Mar Biol (2007) 151:2025–2035 DOI 10.1007/s00227-006-0559-y R E SEARCH ART I CLE Patterns of spatial variability of seagrass epiphytes in the north-west Mediterranean Sea David Balata · Ugo Nesti · Luigi Piazzi · Francesco Cinelli Received: 9 June 2006 / Accepted: 11 November 2006 / Published online: 16 February 2007  Springer-Verlag 2007 Abstract This study aimed to gain insight on patterns of spatial variability of seagrass epiphytes of both leaves and of rhizomes in three diVerent habitats, continental coasts, oVshore banks and islands. Moreover, we tried to discriminate between habitat-dependant variability and scale-dependant variability of Posidonia oceanica epiphytic assemblages. Results showed the absence of signiWcant diVerences in the structure of assemblages of epiphytes both on leaves and on rhizomes among continental coasts, oVshore banks and islands, even if the patterns of spatial variability changed among habitats. In fact, although a high variability at small scales appeared a constant pattern in epiphytic assemblages, large-scale variability resulted higher in continental coasts and oVshore banks than in islands. In conclusion, epiphytic assemblages of Posidonia oceanica appear homogeneous among habitats, showing a similar structure and species composition in the same geographic area. On the contrary, diVerences between meadows appeared linked to local diVerences in environmental factors that are more evident in habitats inXuenced by human disturbance. Communicated by R. Cattaneo-Vietti, Genova. D. Balata (&) University of Pisa, Pisa, Italy e-mail: balata@discat.unipi.it U. Nesti I.C.R.A.M., Via di Casalotti 300, Rome 00166, Italy L. Piazzi · F. Cinelli Dipartimento di Biologia, Università di Pisa, Via Volta 6, Pisa 57126, Italy Introduction Seagrass meadows play a signiWcant role in temperate and tropical coastal marine systems, mostly in the structuring of habitats through the production of organic matter and oxygen (Walker and McComb 1988; Pergent et al. 1994; Cambridge and Hocking 1997). Seagrass systems are characterised by high biodiversity to which epiphytes assemblages give a fundamental contribution (MoncreiV et al. 1992; Nelson and Waaland 1997; Klumpp et al. 1992). Leaves and rhizomes of seagrasses oVer substrata suitable for settlement and growth of a number of sessile organisms that form stratiWed assemblages characterised by high diversity of species (Mazzella et al. 1989). Seagrass rhizomes are long-living structures, whereas leaves represent a relatively exposed and unstable substrate controlled by the life cycle of the plant. Leaves also reduce light and water movement, creating sheltered conditions for rhizomes. Thus epiphytes of leaves consist of photophilous and ephemeral species while epiphyte assemblages on rhizomes are characterized mainly by sciaphilous and long-living organisms (Boudouresque 1974; Borowitzka and Lethbridge 1989; Mazzella et al. 1992). While leaf epiphytes have been widely investigated (Panayotidis 1980; Heijs 1984, 1985b; Reyes et al. 1998; Trautman and Borowitzka 1999), little attention has been devoted to rhizome assemblages of seagrass (Pansini and Pronzato 1985; Kendrick et al. 1988) as they present a relative homogeneity in comparison to other coastal assemblages (Boudouresque 1974). However, recent studies have evidenced several peculiar aspects in the structure of assemblages of seagrass, including the sensitivity to the spread of invasive species (Piazzi and Cinelli 2001; 2003; Piazzi et al. 2002). 123 2026 123 assemblages in three habitats (little islands, oVshore banks, and continental coasts) and to evaluate patterns of spatial variability in each habitat at three diVerent spatial scales ranging from few metres to tens of km. The data collected were analysed by a combination of univariate and multivariate statistical techniques. Materials and methods Sampling design and data collection The epiphytic assemblages on leaves and on rhizomes of Posidonia oceanica were studied in three diVerent habitats in the north-west Mediterranean Sea: continental coasts, small islands and rocky oVshore banks. Samplings were carried out at a depth of 10 m, between 20 August and 5 September, which corresponds to the period in which epiphytes assemblages of P. oceanica reach their maximum development (Panayotidis 1980). Two P. oceanica meadows set several kilometres apart were studied for each habitat: Livorno and Baratti for the continental coast, Secche della Meloria and Secche di Vada for the oVshore banks (about 10 km far from the coast) and Isola di Gorgona and Isola di Pianosa for the islands (Fig. 1). In each meadow, two sites (about 600 m2 wide and 100 m apart) were chosen randomly; for each site, three replicate plots (1 m2 wide and about 25 km Tuscany ITALY 43’ 30° The sensitivity of seagrass epiphytes to changes in environmental conditions makes them a useful system to detect human-induced disturbances (May 1982; Borum 1985; Frankovich and Fourqureau 1997; Piazzi et al. 2004a). In order to identify these forms of impact, it is essential to Wnd patterns that can discriminate between natural and anthropogenic disturbance, in consideration of the fact that natural populations show a large temporal and spatial variability (Benedetti-Cecchi 2001b; Hewitt et al. 2001; Fraschetti et al. 2005). Moreover, because variability of natural assemblages is not scale independent (Underwood and Chapman 1996; Benedetti-Cecchi 2001a, b), one of the main goals of ecology is to identify those scales in space and time at which variability is large, and the processes generating these patterns (Benedetti-Cecchi 2001a). Although patterns of spatial and temporal variability in assemblages of leaf epiphytes have been investigated for several species of seagrasses (Heijs 1985a; Mazzella et al. 1989; Borowitzka et al. 1990; Vanderklift and Lavery 2000; Lavery and Vanderklift 2002; Saunders et al. 2003), some aspects still remain unclear. Some important issues concern understanding patterns of large-scale variability and in particular the discrimination between scaledependent patterns and those due to diVerences among the habitats in which seagrasses grow. In fact, seagrass meadows can develop in several coastal habitats including continental coasts, islands, and oVshore banks. Small islands show peculiar characteristics in terms of isolation, diVerences in some abiotic factors, such as water transparency and sedimentation rates, and relatively lower exposure to human activities (Whittaker 1998; Benedetti-Cecchi et al. 2001). Also oVshore banks present peculiar hydrodynamic conditions and interactions with pelagic systems that can determine assemblages diVerent from those of islands and continental coasts (Kendrick and Burt 1997; Piazzi et al. 2004b). Yet, the importance of these aspects for marine assemblages have been investigated formally only by few studies, and with contrasting results: algal and invertebrate assemblages on islands diVered from those on the mainland in shallow rocky habitats (Benedetti-Cecchi et al. 2003), while no signiWcant diVerences were detected for deeper rocky habitats (Piazzi et al. 2004b). Moreover, these issues have never been investigated on leaf epiphytes. The aims of the present study were to discriminate between habitat-dependent variability and scaledependent variability both for epiphyte assemblages of leaves and rhizomes of the Mediterranean seagrasses Posidonia oceanica (L.) Delile. To achieve these objectives, a hierarchical sampling design was used to compare the structure and composition of epiphytic Mar Biol (2007) 151:2025–2035 Corsica 45’ 10° Fig. 1. Map of the study area, showing the meadows of sampling: Wlled triangle Livorno, Wlled circle Baratti, shaded triangle Secche della Meloria, shaded circle Secche di Vada, open triangle Isola di Gorgona, open circle Isola di Pianosa Mar Biol (2007) 151:2025–2035 Table 1 List of taxa identiWed in the epiphytic assemblages of leaves and rhizomes 2027 Taxa Leaves Rhizomes Chlorophyta Caulerpa racemosa (Forsskål) C. Agardh var. cylindracea (Sonder) Verlaque, Huisman et Boudouresque Chaetomorpha linum (O. F. Müller) Kützing Cladophora prolifera (Roth) Kützing Derbesia tenuissima (Moris et De Notaris) P.L. et H.M. Crouan Flabellia petiolata (Turra) Nizamuddin Pseudochlorodesmis furcellata (Zanardini) Børgesen Siphonocladus pusillus (C. Agardh ex Kützing) Hauck ¡ + + + ¡ ¡ + + ¡ ¡ + + + ¡ Phaeophyta Asperococcus sp. Cladosiphon cylindricus (Sauvageau) Kylin Cladosiphon irregularis (Sauvageau) Kylin Dictyota dichotoma (Hudson) J. V. Lamouroux Dictyota fasciola (Roth) J. V. Lamouroux Dictyota linearis (C. Agardh) Greville Ectocarpus siliculosus (Dillwyn) Lyngbye Elachista intermedia P. L. et H. M. Crouan Giraudia sphacelarioides Derbés et Solier Padina pavonica (Linnaeus) Thivy Sphacelaria cirrosa (Roth) C. Agardh + + + + + + + + + ¡ ¡ + + + + + + ¡ ¡ ¡ + + Rhodophyta Acrothamnion preissii (Sonder) Wollaston Amphiroa rigida J.V. Lamouroux Anthithamnion cruciatum (C. Agardh) Nägeli Apoglossum ruscifolium (Turner) J. Agardh Botryocladia boergesenii J. Feldmann Botryocladia botryoides (Wulfen) J. Feldmann Ceramium codii (Richards) G. Feldmann Ceramium diaphanum (Lighfoot) Roth Chondria mairei G. Feldmann Contarinia peyssonelliaeformis Zanardini Dipterosiphonia dendritica (C. Agardh) F. Schmitz Dipterosiphonia rigens (Schousboe) Falkenberg Feldmannophycus rayssiae (Feldmann et Feldmann-Mazoyer) Augier et Boudouresque Haliptilon virgatum (Zanardini) Garbary et H. W. Johansen Heterosiphonia crispella (C. Agardh) Wynne Hydrolithon cruciatum (Bressan) Chamberlain Hydrolithon farinosum (Lamouroux) Penrose et Chamberlain Hypoglossum hypoglossoides (Stackhouse) Collins et Harvey Jania rubens J. V. Lamouroux Laurencia spp. Lithophyllum cystoseirae (Hauck) Heydrich Mesophyllum lichenoides (J. Ellis) M. Lemoine Monosporus pedicellatus (Smith) Solier Nitophyllum punctatum (Stackhouse) Greville Peyssonnelia bornetii Boudouresque et Denizot Plocamium cartilagineum (Linnaeus) Dixon Pneophyllum coronatum (RosanoV) Penrose Pneophyllum fragile Kützing Polysiphonia spp. Rhodymenia sp. Womersleyella setacea (Hollenberg) R. E. Norris Wrangelia penicillata (C. Agardh) C. Agardh + + + + + ¡ + + ¡ ¡ ¡ ¡ ¡ + + ¡ + + + ¡ ¡ + + + + + ¡ + + + + + + ¡ ¡ + + ¡ ¡ + + + ¡ + + + ¡ + ¡ + + + + + + + + + + + + + + ¡ Rhizopoda Cyclocibicides vermiculatus d’Orbigny Elphidium crispum Linnaeus Lobatula lobatula Walker et Jacob Miniacina miniacea Linnaeus Planorbulina mediterranensis Walker et Jacob Rosalina brady Cushman + + + ¡ + + + + + + + ¡ 123 2028 Table 1 continued Mar Biol (2007) 151:2025–2035 Taxa Leaves Rhizomes Porifera Clathrina contorta Bow Cliona viridis Schmidt Dysidea avara Schmidt Oscarella lobularis Schmidt Plakortis simplex Schulze Sycon raphanus Schmidt Tethya citrina Sarà et Melone ¡ ¡ ¡ ¡ + ¡ ¡ + + + + + + + Cnidaria Laomedea angulata Hinks Dynamena cavolini Neppi Obelia geniculata Linnaeus Orthopyxis asymmetrica Stechow Plumularia obliqua Thompson Podocoryna carnea M. Sars Sertularia perpusilla Stechow ¡ + + + + ¡ + + ¡ + + + + + Anellida Janua pagenstecheri Quatrefageau Pomatoceros triqueter Linnaeus + ¡ + + Bryozoa Aetea truncata Landsborough Beania hirtissima Heller Beania magellanica Bush Caberea boryi Audouin Callapora lineata Linnaeus Carbasea papyrea Pallas Cellepora pumicosa Hincks Cellaria salicornoides Lamouroux Chilidonia pyriformis Bertolini Chorizopora brogliarti Audouin Collarina balzaci Audouin et Savigny Colletosia radiata Moll Cryptosula pallasiana Moll Diastopora patina Lamarck Electrae posidonia Gautier Escharoides coccinea Abildgaard Fenestrulina malusii Audouin Idmonea serpens Bidenkap Lichenopora radiata Audouin et Savigny Margaretta cereoides Ellis et Solander Microporella ciliata Pallas Pherusella tubulosa Ellis et Solander Reteporella sp. Schizobrachiella sanguinea Norman Scrupocellaria reptans Linneaus Tubulipora Xabellaris Fabricius + ¡ ¡ ¡ + ¡ ¡ ¡ ¡ + + + ¡ ¡ + ¡ + + + ¡ ¡ + ¡ ¡ + + + + + + + + + + + + + + + + + + + + + + + + + + + + Tunicata Botryllus schlosseri Pallas Didemnum fulgens Milne-Edwards Diplosoma listerianum Milne-Edwards Sidnyum turbinatum Savigny Tridemnum cereum Giard + ¡ ¡ ¡ + + + + + + 10 m apart) were distributed randomly. Within each plot, Wve shoots were sampled and preserved in 4% formalin seawater for laboratory observation. All the sites studied were characterized by a homogenous structure of the meadow with 100% of substrate cover. In each site density was measured in Wve replicated surface of 0.25 m2 and expressed as number of shoots/m2. 123 The oldest part (the Wrst 10 cm from the tip) of the internal face of the two external leaves per shoot and the Wrst 10 cm of rhizome were observed under a dissecting microscope. Data from the two leaves within each shoot were averaged. Animal and macroalgal organisms were identiWed at level of species or genera and the abundance of each taxon was expressed as percentage cover. Mar Biol (2007) 151:2025–2035 2029 Shoots m-2 800 600 400 200 0 L B M V G P Fig. 2. Density of shoots of Posidonia oceanica (mean + SE, n = 10) in the studied meadows. L Livorno, B Baratti, M Secche della Meloria, V Secche di Vada, G Isola di Gorgona, P Isola di Pianosa Percentage cover was calculated as the surface covered by the species in orthogonal projection and referred to the total surface of leaves or rhizomes. Total percent cover was calculated for each sample by summing the percent cover of all the species of the sample. Analysis of data Multivariate analysis of variance based on permutations (PERMANOVA) was used to test the hypothesis that epiphytes showed diVerent patterns of variation in composition and in abundance of species in relation to habitat and spatial scales (Anderson 2001a). Bray– Curtis dissimilarity was calculated using untransformed data. The permutable units and the mean square (MS) used as denominator for each source of variability are reported in Tables 1 and 2. For both rhizome and leaf epiphytes, the analysis consisted in a four-way model with Habitat (three levels, Wxed), Meadow (two levels, random) nested in Habitat, Site (two levels, random) nested in Meadow and Plot (three levels, random) nested in Site. Five replicates were considered for each plot. Monte Carlo procedures were used to calculate probability when possible permutations were not enough to get a reasonable test (Anderson 2001b). Components of variance were calculated for all the spatial scales, separately for each habitat. A two-dimensional metric MDS (multidimensional scaling), based on the centroids for replicate meadows, was used for a graphical representation of the data both for leaf and for rhizome epiphytic assemblages. Distances among centroids were obtained using principal coordinate axes from the original Bray–Curtis matrix. The program IndVal (indicator value) was used to identify the species that contributed most to the multivariate pattern (Dufrene and Legendre 1997). This method combines the species’ relative abundance and frequency of occurrence in the various groups of samples to recognize “indicator species”. The indicator species are deWned as the most characteristic species of each group, found mostly in a single group and present in the majority of the samples belonging to that group. In the present study IndVal analysis was used to determine which species are responsible for the diVerences among the studied meadows. A hierarchical four-way ANOVA was used to analyse spatial variability of number of species and total percentage cover of the leaf and rhizome assemblages, using the same model of multivariate analysis. Cochran’s C test was utilised before each analyses to check for homogeneity of variance and data were transformed when necessary (Underwood 1997). Student– Newman–Keuls (SNK) test was used for a posteriori multiple comparisons of means. Results Shoot density in the meadows studied ranged from 573 § 27.9 to 645 § 22.7 (Fig. 2); values that can be considered high in relation to the sampling depth (Pergent et al. 1995). Table 2 PERMANOVA on the structure of the epiphytic assemblages of leaves and of rhizomes Source Epiphytic assemblages of leaves df MS Habitat = Ha Meadow (Ha) = Me(Ha) Site (Me(Ha)) = Si(Me(Ha)) Plot (Si(Me(Ha))) = Pl(Si(Me(Ha))) Residual Total Pseudo F P P(MC) Epiphytic assemblages of rhizomes Denominator for F MS Pseudo P P (MC) F Number of permutable units 2 66453.63 0.79 3 84027.47 36.50 0.574 0.605 0.002 0.001 23443.40 0.70 33658.71 5.19 0.607 0.806 0.001 0.001 Me (Ha) Si (Me(Ha)) 6 12 6 2302.18 1.79 0.046 0.032 6480.13 1.01 0.439 0.447 Pl (Si(Me(Ha)) 36 24 1283.57 1.74 0.001 0.001 6395.89 4.00 0.001 0.001 Residual 144 179 736.48 180 1597.37 SigniWcant eVects are indicated in bold 123 2030 A B Mar Biol (2007) 151:2025–2035 Stress: 0.00 Stress: 0.00 Fig. 3. Metric MDS showing the dissimilarities among centroids based on the factor Meadow of epiphytic assemblages of leaves a and rhizomes b. Wlled triangle Livorno, Wlled circle Baratti, shaded triangle Secche della Meloria, shaded circle Secche di Vada, open triangle Isola di Gorgona, open circle Isola di Pianosa In epiphyte assemblages, 50 taxa of macroalgae (7 Chlorophyta, 11 Phaeophyta, 32 Rhodophyta), 47 taxa of animals (7 Porifera, 7 Cnidaria, 26 Bryozoa, 2 Annelida, 5 Tunicata) and 6 Sarcomastogophora (Foramiferida) were identiWed (Table 1 with nomenclature authority). Leaf assemblages were dominated by encrusting algae belonging to genus Pneophyllum and Hydrolithon; common algal species were also the Wlamentous 123 Heterosiphonia crispella and several species in the genus Ceramium, the foliose Dictyota linearis and various corticated terete in the genus Laurencia. Among animals, the Bryozoa Electra posidoniae and Aetea truncata and the Cnidaria Obelia geniculata and Plumularia obliqua were widely distributed. Foraminiferida showed low cover in all samples. Rhizome assemblages were mostly characterised by the Wlamentous Rhodophyta Acrothamnion preissii and Womersleyella setacea; other common species were the Cnidaria Laomedea angulata, the Bryozoa Aetea truncata, Beania hirtissima cylindrica, Collarina balzaci, Fenestrulina malusii and Margaretta cereoides, the Porifera Plakortis simplex and the Tunicata Diplosoma listerianum. The Foraminiferida Miniacinia miniacea was locally abundant. PERMANOVA analysis showed no signiWcant diVerences among habitats both for leaf and rhizome assemblages (Table 2). Leaf assemblages were signiWcantly variable at all spatial scales examined, while rhizome assemblages varied among meadows and plots (Table 2). Metric MDS ordination of leaf epiphytic assemblages showed the three separate groups constituting the Livorno meadow, the Secche di Vada meadow and the others meadows (Fig. 3a). The IndVal analysis showed that leaf assemblages of Livorno meadow were mostly characterized by the Wlamentous Rhodophyta Womersleyella setacea, by the encrusting Bryozoan Electrae posidoniae and by the Foramiferida Rosalina brady; while the assemblages of Secche di Vada meadow showed low cover of Pneophyllum spp. and high abundance of the Hydrozoans Plumularia obliqua and Obelia geniculata, the Wlamentous algae Heterosiphonia crispella and Cladosiphon irregularis, the Tunicata Trididemnum cereum (Table 3). Metric MDS ordination of rhizome epiphytic assemblages showed a clear separation between the meadows of Livorno, Secche della Meloria, and all others (Fig. 3b). The IndVal analysis showed that the Wlamentous algae Sphacelaria cirrosa and Pseudochlorodesmis furcellata and the Bryozoan Schizobrachiella sanguinea characterized the rhizome assemblages of Livorno meadow, while the algae Dictyota dichotoma, D. linearis and Botryocladia boergesenii, the Bryozoan Margaretta cereoides and the Tunicata Didemnum fulgens and T. cereum contributed to separate the assemblages of Secche della Meloria meadows from the others (Table 4). In continental coast and bank habitats, the analysis of components of variance showed that the largest variability of leaf assemblages was between meadows, and that variability among shoots was larger than that mea- Mar Biol (2007) 151:2025–2035 Table 3 Results of the indicator species analysis (IndVal), of epyphytic assemblages of leaves 2031 Meadows Species L B V Numbers indicate cases (numbers of sample out of 30) where each taxon is signiWcantly diVerent in abundance a or presence p among the studied meadows. L Livorno, B Baratti, V Secche di Vada, M Secche della Meloria, G Isola di Gorgona, P Isola di Pianosa M P G IndVal Level Meadows Pneuphyllum spp. Womersleyella setacea Electrae posidoniae Rosalina brady Laurencia spp. Hypoglossum hypoglossoides Collapora lineata Ectocarpus silicosus Plumularia obliqua Heterosiphonia crispella Tridemnum cereum Obelia geniculata Cladosiphon irregularis Dictyota linearis Wrangelia penicillata Sphacelaria cirrosa Tubulipora Xabellaris 84.40 51.98 49.83 21.86 64.01 30.87 1 1 1 1 1 1 13.64 11.45 100 79.61 48.3 46.77 33.83 60.35 53.16 71.97 42.35 Polysiphonia spp. 32.64 Ceramium codii 24 Ceramium diaphanum 19.1 Elachista intermedia 64.05 Elphidium crispum 18.75 Chorizopora brogniarti 9.58 3 15 1 1 1 1 1 1 1 1 1 1 1 2 1 1 20 sured at the intermediate scales examined (Fig. 4). In the island habitat, the largest variability was detected among shoots, even if variability between meadows and plots was also evident (Fig. 4). Variability of rhizome assemblages was large at the scales of plot and shoot in all habitats, while variability between meadows was large in continental coast and bank habitats but not in the islands (Fig. 4). The number of species did not diVer among habitats both on leaves and rhizomes, while large variability was detected at the scales of site and plot (Table 5). Total percentage cover of organisms on leaves diVered signiWcantly among habitats (SNK test: island > coast = bank), while signiWcant diVerences in this variance were detected between meadows in rhizomes and among plots in both systems (Table 5). Discussion and conclusions The present study documented the absence of signiWcant diVerences in the structure of assemblages of Posidonia oceanica epiphytes both on leaves and on rhizomes among the habitats studied. However, it also evidenced clear diVerences through patterns of spatial variability within the habitats: although a large variability at small scales appeared a constant pattern in epiphytic assemblages, large-scale variability resulted L a/p B a/p V a/p M a/p G a/p P a/p 104./30 3./17 32./25 1./9 0./0 0./0 114./30 0./0 0./0 0./1 9./24 1./18 0./3 0./0 0./4 0./0 1./9 1./15 87./30 0./0 21./26 0./0 1./7 0./0 111./30 0./3 0./10 0./3 0./0 0./4 141./29 0./0 0./4 0./1 0./0 0./2 0./0 0./0 0./0 0./1 0./0 0./0 0./0 4./11 1./3 0./0 0./0 0./1 0./0 0./3 0./0 0./0 0./0 0./5 1./8 0./0 0./1 0./0 1./9 1./3 4./10 0./0 1./27 5./28 0./0 0./0 0./0 1./13 1./8 0./2 0./1 0./1 106/30 24./30 1./16 4./20 1./14 0./2 0./16 0./0 0./1 0./0 0./0 0./0 8./23 0./1 0./0 0./0 0./0 0./0 2./14 0./1 0./0 0./0 33./23 1./28 0./0 0./0 0./0 0./0 0./0 0./0 0 0./0 0./0 0./0 0./0 1./5 0./0 0./0 0./0 0./3 0./0 9./27 7./24 1./11 0./9 1./7 19./27 1./3 0./2 0./0 1./2 0./0 3./13 0./1 1./8 0./0 0./2 0./0 1./19 1./7 0./0 0./4 0./1 54./29 2./9 1./4 higher in continental coast and bank habitats than in islands. Large variability at small spatial scale has been reported for seagrass leaf epiphytes (Piazzi et al. 2004b; Vanderklift and Lavery 2000) while no data are available for spatial variability assemblages on rhizomes. In the present study, assemblages on rhizomes showed patterns of spatial variability similar to those of leaf epiphytes. A possible explanation could be that, even if the two assemblages diVer in terms of abiotic conditions, structure and species composition, the mechanisms responsible for patterns of settlement and colonization of their constituting organisms are analogous and likely related to structural features of the meadow. Colonization of epiphytes on leaves depends on a combination of stochastic events and factors acting locally in the Meadow, such as diVerences in shoot density, local hydrodynamics, dispersal of propagules, grazing and competition among sessile organisms (Trautman and Borowitzka 1999; Vanderklift and Lavery 2000). Moreover, the biomass and species composition of epiphytic macroalgal assemblages on seagrasses is known to diVer in relation to distance from reefs (Van Elven et al. 2004). Therefore, the presence of rocky substrata within the meadow could be relevant for small-scale patterns of distribution of epiphytic assemblages in the system studied. Even if rhizomes could be considered a steadier system rela- 123 2032 Mar Biol (2007) 151:2025–2035 Table 4 Results of the indicator species analysis (IndVal), of epyphytic assemblages of rhizomes Meadows L B V M G P Species Sphacelaria cirrosa Pseudochlorodesmis furcellata Schizobrachiella sanguinea Rhodymenia sp. Plakortis simplex Pherusella tubulosa Fenestrulina malusii Janua pagenstecheri Cellepora pumicosa Laomedea angulata Sidnyum turbinatum Colletosia radiata Callapora lineata Dictyota dichotoma Didemnum fulgens Margaretta cereoides Dictyota linearis Botryocladia boergesenii Tridemnum cereum Cliona viridis Podocoryna carnea Pneophyllum spp. Hypoglossum hypoglossoides Orthopyxis asymmetrica Tubulipora Xabellaris Hydrolithon farinosum Miniacina miniacea Idmonea serpens Peyssonnelia bornetii Oscarella lobularis IndVal 35.26 19.92 14.83 13.77 33.47 24.61 56.61 51.44 41.94 36.1 34.07 27 19.68 68.47 45.07 42.31 19.23 13.33 11.01 26.67 26.67 23.02 19.91 18.92 16.35 37.34 36.29 33.71 20.68 12.63 Level 1 1 4 1 1 1 1 1 1 1 1 1 4 1 1 1 1 4 15 1 1 2 1 1 2 1 1 1 1 4 Meadows L a/p B a/p V a/p M a/p G a/p P a/p 2./12 1./8 6./7 1./6 0./3 0./0 0./0 0./0 0./0 0./0 1./9 0./0 0./3 3./13 0./3 0./3 2./7 0./0 0./0 0./0 0./0 1./3 0./3 1./7 0./0 0./0 0./0 0./0 1./5 0./1 0./0 0./1 1./2 0./0 18./19 5./13 4./19 0./5 1./4 10./25 2./4 0./1 2./12 8./19 0./1 0./1 0./0 0./0 2./2 0./0 0./0 0./1 0./0 1./2 0./1 1./1 0./1 4./13 0./0 0./0 0./1 0./1 2./6 0./0 7./6 1./4 15./30 2./19 8./15 14./23 7./18 2./13 3./12 0./1 1./1 2./4 0./0 0./0 2./4 0./0 0./0 1./1 0./0 1./4 0./0 25./20 6./13 0./1 0./0 0./0 0./0 0./0 0./1 0./2 1./2 0./0 1./2 0./1 0./0 1./6 2./12 1./6 0./1 43./26 35./14 12./17 4./8 1./4 4./6 0./0 0./0 1./1 0./0 0./2 0./0 11./10 0./0 0./0 0./0 0./0 0./0 0./0 0./0 0./0 6./4 2./7 3./9 0./3 0./0 0./0 0./2 0./0 0./0 0./0 0./0 1./0 0./0 0./0 0./0 8./8 4./8 10./11 3./7 3./11 3./7 6./10 15./22 3./11 0./0 4./2 0./1 0./0 0./0 0./0 2./2 1./5 0./0 0./0 0./0 0./0 1./9 0./0 0./3 3./13 0./3 0./3 2./7 0./0 0./0 0./0 0./0 3./4 0./1 0./0 1./6 55./20 14./27 5./22 9./7 15./5 Numbers indicate cases (numbers of samples out of 30) where each taxon is signiWcantly diVerent in abundance a or presence p among the studied meadows. L Livorno, B Baratti, V Secche di Vada, M Secche della Meloria, G Isola di Gorgona, P Isola di Pianosa tively to leaves, as they are not subjected to substrate renewal, patterns of variability of their epiphytes could be driven by the same factors. The large variability at small spatial scales (from centimetres to few meters) detected in leaf and rhizome assemblages suggests that P. oceanica meadows, despite their apparent homogeneity, are systems characterized by a patchy distribution of epiphytic organisms. On the contrary, these assemblages are more homogenous at large scale (kilometres), particularly for islands. Continental shores can be considered systems that are more subjected than islands to environmental modiWcations related to natural events (soil erosion, sedimentation, river Xow) and anthropogenic activities (pollution, urbanization), factors that can drastically aVect the local structure of assemblages (Benedetti-Cecchi et al. 2001). Similar patterns observed between banks and continental coast could be explained considering that the two meadows of the bank habitat considered in the present study are located at smaller distances from mainland than those 123 of the islands. Thus they could be inXuenced by the same factors acting on the coastal meadows. DiVerences between meadows within coastal and bank habitats could be related to local diVerences in environmental conditions; in fact, the Livorno meadow is located near a highly urbanized area, while Secche di Vada and Secche della Meloria meadows are moderately aVected by potential sources of disturbance. However, epiphytes assemblages of leaves and rhizomes showed diVerent patterns in relation to the two meadows within bank habitat. Secche di Vada were diVerent from the other locations in relation to leaf assemblages because of the low cover of encrusting organisms and the abundance of Hydroids. On the contrary, Secche della Meloria were diVerent from the other locations in relation to rhizome assemblages, mostly in relation to the abundance of Tunicata and algae belonging to Dictyotales. This Wnding, that can be probably related to the diVerent kinds of disturbances that characterized the two banks (Piazzi et al. 2004a), suggests that leaf and rhizome epiphytic assem- Mar Biol (2007) 151:2025–2035 2033 Fig. 4. Percentage variance components of leaf and rhizomes epiphytic assemblages in the three studied habitats Leaves Rhizomes 60 100 75 Coasts 40 50 20 25 0 0 Site Plot Shoot Meadow Site Plot Shoot Meadow Site Plot Shoot Meadow Site Plot Shoot 60 100 75 Banks 40 50 20 25 0 0 Meadow Site Plot Shoot 100 60 75 40 Islands P e r c a n t a g e v a r ia nc e c o m p o n e nt s Meadow 50 20 25 0 0 Meadow Site Plot Shoot Table 5 Results of four-way ANOVA on number of species and on total percentage cover of epiphytic assemblages of leaves and of rhizomes Source df Epiphytic assemblages of leaves Epiphytic assemblages of rhizomes Number of species Number of species MS Habitat = Ha 2 13.12 Meadow (Ha) = 3 222.57 Me(Ha) Site (Me(Ha)) = 6 49.86 Si(Me(Ha)) Plot (Si(Me(Ha))) = 24 5.94 Pl(Si(Me(Ha))) Residual = res 144 3.37 Total 179 Cochran’s C test 0.0849 Transformation None SNK test for factor habitat Mean (§SE) F P Percentage Cover F P MS F 0.060 NS 30.93 4.460 NS 1.05 29.400 0.080 * NS 51.45 105.69 0.490 NS 296.13 1.110 NS 623.51 0.470 NS 5.600 * 8.390 *** 12.81 1.570 NS 95.38 4.560 ** 111.26 1.030 NS 1.760 ** 2.120 ** 20.91 2.080 ** 107.58 4.630 *** MS 8.17 3.86 NS 10.04 0.0125 NS None Islands > coasts = banks 0.0976 NS None P Percentage Cover MS F P 23.26 0.1155 NS None 6.47 (§0.31) > 5.14 (§0.33) = 5.33 (§0.18) * P < 0.05; ** P < 0.01; *** P < 0.001, NS not signiWgant blages can respond diVerently to the same disturbance and thus should be both included in monitoring programs. Moreover, in relation to their life cycle, epiphyte assemblages of rhizomes can integrate information at much longer time scales than those observable by leaf assemblages. According to our results, epiphytic assemblages of P. oceanica appeared homogeneous within the same geographic area, independently from the habitat in which they develop; this Wnding suggests that epyph- ites assemblages of meadows colonizing either islands, banks or continental coasts can be compared in monitoring and impact assessment programs. 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