable and relevant. The asb’s multidisciplinary thematic working
groups—on biodiversity, climate change, agronomic sustainability, and global synthesis of implications for policy, institutional, and technological options—developed new
methods as needed and ensured that data were comparable across sites. They share a
commitment to measurement techniques that are reliable, cost-effective, and therefore
readily adoptable by national partners. The asb researchers have developed and tested innovative indicators of above- and below-ground biodiversity, carbon stocks and
greenhouse gas emissions, agronomic sustainability, returns to labor and other determinants of adoptability by smallholders, and national policymakers’ concerns. These
methods have been applied to a range of land use systems at asb benchmark sites, and
these integrated results enabled the analysts to the link global environmental benefits
434
Cross-Site Comparisons and Conclusions
to sustainable land use alternatives. The basic concepts and methods were made available for education systems at postgraduate level (van Noordwijk et al. 2001b; Wunder
and Verbist 2003).
Instead of supporting the simple sustainable–unsustainable dichotomy, asb
results indicate that a remarkably wide range of smallholder land use options can be
agronomically sustainable and profitable, depending on the larger environmental and
economic context. A key policy insight from this work is that these (locally) sustainable options differ significantly in their environmental impacts and their profitability
and adoptability by poor households.
Much of the institutional innovation and reorientation necessary to produce this
integrated assessment of tradeoffs and alternatives occurs at the national level as asb
scientists work with partners in national research systems to develop research strategies
that combine environmental and development concerns. In Brazil, for example, scientists from Embrapa have taken the lead in incorporating the environmental insights
derived from their collaborative work with asb into Embrapa’s agricultural research
agenda. In addition, Embrapa scientists are achieving impact at the national level by
assisting government officials as they set national priorities for sustainable agricultural
and silvopastoral development in the Amazon. With the support of asb research,
Embrapa scientists also collaborated with Brazil’s Ministry of Environment in designing a new Forest Code that will have large and widespread implications for Brazil’s
land use and deforestation policies.
Although no forest-derived system is a perfect substitute for the global environmental benefits of rainforest conservation, asb results suggest that a middle path of
development exists—involving smallholder tree-based systems and community-based
and private forest resource management—that could attain an attractive balance
between the environment and development. Whether this balance can be achieved
depends on a range of policy and institutional innovations, including means to effectively protect natural forests and compensate households for foregone opportunities.
The asb does not claim to have all the answers to these challenges in hand. However, by building on what is known about participatory research and development and
by simultaneously considering the workings of coupled biophysical and socioeconomic
systems, we feel that the various asb consortiums can become vehicles for participation by diverse interests in the countries concerned. Examples include local community
associations and conservation groups, local government and civic organizations, local
and national ngos, and policymakers and other officials at various levels.
Looking ahead, the asb consortium plans to stick to its basic goals: to identify
and articulate combinations of policy, institutional, and technological options that
can raise productivity and income of rural households without increasing deforestation or undermining essential environmental services. However, the consortium recognizes it is both feasible and desirable to shift its emphasis as follows:
From plot to landscape: The asb has made important contributions to clarification of tradeoffs between the welfare of poor rural households and global environmental concerns. However, hydrologic, ecological, and other more localized environmen-
Balancing Development and Environmental Objectives
435
tal services are a significant gap in this analysis in terms of impacts on local people,
priorities of key policymakers, and their potential complementarity with global environmental objectives. The asb will work to help fill this gap by developing replicable
assessment techniques and policy-relevant databases on local environmental services
that underpin the sustainability, resilience, and stability of rural production systems at
various scales. These methods and databases will build on and extend asb’s repertoire
of data and techniques to assess global environmental concerns, agronomic sustainability, household socioeconomic concerns, institutional options, and opportunities
for policy reform. A working group on sustainable mosaics of land uses focuses and
implements asb’s work in a broader landscape context.
From prescription to dynamic adaptation: The asb works in a broader context of
social, political, economic, and environmental change. Natural resource problems in
the tropics are compounded by population growth, climatic shocks such as El Niño,
and social, economic, and political turmoil. Clearly no single prescription can deliver
a sustainable balance between human needs and environmental services under these
shifting circumstances over time and space. The asb will seek replicable ways to better meet the needs of various stakeholders for methods they can use to monitor and
understand the impacts of ongoing change and develop workable responses under
dynamic and uncertain conditions. A range of flexible tools—including participatory
approaches, formal models, and practical methods to assess impact—will be identified
and developed for communities, local government agencies, ngo activists, research
managers, and policymakers and other officials. These diverse stakeholders can then
better explore their options to influence the individual choices that ultimately determine the rate and pattern of land use change.
From assessment of tradeoffs to management of inevitable conflicts: The asb’s
work to clarify tradeoffs between global, national, and local objectives is just the beginning, because achieving impact on natural resource problems depends on effective
means to disseminate information to myriad stakeholders in forms they can use. But
even more and better information is not enough because social and political mechanisms also are needed to address the inevitable conflicts between the interests of these
stakeholders, who range from extractivists and farmers, to national research managers
and policymakers, to environmental advocacy groups, multinational corporations, and
international development agencies. Unless workable interventions can be identified
and disseminated, the future in much of the tropics will include intensifying social
conflicts over natural resources and environmental services. The ability to strengthen
or create mechanisms for conflict management—between neighboring communities,
upstream and downstream populations, and local, national, international, and global
concerns—depends on a better understanding of collective processes of governance,
including negotiation, identification, and implementation of incentive schemes and
sanctions and monitoring and enforcement of agreements (van Noordwijk et al.
2001a). The asb will seek to identify means and build capacities to manage inevitable
conflicts between stakeholders at various scales, including mechanisms to compensate
local people for foregone opportunities.
436
Cross-Site Comparisons and Conclusions
C O N C LUSION
The challenge of preventing deforestation is complicated by two facts: In some cases
halting deforestation would increase poverty, and in most cases deforestation has no
single cause that can be easily identified and tackled. Regarding poverty in forest
margins areas, knowing how and how much the forest can help reduce poverty is an
essential factor in policy decisions. Regarding the causes of deforestation, it generally results from a combination of different factors, so a mix of policies, rather than
a single measure, will be needed. Careful identification of the factors at work in a
given location will be a prerequisite for getting the mix right while minimizing the
cost to other legitimate development objectives. However, a common and dominant
theme for all asb sites, despite the variability of their socioeconomic and biophysical conditions, is that small-scale farmers cut down tropical forests because current
national and international policies, market conditions, and institutional arrangements either provide them with incentives for doing so or do not provide them with
alternatives.
If the development community is serious about preventing deforestation, it must
pay more attention to powerful macroeconomic forces that drive people to clear land
for other uses. At present, these forces can swamp local conservation efforts: The area
of forest cleared by successive waves of migrants, facilitated by the building of roads
and driven by the lack of opportunities elsewhere in the economy, vastly exceeds the
area “saved” by projects focusing on sustainable forest use by individual farms or villages. A major weakness of past conservation efforts is that they have routinely limited
their activities to technical interventions at the local level while failing to tackle the
larger policy and institutional issues that also determine success or failure. Changing
the economic incentives to clear forest into incentives to conserve it will be extremely
costly, not only in terms of the direct costs of changing incentives at the local level but
also perhaps in terms of the opportunity costs of forgone economic growth. Indeed,
the developing countries that still have large areas of natural forest are unlikely to
design their macroeconomic policies solely to protect these forests, because they face
other pressing development imperatives.
But without tangible incentives linked to the supply of global environmental benefits, people will continue to cut down tropical rainforests. Results from asb research
at all the benchmark sites show that it is futile to attempt to conserve forests in developing countries without addressing the needs and objectives of local people, poor or
not. But how can the necessary incentives to conserve be put in place? Only a limited
number of policy instruments have been tried, and there is still much to learn about
what does and does not work. Part of the answer lies in the developing countries
themselves, which can take measures such as securing land tenure and use rights. But
should these countries have to shoulder the entire financial burden of forest conservation when all face urgent development imperatives, such as educating and vaccinating
rural children?
Balancing Development and Environmental Objectives
437
If the international community wants the global benefits of rainforest preservation, it is going to have to pay some of the costs. Opportunities for changing tropical
land use patterns through the Clean Development Mechanism of the Kyoto Protocol
are being explored as one of many possible approaches to environmental service payments. In Latin America, pilot carbon sequestration projects implemented after the
Earth Summit in Rio de Janeiro have demonstrated the economic feasibility of carbon storage by smallholders at costs likely to be attractive in a global carbon market
(cifor 2000; also see Smith and Scherr 2002). The asb research provides evidence
of the potential responsiveness of Brazilian smallholders to payments for carbon storage and forest conservation (Carpentier et al. 2000). If an institutional framework can
be designed to efficiently deal with the significant transactions costs and monitoring
issues associated with such pilot projects, there is the promising possibility of internalizing some of the environmental costs and benefits of various agricultural land uses
along the forest margins. This could help shift incentives toward more environmentally benign land uses and provide resources for addressing the many constraints to the
adoption of these systems. Moreover, asb research has already provided some guidance to the international community regarding where forests might be most cheaply
preserved via these mechanisms and where the greatest amount of poverty alleviation
might be achieved per conservation dollar spent.
AC K N OWLEDGMENTS
We have benefited particularly from discussions with Arild Angelsen, Kenneth Chomitz, Polly Ericksen, Merle Faminow, Erick Fernandes, Dennis Garrity, Andy Gillison, Anne-Marie Izac, Stewart Maginnis, Pedro Sanchez, Mike Swift, Stephan Weise,
Julie Witcover, and participants in the asb “Synthesis and Linkages” working group.
Support for elements of this work has been provided by the Global Environmental
Facility, the Danish International Development Agency, the Ford Foundation, the
Asian Development Bank, the Interamerican Development Bank, the Australian Centre for International Agricultural Research, Embrapa, and the governments of Indonesia, Japan, the Netherlands, and the United States. Portions of the text draw on asb
Policybrief no. 5 and no. 6 (Tomich and Lewis 2003a, 2003b).
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Index
Acacia mangium (acacia), 20, 44, 51, 251, 258,
260
Achard, F., 3
Acre, state of (Brazil): ASB in, 28, 278–80,
335, 425; benchmark sites in, 13, 266; biodiversity studies in, 95, 100; deforestation
in, 271, 272; economic development in,
268, 273–74, 275; Embrapa research center
in, 14, 95, 174, 279, 284; labor needs in,
403; LUSs in, 238–40, 404; migration to,
271; policy in, 282–85; population growth
in, 269; sustainability in, 276; tradeoffs in,
430; transportation in, 181. See also Pedro
Peixoto
Acre State Technological Foundation (FUNTAC; Brazil), 203
Afamba (Cameroon), 96–97
Africa, 4–6, 14, 20, 22, 283, 305, 321; forest
management in, 205, 217; urbanization in,
307, 330, 408. See also Cameroon; Congo
Basin
Agency for Agricultural Research and Developemnt (AARD; Java), 14
Agenda 21, 10, 29–30
agricultural intensification, 6–8; in Africa, 308,
318, 323–24, 325, 329; and ASB, 11, 425;
and biodiversity, 111, 121, 122, 123, 131,
132; and deforestation, 280, 297, 417, 418,
433; and LUSs, 323–24, 372–76, 410; in
Thailand, 361, 371, 372–76. See also land
use intensity
agriculture: and biodiversity, 89, 121–22, 131,
133, 134, 135; in Brazil, 173, 266, 268;
and cash crops, 20, 373–74; and currency
devaluation, 179, 192; diversification of,
122, 131, 318, 330, 373–74; innovations
in, 372–76; intercropping in, 5–6; and land
use change, 172, 362–63; low- vs. highinput, 70–71, 72; and markets, 173, 182,
318; products of, 349, 362–63; subsistence, 122, 127; sustainability of, 143–46;
and technology, 6, 173, 185–91, 193; in
Thailand, 358, 359–60, 368, 373–74;
wage labor in, 17, 227. See also crop-fallow
systems; cropping, continuous; crops, annual; crops, perennial; farmers, small-scale;
frontiers, agricultural; horticulture; land
clearing, agricultural; shifting cultivation;
slash-and-burn agriculture; tree-based
systems
agriculture, large-scale, 5, 9, 175, 176, 406;
in Brazilian Amazon, 271, 282, 286; in
Cameroon, 306, 312, 313, 319, 322; and
deforestation, 271, 292, 306, 313, 416; and
GHG, 66, 69; in Indonesia, 14, 223, 249,
250, 255, 291, 292, 300, 302, 420–22;
monoculture in, 20, 300, 312, 319; vs.
small-scale farmers, 300, 319, 322; and
technology, 185, 186, 187–91, 193; in
Thailand, 363; and transportation, 182
agrochemicals, 318, 370, 373, 395, 405. See
also fertilizers; herbicides; pesticides
agroforests, 5, 7, 396, 432; and ASB, 26, 222,
224, 425; bananas in, 239; biodiversity in,
20, 90, 93, 94, 107, 108, 109, 111, 123,
131–35, 137, 223, 224, 301, 340; Brazil
nuts in, 20–21, 282; in Cameroon, 20,
307, 310, 311–12, 314, 321, 329; carbon
stocks in, 44, 49, 51, 52, 54, 55, 59, 60,
223, 224, 329; cocoa in, 20, 311–12, 314,
321; community-managed, 375–76; complex, 18–20, 19, 25, 375; and deforestation
234, 271, 302; as factor of production,
175, 176; fruit trees in, 20, 228, 230, 292,
442
Index
agroforests, (continued )
374, 375; and genetic resources, 249, 344–46;
and GHG, 67, 68, 69, 70, 71–76, 342, 343;
and Imperata control, 249, 252, 256–61; in
Indonesia, 18, 19, 20, 224–30, 295, 297, 299,
301, 302, 397, 422, 423, 428; labor in, 224–27,
229, 230, 231, 271, 301, 349, 375; and LUS
change, 282, 284, 378, 388, 411; peach palm
in, 20, 282; in Peruvian Amazon, 338, 339, 341,
350; pests in, 160, 223, 226, 228, 229, 230;
policy on, 231, 245, 301, 324; property rights
in, 28, 295–96; research on, 281, 378; rubber in,
20, 160, 165, 166, 222–31, 292, 294–95, 399,
422, 423, 425, 428, 433; Shorea javanica-based,
295; simple, 19, 20–21, 374–75; and slash-andburn agriculture, 291–92; small-scale, 222–31,
294–95; and soil structure, 154, 155; subsidies
to, 328–29; sustainability of, 157, 161, 163–66,
328; in Thailand, 371, 374–76; and women,
319. See also tree-based systems
air quality, 146, 147, 150
Akha (minority group), 359, 366
Akok (Ebolowa Station, Cameroon), 90, 97, 135
alang-alang. See Imperata cylindrica grasslands
Alegre, Julio C., 338
Alternatives to Slash and Burn (ASB) consortium,
3–30; founding of, 10; goals of, 11–12; impact
of, 12, 13, 16, 27–29, 278–86, 435; matrix of,
24–25, 26, 183, 378, 406, 424–33; research of,
12–13, 16–30, 278–81, 387–91
altitude zones, 358–60, 365, 366–69, 380
aluminum, 21, 106, 300
Amazonas, state of (Brazil), 200
Amazon Basin, 18, 21, 54, 222, 266
Amazon, Brazilian: agriculture in, 21, 173, 266,
268, 271, 282, 286, 402, 404, 426; and ASB,
10, 18, 22, 27, 266; ASB matrix for, 25, 425,
426; benchmark sites in, 13–14, 15, 17, 266;
biodiversity in, 90, 93–95, 100, 107–9, 111,
125, 128, 132–35, 137, 200, 265, 267, 268,
270, 426, 429; carbon stocks in, 42, 44, 48–49,
51–55, 59, 60, 265, 267, 270, 426, 429, 437;
cattle in, 21, 239, 265, 268, 401, 402, 403;
in cross-site comparisons, 406–9; and currency devaluation, 178, 179; deforestation in,
3, 171–72, 200, 233–46, 265, 266, 270–71,
272, 430; economic development in, 265, 266,
268, 273–75; forest management in, 199–218;
labor in, 266, 268–69, 401, 402–3, 404, 426,
429, 430; land tenure in, 183–85; LUSs in, 19,
401–5, 410–11, 426; macroeconomic factors in,
170–94; markets in, 266, 403–5, 430; migration
in, 266, 268, 269, 424; pastures in, 401–4, 426,
429, 430–31; vs. Peruvian Amazon, 346, 350,
351; policy towards, 265–69, 282–85, 419, 426;
population density in, 266, 269–70; production activities in, 173–75; small-scale farmers
in, 401–5, 426, 429, 431; socioeconomic issues
in, 24, 181–91; sustainability in, 154–64, 266,
401, 426, 431; tradeoffs in, 429, 430–31, 432,
433; transportation in, 9, 13, 181–83, 192, 268;
várzeas (flooded areas) in, 200; welfare effects
in, 274–75. See also Acre, state of; Pará, state of;
Rondônia, state of
Amazon, Peruvian, 20, 332–51; Andes region of,
8, 332; and ASB, 333; biophysical research in,
338–46; vs. Brazilian Amazon, 346, 350, 351;
land use patterns in, 334–38
Amazon Treaty Organization, 233
Ambam (Cameroon), 307, 314
Ambassa-Kiki, R., 16
Anderson, J. M., 127
Angelsen, A., 172, 234, 245
animals. See cattle ranching; fauna; livestock
ants, 23, 120, 154, 322, 340; and biodiversity, 101,
124, 125, 131–33, 138, 139
aquaculture, 175, 176, 371. See also fish
Arachis spp. (peanuts), 21, 281, 283, 310, 311, 312.
See also groundnuts
arachnids, 102, 120, 124, 340
arthropods, 101–2, 124, 340. See also ants; insects
ASB. See Alternatives to Slash and Burn (ASB)
consortium
Asia, 4, 42, 248. See also China; Southeast Asia
Asian Development Bank, 28
Aspidosperma vargasii, 209
Asteraceae, 21, 338
Ávila, M., 16
Awae (Cameroon), 90, 96, 135
bacteria, 126, 134, 155; chemolithotrophic, 120,
121; root-nodulating, 124–25, 128–29, 131,
133, 135, 136, 138–39
Bactris gasipaes (peach palm; pupunha), 19, 20, 44,
94, 107, 108, 281, 282, 340–42
Bafia (Cameroon), 97
Bagnall-Oakeley, H., 259
bandarra. See Schizolobium amazonica
Bangkok (Thailand), 361
Batoum (Cameroon), 97
Index
Belém-Brasília road (Brazil), 9, 268
benchmark sites, 12, 27, 28, 424; alternative LUSs
for, 18–22; in ASB matrix, 25, 425–33; biodiversity studies at, 89, 90–100; in Brazilian Amazon,
13–14, 15, 17, 266; in Cameroon, 14, 15, 16,
17, 306–13; carbon stocks at, 42, 44, 48–49;
characterization of, 16–22; cross-site comparisons
of, 406–9; and GHG, 64–79; in Mexico, 14, 18;
PAM results for, 391–405; in Peruvian Amazon,
335–38; similarity classes for, 15; in Sumatra,
14–15, 292, 294–301. See also particular sites
Bertholletia excelsa (Brazil nuts; castanha), 18, 19,
44, 206, 281, 402; in agroforests, 20–21, 282;
in biodiversity studies, 94, 107, 108; in Brazilian
Amazon, 401, 429–30; in FaleBEM, 235, 238,
242; prices of, 238, 241
Bignell, D., 23
biodiversity: and agriculture, 89, 121–22, 131, 133–
35, 320; in agroforests, 20, 90, 93, 94, 107–9,
111, 123, 131–35, 137, 223, 224, 301, 315,
340; and ASB, 6, 7, 11, 13, 23, 27, 122, 433; in
ASB matrix, 26, 424, 425; assessment of, 83–84,
85, 88, 90–100; and best-bet alternatives, 107,
108, 109, 112; in Brazilian Amazon, 90, 93–95,
100, 107–9, 111, 125, 128, 132–35, 137, 200,
265, 267, 268, 270, 286, 426, 429; in Cameroon, 90, 96–97, 107–10, 125, 128, 132, 133,
135, 138, 308–11, 427; and carbon stocks, 98,
102, 103, 106, 112, 120, 126, 137; and cassava,
90, 92, 93, 96–98, 109–11, 132; and cocoa, 90,
97, 98, 107–10, 315, 320, 321, 322; and community-based forests, 98, 314, 323; correlation
of plant and animal, 85, 88, 100–107, 109; and
crop-fallow systems, 92, 98, 111, 123, 133, 134,
135; definition of, 84; and deforestation, 3, 23,
233, 416, 433; and ecosystem dynamics, 83, 85,
119–20, 122, 134; in forests, 91, 94–97, 103,
109–11, 123, 132–35, 137, 201, 212–13, 293;
and geology, 98, 99, 106; and government, 84,
297; in grasslands, 90, 92, 107, 109, 110, 123,
132, 137, 139; in Indonesia, 85, 90–92, 98,
100, 106, 107, 109–11, 125, 129, 130, 132,
133, 136, 137, 139, 300–302, 428; at landscape
scale, 89–90; and LUS alternatives, 4, 23, 85, 98,
121–23, 130–33, 138, 328, 340, 378; and LUSs,
23, 85, 98, 121, 122, 123, 130–33, 138, 340; in
MMSEA ecoregion, 355; and oil palm, 90, 95,
111, 322, 323; in Peru, 332–33, 338–40; and
PFTs, 91–103, 105, 106, 112–13; and policy,
84, 111–12, 301, 303; and productivity, 83, 84,
443
90, 106, 111, 112, 122; and profitability, 83,
111, 112, 301; rapid assessment (RBA) of, 85,
88; research on, 10, 280, 286, 302, 350; and
rubber, 90, 92–94, 103, 106, 107, 109–11, 132,
133, 136, 137, 223, 224; and sustainability, 146,
150; in Thailand, 106, 111, 357; and tradeoffs,
25, 432; transferability of, 83–84
biodiversity, below-ground, 119–39, 280, 286, 302,
338–39, 433; vs. above-ground, 98, 121, 122;
and ASB, 10, 13, 23, 27; assessment of, 122,
123–30, 126, 127; importance of, 119–22;
and land use systems, 121, 123, 130–33; and
nutrients, 121, 124, 139; sampling methods for,
127–30, 138–39; and soil, 119–22, 124, 131;
and tree-based systems, 123, 132, 137
Biodiversity Convention, 233
biodiversity indicators, 23, 83–113; in field studies,
90–112; FTs as, 86–89; interregional, 87, 88
bioeconomic simulation models, 193–94, 276, 280–
81, 285. See also Farm Level Bioeconomic Model
Biological Management of Soil Fertility Project, 251,
253
BIOTROP permanent plots, 91
bioturbation, 120, 121, 139
birds, 20, 23, 85, 102, 103, 109, 138, 217
Bixa orellana (achiote), 347
Blair, G. J., 152
Bolivia, 346
Bora people, 19, 20
Borneo, 18, 420
Boserup, E., 6
Brachiaria brizantha (braquiarão/brizantão) pastures,
93, 95, 275, 283, 341, 348, 349
Brachiaria humidicola, 21
Brassica spp. (cabbage), 19, 362, 374
Brazil: ASB in, 434; benchmark sites in, 13–14, 15,
16, 17, 266; colonization programs in, 8, 170,
200, 269; currency devaluation in, 176, 178–79,
419; deforestation in, 3, 170–94, 305–6, 419;
economic development in, 409; environmental
movements in, 233; forest management in,
199–200; map of, 267; roads in, 9, 13, 268;
savannas of, 90, 409; Western, 233–46, 265–87.
See also Amazon, Brazilian
Brazilian Institute for the Environment and Natural
Resources (IBAMA), 199, 209, 218
Brewer, K.R.W., 98
BR-362 highway (Brazil), 13
BR-364 highway (Brazil), 268
Brown, K., 8
444
Index
Brown, S., 43, 53
bryophytes, 104
Bungo Tebo benchmark site (Jambi, Sumatra), 294,
295, 297, 298
cacao. See Theobroma cacao
Caesalpinaceae, 208, 309
Calliandra calothyrsus, 21
Calycophyllum spruceanum (capirona), 19, 345
Camellia sinensis (jungle tea), 19, 20, 366, 367, 375
Cameroon: agroforests in, 20, 307, 310, 311–12,
314, 321, 329; and ASB, 22, 27; ASB matrix
for, 25, 425, 427; benchmark sites in, 14, 15,
16, 17, 306–13; biodiversity in, 90, 96–97,
107–10, 125, 128, 132, 133, 135, 138, 308–11,
427; carbon stocks in, 44, 48–55, 57, 58, 60,
310, 427, 429; cocoa in, 308, 310–14, 320–22,
392–95, 419, 427, 429; crop-fallow systems in,
310–13, 319–20, 392–95, 427, 429; in crosssite comparisons, 406–9; currency devaluation
in, 314, 321, 420; deforestation in, 307, 313,
419–20; economic development in, 306–8,
408–9; food crops in, 21, 308, 310, 319–20,
392–95, 420; food security in, 311, 407, 420,
427; forest margins in, 305–30; forests in, 18,
306, 308–9, 310, 313, 323, 408–9, 427; fruit
trees in, 310, 392–95, 429, 432; gender in,
407, 420; land tenure in, 314, 424; large-scale
agriculture in, 306, 312, 313, 319, 322; laws in,
313, 326; LUSs in, 19, 308, 310–13, 323–29,
388, 392–96, 410, 411, 429; markets in, 307,
308, 311–14; migration in, 419, 420, 424; oil
palm in, 310, 312–13, 322–23, 427, 429; perennial crops in, 392–95; policy in, 308, 314, 317,
324, 329, 391, 427; population in, 308, 314,
423; profitability in, 314–19, 427, 429; shifting
cultivation in, 21, 307, 419; small-scale farmers
in, 310, 312, 419, 427; socioeconomic issues
in, 24, 311; soil in, 156, 157, 160–62, 308,
309–10, 427; sustainability in, 154–64, 308,
311, 314–19, 427; tradeoffs in, 430, 432–33;
trends in, 319–23; urbanization in, 307, 408
Campinharana, 95
canopy cover, 131, 136, 201, 212, 213; and Imperata
control, 251, 258–60
canopy height, 99, 100, 101–2, 103, 104
capital, 182, 334, 430; in cross-site comparisons,
406, 407; and currency devaluation, 177, 179;
and deforestation, 254, 347, 348; as factor of
production, 173, 176; flight of, 177, 178, 179,
180, 181; and forest management, 199, 217; and
LUSs, 24, 379, 391, 405; and markets, 177, 318,
390, 391, 394, 400–401, 405, 410; migration of,
189; and rubber agroforestry, 224, 229, 231; and
sustainability, 166, 167; and technology, 185–93
capoéira, 93, 95, 109, 273
carbon dioxide, 22, 120, 343–44; in incubation
experiment, 69, 76; radiative forcing of, 64–65;
seasonality of, 68, 73–76; in soil profile, 76–78
carbon stocks, 4–7, 41–61; above-ground, 42,
43–45, 46, 48–49, 50–53, 57, 58–59, 60; in
agroforests, 44, 49, 51, 52, 54, 55, 59, 60, 223,
224, 329; and ASB, 42, 50, 51, 52, 433; in ASB
matrix, 25, 26, 424, 425; below-ground, 42, 43,
45, 47, 50, 53–57, 120, 124; at benchmark sites,
22–23, 42, 44, 48–49; and biodiversity, 98, 102,
103, 106, 112, 120, 126, 137; in bioeconomic
models, 234, 237; in Brazilian Amazon, 42,
44, 48–49, 51–55, 59, 60, 240, 265, 267, 270,
280, 426, 429, 437; in Cameroon, 44, 48–55,
57, 58, 60, 310, 328, 427, 429; and cocoa, 44,
51, 52, 54, 55, 58, 59, 321; and crop-fallow
systems, 320; and deforestation, 3, 42, 234, 416;
and economic development, 297; in forests, 48,
50–51, 53, 54, 57, 58, 60, 314; global budget of,
42, 50; in grasslands, 44, 50, 52, 54, 55, 58, 60,
249, 261; in Indonesia, 42, 44, 47, 48–58, 60,
64, 300, 428; and LUSs, 41–61; measurement
of, 10, 22–23, 27, 29, 42–50; offsets for, 61; and
oil palm, 44, 51, 58, 59, 322, 323; in Peruvian
Amazon, 338, 339–42, 350; and policy, 301,
303; and saturation, 151, 155; and sustainability,
24, 148, 150, 151–52; time-averaged, 45, 46,
47–53, 57, 58–59, 60; and tradeoffs, 24, 432,
433
Care-Thailand Collaborative Natural Resources
Management Project, 378
Carney, D., 167
Carpenter, G., 15, 87, 98
Carpentier, Chantal L., 234, 430
Carretera Marginal de la Selva road (Peru), 9
cassava-Imperata systems, 249, 250, 255, 259, 299;
and carbon stocks, 55–56, 57; and nutrients,
158, 159; and soil structure, 154, 155; sustainability of, 156, 157, 160, 166, 167. See also
Manihot esculenta
Cassia siamea (cassia), 93, 111
Castañeda, A., 215
castanha. See Bertholletia excelsa
Castro, M. S., 65
Index
cattle ranching, 5, 255, 388, 410; in Brazilian Amazon, 21, 239, 265, 268, 401–3; and
deforestation, 21, 271, 416, 417, 418; and
economic development, 273, 274, 275; and forest management, 199, 217, 276, 347; large-scale,
407; in Peruvian Amazon, 335; and prices, 241,
408; products of, 173, 174, 185, 281, 405, 408;
research on, 283, 350; small-scale, 281; and soil
productivity, 175; and technology, 185, 188,
189, 192. See also pastures
Cedrela odorata, 206, 208, 209
Cedrelinga cataeniformis (tornillo), 20, 340, 341
Ceiba pentandra, 206, 208, 217, 260
Center for Forestry Research (CENFOR), 14
Center for International Forestry Research (CIFOR),
329, 350, 419
centipedes, 124
Central African Republic, 14, 305
Central America, 14
Central Research Institute for Food Crops (CRIFC;
Java), 14
Centrosema macrocarpum, 21, 340, 341
CENTURY model, 50, 55–57, 159
cerradão (woodland savannas), 90
Chiang Mai (Thailand), 21, 356, 362, 371, 379;
conference at (1999), 29; ethnic minorities in,
358, 359, 360
Chiang Mai University (Thailand), 15
China, 15, 355, 356
Chomitz, K. M., 423
Chromolaena odorata, 21, 259; and biodiversity, 92,
96, 97, 110, 132; in Cameroon, 310, 311, 312,
313, 392; and carbon stocks, 44, 48, 52, 58,
59; as fallow crop, 19, 48, 52, 58, 59, 310, 311,
312, 313, 392; and soil structure, 155, 156; and
sustainability, 160, 163
Cinnamomum burmanii (cinnamon), 297, 298
Citrus spp., 312, 347, 392
Claveria (Mindanao, Philippines), 15
Clean Development Mechanism (CDM; Kyoto
Protocol), 61, 437
Clibadium, 92
climate, 17, 90, 98, 106, 308, 309
climate change, 64, 79, 121, 265, 328, 416; and
ASB, 11, 13, 27, 433; and benchmark sites, 22–
23; and GWP, 343–44; Intergovernmental Panel
on, 28, 45; and LUS change, 355, 357, 378
cocoa. See Theobroma cacao
Cocos nucifera (coconut), 20, 300
cocoyam. See Xanthosoma sagittifolium
445
Coffea spp. (coffee), 5, 20, 389, 410; and bandarra,
44, 401–4, 426; in benchmark sites, 18, 19; and
biodiversity, 90, 93, 94, 107, 111; in bioeconomic model, 233–46; in Brazilian Amazon, 239–40,
271, 401–3, 405, 429, 430; in Cameroon, 307,
310, 313, 314, 322, 324, 330, 419; and carbon
stocks, 44, 45, 51, 52, 59, 60; as commodity,
173, 174, 176; and currency devaluation, 281,
321; and deforestation, 233–46; and economic
development, 273, 409; as factor of production, 175, 176; genetic resources for, 405; and
Imperata control, 251, 252, 259; in Indonesia,
250–52, 259; markets for, 245, 403, 408; and
pasture, 245–46; in Peruvian Amazon, 340, 341,
346; and policy, 244, 245; prices of, 240, 241,
244, 245, 408
cogon. See Imperata cylindrica grasslands
Cola, 309
Coleoptera, 340
collembolans, 124
colonization, 13, 398, 424; in Brazil, 8, 170, 200,
217, 269, 284; and deforestation, 233, 418; and
economic development, 269–70; in Indonesia,
8, 14, 171, 420; and land use patterns, 284–85;
and LUSs, 284–85; in Peruvian Amazon, 8, 334;
policy on, 267–69, 284–85; subsidies for, 233
Colonization Projects (PCs), 200
Colubrina glandulosa (bolaina blanca), 19, 340, 341,
345
computable general equilibrium (CGE) models,
171–72, 176–81
Congo Basin, 14, 305–7, 313, 317–21; ASB in, 306,
329. See also Cameroon
Consorcio para el Desarrollo Sostenible de Ucayali
(CODESU; Peru), 14
Consultative Group on International Agricultural
Research (CGIAR), 27, 28, 329
consumption, 240, 244, 245, 322; and currency
devaluation, 176, 177; in FaleBEM, 235, 236,
237, 242
Convention on Biological Diversity (CBD), 84
Corchorus olitorius, 311
Costa Rica, 172, 205
costs: of alternative LUSs, 323–29, 378, 389, 430,
431, 437; and biodiversity assessment, 83, 84,
90; and carbon stocks, 437; of deforestation,
233–34, 436, 437; of forest management, 208,
215, 216, 218, 430; of Imperata control, 253,
255–56; of logging, 205, 208, 430; opportunity,
435, 436; and rubber agroforestry, 229–30;
446
Index
costs, (continued )
transportation, 170, 171, 181–183, 192, 215,
251, 267, 321, 346, 395, 400, 405
Côte d’Ivoire, 321
cotton, 408
Couratari macrosperma, 208, 214
Cramer, W., 87
credit, 9, 170, 407; and alternative LUSs, 391,
405, 410, 431; in ASB matrix, 424; in Brazilian
Amazon, 268, 275, 278, 283; and deforestation, 347, 348; in Indonesia, 250, 400–401;
markets for, 395; in Peruvian Amazon, 346, 347,
348; subsidized, 268, 283, 346, 347, 405; and
technology, 185
crop-fallow systems, 19, 430; and alternative LUSs,
366–68, 388–89, 410; and biodiversity, 92, 98,
111, 123, 133, 134, 135; in Brazilian Amazon,
236, 239, 402, 404, 426; in Cameroon, 310–13,
316, 319–20, 324, 328, 392–95, 427, 429; carbon stocks in, 44–46, 48, 51–52, 54, 55, 57–59,
315, 320; vs. cocoa-fruit tree system, 432–33;
and GHG, 71, 72; improved, 402–5, 426; in
Indonesia, 71–72, 222–23, 297–98, 396, 397,
399, 428; of Krui, 431; and labor, 320, 328,
398, 403; legume-based, 20, 21, 223, 402; and
markets, 319, 320, 328; and profitability, 316,
402; and soil structure, 155, 156; and sustainability, 161, 163, 164, 166; in Thailand, 366–68.
See also fallow land; fallow periods
cropping, continuous, 21, 26, 388, 430; and carbon
stocks, 42, 52, 55, 57; and deforestation, 417,
418; and GHG, 342, 344; in Indonesia, 300,
396, 397, 399, 428; and sustainability, 161, 164
crops, annual: in Brazil, 173, 239, 242–44, 271,
273, 282, 284; in Cameroon, 321, 328,
329–30; and deforestation, 243, 271, 347, 349;
as factor of production, 175, 176; in Indonesia,
298; in Peruvian Amazon, 337, 340–42, 347,
349; policy on, 244, 329–30; and soil, 175,
273; substitution of, 174; sustainability of, 328,
349; and technology, 185, 187–91. See also
food crops
crops, perennial: in Brazilian Amazon, 239–40,
242–45, 273, 281; in Cameroon, 315, 318–20,
322, 324, 328, 329–30, 392–95; and factors of
production, 175, 176; in FaleBEM, 242, 243; in
Indonesia, 297, 298; in Peruvian Amazon, 337,
338, 349; policy on, 244, 245, 324, 329–30;
sustainability of, 328; and women, 319. See also
tree-based systems
culture, 144, 418. See also socioeconomic issues
Cupressus (cypress), 20
currency devaluation: bioeconomic simulations of,
171, 176–81, 281; in Brazil, 176, 178–79, 419;
in Cameroon, 314, 321, 420; and exports, 177–
79, 191, 192, 321; in Indonesia, 176, 180–81,
422; and LUSs, 176, 192; and profitability, 300
Dacryodes edulis (African plum), 312, 317, 392
damar. See Shorea javanica
dams, hydroelectric, 268
decision-making patterns, 11, 16, 143, 279; and deforestation, 234, 347, 348, 417; in FaleBEM, 235,
237; in Peruvian Amazon, 332–33, 347, 348, 350;
and policy, 245, 350; in Thailand, 228–29, 369
deforestation: and agricultural intensification, 280,
297, 417, 418, 433; and agroforests, 222, 234,
271, 302; and alternative LUSs, 234, 243, 371,
388, 431; and altitude zones, 367; and annual
crops, 243, 271, 347, 349; and ASB, 8–11, 21,
419, 425; and biodiversity, 3, 23, 233, 416, 433;
bioeconomic models of, 193–94, 235, 242, 280,
281; in Brazil, 3, 170–94, 305–6, 419; in Brazilian Amazon, 3, 171–72, 200, 233–46, 265, 266,
270–71, 272, 277, 285, 430; in Cameroon,
307, 313, 320, 419–20; and carbon stocks,
3, 42, 234, 416; and cattle ranching, 21, 271,
416, 417, 418; and coffee, 233–46; in Congo
Basin, 305–6; costs vs. benefits of, 233–34, 436,
437; and currency devaluation, 176–81; and
economic development, 270–71, 273, 275; and
ecosystem services, 3, 301, 416, 436; factors in,
11, 170–94, 233–34, 416–24, 436; and forest
categories, 293–94; and genetic variation, 344;
and GHG, 64–66, 72, 75, 79, 342, 343–44; in
Indonesia, 170–94, 248, 249–50, 291, 292, 295,
305–6; and infrastructure, 181, 191, 417, 418;
and labor, 171, 243, 347–48, 349, 424; and land
tenure, 171, 181, 183–85, 192, 436; and largescale agriculture, 271, 292, 306, 313, 416; and
laws, 240, 242, 349; and logging, 171, 172, 301,
302, 416; and LUSs, 234, 243; and markets,
171, 172, 417, 418, 436; and migration, 8–9,
417, 436; in Peruvian Amazon, 335, 337, 347,
348; and policy, 171, 181, 193, 233, 234, 240,
244, 245, 284, 285, 347, 348, 417, 418, 433,
434, 436; and population density, 8, 294, 306,
418; and poverty, 28–30, 233, 302, 436–37; and
prices, 243, 347, 349, 418; and productivity,
330, 348, 424, 433; and profitability, 191, 349,
Index
416, 424; rates of, 3, 10, 16, 200, 272, 350, 358;
and shifting cultivation, 29, 302, 349, 416, 417,
418; and small-scale farmers, 3–4, 8, 233–34,
306, 329, 416, 436; socioeconomic factors in,
29–30, 181–91, 233, 346–50, 417, 418; and
soil, 233, 234, 243, 271, 348; squatter, 172; and
technology, 171, 181, 187–93, 234, 347–49,
416, 418, 424, 433; in Thailand, 357–60, 367;
and transportation costs, 171, 181–83, 192
DeFries, R. S., 42
Desmodium ovalifolium, 21
Detwiler, R. P., 53, 55
Diaz, S., 86
Dick, J., 421
Dillenia spp., 259
Dimocarpus longan (longan), 363
Dinas Perkebunan (tree crop advisory service, Indonesia), 251
Diospyros spp. (persimmon), 309, 374
Dipteryx odorata, 207, 208, 214
diseases, 120, 124, 201, 223, 319; in cocoa, 312,
322, 325; and sustainability, 24, 146, 147, 149,
154, 160–63, 165. See also pests
diversity indexes, 126, 127; Fisher, 88, 100, 101–2,
105, 106, 206; Shannon-Wiener, 88, 100,
101–2, 105, 106, 132–34; Simpson, 88, 100,
101–2, 105, 106, 133, 134
Dobbie, K. E., 65
Doi Kham (brand), 363
Doi Pui (Thailand), 361
DOMAIN mapping procedure, 15
Dorstenia, 309
Dosi, C., 234
Douala (Cameroon), 307
drought, 164, 165, 259, 295. See also precipitation
drugs, illegal, 265, 266. See also opium
Duguma, B., 312
Durio zibethinus (durian), 18, 158, 228, 230, 260,
298
Dury, S., 312
Earth Summit (Rio de Janeiro; 1992), 10, 437
Ebolowa Station (Cameroon), 42, 90, 96, 97, 135,
307, 308, 314; LUSs in, 310–13
economic development: in ASB matrix, 25, 424; in
Brazilian Amazon, 265, 266, 268, 269–70, 273–
78; in Cameroon, 306–8, 321, 408–9; and cattle
ranching, 273–75; and colonization, 269–70;
consequences of, 64, 269–75; and deforestation, 8, 270–71, 273, 275; vs. environment, 4,
447
16, 415–37; and forest management, 276–78;
in Indonesia, 297, 302, 409; new paradigm for,
275–78; in Peruvian Amazon, 333, 334, 349;
and policy, 273, 287, 409; research on, 286, 387,
433; sustainable, 269, 276, 286, 409; in Thailand, 356, 357; welfare effects of, 269, 274–75.
See also macroeconomics; tradeoff analysis
economic models, 276, 285, 286, 435; CGE,
171–72, 176–81; of deforestation, 172, 193–94,
233–34, 280, 281; partial equilibrium, 422. See
also Farm Level Bioeconomic Model
ecosystem dynamics, 86, 121, 149, 154, 267; and
biodiversity, 83, 85, 119–20, 122, 134
ecosystem services, 6–8; of agroforests, 20, 231; and
biodiversity, 120, 121, 122; and deforestation,
3, 301, 416, 436; and genetic variation, 344;
hydrologic, 29, 360–61, 364, 378; and markets,
408; research on, 13, 302, 435; in Thailand,
356, 358, 360–61; tradeoffs with, 434
Elaeis guineensis (oil palm), 5, 19, 20, 25, 401, 410;
and biodiversity, 90, 95, 111, 322, 323; in Cameroon, 310, 312–13, 318, 319, 321, 322–23, 330,
427, 429; and carbon stocks, 44, 51, 58, 59, 322,
323; and currency devaluation, 321; and economies of scale, 319, 322; as factor of production,
175, 176; and GHG, 70, 72; hybrids of, 312,
318, 322, 325, 392–93, 395; Imperata control,
252, 253, 255, 259; in Indonesia, 70, 72, 251–53,
255, 259, 293, 299, 301, 396, 397, 399, 428; in
Krui system, 431; and labor, 317, 395, 398; largevs. small-scale plantations of, 175, 176, 312; and
markets, 312, 318, 325, 395, 398; monoculture
of, 312, 393, 396, 397, 398, 399; in Peruvian
Amazon, 340, 341; processing of, 322, 325, 328,
396; profitability of, 315, 316; sustainability of,
157–59, 162, 163, 166
elephants, 103
Ellis, J. K., 234
El Niño, 28, 84, 211, 212, 252, 435
employment, 246, 268–69, 417, 424. See also labor
Empresa Brasileira de Pesquisa Agropecuária
(Embrapa), 18, 203, 238, 277, 350, 431; Acre
research center of, 14, 95, 174, 279, 284; and
ASB, 278–81, 282, 284, 285–86, 434; policy
role of, 282–85
England, 5
Entandrophragma, 205
enterprises, postharvest, 250, 294, 322, 324, 325,
328, 349, 396, 405
Equatorial Guinea, 305
448
Index
Erythrina orientalis, 259
eucalyptus, 20, 44
Eugenia stipitata (arazá), 20, 340
Euphorbiaceae, 259
Europe, 79
European Union (EU), 250
exports, 183, 395, 410; in Brazilian Amazon, 233,
419; in Cameroon, 321, 419; and currency
devaluation, 177–79, 191, 192, 321; in Indonesia, 222–23, 294, 397, 398, 400, 407, 422; in
Thailand, 358
extension services, 226, 318–19, 329, 398
extractive reserves, 18, 19, 275, 286
fair trade movement, 324
fallow land: in Brazilian Amazon, 242, 243, 244,
273; in Cameroon, 307, 310–13; and Chromolaena, 19, 48, 52, 58, 59, 310–13, 392; forests
as, 21, 310, 311, 347, 366, 373, 375; in Indonesia, 70; kudzu-improved, 348, 349; in Peruvian
Amazon, 339, 340, 341, 347–49; in Thailand,
366, 373, 375
fallow periods, 5–7, 19, 22, 25, 26; and belowground biodiversity, 121, 131; in Cameroon,
320, 321, 392–95, 427; and carbon stocks, 315;
in Peruvian Amazon, 334, 337, 338; and sustainability, 24, 143–44, 160, 162–63, 164, 167, 291.
See also crop-fallow systems
farmers, small-scale, 5, 7–9, 11–13, 25; and alternative LUSs, 315, 329, 370, 371, 387–411; in
ASB matrix, 26, 424; in bioeconomic models,
235, 280, 281; in Brazilian Amazon, 199–218,
233–34, 235, 245, 278–81, 283, 285, 286,
401–5, 426, 429, 431; in Cameroon, 306, 307,
310, 312–13, 315, 318–19, 322, 325–27, 329,
419, 427; and carbon stocks, 437; and community-based action, 318–19, 329; credit for,
283, 405; and deforestation, 3–4, 8, 233–34,
306, 329, 416, 436; forest management by,
199–218, 278, 326, 327; and genetic variation,
344–46; and GHG, 66, 69; and grassland reclamation, 248–61; in Indonesia, 222–31, 248–
61, 291, 292, 294–95, 300–303, 396–401,
420, 421, 423, 428; interviews with, 224–25;
vs. large-scale agriculture, 182, 300, 319, 322;
vs. monoculture, 20, 300, 312–13, 319; and oil
palm, 322, 325; organizations of, 318–19, 325,
326, 327, 329; in PAM, 391; participation in
research by, 279, 280, 329, 333, 345, 350, 433,
435; in Peruvian Amazon, 333, 334, 338, 339,
344–46, 350; and policy, 245, 285, 303, 350;
production activities of, 175, 176; and research,
286, 338, 339, 389–90, 433, 434; and rubber
agroforestry, 222–31, 294–95; and sustainability, 164, 278; and technology, 185, 186,
187–91, 193; in Thailand, 355–80
Farm Level Bioeconomic Model (FaleBEM),
233–46; description of, 235–38; and policy,
243–46; results of, 240–44
fauna, 20, 98, 217, 309, 311, 363, 378; micropredators, 120, 124, 139; in soil, 23, 128–31, 136,
138, 139, 154; vs. vegetation, 85, 88, 100–107,
109. See also birds; cattle ranching; hunting;
insects; livestock
Fearnside, P.M., 53
Federico Basadre road (Peru), 9
fertilizers, 21, 111; in Brazilian Amazon, 236, 237,
238, 240, 241, 279, 342, 343; in Cameroon,
314, 318, 320; and deforestation, 348, 349; in
FaleBEM, 236, 237, 238; and GHG, 70, 71, 72,
79, 342, 343; in horticulture, 314; in Indonesia, 71, 225, 250, 300; and markets, 318, 401,
405; nitrogenous, 66, 71, 79, 241; in Peruvian
Amazon, 334, 348, 349; price of, 158, 159, 241;
and sustainability, 149, 153, 158, 159, 162, 164,
167; in Thailand, 373
Findlay, R., 170
fire, 28; in Cameroon, 309; and Imperata control,
248–50, 252, 259, 261; in Indonesia, 223,
248–50, 252, 259, 261, 291, 300, 302, 421; in
Peruvian Amazon, 335; and sustainability, 164,
165; in Thailand, 366, 371, 375
fish, 176, 333, 371
Fisher diversity index, 88, 100, 101–2, 105, 106, 206
Fisher, M. J., 55
food crops, 19, 25, 408; in Cameroon, 21, 308, 310,
314, 317, 319–25, 392–95, 420; and Imperata
control, 252, 254, 255, 258–60, 261; improved
varieties of, 319; in Indonesia, 223, 252, 254,
255, 258–61, 291, 295, 297–99, 397, 421, 422;
and sustainability, 164, 165
food security, 25, 122; and alternative LUSs, 24,
315–17, 370, 372–74, 379, 394, 395; in ASB
matrix, 424; in Brazilian Amazon, 274, 403,
404, 426; in Cameroon, 311, 315–17, 328, 330,
407, 420, 427; and genetic variation, 344; in Indonesia, 302, 398, 399, 428; and markets, 403,
407; in PAM, 391; in Peruvian Amazon, 344,
346; and policy, 317, 330; research on, 302, 387,
389, 390; in Thailand, 367, 370, 372–74, 379
Index
Forest Code (Brazil), 434
forest conversion rates, 16. See also deforestation
forest management: in Brazil, 199–200; in Brazilian Amazon, 202–18, 276–78, 280, 401, 404,
426; and carbon stocks, 48, 51, 60; and cattle
ranching, 199, 217, 276, 347; collective, 18,
217, 218, 278; compartments in, 203, 204,
217; costs of, 208, 215, 216, 218, 430; and
economic development, 276–78; harvesting rules
in, 205; and income, 203, 276; in Indonesia,
295–96, 298; investment in, 199, 217, 278;
jungle rubber, 216; and labor, 203, 208, 214,
215, 216, 403; land use systems (LUSs), 217;
local, 295–96, 298; and LUS trends, 411; and
markets, 199, 215, 217, 278; mechanized, 216;
methods for, 202–8; in Peruvian Amazon, 347;
and policy, 199, 218, 277, 278, 408; and prices,
200, 215, 217, 277; and profitability, 201, 202,
215, 216–17, 277, 278, 402; and regeneration,
205–6; silvicultural treatments in, 202, 204,
205, 215, 216; by small-scale farmers, 199–218,
276–78, 326, 327; and socioeconomic issues,
216–17; sustainable, 18, 199–218, 276–78; and
technology, 199, 215, 217; traditional, 200
Forest Management Project (legal document), 199
forest margins, 4–9, 11, 20, 24–25, 127, 131; in
Brazilian Amazon, 233, 234; in Cameroon,
305–30; deforestation at, 233, 234, 347, 417; vs.
forests, 315; in Indonesia, 222, 291–303; migration to, 8–9; and population growth, 423–24
forest reserves, 200, 204, 217, 218, 249, 363–64
forests: and alternative LUSs, 18–22, 282, 284;
and altitude zones, 366; annual mortality rates
(AMRs) in, 207, 211–12; in ASB matrix, 26;
Barren, 308, 309; in Brazilian Amazon, 200,
202–4, 206–12, 216, 239, 281, 284; in Cameroon, 306–9, 315, 330; Cameroon-Congo,
309; categories of, 14, 15, 17, 86, 292–94, 307,
308–9, 330, 421; costs of, 430; crown exposure
in, 210, 211, 216; dynamics of, 206–7, 216; and
economic development, 408–9; evergreen Atlantic, 308, 309; vs. forest margins, 315; fragmented, 89, 306, 309; gap replanting of, 20, 422;
Guineo-Congolian, 308, 309; in Indonesia, 250,
292–94, 295; inventory of, 202–4, 208–9; limited production, 293, 294; lowland humid tropical, 86, 292, 293, 421; in MMSEA ecoregion,
355; montane, 17, 293; production, 293, 294,
295; recruitment rates in, 207, 211–12; semideciduous, 17, 309; species richness in, 206–7;
449
squatters in, 172, 293; successional sequences
in, 88; and sustainability, 161; in Thailand, 366,
368; tropical moist, 17, 233, 234, 266, 307,
387–411; use rights to, 61, 175, 377
forests, community-based, 19, 28, 388, 425; biodiversity in, 98, 314, 323; in Cameroon, 310,
313, 314, 317, 323, 326, 327; in Indonesia, 396,
397, 399, 400, 428; and Krui system, 432; and
labor, 317, 398; and land tenure, 323, 326, 327;
risk vs. benefits of, 326–27; sustainability of, 18,
157, 162, 163, 166, 323; in Thailand, 364, 373,
375–76; tradeoffs with, 432, 434
forests, primary, 22, 388, 410, 433; agroforestry in,
222, 292, 312, 329; biodiversity in, 91, 103,
110, 111, 123, 132, 133, 135, 137, 293; in
Brazilian Amazon, 270, 401; in Cameroon, 308,
312, 329, 427; carbon stocks in, 48, 50–51, 54,
57, 58, 60; GHG in, 66, 67, 68, 71–76; in Indonesia, 222, 291–93, 299–301, 396, 399, 423;
and migration, 270; in Peruvian Amazon, 337,
347, 348; vs. secondary, 18; and soil structure,
154; sustainability of, 157, 165, 166
forests, secondary, 172, 410; agroforestry in, 222,
223, 312; biodiversity in, 91, 94–97, 109–11,
123, 132, 134, 135; biomass of, 53; in Brazilian
Amazon, 206–7, 209–13, 218; in Cameroon,
310–12, 321; carbon stocks in, 42, 48, 51, 53,
54, 57, 58, 60; community-protected, 18; as
factor of production, 175, 176; as fallows, 21,
310, 311, 347, 366, 373, 375; GHG in, 67–76,
342, 343; in Indonesia, 222, 223, 291, 298–300;
monitoring of, 206–7, 209–13, 218; in Peruvian
Amazon, 340, 341–43, 347, 348; and slash-andburn agriculture, 51; and soil structure, 154; sustainability of, 157, 160, 165, 166; in Thailand,
350, 366, 373, 375
frontiers, agricultural, 192–93, 409, 431; in Brazil,
170, 266, 275; deforestation on, 248, 347, 433;
in Indonesia, 170–71, 248, 250; in Peru, 347
fruit trees, 19, 411, 425; in agroforests, 20, 228,
230, 292, 374, 375; and biodiversity, 93, 94;
in Cameroon, 310, 312, 315, 317–21, 328,
392–95, 429, 432; and carbon stocks, 51; and
cocoa, 312, 320–21, 432–33; improved, 432;
in Indonesia, 223, 228, 230, 260, 292, 297,
300; and markets, 318, 392, 395; in Peruvian
Amazon, 340, 347; and sisipan system, 223; sustainability of, 157, 162, 164, 328; in Thailand,
362, 367, 373–75; and women, 319
Fujisaka, S., 43, 239, 338, 339, 347, 401
450
Index
functional groups, 121, 123–27, 133–37, 138
functional types (FTs), 86–89, 87, 112, 338. See also
plant functional types
fungi, 23, 120, 121; mycorrhizal, 124, 125, 128–31,
133, 135, 138, 139, 146, 147, 149
fungicides, 312, 314, 322
Gabon, 14, 305
Garcinia, 309
gas, natural, 334
Geist, H. J., 8, 416–19, 423
genetic resources, 249, 429, 432; cloned rubber,
223, 227–31, 396, 398, 399, 428; coffee, 405;
commercial value of, 345–46; in Peruvian Amazon, 333, 338, 344–46, 350; and sustainability,
166, 167, 344–46
geographic information systems (GIS), 16, 379
Ghana, 321
Gillison, Andrew N., 23, 87, 88, 98, 311, 338
Gintings, A. N., 16
Gliricidia sepium, 251, 258, 259
Global Environment Facility, 28, 29
global warming, 79, 328, 416; potential for (GWP),
343–44. See also climate change; greenhouse gases
Glossina spp. (tsetse fly), 313
Glycine max (soybeans), 176, 181, 254, 363, 373
Gmelina arborea, 69, 74
Gockowski, James, 24, 312, 315, 389, 390
Gorupi Forest Reserve, 217
government, 28, 181, 407; and alternative LUSs,
328, 363–64, 369, 380; and biodiversity, 84,
297; Brazilian, 233, 265, 266, 267–68, 275,
283–84; of Cameroon, 308, 325, 326, 327,
328; and community forestry, 326, 327; and
currency devaluation, 176; and Embrapa,
283–84; and genetic research, 345–46; Indonesian, 297, 301, 397, 400, 431–32; and Krui
system, 431–32; local, 364, 369, 371, 377; and
migration, 8, 13–14, 249, 250, 292, 295; Peruvian, 333, 334, 345–46, 347; and sustainability,
147, 167; of Thailand, 363–64, 367, 369, 371,
377, 380
gradient-oriented transect (gradsect) method, 98
grasslands, 19, 21–22, 26, 163, 172, 367, 388;
biodiversity in, 90, 92, 107, 109, 110, 123, 132,
137, 139; Brachiaria humidicola, 21; carbon
stocks in, 44, 49, 50, 52, 54, 55, 58, 60, 249,
261; degraded, 6, 14, 90; as factor of production,
173, 175, 176; Panicum maximum, 283; reclamation of, 248–61; Setaria, 259; and technology,
188, 189. See also Imperata cylindrica grasslands;
pastures
Gray, D. A., 423
greenhouse gases (GHG), 9–10, 24, 61, 64–79; and
agroforests, 67, 68, 69, 70, 71–76, 342, 343; and
ASB, 11, 64, 66, 433; and below-ground biodiversity, 120, 123; in Brazilian Amazon, 268, 270;
in Cameroon, 328; and deforestation, 64–66, 72,
75, 79, 342, 343–44; in forests, 66, 67–76, 342,
343; and fossil fuel, 42; in Imperata cylindrica
grasslands, 68, 69, 70, 71, 72; in Indonesia, 22,
23, 66–79, 342–43; and LUSs, 22–23, 64–79;
measurement of, 22–23; in Peru, 22, 23, 67, 72,
333, 338, 342–44; seasonality of, 68, 71–76, 77;
and soil, 65–67, 69, 70, 76–78, 154, 342; and
sustainability, 148, 150
gross domestic product (GDP), 8, 273, 274
groundnuts, 96, 316, 317, 319, 324, 392. See also
Arachis spp.
Grupo de Pesquisa e extensão em Sistemas Agroflorestais do Acre (PESACRE), 278, 284
Guarea pterorachis, 207
Guimaraes, W. M., 53
habitat, 83, 88, 89, 106, 120
Haggar, J., 18
heart of palm. See Bactris gasipaes
herbicides, 251, 252, 253–56, 271, 348, 373
Hevea brasiliensis (rubber), 5, 18–20, 411, 425; as
best-bet alternative, 222; and biodiversity, 90,
92–94, 103, 106, 107, 109–11, 132, 133, 136,
137, 223, 224; in Brazilian Amazon, 216, 401–4;
in Cameroon, 310, 330; and carbon stocks,
44, 51, 52, 54, 55, 58; vs. cassava, 433; cloned,
223, 227–31, 396, 398, 399, 401, 428; costs of,
229–30; cyclical vs. permanent, 223–24, 225,
226, 229–31; and deforestation, 292, 301; exports
of, 294; as factor of production, 175, 176; and
GHG, 67, 68–69, 71–76; grafting of, 230; and
Imperata control, 251, 252, 255, 258, 259, 260;
income from, 223, 227–30; in Indonesia, 222–31,
251, 252, 255, 258, 259, 260, 292, 294–95,
297–99, 301, 396, 397, 399, 400, 422, 423, 428;
industrial processing of, 294; jungle, 92, 106, 107,
110, 132, 136, 137, 175, 176, 216, 223, 291,
294–95, 297–99, 423; large-scale production of,
175, 176, 223; and markets, 398; monoculture
vs. jungle, 106; in Peruvian Amazon, 340, 341;
productivity of, 223, 224, 227–31; profitability
of, 402, 408; small-scale production of, 175, 176,
Index
222–31, 294–95, 301; and soil, 156, 158; sustainability of, 157, 160, 164, 165, 166
H’mong (minority group), 359, 360, 366
Holmes, D., 421
Hordeum vulgare (barley), 19, 362
horticulture: intensive, 21, 313, 314; subsistence,
90, 94, 97, 98, 111
Houghton, R. A., 51, 52
households: in bioeconomic models, 234, 237,
280; and land use alternatives, 252–53, 323,
324–28; livelihoods of, 24, 323, 324; research
on, 253–56, 280, 283
Howard, P., 85
Htin (minority group), 359
human development index (UNDP), 274–75
Humid Forest Centre (IITA), 14
hunting, 217, 230, 308, 315, 323, 324, 416
hydrogen, 121
Hymenaea courbaril, 208
Hymenolobium excelsum, 207
Imperata brasiliensis, 339
Imperata cylindrica grasslands, 6, 14, 19, 21, 22;
and agroforests, 249, 252, 256–61; and artificial
shade, 253, 256, 259; biodiversity in, 90, 92,
123, 132, 137, 139; biomass of, 253, 256–57,
259; and carbon stocks, 44, 50, 52, 54, 58; and
fire, 248–50, 252, 259, 261; GHG in, 68–72;
herbicidal control of, 251, 252, 253–56; and income, 251, 259, 261; in Indonesia, 22, 248–61,
291, 299, 300, 396, 397, 399, 428, 433; reclamation of, 248–61; shade-based control of, 249,
251–61; and sustainability, 155, 160, 164, 165.
See also cassava-Imperata systems
incentives, 147, 387, 390, 436; for adoption of alternative LUSs, 361–69, 411, 431; and biodiversity,
83, 112; in Brazilian Amazon, 205, 217, 429; in
Cameroon, 313, 321, 322, 323; for colonization,
170; effects of, 365–69; and prices, 321, 408; in
Thailand, 361–69
income, 390, 425, 433, 434; in bioeconomic models,
234, 235, 242, 280; in Brazilian Amazon, 203,
244, 245, 271, 274, 276, 280, 285; in Cameroon,
308; and forest management, 203, 276; and genetic variation, 344; and Imperata grasslands, 251,
259, 261; in Indonesia, 223, 227–30, 251, 259,
261, 421; and markets, 408; in Peruvian Amazon,
344, 346; and policy, 244, 245; from rubber, 223,
227–30; in Thailand, 370, 373
India, 5
451
indigenous peoples, 5, 7, 21; in Brazilian Amazon,
265, 268, 275; in Indonesia, 14, 396, 431–32;
LUSs of, 8, 9, 19, 20, 431–32; in Peruvian Amazon, 333, 334; and policy, 408, 431–32
Indonesia: agroforests in, 18–20, 222–31, 295, 297,
299, 301, 302, 397, 422, 423, 428; ASB in, 27,
297–301; ASB matrix for, 25, 425, 428; benchmark sites in, 14–17, 294–301; colonization in,
8, 14, 171, 420; in cross-site comparisons, 406–9;
currency devaluation in, 176, 180–81, 422; deforestation in, 170–94, 248, 249–50, 291, 292, 295,
305–6; economic development in, 297, 302, 409;
forest margins in, 291–303, 387–411; GHG in,
22, 23, 64–79, 342–43; government of, 297, 301,
397, 400, 431–32; Imperata grasslands in, 22,
248–61, 291, 299, 300, 396, 397, 399, 428, 433;
indigenous peoples of, 14, 396, 431–32; LUSs
in, 5, 18, 19, 21, 297–99, 388, 396–401, 410,
411; macroeconomic factors in, 170–94, 420–23;
migration in, 222, 226, 248–50, 291–93, 295,
297, 298, 300, 301, 396, 420–24; population of,
170, 292, 294, 423–24; sustainability studies in,
154–64; tradeoffs in, 430, 431–32. See also Jambi
province; Lampung province; Sumatra
Indonesian Rubber Research Institute, 230
industrialization, 294, 365, 418, 422
Industrial Timber Plantation Company (HTI), 250,
258
infrastructure, 6, 13, 20, 61; in Africa, 314, 318,
321, 330; and deforestation, 181, 191, 417, 418;
and population, 406–7, 424; in Southeast Asia,
365, 370, 423. See also transportation
Inga edulis (inga), 20, 21, 44, 52, 93, 111, 340, 341
Ingram, J.S.I., 127
insects, 23, 85, 102, 138, 312, 313. See also ants;
arachnids; pests; termites
Institut de Recherche Agricole pour le Développement (IRAD; Cameroon), 14, 329
institutions, 13, 28, 387, 425, 433, 434, 436;
induced innovation in, 6–7, 376–80. See also
government; land tenure
Instituto de Investigación de la Amazonía Peruana
(IIAP; Peru), 14, 350
Instituto Nacional de Colonização e Reforma
Agrária Acre (National Colonization Institute;
Brazil), 284
Instituto Nacional de Investigación Agraria (INIA;
Peru), 14, 339, 350
Instituto Nacional de Investigación Agrícola, Pecuaria y Forestal (INIFAP; Mexico), 14
452
Index
Instituto Nacional de los Recursos Naturales (Peru),
350
Instituto Veterinario de Investigaciones Tropicales y
de Altura (IVITA), 350
integrated natural resource management (INRM),
12, 16, 27
Integrated Natural Resources Conservation Project,
CARE-Thailand, 371
Intergovernmental Panel on Climate Change (IPCC),
28, 45
intermediate disturbance hypothesis, 103, 131
International Center for Research in Agroforestry
(ICRAF), 261, 329, 340, 380
International Center for Tropical Agriculture
(CIAT), 349, 350
international community, 83–84, 268, 416, 437;
development agreements of, 275; and research,
279, 280, 285, 380; trade, 391; and trade, 245,
396, 400, 408
International Food Policy Research Institute (IFPRI), 174
International Fund for Agricultural Development
(IFAD), 28
International Institute for Tropical Agriculture (IITA),
329
International Monetary Fund (IMF), 314
investment, 143, 170, 172, 235, 251, 275, 407; and
currency devaluation, 176, 177, 179, 181; and
forest management, 199, 217, 278
iron, 121
irrigation, 21, 250, 367, 372–74
Ishizuka, Shigehiro, 23
Jambi province (Sumatra, Indonesia), 14, 291–303,
421; benchmark sites in, 67, 91–92, 294, 295,
297, 298; biodiversity in, 90, 91–92, 110, 130,
132, 133, 136, 137; carbon stocks in, 42, 47;
GHG studies in, 66–79; LUSs in, 294–95; migration to, 422–23; population density of, 292;
research in, 297–301; rubber agroforestry in,
224–30; sustainability studies in, 154–57
Jaracatea spinosa, 209
Jardin do Botanica (Brazil), 95
Java, 8, 14, 170; migrants from, 250, 292, 295, 300,
422
jengkol. See Pithecellobium jiringa
Jí-Paraná (Rondônia, Brazil), 93, 135
Kaimowitz, David, 172, 234
Kalimantan, 420
Karen (minority group), 359, 366, 375
Kawasan Dengan Tijuana Istimewa (Zone with
Distinct Purpose; Indonesia), 295–96
Kerala National Park (Uganda), 217
Khamu (minority group), 359
Khaya, 205
Kotto-Same, Jean, 43, 315
Krui LUS, 431–32
Krui research site (Lampung province, Sumatra), 20,
295
Kuamang Kuning (Sumatra, Indonesia), 92
kudzu. See Pueraria phaseoloides
Kyoto Protocol (1997), 61, 233, 328, 437
labor: in agroforestry, 224–27, 229–31, 271, 301,
349, 375; and alternative LUSs, 24, 315, 316,
388–91, 393, 398–404, 409–11, 426, 429–31;
in ASB matrix, 26, 170, 424; in bioeconomic
models, 234–38, 280; in cocoa systems, 316,
317, 320, 321; as constraint, 245, 334; in cropfallow systems, 320, 328, 398, 403; cross-site
comparisons of, 406; and currency devaluation,
177, 179, 181; and deforestation, 171, 243,
254–56, 330, 347–49, 424; as factor of production, 173, 175, 176; family, 225–27, 229, 230,
254–56, 319, 389, 390; and forest management, 203, 205, 208, 214–16, 403; gendered
division of, 407, 420; hired, 225–27, 229,
230, 254–56, 407; and Imperata control, 253,
254–55; in logging, 205, 301, 398; and macroeconomic factors, 170, 173, 175, 176, 182,
183, 189; markets for, 177, 390, 394, 395, 400,
402–3, 405, 407; needs for, 390, 393–95, 398,
403; off-farm, 240, 246, 249, 250, 295, 349;
and oil palm, 317, 322, 395, 398; in pasture
systems, 239; and policy, 244, 245, 347, 391;
and population density, 68, 170, 266, 268–69;
returns to, 143, 315, 321, 389, 391, 393, 394,
397–99, 402–3, 406, 407, 410, 411, 424, 429,
433; and rice, 373, 398; and rubber agroforestry, 224–27, 229–31; and technology, 185–93,
400; in tradeoff analyses, 420, 421, 427, 428,
429, 433; and unemployment, 268–69; wage,
17, 227, 396, 398, 430
Lahu (minority group), 359
Lambin, E. F., 8, 416–19, 423
Lampung province (Sumatra, Indonesia), 14, 421;
biodiversity in, 132, 137; GHG studies in,
66–79; Imperata grasslands in, 22, 248–61; Krui
in, 20, 295, 431–32; LUSs in, 296–97, 431–32;
Index
migrants to, 295, 422; population density of,
292; sustainability studies in, 154–57, 164, 165
land: in alternative LUSs, 389, 393, 399, 402, 404,
411, 426; arable, 172, 182, 188, 189, 191; in
ASB matrix, 424; in bioeconomic models, 234,
235, 236; as commodity, 173, 174–75; as factor
of production, 172, 173, 175, 176, 320, 334;
markets for, 390; policy on, 7, 64, 300, 391;
prices of, 175, 182, 191, 335; productivity of,
185–87, 320, 330; rehabilitation of, 6–8, 11;
returns to, 315, 389, 391, 393, 394, 397–99,
402, 411, 424; and rubber agroforestry, 224,
225, 226; speculation in, 358; and technology,
188; in tradeoff analyses, 427, 428, 430; types
of, 172, 175, 176. See also fallow land; land
degradation; land tenure
land clearing, agricultural: in Brazilian Amazon, 233,
239, 240, 242, 244, 277, 284; in Cameroon,
307; and currency devaluation, 178; and deforestation, 18, 171, 172, 233; in Indonesia, 223,
253–57, 298, 422; vs. logging, 192; mechanized,
253, 254, 255; methods of, 253–56, 258; in Peruvian Amazon, 347; policy on, 240, 242, 244,
284, 347; and property rights, 175, 183–85; in
Thailand, 358; and transportation, 183. See also
deforestation
land degradation, 6–7, 8, 11, 13, 22, 60; in Brazilian
Amazon, 239, 266, 270, 271, 273, 284, 433; in
Cameroon, 321–22, 329; and deforestation, 3,
172; and grasslands, 6, 14, 90, 248; in Indonesia,
242, 243, 248, 250, 294; at landscape scale, 432;
in pastures, 6, 242, 243, 433; policy on, 271, 284,
361; and technology, 191; in Thailand, 360, 361
landscape scale, 248, 422, 432, 434–35; biodiversity at, 89–90; integrated management at, 323;
policy at, 378–79; research on, 279, 286, 302;
sustainability at, 146, 164–67
land tenure, 6, 61, 111, 143; in Brazilian Amazon,
183–85; in Cameroon, 314, 318, 323, 326,
327, 330, 424; and community forests, 323,
326, 327; in cross-site comparisons, 406, 407;
and deforestation, 171, 181, 183–85, 192, 436;
individual, 314; in Indonesia, 248, 261, 300,
301, 397, 423; and Krui system, 432; privatized,
373; in Thailand, 367, 373
land use intensity: and biodiversity, 83, 89, 100;
chronosequences (gradients) of, 22, 42–43, 89,
100, 108; and GHG, 68, 70–76, 79, 342; and
seasonality, 71–76. See also agricultural intensification
453
land use planning, participatory (PLP), 370,
376–77, 379, 380
land use systems (LUSs), 4–13, 15, 172; adoption
of alternative, 315–19, 409–11, 424, 431, 433,
434; alternative, 4, 164–67, 300, 323–29; at
benchmark sites, 13, 16–22; best-bet alternative, 25, 27, 83–113, 222, 277, 302, 323; and
bioeconomic models, 235, 237, 242, 280–81;
changes in, 165–67, 357–61; commercial, 392;
costs vs. benefits of, 323–29, 430, 437; cross-site
comparisons of, 406–9; defining, 388–89; of
ethnic minorities, 358–60, 431–32; evaluations
of, 393–405; and functional groups, 133–37; and
impact assessment, 27–29; and institutional innovation, 376–80; intensification of, 6–8, 297, 433;
long-range impacts of, 279; meta- (LUTs), 18–22,
26, 90, 98, 100, 103, 107, 109, 387; in MMSEA
ecoregion, 355; models for, 370, 377; multiproduct, 279; research on, 276–78, 286, 380, 433;
spatial issues in, 362, 367–69, 388; and substitution relationships, 174, 183; temporal issues in,
388–89; traditional, 365–66, 380, 431–32; trends
in, 319–23, 409–11; zoning for, 282–84. See also
under particular topics and regions
land use types (LUTs), 18–22, 26, 90, 98, 100, 103,
107, 109, 387
Lanou, S., 84
Lansium domesticum (duku), 18, 260
Lantapan (Mindanao, Philippines), 15
Laos, 15, 355, 356
Latin America, 4, 5, 6, 20, 22; benchmark sites in,
13–14; carbon stocks in, 42, 437; GHG from,
65, 66. See also Amazon, Brazilian; Amazon,
Peruvian; Brazil; Peru
laws: in Brazil, 205, 218, 240, 242, 275; in Cameroon, 313, 326; and deforestation, 240, 242, 349;
forestry, 205, 218, 313, 326, 350; in Indonesia, 300, 397, 400; international, 391; local
enforcement of, 376, 377; in Peru, 349, 350; and
sustainability, 147
Lawton, J. H., 126, 138
legumes, 19, 52; as crop cover, 20, 21, 223, 402; in pastures, 251, 281, 431; and sustainability, 153, 164
Lewis, J., 401
Lisu (minority group), 359, 360, 366
Litchi chinensis (lychee), 363, 374
literacy rates, 274
litter transformers, 120, 124, 139
livelihoods, 8–9, 320, 387, 416, 422, 432; and agroforestry, 374–76; and alternative LUSs, 315,
454
Index
livelihoods, (continued )
323, 371, 372, 378, 379; household, 24, 323,
324; and sustainability, 144–46. See also income;
welfare effects
livestock, 6, 176; in Brazilian Amazon, 173, 203,
205, 208, 212, 214–18, 239–41, 245–46,
271, 419, 429, 430–31; in Cameroon, 313;
constraints on, 245–46; in Indonesia, 251, 253,
254, 255; in Peruvian Amazon, 333, 346; and
prices, 240, 241, 408; products from, 173, 174,
185; and technology, 185, 187–91; in Thailand,
366; for traction, 203, 205, 208, 212, 214–18,
253, 254, 255. See also cattle ranching
logging, 5, 18, 19, 84, 389; animals used in, 203,
205, 208, 212, 214–18; in Brazilian Amazon,
201–5, 207–9, 211–18, 240, 246, 277, 281,
401, 419; in Cameroon, 307, 323, 326, 327,
420; and capital markets, 401; commercial,
51, 397, 398; and community forestry, 323,
326, 327; costs of, 205, 208, 430; and currency
devaluation, 178, 181, 281; cutting cycles in,
201–5, 209, 217, 218; damage from, 212, 213,
216; and deforestation, 171, 172, 301, 302, 416;
directional felling in, 204, 205, 211, 216; felling
cycles in, 216; and genetic variation, 344; illegal,
246, 250, 358, 364, 365, 371, 397; in Indonesia, 14, 171, 249, 250, 291, 293, 300–302,
396–400, 423, 428; and Krui system, 431; labor
in, 205, 301, 398; and land clearing, 175, 192;
low-intensity, 201–2, 217; lumber produced by,
175, 205, 207, 208, 213–14; mechanized, 201,
216, 217; in Peruvian Amazon, 333, 334, 344;
selective, 201, 205, 293; skidding in, 207–8,
214–15, 216; smallholder, 201–18, 400, 401; in
Thailand, 358, 364, 365, 371; and transportation, 182, 183, 192
Loreto region (Peru), 14
Lua (minority group), 359, 360, 366
Mae Chaem watershed (Thailand), 15, 17, 356–60,
368, 371, 377, 378; ethnic minorities in, 358,
359, 360; and land use change, 362–64, 370,
379; subdistricts of, 369
macroeconomics, 170–94, 301, 302, 314, 417,
419–23, 436
Macrolobium acaceifolium, 208
mahogany. See Swietenia macrophylla
Ma Hong Son (Thailand), 371
maize. See Zea mays
Makham (Cameroon), 97, 110
malaria, 270
Malaysia, 5, 410
Mangifera indica (mango), 312, 363, 392
Manihot esculenta (cassava; manioc), 19–21, 173,
174, 176, 401; and biodiversity, 90, 92, 93,
96–98, 109–11, 132; in Brazilian Amazon, 242,
402; in Cameroon, 307, 310, 311, 324; and
carbon stocks, 44, 50, 52, 54; and GHG, 68, 70,
72; in Indonesia, 250, 396, 397, 399, 400, 428;
monoculture of, 396–97; and nutrients, 158,
159; and peanuts, 310; in Peruvian Amazon,
341; processing of, 250; vs. rubber, 433; and
sustainability, 163, 164, 167
manioc. See Manihot esculenta
Maranhão, state of (Brazil), 181
markets, 9, 61, 84; agricultural, 173, 182, 318;
and agrochemicals, 318, 395, 401, 405; and
alternative LUSs, 24, 316–18, 324, 388,
394–96, 410, 431; in ASB matrix, 424, 425;
in Brazilian Amazon, 199, 200, 215, 217, 235,
240, 245, 266, 276, 278, 281, 403–5, 430; in
Cameroon, 307, 308, 311–14, 316–21, 324,
325, 328, 329; capital, 177, 318, 390, 391,
394, 400–401, 405, 410; cocoa, 312, 321; coffee, 245, 403, 408; in Congo Basin, 317–18,
319; credit, 395; cross-site comparisons of,
406; and currency devaluation, 177; and
deforestation, 171, 172, 417, 418, 436; and
food, 403, 407; and forest management, 199,
215, 217, 278; for fruit, 318, 392, 395; global,
245, 316, 321, 396, 408; and grasslands, 248,
249, 252; imperfections of, 390–91, 395–96,
398–404, 406–7, 410; in Indonesia, 225, 248,
249, 251, 252, 301, 303, 398–401, 423; input,
317–18, 320, 321, 391; labor, 177, 390, 394,
395, 400, 402–3, 405, 407; oil palm, 312,
318, 325, 395, 398; in Peruvian Amazon, 338,
346, 347, 350; and policy, 301, 303, 391, 408;
research on, 235, 281, 350; and sustainability,
146, 147, 150, 159, 278; in Thailand, 367;
timber, 200, 251, 403; and transportation,
181, 395–96, 405, 408; urban, 312, 321, 324,
392, 395, 417
Martinez, N. D., 87
Massai (grass), 283
Ma Taeng watershed (Thailand), 357
mateiros (native botanical experts), 203
Mato Grosso, state of (Brazil), 181
M’Balmayo (Cameroon), 42, 90, 110, 307–13
Melastoma, 259
Index
melons (Cucumeropsis spp.), 19, 310, 313, 320,
321, 324; C. mannii, 311, 392; egusi, 96; and
plantain, 316, 317
Mendelsohn, R., 183, 185
Mengomo (Ebolowa Station; Cameroon), 96, 97
Mercado, A. R., Jr., 18
methane, 22, 23, 66, 68, 120, 342–44; in incubation experiment, 69, 76; measurement of, 70–71;
radiative forcing of, 64–65; seasonality of, 71–74;
and soil, 76–78, 300; and sustainability, 150
Mexico, 14, 18
microsymbionts, 23, 125, 126, 127, 133, 138, 154
migration, 4, 10; in Brazilian Amazon, 266,
268–71, 273, 424; in Cameroon, 328, 330,
419, 420, 424; and currency devaluation, 179;
and deforestation, 8–9, 417, 436; and economic
development, 269–70, 273; and frontiers, 170;
government-sponsored, 8, 13–14, 249, 250, 292,
295; in Indonesia, 222, 226, 248–50, 291–93,
295, 297, 298, 300, 301, 396, 420–24; from
Java, 250, 292, 295, 300, 422; and land tenure,
183; in Peruvian Amazon, 334, 337, 338; and
population growth, 423–24; reverse, 417, 420;
and rubber agroforestry, 222, 226; rural-rural,
330, 420; rural-urban, 269; and sustainability,
143, 145; and technology, 187; in Thailand, 362
Millennium Ecosystem Assessment, 28
Miller, K. R., 84, 85
Mimosa sp., 259
mining, 173, 176, 268, 333
Ministry of Forestry (Indonesia), 28
minorities, ethnic, 356, 358–60, 362, 365, 366,
377. See also indigenous peoples
Mlabri (minority group), 359
Monke, E., 391
monoculture, 5, 388, 425; cassava, 396–97; coffee,
271; oil palm, 312, 393, 396–99; rubber, 106;
vs. small-scale farmers, 20, 300, 312–13, 319
Moraes, J. L., 54
Moretto, M., 234
Mucuna, 21
Munasinghe, M., 172
Murdiyarso, D., 67, 301
Musa paradisiaca (plantain), 307, 310–14, 320, 324,
392; and cocoa, 312, 321; and melon, 316, 317;
and oil palm, 313; in Peruvian Amazon, 341,
342
Musa X paradisiaca (bananas), 239, 240, 241, 242,
312
Myanmar, 15, 355, 356
455
Myers, N., 3, 8
Myrciaria dubia (camu-camu), 347
Myriapodes, 340
national parks, 217, 293, 294, 363–64
national security, 266, 358, 364, 365
natural resource management, 6, 143–48, 167; in
Brazilian Amazon, 266, 285, 286; in Indonesia,
302; integrated (INRM), 12, 16, 27; in Peruvian
Amazon, 334, 335; in Thailand, 355, 370,
376–78
nematodes, 23, 120, 124–29, 131, 133, 134, 138,
139, 154
Nepstad, D.C., 55
Nicaragua, 215, 350
Nicotiana tabacum (tobacco), 292
Nigeria, 321
nitrogen, 50, 65–66, 120, 236, 300; and biodiversity, 106, 124, 139; in fertilizers, 66, 71, 79, 241;
seasonality of, 75; and sustainability, 149–53,
159, 160, 162–64
nitrous oxide, 22, 23, 65–66, 68, 300, 342–44; in
incubation experiment, 69, 76; measurement
of, 71; radiative forcing of, 65; seasonality of,
72–74, 75, 76; in soil profile, 76–78
Nkol-fulu (Cameroon), 96, 135
Nkolitam (Cameroon), 97
Nkometou (Cameroon), 97
nongovernment organizations (NGOs), 9, 13, 28,
322, 326, 434; and alternative LUSs, 318–19,
329, 379; and farmer organizations, 329; and
Krui system, 431, 432; in Thailand, 369, 371
nontimber forest products (NTFPs), 18, 406; and
alternative LUSs, 379, 388; in Brazil, 173, 200,
235, 285, 401; in Cameroon, 308, 313, 315,
323, 324, 327; from community-based forests,
313, 327, 376; and currency devaluation, 178; in
Indonesia, 227, 228, 293, 397; and livelihoods,
323, 324; in Peruvian Amazon, 347, 349; policy
on, 285, 324; and rubber agroforestry, 227, 228;
substitution of, 174; and sustainability, 158, 159,
161, 163; in Thailand, 376, 379; in várzeas, 200
North Carolina State/TropSoils Collaborative Research Support Program, 337
Northern Mountain Area Agroforestry Systems Research and Development Project (Thailand), 378
North Queensland (Australia), 87–88
nutrients, 172, 270, 271, 299, 333, 426–28; and below-ground biodiversity, 121, 124, 139; cycling
of, 120; depletion time range (NDTR) of, 153;
456
Index
nutrients, (continued )
in FaleBEM, 236, 237; and fallow periods, 5, 6,
7; net export of (NNE), 153; relative replacement value (RNRV) of, 153, 158, 159; and soil
biota, 155; and sustainability, 23–24, 146, 147,
149, 152–53, 158–59, 161–63, 165, 167
oil. See palm oil; petroleum
Oliveira, M.V.N. d’, 206
Operation Amazon, 268–69
opium, 358, 362, 364, 365, 366, 367, 371; substitution for, 369–70
Oryza sativa (rice), 20, 66; and altitude zones, 366,
367; in Brazilian Amazon, 240, 241, 281, 285,
402; as commodity, 173, 176; in Congo Basin,
330; and Imperata grasslands, 21, 254, 259, 260;
in Indonesia, 223, 250, 254, 259, 260, 292, 295,
297, 299, 396–99, 428; in Krui system, 431;
and labor, 373, 398; paddy, 21, 297, 372–74;
in Peruvian Amazon, 341, 342, 347; prices of,
240, 241, 373, 407; sawah-lowland, 164, 165;
subsidies for, 285; substitution of, 174; and sustainability, 157, 159, 164–66; in Thailand, 360,
366, 367, 371, 373; upland, 19, 157, 158, 166,
172, 299, 341, 342, 376, 396–99, 428; upland
vs. paddy, 372–74
Pakuan Ratu (Lampung, Sumatra), 248, 249–61, 295
Palm, Cheryl A., 22, 23, 43, 45
palm oil, 317, 324, 346, 408
Pancuran Gading (Sumatra, Indonesia), 92
Panicum maximum (guineagrass), 283
Paraserianthes falcataria (sengon), 20, 44, 51, 55–56,
91, 156, 251, 298; and Imperata control, 258–61
Pará, state of (Brazil), 171, 181, 217, 268, 271
Pasir Mayang Research Station (Jambi province,
Sumatra), 67, 91–92
pastures, 5, 19, 21–22, 26; and alternative LUSs,
282, 284, 388, 410; vs. arable land, 172, 188,
189; and below-ground biodiversity, 123,
133–35, 137; in bioeconomic models, 237, 242,
280; Brachiaria-improved, 21, 93, 95, 275, 283,
341, 348, 349; in Brazilian Amazon, 200, 218,
237–39, 242–46, 273–75, 280–84, 401–5, 426,
429, 430–31, 433; carbon stocks in, 42, 44,
52–55, 57, 59, 60; and coffee, 245–46; and deforestation, 233–46, 271; degraded, 6, 242, 243,
433; and GHG, 65, 66, 71, 342, 344; grasslegume, 251, 281, 431; improved, 401–5, 426,
429; management of, 188, 189, 410; in Peruvian
Amazon, 335, 337, 338, 341, 342, 344, 347–50;
and policy, 244, 245; research on, 281, 283, 350;
soil of, 65, 273; and sustainability, 161, 164; and
technology, 188, 189. See also grasslands
peach palm. See Bactris gasipaes
Pearce, D. W., 8
Pearson, S. R., 391
Pedro Peixoto (Acre, Brazil), 13, 42, 200, 233–46;
biodiversity in, 94, 95, 135; forest management
in, 202–18, 276, 277; land use in, 238–40
Peltogyne, 208, 209
Peltophorum dasyrrachis tree, 251, 259
pepper, 251, 252, 258, 259, 260
Persea americana (avocado), 312, 317, 392
Persson, A., 172
Peru, 9, 18–23, 27, 28; benchmark sites in, 13, 14,
15, 17; biodiversity in, 125, 129, 132. See also
Amazon, Peruvian; Pucallpa; Yurimaguas Experiment Station
pesticides, 21, 163, 238, 240, 281, 314, 349; and
cash crops, 374; and cocoa, 312, 320; prices of,
241
pests, 120, 239, 373; in agroforests, 160, 223, 226,
228–30; in Cameroon, 312, 315, 319, 325, 328;
and cocoa, 163, 312, 325; and crop-fallow systems, 319, 328; in Indonesia, 223, 226, 228–30,
298, 299; and sustainability, 24, 146, 147, 149,
154, 160–63, 165
petai tree (Parkia speciosa), 158, 159, 228, 230, 260
petroleum, 173, 268, 334, 419
Pfaff, A. S., 171
PG Bunga Mayang (sugar plantation), 250
Phaseolus vulgaris (beans, edible), 173, 174, 240,
241, 280, 281, 285, 402. See also Glycine max;
Vigna radiata
Philippine Council for Agriculture, Forestry, and
Natural Resources Research (PCARRD), 15
Philippines, 5, 14, 15, 18, 22
phosphorus, 50, 106, 120, 149, 153, 159, 300
Pilot Program to Conserve the Brazilian Rain Forest,
233
Ping Basin (Thailand), 364
Pinus (pine), 20
Piper hispidinervum (pimenta longa), 209, 281
Pithecellobium dulce, 260
Pithecellobium jiringa (jengkol), 158, 159, 228, 230
plantain. See Musa paradisiaca
plant functional attributes (PFAs), 87, 106, 112–13
plant functional complexity (PFC), 88, 100, 101–2,
105
Index
plant functional types (PFTs), 23, 27, 86, 87–88,
89; in biodiversity studies, 91–103, 105, 106,
112–13. See also vegetation
policy: agricultural, 6, 244, 245, 324, 328, 329–30;
on agroforests, 231, 245, 301, 324; and alternative LUSs, 64, 244, 245, 300, 323–29, 357,
363–64, 369, 378, 379, 390–91, 424, 434;
and ASB, 9, 11–13, 16, 27, 28; in ASB matrix,
25–27, 424, 425; and biodiversity, 84, 111–12,
301, 303; in bioeconomic models, 235, 237,
243–44, 280–81; in Brazilian Amazon, 199,
218, 235, 237, 243–45, 265–69, 271, 273, 275,
277, 278, 280–85, 287, 419, 426; in Cameroon,
308, 314, 317, 322, 323–30, 391, 427; and
carbon stocks, 60–61; colonization, 267–69,
284–85; and community forestry, 326, 327; in
cross-site comparisons, 406–9; and currency
devaluation, 178, 191–92; and deforestation,
171, 181, 193, 233, 234, 240, 244, 245, 284,
285, 347, 348, 417, 418, 433, 434, 436; distortions by, 390–91; and economic development,
273, 275, 287, 409; Embrapa’s role in, 282–85;
and exports, 400; and food security, 317, 330;
forest management, 199, 218, 277, 278, 408;
and frontiers, 170; and global objectives, 303; on
indigenous peoples, 408, 431–32; in Indonesia,
84, 231, 300, 301, 303, 391, 400, 428, 431–32;
labor, 244, 245, 347, 349, 391; land, 7, 64, 240,
242, 244, 271, 284, 300, 347, 361, 391; at landscape scale, 378–79; macroeconomic, 178, 301,
314; and markets, 301, 303, 391, 403, 408; in
Peruvian Amazon, 332–33, 334, 347, 350; and
population, 424; and poverty, 283, 287, 408;
and prices, 244, 245, 285, 408; and research,
9–13, 16, 278–80, 282–87, 387, 433, 434;
resettlement, 267–69; and small-scale farmers,
245, 285, 303, 350; and sustainability, 167, 240,
277, 278, 284, 287, 301, 347; and technology,
181; in Thailand, 347, 348, 357, 361, 363–65,
367, 369, 378, 379; trade, 301, 317, 330, 390,
391; in tradeoff analysis, 25, 64, 301; welfare
effects of, 274, 350
policy analysis matrix (PAM) technique, 391–405
political issues, 199, 266, 435. See also socioeconomic issues
pollution, 120, 121, 153, 367, 416; air, 146, 147,
150; water, 275, 361, 374
Pontoscolex corethrurus (earthworms), 23, 120, 149,
154, 339, 340; and below-ground biodiversity,
124–26, 131–33, 136, 137, 139
457
population density, 5–7, 9, 13, 14, 17, 432; and alternative LUSs, 323, 328, 363, 366, 410; in ASB
matrix, 425; in Brazilian Amazon, 266, 268–69,
269–70; in Cameroon, 308, 314, 317–18, 320,
321, 323, 328, 423; in cross-site comparisons,
406; and currency devaluation, 181; and deforestation, 8, 294, 306, 418; in Indonesia, 170,
291, 292, 294, 301, 423–24; and infrastructure,
406–7, 424; and labor, 68, 170, 266, 268–69;
and markets, 317–18; in Peruvian Amazon, 333,
338, 340; in Thailand, 363, 366, 367
population growth, 269–70, 274, 335, 337, 358,
362, 423–24, 435
Porto Velho conference (Rondônia, Brazil; 1992),
10, 29–30
potassium, 106, 153, 158, 159, 162
poverty, 4, 10–12, 122, 407, 409, 431, 432; in
ASB matrix, 25, 425; in Brazilian Amazon, 266,
270, 274, 283, 287; in Cameroon, 321, 327;
and deforestation, 28–30, 233, 302, 436–37;
in Indonesia, 297, 301, 421, 422; and policy,
283, 287, 408; research on, 302, 380, 387; in
Thailand, 355, 358, 363–65
precipitation, 15, 17; in Cameroon, 309; in Indonesia, 67, 294; in Peruvian Amazon, 332, 335, 342
Presidente Figueiredo Igarape do lajes (Brazil), 95
prices: and agroforestry, 225, 229, 375; and alternative LUSs, 389, 393, 410; in bioeconomic models,
234–38, 241, 243; in Brazilian Amazon, 200,
215, 217, 234–38, 240, 241, 243–45, 277, 280,
430; of Brazil nuts, 238, 241; in Cameroon, 314,
318, 321, 322, 325, 328, 419; of cocoa, 321,
325, 408; of coffee, 240, 241, 244, 245, 408; and
currency devaluation, 177, 180; and deforestation,
243, 347, 349, 418; elasticity of, 174; of fertilizer,
158, 159, 241; and forest management, 200,
215, 217, 277; and frontiers, 170; and Imperata
control, 251, 256, 261; as incentives, 321, 408;
in Indonesia, 225, 229, 251, 256, 261, 397, 400;
land, 175, 182, 191, 335; and macroeconomics, 314; and markets, 318, 390; in Peruvian
Amazon, 238, 241, 335, 346–47, 349; and policy,
244, 245, 285, 408; of rice, 240, 241, 373, 407;
stabilization of, 407; subsidies for, 346, 347; in
Thailand, 373, 375; of timber, 28, 199, 241, 408;
and transportation, 182
production: in Brazil, 173–75; complementarity vs.
substitution of, 182–83; constraints on, 234,
235, 237, 244; factors of, 173, 175–77, 181,
185–87, 225, 347–48; in Sumatra, 175–76
458
Index
productivity: of agroforests, 20, 223, 224, 227–31,
302; and alternative LUSs, 328, 410, 434; and
biodiversity, 83, 84, 90, 106, 111, 112, 122; in
bioeconomic models, 234, 236, 237; of cocoa
systems, 320, 321, 322; of crop-fallow systems,
6, 319, 320; and deforestation, 330, 348, 424,
433; and economic development, 275, 334;
and forest management, 202–4, 214, 216, 277;
at forest margins, 299; and genetic resources,
344–45; and grassland reclamation, 248; of land,
6, 185–87, 320, 330; of livestock, 191; and
paddy rice, 373; and PFTs, 87–88; of rubber,
223, 224, 227–31; of shifting cultivation, 5, 6,
306; stable, 144; and sustainability, 24, 143–44,
149, 277; and technology, 185–92
profitability: of agroforests, 222, 301; and alternative LUSs, 24, 315–16, 363, 389, 393, 394,
397–98, 410, 429; in ASB matrix, 25, 26, 425;
and biodiversity, 83, 111, 112, 301; in bioeconomic models, 237; in Brazilian Amazon, 201,
202, 216–17, 237, 244–46, 276–78, 281, 286,
402–4, 426, 429–31; in Cameroon, 314–22,
325, 328, 427, 429; and cash crops, 373; and
cash flow, 430; of cocoa, 315, 316, 320, 321,
325; of coffee, 245–46; of crop-fallow systems,
320, 328; and currency devaluation, 300; and
deforestation, 191, 349, 416, 424; vs. exploitation, 143; and forest management, 201, 202,
215, 216–17, 277, 278, 402; and grassland reclamation, 249, 252; in Indonesia, 222, 249, 252,
299–302, 397–99, 422, 428; and land, 6–7,
172; and land tenure, 185; and macroeconomics,
314; and markets, 395; of oil palm, 322, 325;
in Peruvian Amazon, 347, 349; and policy, 244,
245, 391; in research, 281, 286, 302, 387, 434;
of rice, 373; social, 316; and sustainability, 148,
158, 277, 278; and technology, 185, 188, 189,
192; in Thailand, 363, 373; tradeoffs with, 25,
60, 314–19, 430, 432; and transportation, 182,
183; of tree-based systems, 252, 347
Projeto Reca (Rondônia, Brazil), 94, 281, 282
property rights, 25, 84, 323, 424; in agroforests,
28, 295–96; and alternative LUSs, 318, 363;
communal, 313; and deforestation, 192, 418;
and land clearing, 175, 183–85; private, 363; to
trees, 6, 61, 249, 295–96, 377; vs. use rights, 61,
175, 377; to water, 361. See also land tenure
protists, 124, 126
Protium apiculatum, 208, 209
protozoa, 120
Prunus africana, 309
Prunus mume (Japanese apricot), 374
Prunus salicina (Japanese plum), 374
Pucallpa (Ucayali Department, Peru), 14, 335–42,
345–47, 349, 350
Pueraria phaseoloides (kudzu), 21, 241, 281, 283,
340, 341, 348, 349
pulpwood plantations, 5, 19, 20, 50, 51, 54, 55–56,
58
pupunha. See Bactris gasipaes
Pyrus pyrifolia (Asian pear), 374
Quaribea guianensis, 209
Queen Sirikit Forest Development Project (Suan Pah
Sirikit; Thailand), 370–71, 373, 378
Raffia palm swamps, 97, 110
Rainforest Challenge Partnership, 28–29
Raks Thai Foundation, 378
Rantau Pandan benchmark site (Jambi, Sumatra),
294, 295, 297, 298
rattan, 228, 400
reforestation, 249, 345, 358, 375
research: agricultural, 14, 27, 28, 320, 328, 329; on
agroforestry, 261, 329, 340, 380; and alternative
LUSs, 276–78, 286, 318–19, 323, 329, 357,
380, 433; ASB, 12–13, 16–30, 387–91, 433,
434, 435; ASB impact on, 27, 278–81; on biodiversity, 10, 280, 286, 302, 350; biophysical, 278,
281, 286, 338–46; in Brazilian Amazon, 268,
276–81, 283, 286; in Cameroon, 302, 318–19,
320, 322, 323, 328, 329; and complementarity
vs. substitution relationships, 183; on economic
development, 286, 387, 433; on ecosystem
services, 13, 302, 435; farmers’ participation
in, 279, 280, 329, 333, 345, 350, 433, 435; on
food security, 302, 387, 389, 390; on forestry,
14, 329, 350, 419; future needs for, 302; genetic,
333, 338, 345–46; on households, 253–56,
280, 283; in Indonesia, 20, 67, 91–92, 253–56,
261, 295, 297–302; innovations in ASB,
433–35; integrated natural resource management (INRM), 12, 16; international, 279, 280,
285, 380; on landscape scale, 279, 286, 302; on
markets, 235, 281, 350; measurement techniques
in, 433; multidisciplinary, 9, 10, 12–13, 28,
30, 278, 302, 378, 433; in Peruvian Amazon,
333, 335–46, 349, 350; and policy, 9–13, 16,
278–80, 282–87, 387, 433, 434; on poverty,
302, 380, 387; socioeconomic, 278, 280–81,
Index
286, 346–50, 387–91, 435; staff for, 285–86; on
sustainability, 27, 281, 286, 302, 387, 433, 434,
435; and technology, 279, 280, 281, 286, 302,
387, 433; in Thailand, 357, 361, 378, 380. See
also economic models
Reserva Biologica de Campina (Brazil), 95
Rhizobium, 23, 146, 147, 149
rice. See Oryza sativa
risk, 280, 405, 429; of alternative LUSs, 24, 315,
325–28, 330, 431; vs. benefits, 325–27
Rondônia, state of (Brazil), 13, 42, 181, 279, 281,
282, 404; benchmark sites in, 266; biodiversity in,
93–94, 100, 135; coffee in, 240, 403, 405; deforestation in, 200, 270–71, 272; economic development in, 268, 273, 275; population growth in,
269, 270; Porto Velho conference in, 10, 29–30
roots, 120, 121, 154; bacteria on, 124–25, 128–29,
131, 133, 135, 136, 138–39; biomass of, 53–54,
55; and carbon stocks, 47, 53–54, 55, 57
Roper, J., 8
Rottboellia cochinchinensis, 339
Royal Forest Department (Thailand), 15, 369, 371,
378, 379, 380
Royal Project Foundation (Thailand), 362–63, 369,
371, 373, 374
rubber. See Hevea brasiliensis
Rudel, T., 8
Saccharum officinarum (sugar cane), 249, 250, 255,
293, 299; as commodity, 173, 176; substitution
of, 174; and sustainability, 164, 165
Sam Mun Highland Development Project (Thailand), 357, 369–70, 371, 372, 374–78
Sanchez, P. A., 42
São Paulo-Rio Branco road (Brazil), 9
savannas, 90, 97, 110, 330. See also grasslands
Schima wallichii, 259
Schizolobium amazonica (bandarra), 44, 93, 111,
401–4, 426, 429
seasonality, 89; of GHG, 68, 71–76, 77
Selective Logging System, Indonesian, 293
Selva Baja (Peru), 14, 17
Sen, A., 390
sengon. See Paraserianthes falcataria
Senna reticulata (senna), 44, 52
Seringal São Salvador (Acre, Brazil), 284
Setaria grass, 259
Shannon-Wiener diversity index, 88, 100, 101–2,
105, 106, 132–34
Sheil, D., 207
459
shifting cultivation, 4–6, 8–10, 13, 406; and alternative LUSs, 21, 370, 388, 389, 410; and altitude
zones, 366, 367, 368; and biodiversity, 89,
340; in Brazilian Amazon, 200, 217, 218, 402;
in Cameroon, 21, 222, 307, 419; and carbon
stocks, 51–52, 58, 60; and cash crops, 373; and
community forests, 375; and deforestation, 29,
302, 349, 416–18; and forest management, 200,
217, 218; and GHG, 71, 342; in Indonesia, 248,
291, 295, 297, 299, 302, 396, 421; in MMSEA
ecoregion, 355; vs. paddy rice, 372; in Peruvian
Amazon, 340, 342, 349; productivity of, 5,
6, 306; vs. slash-and-burn agriculture, 4, 5–6;
sustainability of, 24, 143, 159, 291; in Thailand,
358–61, 366–68, 370, 372, 373, 375, 380
Shorea javanica (damar), 18, 19, 223, 295, 431
Shortle, J. S., 234
Shugart, H. H., 86
Sida, 163
Silva, J.N.M., 206
Silver, W. L., 60
Simpson diversity index, 88, 100, 101–2, 105, 106,
133, 134
sisipan system, 223–30, 231
slash-and-burn agriculture, 11, 45, 51; best-bet
alternatives to, 25, 27, 83–113, 222, 277, 302,
323; in Cameroon, 306; and deforestation, 306,
349; in Indonesia, 291, 292, 299, 303, 422;
large-scale, 9; in Peruvian Amazon, 333, 338; vs.
shifting cultivation, 4, 5–6
Smith, J., 347
Smith, K. A., 65
Soca monocrop, 325
social conflict, 269, 346, 361, 365, 377, 435
socioeconomic issues: and alternative LUSs, 24, 315,
319, 389–90; in ASB matrix, 26; at benchmark
sites, 13, 16, 22; and biodiversity, 84, 111;
in Brazilian Amazon, 24, 181–91, 216–17,
265–66, 269, 285; in Cameroon, 24, 311, 319;
and colonization, 285; cross-site comparisons of,
406–9; and deforestation, 29–30, 181–91, 233,
346–50, 417, 418; in Indonesia, 24; in PAM,
391; in Peruvian Amazon, 332–33, 346–50;
research on, 278, 280–81, 286, 302, 387–91,
435; in Thailand, 355, 361, 365, 377; and
tradeoffs, 434
soil, 17, 21, 27, 175, 410; biodiversity in, 85, 90,
98, 99, 104–6, 111, 112, 119–39, 311; in
bioeconomic models, 234, 236, 237; biota in,
23, 65, 146, 147, 149, 151–52, 154, 155;
460
Index
soil, (continued )
in Brazilian Amazon, 201, 239, 240, 243,
269–71, 273, 426; in Cameroon, 160–62,
308, 309–10, 427; and carbon stocks, 43, 45,
47, 50, 53, 54, 56, 57, 60; and colonization,
269; compaction of, 148–50; conservation
of, 6, 371; and deforestation, 233, 234, 243,
271, 348; degradation of, 233, 234, 271–73,
275, 319, 339; and economic development,
271–73, 275; erosion of, 6, 24, 270, 361, 374;
in European forests, 79; exposure of (SE), 152,
155–56, 157, 160, 162, 167; fertility of, 23–24,
121, 124, 131, 164, 165, 236, 249, 250, 255,
294, 298, 300, 310, 320, 334, 335, 348;
functions of, 148; and GHG, 65–67, 69, 70,
76–78, 342; and Imperata control, 249, 255;
incubation of, 69; in Indonesia, 294, 298, 300,
423, 428; and logging, 205; macrofauna in, 23,
128–29, 130, 131, 136, 138, 139, 154; and
methane, 76–78, 300; organic matter (SOM)
in, 152, 155; in Peruvian Amazon, 333, 334,
335, 338, 339; and plowing, 255; properties of,
67, 120; structure of, 121, 146–52, 154–57,
160–64; and sustainability, 23–24, 146–52,
154–57, 160–65, 167; topsoil, 53, 54, 57, 60;
water-filled pore space (WFPS) in, 65, 66, 71,
75; and watershed degradation, 361. See also
nutrients
Soil Biodiversity Network (ASB), 122–23, 138
soil cover index, 152, 155–56, 157, 160
Solanum scabrum, 311
Solanum tuberosum (potato), 363
Sommer, R., 55, 60
Southeast Asia, 6, 21, 22, 410; benchmark sites in,
14–15; economic crisis in, 379, 422; mountainous mainland (MMSEA), 355–56, 358, 359,
360, 366, 380. See also particular countries
species: abundance of, 88, 127, 131, 132, 133, 137,
217, 344; in biodiversity studies, 106, 112, 121,
125, 127; in forests, 208–9, 210, 212–13; vs.
functional groups, 133; keystone (flagship), 85,
112; native vs. introduced, 281; and PFTs, 87;
richness of, 88, 100, 103, 106, 126, 212–13,
223; richness vs. abundance of, 132, 133, 137
Suan Pah Sirikit. See Queen Sirikit Forest Development Project
subsidies, 170, 424; for agroforests, 328–29; in
Brazilian Amazon, 233, 268, 283, 430; in
Cameroon, 314, 325, 328–29, 419–20; for colonization, 233; credit, 268, 283, 346, 347, 405;
income, 285; in Peruvian Amazon, 334, 346,
347; price, 346, 347; wage, 430
sugar cane. See Saccharum officinarum
Sulawesi, 420
sulfur, 120, 121
Sumatra (Indonesia), 28, 425, 429; agroecological
zones of, 295; agroforests in, 18, 20, 222–31;
benchmark sites in, 14–15, 17, 292, 294–301;
biodiversity in, 85, 92, 98, 100, 106, 107,
109–11; carbon stocks in, 42, 44, 47, 48–58,
60, 64, 300, 428; colonization program in, 171;
currency devaluation in, 180–81; forest margins
in, 291–303; GHG in, 64–79; Imperata cylindrica
grasslands in, 248–61; macroeconomic factors
in, 420, 421–23; migrants in, 222, 226, 248–50,
291–93, 295, 297, 298, 300, 301, 396, 420–24;
models of, 172, 194; montane zone in, 302;
nutrient balance in, 158–59; peneplain of, 224,
225, 231, 250, 292, 294, 295, 300, 302, 397;
piedmont of, 224, 225, 231, 294, 295, 300, 302;
population density of, 170, 292; production activities in, 175–76; sustainability studies in, 153–60;
tradeoffs in, 431–32; Trans-Sumatra highway in,
9, 292, 295, 423; tree-based systems in, 291, 422,
423. See also Jambi province; Lampung province
sustainability, 5, 10, 29; and adaptation, 144–46,
165, 167; of agroforests, 157, 161, 163–66, 328;
and air quality, 146, 147, 150; in alternative
LUSs, 143–67, 282, 284, 328, 378; and ASB,
11, 13, 148, 277; in ASB matrix, 26, 424; in
Brazilian Amazon, 154–64, 199–218, 235, 266,
276–78, 282, 284, 401, 426, 431; in Cameroon,
154–64, 300, 303, 308, 311, 314–19, 328, 427;
and carbon stocks, 24, 148, 150, 151–52; of
cassava-Imperata systems, 156, 157, 160, 166,
167; of community-based forests, 18, 157, 162,
163, 166, 323; cross-site comparisons of, 406;
definitions of, 143–46; and deforestation, 30,
433, 436; and disease, 24, 146, 147, 149, 154,
160–63, 165; of economic development, 269,
276, 286, 409; and fallow periods, 24, 143–44,
160, 162–63, 164, 167, 291; and fertilizers,
149, 153, 158, 159, 162, 164, 167; and forest
management, 18, 199–218, 276–78; and genetic
resources, 166, 167, 344–46; and GHG, 64;
indicators for, 147–50, 152–53, 160; in Indonesia, 154–64, 291, 298, 299, 428; and Krui
system, 432; at landscape scale, 146, 164–67;
and land tenure, 183; and livelihoods, 144–46;
local, 435; and markets, 146, 147, 150, 159;
Index
measurement of, 23–24; vs. nonsustainability,
145; and persistence, 146; in Peruvian Amazon,
344–46, 349; plot-level assessment of, 146–54;
and policy, 167, 240, 277, 278, 284, 287, 301,
347; rapid assessment of, 147; research on, 27,
281, 286, 302, 387, 433–35; and scale of system,
144–45; of shifting cultivation, 24, 143, 159,
291; and soil, 23–24, 146–52, 154–57, 160–65,
167; and technology, 144, 154, 166, 167, 185;
in Thailand, 371, 373, 378; threats to, 146–48;
tradeoffs with, 314–19; of tree-based systems,
161, 164, 165, 167, 300, 303, 315; and water
quality, 146, 147, 149, 150, 153
Sweden, 5
Swietenia macrophylla (mahogany), 20, 205, 206,
217
Swift, M., 23
Tabebuia serratifolia, 208
tapirs, 103
tea, jungle. See Camellia sinensis
technology, 11, 172, 175, 434; agricultural, 6, 173,
185–91, 193; and alternative LUSs, 323, 328,
329, 379, 410; in ASB matrix, 424, 425; and
bioeconomic models, 235, 237–38, 281; in
Brazilian Amazon, 199, 215, 217, 235, 237–38,
240, 266, 268, 281; in Cameroon, 325, 328,
330; and capital, 185–93; and deforestation,
171, 181, 187–93, 234, 347–49, 416, 418, 424,
433; and economic development, 275, 276; and
forest management, 199, 215, 217; and frontiers,
170; GIS, 16, 379; in Indonesia, 302; and information, 379, 400, 405; and land tenure, 185;
long-run effects of, 189–91; long- vs. short-run
effects of, 192–93; in Peruvian Amazon, 347–49;
and policy, 181, 302, 391; and prices, 174; and
research, 279, 280, 281, 286, 302, 387, 433;
short-run effects of, 187–89, 191; and sustainability, 144, 154, 166, 167, 185; in Thailand,
356, 361, 367
termites, 23, 120, 322, 340; and below-ground
biodiversity, 101, 103, 124–27, 130, 131–33,
136–39; and sustainability, 149, 154
Thai-Australian Highland Development Project, 371
Thai-German Highland Development Project, 371
Thailand, 18–21, 355–80; ASB in, 27, 355, 369,
371, 377–80; benchmark sites in, 15, 17;
biodiversity in, 106, 111, 357; and cash crops,
373–74; conservation projects in, 369–71;
constitutional reform in, 377; deforestation in,
461
357–60; ethnic minorities in, 356, 358–60, 362,
365–67; LUSs in, 19, 357–61; and MMSEA,
355, 356; tourism in, 365
Thai-U.S. Agency for International Development
Mae Chaem Development Project, 371
Theobroma (Rondônia, Brazil), 13, 42, 93, 94, 135,
200
Theobroma cacao (cocoa), 19, 25, 157, 173, 174; in
agroforests, 20, 311–12, 314, 321; and alternative LUSs, 410, 411; in ASB matrix, 425; and
biodiversity, 90, 97, 98, 107–10, 315, 320–22;
in Cameroon, 308, 310–14, 316, 317, 319,
320–22, 324, 330, 392–95, 419, 427, 429; and
carbon stocks, 44, 51, 52, 54, 55, 58, 59, 321;
and currency devaluation, 321; and degraded
vs. forest land, 321–22; and economic development, 273, 409; extensive vs. intensive systems
of, 312; and fruit trees, 312, 320–21, 432–33;
markets for, 318, 408; in Peruvian Amazon,
346–47; pests in, 163, 312, 320, 325; prices of,
321, 325, 408; profitability of, 315, 316, 320,
321, 325; sustainability of, 162, 163, 328; and
women, 319
Theobroma grandiflorum (cupuaçú), 19, 21, 44, 281,
282; in biodiversity studies, 94, 107, 108
Thiele, R., 171
Tiki Manga, T., 16
timber: in agroforests, 18–20, 228, 230, 292; in
Brazilian Amazon, 173, 199, 200, 202–5, 207,
208, 211, 213–14, 217, 241, 278, 285, 401; in
Cameroon, 307, 309, 313, 323; commercial,
87–88, 202–3, 211, 217, 309; from communitybased forests, 313, 323; and deforestation, 417,
418; and economic development, 409; felling
cycles of, 199; and forest categories, 293; in forest
inventories, 202–4; and forest management, 199,
278; and Imperata control, 252, 255; in Indonesia, 228, 230, 251, 252, 255, 292, 293, 295, 420,
423; and Krui system, 432; markets for, 200, 251,
403; plantations of, 90, 156, 423; for plywood,
217; policy on, 285; prices of, 28, 199, 241, 408;
sawn, 205, 207, 208, 213–14; and soil, 156, 158;
species used for, 202–3, 339; substitution of, 174;
in várzeas, 200; yields of, 205. See also logging;
tree-based systems; trees
Tithonia diversifolia, 21
Togo, 321
Tomich, Thomas P., 24, 29, 43, 389, 391, 396
Toona sinensis (surian), 298
Torresia acreana, 206, 209
462
Index
Torsvik, V., 126
trade: in Brazil, 173, 245, 276; in Cameroon, 317,
324, 330; and deforestation, 171; and economic
development, 276; fair, 324; and frontiers, 170;
in Indonesia, 301, 422; international, 245, 391,
396, 400, 408; liberalization of, 330; policy on,
301, 317, 330, 390, 391; as production activity,
176. See also markets
tradeoff analysis, 11–13, 24–25, 27, 29, 415–37;
in ASB matrix, 425–32; and ASB research, 16,
433; in bioeconomic models, 280; for Brazilian
Amazon, 276, 297, 426; for Cameroon, 314–19,
323–29, 427; and economic development, 297;
and environmental issues, 314–19, 432; and
GHG, 79; for Indonesia, 301, 428; for Peruvian
Amazon, 333, 334; policy in, 25, 64, 301; for
Thailand, 378
Trans-Amazon highway (Brazil), 9, 268
Trans-Gabon highway, 9
transmigration, 249, 250, 420, 421. See also colonization; migration
transportation infrastructure: and alternative LUSs,
181, 183, 395; in Brazilian Amazon, 9, 13, 181–
83, 192, 215, 267, 268, 276, 419; in Cameroon,
308, 320, 321; and capital, 405; in Congo Basin,
330; and deforestation, 9, 171, 181–83, 192,
349, 417; and economic development, 276;
and frontiers, 170; in Indonesia, 251, 400, 423;
and logging, 182, 183, 192; and markets, 181,
395–96, 405, 408; in Peruvian Amazon, 346,
349; policy on, 408; and population, 424; in
Thailand, 365; and welfare effects, 182–83
transportation services, 173, 176
Trans-Sumatra highway, 9, 292, 295, 423
tree-based systems: as alternative LUSs, 388, 410;
and below-ground biodiversity, 123, 132, 137;
in Brazilian Amazon, 173, 281; in Cameroon,
320, 329, 330, 419, 420; carbon stocks in, 45,
46, 49–53, 55, 57, 60, 61, 314–15; costs of,
430; cross-site comparisons of, 406; diversification of, 330; as factor of production, 175, 176;
and GHG, 66–67, 69, 71; and GWP, 344;
and Imperata, 251–61; in Indonesia, 251–61,
291–92, 295, 297, 299, 300, 303, 421, 422,
423; intensive, 19, 20–21; and land tenure, 185;
large-scale, 5, 46, 423; and markets, 408; and
migrants, 295; in Peruvian Amazon, 347; profitability of, 252, 347; for pulpwood production,
5, 19, 20, 50, 51, 54, 55–56, 58; substitution of,
174; sustainability of, 161, 164, 165, 167, 300,
303; and technology, 185, 187–91, 192; tradeoff
analysis of, 301, 434; and women, 319. See also
agroforests; fruit trees
Treecrops Advisory Service (Indonesia), 398
trees: artificial regeneration of, 207; biomass of,
43; domestication of, 345, 350; fast-growing,
251, 258, 299; genetic resources of, 333, 338,
344–46; and PFTs, 87–88; property rights to, 6,
61, 249, 295–96, 377; replanting of, 205–6; seed
orchards for, 345–46; studies of, 90, 200. See also
forests; timber
Trinorea publifora, 209
Triticum aestivum (wheat), 330
Tropical Soil Biology and Fertility (TSBF) Programme, 127, 128, 129, 339, 340
Tropileche (research consortium), 350
Trumbore, S. E., 55
Tucuruí Dam (Pará, Brazil), 268
Ucayali region (Peru), 14, 28. See also Pucallpa
Uganda, 85, 217
Uncaria tomentosa (uña de gato), 347
United Nations: Development Program (UNDP) of,
10, 274–75; Drug Control Program of, 369
Universidade Federal do Acre, 278
Universidad Nacional Agraria la Molina, 350
Universidad Nacional del Ucayali (UNU), 339
urbanization, 14, 418; in Africa, 307, 312, 319–21,
324, 325, 330, 408; in Brazilian Amazon,
269–70; and markets, 312, 321, 324, 392, 395,
408, 417; and migration, 269; and new development paradigm, 275; in Thailand, 358, 365; and
water pollution, 275, 361
Valentim, Judson F., 239
van Noordwijk, Meine, 16, 29, 47, 396
várzeas (flooded areas, Amazon region), 200
VegClass software, 88, 98, 100
vegetables, 19, 163, 312, 362, 374. See also horticulture
vegetation, 17, 332; biodiversity of, 23, 98, 99, 100,
101–2, 103, 105, 112, 119; biomass of, 42, 53;
and carbon stocks, 42, 50, 57; classification of,
89; vs. fauna, 85, 88, 100–107, 109; as ground
cover, 121; and nutrients, 24, 153. See also plant
functional types; particular species
vegetation index (V-index), 100, 101–2, 103, 105,
109–11
Vietnam, 15, 355, 356
Vigna radiata (mung beans), 223
Vosti, Stephen A., 24, 389, 401
Index
wages, 17, 393, 396, 398, 402, 407, 430; in bioeconomic models, 236, 241; in Brazilian Amazon,
240, 403; cross-site comparisons of, 406; and
currency devaluation, 177; and deforestation,
243; in Indonesia, 227, 255, 397
Wasrin, U. R., 67
water, 6, 293, 367, 378; and deforestation, 233,
416; and GHG, 65; in MMSEA ecoregion, 355;
pollution of, 275, 361, 374; quality of, 146, 147,
149, 150, 153, 233; rights to, 361; and soil, 154,
271; and sustainability, 146, 147, 149, 150, 153;
and urbanization, 275, 361
watershed management, 15, 29, 120; in Brazilian
Amazon, 269; in Cameroon, 329; in Indonesia,
302; networks for, 377, 379; in Thailand, 355,
360–61, 370, 377, 379
watersheds, 10, 371, 377; classification of, 364; services from, 29, 360–61, 378. See also Ma Chaem
watershed; Ma Taeng watershed
weeds: invasive, 335, 339; suppression of, 6, 24,
146, 147, 149, 154, 160–63, 165
Weitzman, M. L., 84
welfare effects, 361, 396, 416; in Brazilian Amazon,
274–75; and currency devaluation, 177; of economic development, 269, 274–75; and land use
change, 365, 377, 379, 380; in Peruvian Amazon, 346–47; of policy, 274, 350; in Thailand,
380; and transportation infrastructure, 182–83
463
White, D., 347
Wiebelt, M., 171
wildlife sanctuaries, 363
Witcover, J., 401
women, 17, 311, 319, 325, 328, 407, 420
Woomer, Paul L., 22, 23, 43
World Bank, 28, 84, 314
Wösten, J.H.M., 148
Xanthosoma sagittifolium (cocoyam), 307, 311–14,
320, 321, 324, 392
Yao (minority group), 359
Yaoundé (Cameroon), 21, 42, 90, 307–14, 319, 425
Yucatan (Mexico), 14
Yurimaguas Experiment Station (Peru), 14, 66, 68,
70, 71, 75, 79, 337–38; biodiversity in, 338,
339, 340; carbon stocks in, 340–42; GHG in,
67, 72, 342–43
Zea mays (maize), 95, 98, 173, 174, 176; in Brazilian
Amazon, 240, 241, 402; in Cameroon, 311,
312, 313, 330, 392; and Imperata control, 21,
254, 259, 260; in Indonesia, 21, 223, 254, 259,
260; in Peruvian Amazon, 341, 347; in Thailand, 363, 373
Zingiber officinale (ginger), 19, 362