Skip to main content

Advertisement

SpringerLink
Log in

Comparative analysis of plotless sampling methods for estimating woody plant density in a West African savanna agroforestry parkland

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Agroforestry parklands are an age-old traditional land use practice that integrates crop cultivation under scattered woody plants. This practice is widespread in West African savannas providing many essential ecological and socio-economic benefits to people such as food, fuelwood, and medicine. Currently, parklands are decreasing due to changes in agriculture and land use practices, often associated with human population growth. Understanding spatial patterns as well as identifying reliable methods of sampling to estimate the density of woody plants is necessary for the sustainable management of parklands. In this study, a comparative analysis of select plotless sampling methods was performed using field and simulated datasets with known spatial patterns from field assessments. Results of spatial indices tests indicated that woody plants in parklands exhibited two spatial patterns: i.e., aggregate and random, the latter being the dominant pattern observed in field datasets. Based on relative measure statistics (i.e., RRMSE and RBIAS), the ordered distance (OD), point-centered quarter (PCQ), and closest individual (CI) methods performed well when woody plants were located in a random pattern while the variable area transect (VAT) method was better at estimating density under patterns of spatial aggregation. Overall, OD and VAT methods are recommended for density estimation in parklands because they are relatively more accurate, less biased, and practical and computations are easy to undertake.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data availability

Field data analyzed during this study are available from the author upon reasonable request. However, source data for the simulation part of this study are included in the article.

References

  • Amanor-Boadu, V., Zereyesus, Y., Ross, K., Ofori-Bah, A., Adams, S., Asiedu-Dartey, J., Gutierrez, E., Hancock, A., Mzyece, A., & Salin, M. (2015). Agricultural production survey for the northern regions of Ghana: 2013–2014 results. Final report (p. 112). METSS/USAID.

  • Amoako, E. E., Asante, W. J., Cobbinah, S., Kuuder, C. J. W., Adongo, R., & Lawer, E. A. (2015). Tree tenure and its implications for sustainable land management: The case of Parkia biglobosa in the Northern Region of Ghana. Journal of Natural Resources and Development, 5, 59–64. https://doi.org/10.5027/jnrd.v5i0.08

    Article  Google Scholar 

  • Baddeley, A., & Turner, R. (2005). spatstat: An R Package for analyzing spatial point patterns. Journal of Statistical Software, 12(6), 1–42. https://doi.org/10.18637/jss.v012.i06

  • Basiri, R., Moradi, M., Kiani, B., & Maasumi Babaarabi, M. (2018). Evaluation of distance methods for estimating population density in Populus euphratica Olivier natural stands (case study: Maroon riparian forests Iran). Journal of Forest Science, 64(5), 230–244. https://doi.org/10.17221/146/2017-JFS

  • Bayala, J., Sanou, J., Teklehaimanot, Z., Kalinganire, A., & Ouédraogo, S. J. (2014). Parklands for buffering climate risk and sustaining agricultural production in the Sahel of West Africa. Current Opinion in Environmental Sustainability, 6(1), 28–34. https://doi.org/10.1016/j.cosust.2013.10.004

    Article  Google Scholar 

  • Ben-Said, M. (2021). Spatial point-pattern analysis as a powerful tool in identifying pattern-process relationships in plant ecology: An updated review. Ecological Processes, 10(1), 56. https://doi.org/10.1186/s13717-021-00314-4

    Article  Google Scholar 

  • Boffa, J.-M. (Ed.). (1999). Agroforestry parklands in sub-Saharan Africa. FAO Conservation Guide 34. Food and Agriculture Organization of the United Nations.

  • Boffa, J.-M., Taonda, S.J.-B., Dickey, J. B., & Knudson, D. M. (2000). Field-scale influence of karité (Vitellaria paradoxa) on sorghum production in the Sudan zone of Burkina Faso. Agroforestry Systems, 49(2), 153–175. https://doi.org/10.1023/A:1006389828259

    Article  Google Scholar 

  • Clark, P. J., & Evans, F. C. (1954). Distance to nearest neighbor as a measure of spatial relationships in populations. Ecology, 35(4), 445–453. https://doi.org/10.2307/1931034

    Article  Google Scholar 

  • Clayton, G., & Cox, T. F. (1986). Some robust density estimators for spatial point processes. Biometrics, 42, 753–767. https://doi.org/10.2307/2530691

    Article  Google Scholar 

  • Cogbill, C. V., Thurman, A. L., Williams, J. W., Zhu, J., Mladenoff, D. J., & Goring, S. J. (2018). A retrospective on the accuracy and precision of plotless forest density estimators in ecological studies. Ecosphere. https://doi.org/10.1002/ecs2.2187

    Article  Google Scholar 

  • Condit, R., Ashton, P. S., Baker, P., Bunyavejchewin, S., Gunatilleke, S., Gunatilleke, N., Hubbell, S. P., Foster, R. B., Itoh, A., LaFrankie, J. V., Lee, H. S., Losos, E., Manokaran, N., Sukumar, R., & Yamakura, T. (2000). Spatial patterns in the distribution of tropical tree species. Science, 288, 1414–1418. https://doi.org/10.1126/science.288.5470.1

    Article  CAS  Google Scholar 

  • Cottam, G., & Curtis, J. T. (1956). The use of distance measures in phytosociological sampling. Ecology, 37, 451–460. https://doi.org/10.2307/1930167

    Article  Google Scholar 

  • Dangai, Y., Hamawa, Y., Tsobou, R., Oumarou, H. Z., & Mapongmetsem, P. M. (2021). Carbon stocks in Daniellia oliveri agroforestry parklands in the Sudano -sahelian zone of Cameroon. Environmental Challenges. https://doi.org/10.1016/j.envc.2021.100397

    Article  Google Scholar 

  • Djossa, B. A., Fahr, J., Wiegand, T., Ayihouénou, B. E., Kalko, E. K., & Sinsin, B. A. (2007). Land use impact on Vitellaria paradoxa C.F. Gaerten. stand structure and distribution patterns: a comparison of Biosphere Reserve of Pendjari in Atacora district in Benin. Agroforestry Systems, 72(3), 205. https://doi.org/10.1007/s10457-007-9097-y

    Article  Google Scholar 

  • Dudley, N., Eufemia, L., Petersen, I., Fleckenstein, M., Campari, J., Periago, M. E., Miñarro, F. O., Siqueira, C., Timmers, J. F., Rincón, S., Musálem, K., Rendón, E., Forero, D. C., Kauffman, M., Miaro III, L., Burns, A., Ge, Z., Pereladova, O., Buyanaa, C., & McConnel, I. (2020). Grassland and savannah ecosystems: An urgent need for conservation and sustainable management. WWF Deutschland.

  • Earnshaw, A., & Emerton, L. (2000). The Economics of Wildlife Tourism: Theory and Reality For Landholders in Africa BT - Wildlife Conservation by Sustainable Use (H. H. T. Prins, J. G. Grootenhuis, & T. T. Dolan (Eds.); pp. 315–334). Springer Netherlands. https://doi.org/10.1007/978-94-011-4012-6_16

  • ELD-UNEP. (2015). The economics of land degradation in Africa: Benefits of action outweigh the costs. The Economics of Land Degradation. Retrieved date: May 20, 2022, from www.eld-initiative.org

  • Elliott, A. C., & Hynan, L. S. (2011). A SAS® macro implementation of a multiple comparison post hoc test for a Kruskal-Wallis analysis. Computer Methods and Programs in Biomedicine, 102(1), 75–80. https://doi.org/10.1016/J.CMPB.2010.11.002

    Article  Google Scholar 

  • Engeman, R., Sugihara, R., Pank, L., & Dusenberry, W. (1994). A comparison of plot-less density estimators using Monte Carlo simulation. Ecology, 75, 1769–1779.

    Article  Google Scholar 

  • Estes, L. D., Searchinger, T., Spiegel, M., Tian, D., Sichinga, S., Mwale, M., Kehoe, L., Kuemmerle, T., Berven, A., Chaney, N., Sheffield, J., Wood, E. F., & Caylor, K. K. (2016). Reconciling agriculture, carbon and biodiversity in a savannah transformation frontier. Philosophical Transactions of the Royal Society of London. Series b, Biological Sciences, 371(1703), 20150316. https://doi.org/10.1098/rstb.2015.0316

    Article  Google Scholar 

  • Grünewald, C., Schleuning, M., & Böhning-Gaese, K. (2016). Biodiversity, scenery and infrastructure: Factors driving wildlife tourism in an African savannah national park. Biological Conservation, 201, 60–68. https://doi.org/10.1016/j.biocon.2016.05.036

    Article  Google Scholar 

  • GSS. (2014). 2010 Population and housing census: District analytical report - Tolon district (p. 85). Ghana Statistical Service (GSS).

  • Haag, M., & Tonn, W. M. (1998). Sampling, density estimation and spatial relationships. In S. J. Karcher (Ed.), Tested studies for laboratory teaching, Volume 19 (pp. 197–216). Proceedings of the 19th Workshop/Conference of the Association for Biology Laboratory Education (ABLE).

  • Hahn, K., & Leßmeister, A. (2021). Sustainable use of savanna vegetation in West Africa in the context of climate and land use change. In B. Blättel-Mink, T. Hickler, S. Küster, & H. Becker (Eds.), Nachhaltige Entwicklung in einer Gesellschaft des Umbruchs (pp. 45–64). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-31466-8_4

  • Hijbeek, R., Koedam, N., Khan, M. N. I., Kairo, J. G., Schoukens, J., & Dahdouh-Guebas, F. (2013). An evaluation of plotless sampling using vegetation simulations and field data from a mangrove forest. PLoS ONE, 8(6), e67201. https://doi.org/10.1371/journal.pone.0067201

    Article  CAS  Google Scholar 

  • Hubbell, S. P. (1979). Tree dispersion, abundance, and diversity in a tropical dry forest. Science, 203(4387), 1299–1309.

  • Jamali, H., Ghehsareh Ardestani, E., Ebrahimi, A., & Pordel, F. (2020). Comparing distance-based methods of measuring plant density in an arid sparse scrubland: Testing field and simulated sampling. Environmental Monitoring and Assessment, 192(6), 343. https://doi.org/10.1007/s10661-020-08329-8

    Article  Google Scholar 

  • Kelly, B. A., Bouvet, J.-M., & Picard, N. (2004). Size class distribution and spatial pattern of Vitellaria paradoxa in relation to farmers’ practices in Mali. Agroforestry Systems, 60(1), 3–11. https://doi.org/10.1023/B:AGFO.0000009400.24606.e3

    Article  Google Scholar 

  • Krebs, C. J. (2014). Ecological methodology (3rd ed.). University of British Columbia.

  • Ky-Dembele, C., Dayamba, S. D., Savadogo, P., Kalinganire, A., Bayala, J., Muchugi, A., & Ramni, A. (2019). Land use dictates diversity, density and regeneration of woody species in southwestern Mali, West Africa. Tropical Ecology, 60(1), 114–128. https://doi.org/10.1007/s42965-019-00015-2

    Article  Google Scholar 

  • Laycock, W. A., & Batcheler, C. L. (1975). Comparison of distance-measurement techniques for sampling tussock grassland species in New Zealand. Journal of Range Management, 28, 235–239.

    Article  Google Scholar 

  • Liu, Q., Wu, X., Chen, B., Ma, J., & Gao, J. (2014). Effects of low light on agronomic and physiological characteristics of rice including grain yield and quality. Rice Science, 21(5), 243–251. https://doi.org/10.1016/S1672-6308(13)60192-4

    Article  Google Scholar 

  • Lohbeck, M., Albers, P., Boels, L. E., Bongers, F., Morel, S., Sinclair, F., Takoutsing, B., Vågen, T. G., Winowiecki, L. A., & Smith-Dumont, E. (2020). Drivers of farmer-managed natural regeneration in the Sahel. Lessons for restoration. Scientific Reports. https://doi.org/10.1038/s41598-020-70746-z

    Article  Google Scholar 

  • Lovett, P., & Phillips, L. D. (2018). Agroforestry shea parklands of Sub-Saharan Africa: Threats and solutions (p. 52). International Bank for Reconstruction and Development / The World Bank. Retrieved May 03, 2022, from https://www.profor.info/sites/profor.info/files/Shea_Case%20Study_LEAVES_2018_0.pdf

  • M’Woueni, D., Gaoue, O. G., Balagueman, R. O., Biaou, H. S. S., & Natta, A. K. (2019). Road mediated spatio-temporal tree decline in traditional agroforests in an African biosphere reserve. Global Ecology and Conservation, 20, e00796. https://doi.org/10.1016/j.gecco.2019.e00796

    Article  Google Scholar 

  • Mason, W. L., Connolly, T., Pommerening, A., & Edwards, C. (2007). Spatial structure of semi-natural and plantation stands of Scots pine (Pinus sylvestris L.) in northern Scotland. Forestry: an International Journal of Forest Research, 80(5), 567–586. https://doi.org/10.1093/forestry/cpm038

    Article  Google Scholar 

  • Mbow, C., Brandt, M., Ouedraogo, I., de Leeuw, J., & Marshall, M. (2015). What four decades of earth observation tell us about land degradation in the Sahel? Remote Sensing, 7, 4048–4067. https://doi.org/10.3390/rs70404048

    Article  Google Scholar 

  • Mitchell, K. (2015). Quantitative analysis by the point-centered quarter method. ArXiv:1010.3303 [q-Bio.QM], 1–56. https://doi.org/10.48550/ARXIV.1010.3303

  • Nath, C. D., Pélissier, R., & Garcia, C. (2010). Comparative efficiency and accuracy of variable area transects versus square plots for sampling tree diversity and density. Agroforestry Systems, 79(2), 223–236. https://doi.org/10.1007/s10457-009-9255-5

    Article  Google Scholar 

  • O’Higgins, R. C. (2007). Savannah woodland degradation assessments in Ghana: Integrating ecological indicators with local perceptions. Earth and Environment, 3, 246–281.

    Google Scholar 

  • Parker, K. R. (1979). Density estimation by variable area transect. The Journal of Wildlife Management, 43(2), 484–492. https://doi.org/10.2307/3800359

    Article  Google Scholar 

  • Patil, S. A., Burnham, K. P., & Kovner, J. L. (1979). Nonparametric estimation of plant density by the distance method. Biometrics, 35(3), 597–604. https://doi.org/10.2307/2530250

    Article  Google Scholar 

  • Pollard, J. H. (1971). On distance estimators of density in randomly distributed forests. Biometrics, 27(4), 991–1002. https://doi.org/10.2307/2528833

    Article  Google Scholar 

  • Poudyal, M. (2011). Chiefs and trees: Tenures and incentives in the management and use of two multipurpose tree species in agroforestry parklands in Northern Ghana. Society & Natural Resources, 24(10), 1063–1077. https://doi.org/10.1080/08941920.2010.523059

    Article  Google Scholar 

  • Ripley, B. D. (1977). Modelling spatial patterns. Journal of the Royal Statistical Society: Series B (Methodological), 39(2), 172–192. https://doi.org/10.1111/j.2517-6161.1977.tb01615.x

    Article  Google Scholar 

  • Ryan, C. M., Pritchard, R., McNicol, I., Owen, M., Fisher, J. A., & Lehmann, C. (2016). Ecosystem services from southern African woodlands and their future under global change. Philosophical Transactions of the Royal Society of London. Series b, Biological Sciences, 371(1703), 20150312. https://doi.org/10.1098/rstb.2015.0312

    Article  Google Scholar 

  • Sanou, J., Bazié, H. R., & Bayala, J. (2019). Treating shea trees as crops improves women’s livelihoods in Burkina Faso. In E. Simelton & M. Ostwald (Eds.), Multifunctional land uses in Africa: Sustainable food security solutions (1st ed., pp. 47–60). Routledge.

  • Scholes, R., & Walker, B. (1993). An African savanna. Cambridge University Press.

    Book  Google Scholar 

  • Sood, K. K., & Mitchell, C. P. (2009). Identifying important biophysical and social determinants of on-farm tree growing in subsistence-based traditional agroforestry systems. Agroforestry Systems, 75(2), 175–187. https://doi.org/10.1007/s10457-008-9180-z

    Article  Google Scholar 

  • Steinke, I., & Hennenberg, K. J. (2006). On the power of plotless density estimators for statistical comparisons of plant populations. Canadian Journal of Botany, 84(3), 421–432. https://doi.org/10.1139/b05-135

    Article  Google Scholar 

  • Suttie, J., Reynolds, S., & Batello, C. (Eds.). (2005). Grasslands of the World. No. 34. Food and Agriculture Organization.

  • Warde, W., & Petranka, J. W. (1981). A Correction factor table for missing point-center quarter data. Ecology, 62(2), 491–494. https://doi.org/10.2307/1936723

    Article  Google Scholar 

  • White, N. A., Engeman, R. M., Sugihara, R. T., & Krupa, H. W. (2008). A comparison of plotless density estimators using Monte Carlo simulation on totally enumerated field data sets. BMC Ecology, 8(1), 6. https://doi.org/10.1186/1472-6785-8-6

    Article  Google Scholar 

  • Yang, Y., Xu, W., Hou, P., Liu, G., Liu, W., Wang, Y., Zhao, R., Ming, B., Xie, R., Wang, K., & Li, S. (2019). Improving maize grain yield by matching maize growth and solar radiation. Scientific Reports, 9(1), 3635. https://doi.org/10.1038/s41598-019-40081-z

    Article  CAS  Google Scholar 

  • Zurell, D., Berger, U., Cabral, J. S., Jeltsch, F., Meynard, C. N., Münkemüller, T., Nehrbass, N., Pagel, J., Reineking, B., Schröder, B., & Grimm, V. (2010). The virtual ecologist approach: Simulating data and observers. Oikos, 119(4), 622–635. https://doi.org/10.1111/j.1600-0706.2009.18284.x

    Article  Google Scholar 

Download references

Acknowledgements

The author is grateful to Esther Darkoh, Doris Lawer, and Kevin Lawer for joining EAL on the field to tag trees and shrubs.

Author information

Authors and Affiliations

  1. Department of Biodiversity Conservation and Management, University for Development Studies, P. O. Box TL1882, Tamale, Ghana

    Eric Adjei Lawer

Authors
  1. Eric Adjei Lawer
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

EAL: Conceptualization, Investigation, Formal analysis, Writing - Original draft preparation, Reviewing and Editing. All author(s) have read, understood, and have complied as applicable with the statement on “Ethical responsibilities of Authors” as found in the Instructions for Authors and are aware that with minor exceptions, no changes can be made to authorship once the paper is submitted.

Corresponding author

Correspondence to Eric Adjei Lawer.

Ethics declarations

Ethical approval

Not applicable.

Conflict of interest

The author declares no competing interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 3100 kb)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lawer, E.A. Comparative analysis of plotless sampling methods for estimating woody plant density in a West African savanna agroforestry parkland. Environ Monit Assess 195, 263 (2023). https://doi.org/10.1007/s10661-022-10896-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-022-10896-x

Keywords

Search

Navigation