Estuarine, Coastal and Shelf Science 68 (2006) 579e592www.elsevier.com/locate/ecss

Multi-scale spatial variability in fish assemblages associatedwith Posidonia oceanica meadows in the Western Mediterranean Sea

Joan Moranta a,*, Miquel Palmer b, Gabriel Morey b,c, Ana Ruiz b, Beatriz Morales-Nin b

a IEO - Centre Oceanografic de les Balears, P.O. Box 291, 07080 Palma de Mallorca, Illes Balears, Spainb IMEDEA (CSIC - UIB), Institut Mediterrani d’Estudis Avancats, Miquel Marques 21, 07190 Esporles, Illes Balears, Spain

c Direccio General de Pesca, Foners 10, 07006 Palma de Mallorca, Illes Balears, Spain

Received 5 July 2005; accepted 9 March 2006

Available online 24 May 2006

Abstract

Fish assemblages associated with Posidonia oceanica from three locations of the western Mediterranean (Mallorca, Formentera and Alacant,Spain) were sampled in order to assess their spatial variability at three different scales ranging from <1 km to >100 km. Sampling was carriedout using a beam trawl. Simultaneous sampling at these three spatial scales with the appropriate number of replicates implies a huge effort whichis rarely possible to achieve. Consequently, we propose an arrangement of data coming from different sampling programs, after testing and mak-ing sure the specificities of each program cannot be confounded with the spatial variability. The two preliminary experimental designs adopted inorder to combine the datasets were: (1) differences between two consecutive years were tested by sampling the same meadow (Formentera) inJune 2001 and June 2002; and (2) differences attributable to the meadow structure were evaluated by sampling two meadows (Mallorca 2000 andFormentera 2001). The absence of any significant correlation pattern for univariate community descriptors and multivariate species-specific den-sities (i.e. individuals per hour) related to both between-year and within-location structural differences of the meadows, allow us to combine datafrom the three locations (Formentera 2001, Mallorca 2000 and Alacant 2000) in a single analysis aimed at determining how much variability isexplained by the three spatial scales considered. The between-location scale (>100 km) is the most variable scale for species-specific densities(multivariate approach). Spatial variability at the smallest scale (<1 km) is also considerable, but the variability corresponding to the interme-diate scale (<10 km) was found to be non-significant. This is an expected result for fishes given that the spatial scale of individual transects is notlarge compared to the high mobility of many of the species considered. The differences observed between the locations placed 100 km apart aredue to changes in the relative density of species rather than differences in species composition. Between-location variability in the univaritecommunity descriptors was not significant. However, within-location (intermediate scale) differences were significant for density but not forbiomass. This is related to the large number of small individuals found in one Formentera site. These results are consistent with the hypothesisthat P. oceanica meadows from different locations in the western Mediterranean might display a similar carrying capacity although large-scalehydrodynamic conditions and meadow structure at the between-location level might lead to differently shaped fish communities (for example,the larger meadow complexity in Formentera might favour smaller sizes, since small species and/or individuals are known to find more shelterand food there), while differences at an intermediate spatial scale remain irrelevant.� 2006 Elsevier Ltd. All rights reserved.

Keywords: fish; littoral zone; community composition; spatial variations; seagrass meadow; Posidonia oceanica; western mediterranean

1. Introduction

The Posidonia oceanica beds are among the most importantMediterranean ecosystems, and their conservation is a high

* Corresponding author.

E-mail address: joan.moranta@ba.ieo.es (J. Moranta).

0272-7714/$ - see front matter � 2006 Elsevier Ltd. All rights reserved.

doi:10.1016/j.ecss.2006.03.008

national and international priority. Posidonia oceanica bedshave a multifunctional role within coastal systems that is com-parable to that of other seagrasses in temperate and tropicalareas. They offer substrate for settlement, food availabilityand shelter, recruitment and nursery areas, as well as participat-ing in key biogeochemical and geological processes (Orth et al.,1984; Orth, 1992; Proccacini et al., 2003; Nakaoka, 2005).

580 J. Moranta et al. / Estuarine, Coastal and Shelf Science 68 (2006) 579e592

Fish assemblages associated with Posidonia oceanica sea-grass meadows have been extensively studied in the Mediter-ranean. For instance, community structure and diel variations(Bell and Harmelin-Vivien, 1982; Harmelin-Vivien, 1984),spatial and temporal fluctuations (Harmelin-Vivien, 1982;Francour, 1997), feeding habits (Bell and Harmelin-Vivien,1983; Khoury, 1984; Harmelin-Vivien et al., 1989), compari-sons with other inshore habitats (Guidetti, 2000), effect of bot-tom trawling (Sanchez-Jerez and Ramos Espla, 1996), effectof protection (Francour, 1994; Francour, 2000; Macphersonet al., 2002) and methodological bias in sampling methods(Harmelin-Vivien and Francour, 1992) should be consideredwell known in this area.

Nevertheless, little attention has been given to the variabil-ity in the fish assemblages associated with Posidonia oceanicameadows at different spatial scales. Studying spatial patterns isof ecological importance in order to understand the causes ofabundance of organisms, and it also provides valuable insightsfor management and conservation. The topic of variability atseveral spatial scales, from meters up to hundreds or thousandsof kilometres, has been addressed for fish communities otherthan the one considered here. Specifically, there are numerousexamples concerning reef fishes (Choat and Ayling, 1987;Sale, 1998; Chesson, 1998; Garcıa-Charton and Perez-Ruzafa,2001; Guidetti et al., 2002; Garcıa-Charton et al., 2004; Chit-taro, 2004; Anderson and Millar, 2004; Nunez-Lara et al.,2005). This is a relevant topic because the patterns that canbe observed (and the processes that lead to them) depend onthe extent to which the system is examined (Sale, 1998). Forexample, analyzing multivariate variability in reef fish assem-blages at different spatial scales revealed that the greatest var-iation occurred at the smallest spatial scale, betweenindividual transects (separated by a few meters), and in con-trast, variability from site to site (separated by hundreds tothousands of meters) and from location to location (separatedby hundreds of kilometres) were comparable (Anderson andMillar, 2004).

Hierarchical multi-scale approaches are conceived forunderstanding how information is transferred across scalesbut they are rarely integrated into survey methodologies andanalysis of the results. This is probably due to the huge effortthat simultaneous sampling at multiple spatial scales with theappropriate number of replicates at each spatial level implies.The marine environment has particular practical, logistical andfinancial challenges that make it more difficult to obtain thistype of dataset (Raffaelli et al., 2005). The analysis of anthro-pogenic and geomorphologic effects on reef fish communitiesalong 400 km of the coast of the Yucatan Peninsula (Nunez-Lara et al., 2005) and the analysis of the effect of habitat struc-ture on reef fishes at a large scale of hundreds of kilometresalong the north-eastern coast of New Zealand (Anderson andMillar, 2004) are two notable exceptions. Similarly, thisspecific matter has been studied in relation to Mediterraneanrocky reef fish assemblages covering more than 500 km, butat the price of extending the sampling program from June toOctober (Garcıa-Charton et al., 2004). According to thiscontribution, the variability observed at the largest spatial

scale in the structure of the fish assemblages studied seemsto be largely determined by differences in local carryingcapacity and hydro-climatic conditions, but at small-to-intermediate spatial scales the habitat structure is more likelyto be responsible for a large part of the observed differences.The importance of habitat structure has also been studied inthe case of Australian seagrasses (Bell and Westoby,1986a,b,c). Specifically, the effect of physical complexityseems to affect the abundance and distribution of fishes differ-ently depending on the spatial scale (i.e. local scale versus anentire bay).

Therefore, a multi-scale analysis should at least considerthe potentially confounding effects of both seasonality andhabitat structure (at the intermediate scale, i.e. from morethan 1 km to less than 10 km), but a fully factorial experimen-tal design that takes all these factors into account is usuallyunavoidable. Consequently, a combination of data comingfrom different sampling programs is proposed, after testingand insuring that the specificities of each program cannot beconfounded with spatial variability per se. The two prelimi-nary experimental designs adopted here to allow the datasetsto be combined were: (1) the differences between two consec-utive years were tested by sampling the same meadow(Formentera) in June 2001 and June 2002; and (2) the differ-ences attributable to the meadow structure (at the within-locationscale; in terms of cover and shoot density) were evaluated bysampling two meadows (Mallorca 2000 and Formentera2001). The absence of any significant correlation patternrelated to these factors allows us to combine the datafrom the three locations (Formentera 2001, Mallorca 2000 andAlacant 2000) in order to carry out a single analysis aimedat determining how much variability is explained by thethree spatial scales considered (i.e. <1 km, <10 km and>100 km).

In addition, in terms of multi-scale analyses, this contribu-tion represents the first attempt in the Mediterranean to ana-lyze the correlation patterns between the structure of thePosidonia oceanica meadows and the fish assemblages that in-habit them. Moreover, in the geographical context of the Ba-learic Islands and the Iberian coast, detailed descriptions ofthe characteristics of the fish assemblages associated withP. oceanica meadows are scarce (Massutı, 1962; Renoneset al., 1995; Jimenez et al., 1997) despite the fact that thesemeadows are among the most important habitats in the areasince they cover nearly 3100 km2 (Mas et al., 1993).

2. Materials and methods

2.1. Sampling method

Surveys were carried out over Posidonia oceanica beds inthree Spanish locations along the Mediterranean coast, twoof them were located in the Balearic Islands (Mallorca andFormentera) while the third was on the eastern coast of theIberian Peninsula (Alacant) (Fig. 1). A beam trawl was usedto sample three randomly chosen sites in Mallorca and Alacant

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Fig. 1. Map of the study area, showing the location of Posidonia oceanica meadows sampled off the Mediterranean Spanish mainland (Alacant), and Mallorca and

Formentera Islands. The stars show the different sites considered at each location.

while five sites where sampled in Formentera. Six hauls (rep-licates) were taken at each site, except in one site of Formen-tera where only three hauls could be taken. The bathymetricrange varied from 15 to 25 m depth in Mallorca and Alacantand from 5 to 30 m depth in Formentera. The beam trawlused was 1.8 m wide and 0.8 m high, with a body of 8 m(12 mm square mesh in the first half and 9 mm at the back),and a 2 m long cod end (6 mm square mesh). Each beam trawlwas towed, whenever possible, for 15 min at a mean speed of1.5 knots during daytime (10:00e13:00 h). However, the pres-ence of rocky discontinuities in some transects did not allowthis duration to be achieved in all cases. Therefore, the dis-tances of the hauls ranged from 361 to 895 meters. All fishescaught were identified, counted, measured (to the lowest mm)and weighed (to the nearest gram). Abundance and biomassvalues were standardized to 1000 m2.

2.2. Sampling design and data analysis

As mentioned above, different subsets of the data were usedto achieve specific objectives. Thus, (1) inter-annual variabil-ity was tested using data from the same five sites of Formen-tera that were sampled twice (June 2001 and June 2002);(2) the effects of meadow structure (at within-location level)

were estimated using data from three sites of Mallorca (July2000) and four sites of Formentera (June 2001; the shallowestsite of Formentera was excluded from the analysis in order tominimize the potentially confounding effects of depth; no dataon meadow structure were available at Alacant); and (3) spa-tial variability at different scales was assessed by combiningthe data from three sites in each of three locations (MallorcaJuly 2000, Formentera June 2001 and Alacant July 2000; theshallowest and the deepest sites of Formentera were excludedfrom the analysis in order to obtain a fully balanced design andto minimize the potentially confounding effects of depth). Asusual, logistical constraints limited the number of availablereplicates (hauls) at each of these locations. Nevertheless,the maximum number of replicates was used for each of thethree analyses with the constraint of obtaining a fully balanceddesign (i.e. the same number of hauls per cell; in the caseswhen there were more hauls available, the specific replicatesused were randomly selected). The numbers of replicates foreach of the levels in each of the analyses are detailed inTable 1.

We tested the existence of spatial autocorrelation betweenthe hauls corresponding to the same years and locations in or-der to allow the hauls to be considered as spatially indepen-dent units (true replicates in a statistical sense). Theexistence of a spatial structure in the residuals (or in the raw

Table 1

Multivariate models: variables and covariables included, sample sizes at the different spatial scales (D: depth, C: cover, H: hauls, L: locations, R: within-site

replicates, SD: Shoot density, S: sites and Y: year). Details of the permutation procedure and number of samples (T) and species (Sp) included in each analysis

are also provided

Test Target effect Var. Covar. L S R T Permutation Sp

1 Inter-annual variability Y D 1 5 3 30 S freely permuted between Y. H constrained within S 14

2 Effect of meadow characteristics C, SD L, D 2 7 (4 þ 3) 3 21 S constrained within L. H constrained within S 17

3 Spatial variability

3a e Meso-scale spatial variability L D 3 9 6 54 S freely permuted. H constrained within S 15

3b e Between-site spatial variability Site L, D 3 9 6 54 S constrained within L. H freely permuted 15

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data) can be explored using certain methods. In this study semi-variograms have been used (Legendre and Legendre, 1998).A semivariogram is a graph that displays a convenient measureof the between-site differences (semivariance at progressivedistance intervals or lags). Semivariograms have recentlybeen extended from univariate to multivariate data by combin-ing them with principal component analysis or correspondenceanalyses (among other multivariate approaches; Wagner,2003). The rationale is to change between-sample differencesin the (univariate) variable of interest by faunistic (dis)similar-ities (Wagner, 2003, 2004; Couteron and Ollier, 2005). Thepattern expected in the case of spatial autocorrelation is thatclosely located sites will be more similar to each other andthus the semivariance (variability) of all pairs falling withinthese first lags will be smaller in comparison with the semivar-iance observed in other lags. The departure of the semivar-iance from the expected value in the case of no spatialstructure was tested using Monte Carlo permutation methods(Wagner, 2003). Random shifting of the spatial coordinatesemulates the null hypothesis of no spatial structure. Therefore,confidence intervals of the null hypothesis can be constructedfrom a large number of iterations. Calculations, significancetests and plotting of the multivariate variograms were com-pleted using the R library mso (Wagner, 2004). Version2.0.1 of the R package was used (http://www.r-project.org/).

After exploring the extent of spatial autocorrelation, bothunivariate and multivariate approaches were considered. Uni-variate analysis (analysis of variance, ANOVA) was appliedin order to differentiate the fish assemblages in terms of uni-variate community descriptors (namely, species richness, indi-viduals per haul [density hereafter], biomass, Shannon-weaverdiversity index and trophic categories). Differences in trophiccharacteristics of the fish assemblages between locations wereelucidated by classifying all the species into five trophic cate-gories (herbivores, microphagous, mesophagous, omnivoresand macrophagous). These categories differ slightly fromthose established elsewhere (Bell and Harmelin-Vivien,1983; Macpherson et al., 2002) and were defined based onrecent results from trophic levels determined by isotope anal-ysis (Jennings et al., 1997; Deudero et al., 2004). All depen-dent variables were tested for the assumptions of normalityand homogeneity of variance before applying parametric testsby means of KolmogoroveSmirnov and Cochram tests respec-tively. When these assumptions were not met, data was Ln orsquare-root transformed.

Comparisons of fish composition in terms of species-specific densities are of a multivariate nature. RedundancyAnalyses (RDA) were used because they link the species com-position (response) matrix directly with the environmental(explanatory) matrix. The response matrix is a matrix withthe species in the columns (i), the samples in the rows ( j )and each Xij value corresponding to the abundance of the spe-cie i in the sample j. RDAs are more appropriate than othermultivariate analyses when species turnover is not very largesince they assume that there is a short gradient when it is plau-sible that the abundance of each species is linearly dependenton environmental variables (ter Braak and Smilauer, 2002).

RDA allows testing hypotheses properly in the case of hierar-chically nested sampling designs using permutation-based tests(split-plot design routine in CANOCO 4.5; ter Braak andSmilauer, 2002). Those species with a frequency of occurrencelower than 5% and 1% were considered occasional or rare re-spectively, and were not considered in the multivariate analysis.In addition, for the rest of the species, with the aim of reducingthe variability in the species matrix due to the presence of a lotof zero values, only those species appearing in at least 20% ofthe hauls were included. The specific number of species used ineach of the analyses performed is detailed in Table 1.

When significant differences were detected, the similaritypercentage analysis (SIMPER) was also performed betweenpairwise locations in order to determine which species contrib-uted most to dissimilarity both with respect to contributions toaverage similarity within a group and average dissimilaritybetween groups (Clarke and Gorley, 2001). This routine wasbased on breaking down the Bray-Curtis dissimilarity betweentwo samples into contributions for each species (�di). A usefulmeasure of how consistently a species contributes to �di acrossall pairs of samples is the ratio �di=SD. When this ratio is largethen the ith species not only contributes greatly to the dissim-ilarity between two groups but it also does so consistently ininter-comparisons of all samples in the two groups (Clarkeand Warwick, 1994).

2.2.1. Inter-annual variabilityFormentera meadows (Fig. 1) were sampled in June for two

consecutive years (2001 and 2002) in order to evaluate the im-portance of inter-annual changes in fish assemblage structure(test 1 in Table 1). In the multivariate analysis, depth was con-sidered as a covariable in order to reduce the possible effectthat it could have on the composition of the fish assemblages.A full factorial ANOVA model was used to detect inter-annualvariations for the univariate community descriptors. Themodel considered was Xijk ¼ mean þ Yi þ Sj þ Yi*Sj þ Hijk,where year (Y ) was a fixed factor, site (S ) factor was random,and the hauls (H ) were the replicates (the error term in themodel). Xijk represented each replicate (k) of the dependentvariable in any site ( j ) in a given year (i).

2.2.2. Effects of meadow characteristicsThe effects of the meadow structure were evaluated using

samples from Mallorca and Formentera (Fig. 1) taken duringsummer 2000 and summer 2001 respectively; cover and shootdensity were also estimated. In the case of Formentera, onlythose samples taken between 15 and 30 m depth were consid-ered in these analyses. In the multivariate analysis the effect ofmeadow structure at the between-site level was evaluated con-sidering the location as a covariable (test 2 in Table 1). Simi-larly, depth was left in the model as a covariable.

Characterization of the Posidonia oceanica meadows wascarried out through direct underwater observation by scuba-divers after the fishing surveys. The cover of the meadowswas determined by mapping the towed courses over the haultransects, whereas the mean shoot density was calculated inthree 1 m2 replicated samples (3-3-3) placed at the initial,

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intermediate and final positions of each haul. The existence ofbetween-location differences in depth and meadow structurewas also tested by means of a nested analysis of variance(the same model applied for spatial analysis, see below).The effect of cover and shoot density on species richness, den-sity, biomass and diversity was analyzed separately for eachlocation using multiple regression analysis.

2.2.3. Spatial variabilityMultivariate analysis was adopted in order to compare the

fish composition in terms of density between the three loca-tions (Alacant summer 2000, Mallorca summer 2000 and For-mentera summer 2001, test 3 in Table 1). In this case, thesampling structure was defined at three sampling levels,namely: (1) the meso-scale (test 3a), which considers hundredsof kilometres and is represented by the three locations (L);(2) the intermediate scale (test 3b), which considers a distanceof between 5 and 10 km and is represented by three sites (S )within each of the localities; and (3) the small scale, between100 m and 1 km, represented by the hauls (H ) located ran-domly within each site (six hauls in each site). In Formenteraonly samples included in the bathymetric range from 15 to25 m depth were considered. Nevertheless, the existence of be-tween-location differences in depth was also tested.

In addition to the multivariate analysis, nested univariateanalyses of variance (Underwood, 1997) were carried out todetermine spatial differences in the univariate community des-criptors. The model used was Yijk¼ meanþ Liþ S(L)ijþ Hijk,where location (L) was a fixed factor, the site (S ) factor was randomand nested within location, and the hauls (h) were the replicates(the error term in the model). Yijk represented each replicate(k) of the dependent variable in any site ( j ) in a given location(i). This allowed us to analyze the variability at the three spatialscales studied.

Finally, biomass spectra (Platt and Denman, 1978) werecompared between locations. To elaborate them, fishes largerthan 1 g were assigned to log2 body-mass classes, and thecumulative biomass for each body-mass class was calculated.Normalized biomass size spectra were computed by dividingthe biomass in a given body-mass class interval by the widthof that class interval (in antilog dimensions). The relationshipbetween normalized biomass and class interval was estimatedusing least squares regressions (Macpherson and Gordoa,1996). The regressions were performed separately for eachlocation and were compared by means of Analysis of Covari-ance. Values to the left of the mode in the distribution of bio-mass by size interval were subsequently excluded from theregression analysis as they did not contribute to slope determi-nation. A slope equal to �1 indicates an even distribution ofbiomass over the size spectra; a slope steeper than �1 indi-cates a decrease in biomass with size, and a slope flatterthan �1 indicates an increase in biomass with size.

3. Results

From the 74 hauls included in the three analyses 5740fishes, belonging to 49 species and 19 families were caught,

representing a total biomass of 81.2 kg (Table 2). Labridaeand Sparidae were the most significant fish families in thethree locations, although their relative contribution to the over-all density differed from one location to another (Labridae49% and Sparidae 16% in Mallorca, 54% and 21% in Formen-tera, and 33% and 34% in Alacant respectively). Only onespecies, Diplodus annularis, was present in all the hauls, whileSerranus scriba and Symphodus rostratus were absent in onlyone haul. 12 species, with a frequency of occurrence greaterthan 50%, were found to be common between the three loca-tions studied. Among these, the most abundant species wereSymphodus ocellatus (23.2% of the total catch), D. annularis(18%), S. scriba (13.8%), S. rostratus (10.8%), Chromis chromis(6.5%), Coris julis (6%) and Symphodus mediterraneus (4.5%),which together constituted 82.8% of the total catch. In terms ofbiomass, the most significant species were S. scriba (20.9%),D. annularis (15.2%), Scorpaena porcus (13.3%), S. ocellatus(7.7%), S. rostratus (6.2%), C. chromis (5.2%), Diplodus vulga-ris (4.9%), Symphodus tinca (4.2%) and C. julis (3.3%), repre-senting 81% of the total biomass.

The effect of depth was evaluated separately in each of thesubsequent sections. It should be noted that this variable wasnot significant in any of the five multivariate analyses detailedin Table 1. For example, in the case of between-year differ-ences, the percentage of variance of species-specific densities(multivariate approach) explained by depth was only 4.8%(F ¼ 1.158; P ¼ 0.667; n ¼ 3 hauls � 5 sites � 2 years).However, depth was left in all the models as a covariable asthe sampling design was focused on testing other variables.

3.1. Inter-annual differences

Differences in fish composition between samples from sum-mer 2001 and summer 2002 in Formentera were not significant.After taking out the depth effect (included as a covariable in themodel; test 1 in Table 1), an RDA indicated that the variabilityin the species density matrix explained by year was only 4.6%(F ¼ 1.359; P ¼ 0.165; n ¼ 3 hauls � 5 sites � 2 years).

Full cross univariate analysis applied to detect the variabilityin the univariate community descriptors, revealed that themain year factor was not significant. The interaction term(year � site) was also not significant, indicating the samepattern for these descriptors between two consecutive years.Significant differences were only identified in between-sitedensity due to the extreme values obtained in both years atsite 1 (mean � SE ¼ 156.77 � 11.10 summer 2001, 141.93 �47.40 summer 2003) and 2 (mean � SE ¼ 44.31� 9.07 summer2001, 29.73 � 8.88 summer 2002).

3.2. Effect of meadow structure

The cover of Posidonia oceanica ranged between 100 and57.6% in Formentera (mean � SE ¼ 90.75 � 3.58) and be-tween 100 and 67.6% in Mallorca (mean � SE ¼ 90.69 � 2.97).Shoot densities ranged between 596 and 238 shoots m�2 in For-mentera (mean � SE ¼ 362.91 � 25.93) and between 281 and120 shoots m�2 in Mallorca (mean � SE ¼ 196.48 � 15.48).

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Table 2

List of fish species recorded at the three locations (Mallorca, Alacant and Formentera) studied in the western Mediterranean during the summers of 2000, 2001 and

2002 with the number of hauls in which the species were present. The trophic category (TC) is also specified. The * indicates the species used in the RDA analysis.

H ¼ Herbivores; MA ¼Macrophagous, ME ¼Mesophagous, MI ¼Microphagous and O ¼ Omnivores

Family Species TC Mall’00 Ala’00 For’01 For’02

Rajidae Raja radula MA e e e 1

Synodontidae Synodus saurus* MA 3 e e 1

Muraenidae Muraena helena MA e 1 e 1

Syngnathidae Nerophis maculatus ME e e 2 2

Syngnathus acus ME 2 1 e eSyngnathus typhle* ME 7 7 9 8

Gadidae Phycis phycis MA e e 1 e

Serranidae Serranus cabrilla* MA 4 2 2 eSerranus scriba* MA 18 18 18 15

Mullidae Mullus surmuletus* ME 11 7 1 e

Sparidae Diplodus annularis* O 18 18 18 15

Diplodus puntazzo O 1 e e eDiplodus sargus O e 1 e e

Diplodus vulgaris* O 15 17 12 8

Pagellus bogaraveo O e e 1 e

Pagellus sp. O e e e 1

Pagrus pagrus MA e 2 e 1

Sarpa salpa H 1 1 e e

Spondyliosoma cantharus O 2 4 e e

Centracanthidae Spicara maena MI 1 e e 1

Spicara smaris MI e e 1 e

Pomacentridae Chromis chromis* MI 18 13 10 5

Labridae Coris julis* ME 16 14 17 10

Ctenolabrus rupestris MI e 1 e e

Labrus merula ME e 2 1 2

Labrus viridis ME 1 2 2 3

Symphodus cinereus* MI 11 5 5 2

Symphodus doderleini* ME 12 3 12 7

Symphodus mediterraneus* MI 15 5 17 12

Symphodus melanocercus MI 2 1 e e

Symphodus ocellatus* MI 18 17 18 14

Symphodus roissali MI e e 3 1

Symphodus rostratus* MI 17 18 18 14

Symphodus tinca* ME 16 5 7 12

Xyrichthys novacula O e e 1 e

Trachinidae Trachinus draco MA 1 e 2 1

Uranoscopidae Uranoscopus scaber MA e e e 3

Gobiidae Gobius cruentatus* ME 2 4 6 7

Gobius geniporus ME 1 e e e

Gobius sp. ME e e 1 e

Odondebuenia balearica MI e e e 1

Bleniidae Parablennius tentacularis ME 2 e e eScorpaenidae Scorpaena notata MA 2 1 1 e

Scorpaena porcus* MA 9 16 16 14

Scorpaena scrofa* MA e e 2 1

Bothidae Arnoglossus rueppelli ME e e 2 eBothus podas* ME 3 e 3 3

Soleidae Solea sp. ME e e e 1

Gobiesocidae Apletodon dentatus MI e e e 3

The results of the nested analysis of variance between the twolocations showed significant differences for shoot density(F1,3 ¼ 14.72, P ¼ 0.03) but not for cover (F1,3 ¼ 0.02,P ¼ 0.89). Significant differences were found between sites forshoot density in both locations (F1,3 ¼ 7.37, P < 0.001). Be-tween-location differences in depth were also not significant(F1,3 ¼ 1.53, P ¼ 0.30). The impact of the beam trawl on shootdensity was also considered by counting the number of shootstrapped in the net, resulting in a small impact with a number ofshoots per haul ranging from 0 to 15.

Multivariate analysis showed that meadow structure (coverand shoot density) were found to be uncorrelated to fish com-position at the within-location level. The degree of variabilityin the species composition matrix explained by the meadowstructure was 15.1% (RDA; F ¼ 1.793; P ¼ 0.226; n ¼ 3 haulsin 7 sites from two locations; test 2a in Table 1).

The small relevance of the meadow structure in determin-ing species composition was visualized better using the sam-ple scores extracted with a Principal Components Analysis(Fig. 2). The within-location sites depicted two clearly

585J. Moranta et al. / Estuarine, Coastal and Shelf Science 68 (2006) 579e592

separated clusters, which demonstrates that the main source ofvariability in fish species composition is the geographic factor(Mallorca versus Formentera) more than meadow structure(cover and shoot density).

For the univariate community descriptors, a significantrelationship was only obtained between shoot density andfish density (b ¼ 0.60, t14 ¼ 2.81, P < 0.05) and biomass(b ¼ 0.53, t14 ¼ 2.32, P < 0.05) in Mallorca. In this locationthe density of Symphodus ocellatus (b ¼ 0.64, t14 ¼ 3.12,P < 0.01), Diplodus vulgaris (b ¼ 0.60, t14 ¼ 2.81,P < 0.01) and Serranus cabrilla (b ¼ 0.53, t14 ¼ 2.37, P <0.05) showed a significant increasing trend with increasingshoot density, and the density of Coris julis (b ¼ � 0.52,t14 ¼ � 2.28, P < 0.05) grew as the cover increased. Never-theless, these relationships were clearly not significant whenthe spatial structure was considered and the two locationswere included in a single analysis.

3.3. Spatial variations

No evidence of the existence of spatial structures at thewithin-site scale (i.e. <10 km apart) was found as denotedby the semivariogram shown in Fig. 3. This case correspondsto the multivariate samples obtained in Formentera, but thesame qualitative results were found at the three locations.None of the distance lags considered is significantly largerthan expected. This means that variability between closely

Fig. 2. PCA ordination plot of samples from Mallorca and Formentera. PCA

scores (this figure) better-visualise the between-samples similarity because

they describe the observed variability in species abundances while RDA scores

describe the variability explained by some putative explanatory variable (e.g.,

Fig. 5). The samples (locations) depicted two clearly separated clusters, sug-

gesting that the main source of variability in fish species composition was

the geographic factor (Mallorca versus Formentera).The lines join the three

locations taken at the same site.

located hauls is similar to the variability between more distanthauls (at the within-location level). Consequently, hauls wereconsidered as (statistically) truly independent samples in allthe statistical analyses.

Since no differences were detected in the inter-annual com-parisons, both datasets from Formentera (Formentera 2001 andFormentera 2002) could be used indistinctively in the multi-scale spatial analysis. The dataset from Formentera 2001was preferred due to its proximity in time to the data fromMallorca 2000 and Alacant 2000.

The multivariate analyses (RDA) showed that the unex-plained (residual) variability in fish composition (i.e. the vari-ability corresponding to the between-haul scale) was 59.9%.Therefore, the variability in fish composition explained bythe other two spatial levels considered (location and site) in-creased to 40.1%. From this latter value, 55.4% correspondedexclusively to the variability related to the location level andthe percentage corresponding to the site level (within-location)was 44.6%. Although the location-related effects were signif-icant (RDA, F ¼ 7.362; P < 0.0001; test 3a in Table 1), thesite-related effects were not significant (RDA, F ¼ 2.280;P ¼ 0.166; test 3b in Table 1). This fact confirmed that be-tween-site differences within the same locations were not sig-nificant in relation to the large between-location differences.

The biplot corresponding to the between-location levelindicated that the variability from location to location wascomparable (Fig. 4). The between-location differences wererelated to the different contributions of specific species. Spe-cies typifying the Mallorca fish assemblage were Chromischromis, Mullus surmuletus, Symphodus tinca and Symphoduscinereus. The Formentera fish assemblage was characterizedby greater densities of Symphodus mediterraneus, Symphodusocellatus, Symphodus doderleini, Symphodus rostratus, Diplo-dus annularis and Scorpaena porcus, whereas the location atAlacant was defined by larger densities of Diplodus vulgaris.

The results of the SIMPER analysis were in full agreementwith those obtained using RDA (Table 3). Between-locationdissimilarity ranged from 53.29 to 56.13 for abundance, andfrom 53.74 to 57.26 for biomass. Concerning density, the spe-cies that contributed most to dissimilarity were Symphodusocellatus, followed by Diplodus annularis, Chromis chromis,Serranus scriba and Symphodus rostratus, which all togetherrepresented more than 65% of the contribution to dissimilarity.Regarding biomass, Scorpaena porcus, S. scriba, D. annularisand S. ocellatus were the main species contributing to dissim-ilarity (>60%) between Formentera versus Mallorca and Ala-cant. Diplodus vulgaris was also significant for explaining thedissimilarity between Alacant and the other two locations. Otherspecies with a high ratio �di=SD and that also contributed to thedifferences between location both in abundance and biomasswere Symphodus mediterraneus, Coris julis and Symphodus tinca.

Univariate community descriptors of the fish assemblagewere found to be similar between the three locations (Table 4,Fig. 5); however differences were detected between sites.These differences were detected for density and diversityand could be attributed to the highest density values obtainedin site one of Formentera. This site was the only one

586 J. Moranta et al. / Estuarine, Coastal and Shelf Science 68 (2006) 579e592

Fig. 3. Multivariate spatial correlogram denoting the variability in faunistic similarity between the pairs of samples (hauls) falling within different distance intervals

(or lags). Interval width is 100 m. The lower panel is a histogram denoting the number of pairs of samples falling within the same intervals. The peak at the left

corresponds to the pairs of samples from the same site. The successive peaks towards the right correspond to pairs located at different sites. The between-sample

variability at the within-site and at the between-site scales is similar. Moreover, variability between samples located at the first interval (i.e. up to 200 m) is similar

or even smaller to the variability displayed by samples located 1000 m apart. The permutation test based on 1000 iteration indicates that none of the considered lags

are smaller than expected by chance.

with a 100% seagrass cover in all three hauls, and presentedthe highest density values of Diplodus annularis (mean �SE ¼ 252.62 � 62.21 ind � 1000 m�2) and Symphodus ocel-latus (mean � SE ¼ 802.34 � 176.67 ind � 1000 m�2). Thelow diversity values obtained in this site of Formentera was

a consequence of these extraordinary density values of the for-mer species, which clearly dominates the fish assemblage innumber of individuals. The biomass value of this site wasnot different from the others (Table 4), which indicates theprevalence of small individuals.

Fig. 4. Spatial patterns experienced by species abundance. RDA ordination diagram (biplot) showing the contribution of fish species to the between-

locations differences. Pie charts indicating the relative abundance of species at the three locations. The angle between arrows (species) denotes the correlation degree.

Location symbols (triangles) can be projected perpendicularly onto the line overlaying the arrow of the particular species. These projected points are in the order of

the predicted increase of the relative abundance of a particular species across the three locations.

587J. Moranta et al. / Estuarine, Coastal and Shelf Science 68 (2006) 579e592

Table 3

Results of the SIMPER routine to analyse dissimilarity between the three geographic areas studied. The species are ordered by decreasing contribution. �di: average

dissimilarity, �di%: contribution of each species to the average dissimilarity, SD: standard deviation

Mallorca vs Formentera �di ¼ 56.13 Formentera vs Alacant �di ¼ 54.56 Alacant vs Mallorca �di ¼ 53.29

Species �di% �di=SD Species �di% �di=SD Species �di% �di=SD

Results of the SIMPER analysis for density

S. ocellatus 28.75 1.12 S. ocellatus 30.62 1.03 S. ocellatus 16.85 1.29

D. annularis 13.11 1.14 D. annularis 14.74 1.3 C. chromis 13.79 0.96

C. chromis 11.1 1 S. scriba 11.36 1.19 D. annularis 13.32 1.46

S. scriba 9.74 1.18 S. rostratus 8.6 1.24 S. scriba 11.11 1.3

S. rostratus 8.5 1.22 C. chromis 6.65 0.79 S. rostratus 10.29 1.33

C. julis 6.11 1.2 S. mediterraneus 6.2 1.62 D. vulgaris 7.6 0.99

S. mediterraneus 4.72 1.36 D. vulgaris 5.76 0.85 C. julis 6.93 1.2

M. surmuletus 4.66 0.69 C. julis 4.62 1.01 M. surmuletus 6.79 0.81

S. porcus 3.07 1.34 S. doderleini 2.85 0.89 S. porcus 2.91 1.09

D. vulgaris 2.9 1.32 S. porcus 2.82 1.16 S. tinca 2.81 1.21

S. doderleini 2.66 0.97 M. surmuletus 1.92 0.53 S. mediterraneus 2.54 1.29

S. tinca 1.93 1.04 S. typhle 1.21 0.72 S. cinereus 1.85 0.9

S. cinereus 1.17 0.82 S. cinereus 0.94 0.72 S. typhle 1.32 0.77

S. typhle 0.92 0.65 G. cruentatus 0.92 0.56 S. doderleini 1.25 1.02

G. cruentatus 0.65 0.44 S. tinca 0.79 0.79 G. cruentatus 0.65 0.54

Mallorca vs Formentera �di ¼ 57.26 Formentera vs Alacant �di ¼ 53.74 Alacant vs Mallorca �di ¼ 55.30

Species �di% �di=SD Species �di% �di=SD Species �di% �di=SD

Results of the SIMPER analysis for biomass

S. porcus 18.87 1.19 S. scriba 19.29 1.28 S. scriba 19.39 1.41

S. scriba 18.22 1.3 S. porcus 16.36 1.08 D. annularis 13.55 1.34

D. annularis 12.46 1.01 D. annularis 13.65 1.12 D. vulgaris 12 1.49

S. ocellatus 11.33 0.91 S. ocellatus 11.19 0.85 S. porcus 11.42 1.15

C. chromis 10.2 0.99 D. vulgaris 10.91 1.4 C. chromis 9.7 0.99

S. tinca 5.73 1.06 S. rostratus 6.52 1.33 S. rostratus 8.13 1.42

D. vulgaris 4.55 0.94 C. chromis 6.03 0.71 S. ocellatus 7.75 1.18

S. rostratus 4.54 1.23 S. mediterraneus 5.05 1.41 S. tinca 7.32 1.13

S. mediterraneus 4.45 1.34 S. tinca 3.43 0.61 C. julis 4.01 1.05

C. julis 4.23 1.13 C. julis 2.84 1.02 S. mediterraneus 1.89 1.34

G. cruentatus 1.49 0.4 G. cruentatus 1.63 0.46 M. surmuletus 1.64 0.71

M. surmuletus 1.49 0.66 S. doderleini 1.36 0.94 S. cinereus 0.99 0.83

S. doderleini 1.39 1.06 S. cinereus 0.63 0.6 G. cruentatus 0.95 0.6

S. cinereus 0.63 0.79 M. surmuletus 0.63 0.64 S. doderleini 0.86 1.06

S. typhle 0.41 0.6 S. typhle 0.49 0.64 S. typhle 0.41 0.63

The plots of Normalized Biomass Spectra (NBS) for thethree studied locations ranged from class 0 to class 10(Fig. 6). The differences in the normalized biomass spectra(NBS) plots between the three locations studied are due tothe relative contribution of individuals smaller than the 23

(8 g) size classes. These size classes (20, 21 and 22) represent43.37% of the total biomass in Formentera, 27.43% in Mal-lorca and only 8.91% in Alacant. Differences between thelargest classes (right side of the distribution) were less

conspicuous. Excluding the values to the left of the mode,where clear differences were observed between the three local-ities, the regressions were significant in the three cases(P < 0.001) with r2 ¼ 0.99 for Mallorca and Formentera and0.97 for Alacant. No significant differences were found forthe slopes between the three locations (ANCOVA,F2,12 ¼ 3.83, P > 0.05) and they were less than �1 in the threecases, which indicates that biomass tended to increase acrossthe size classes towards the right of the mode.

Table 4

Results of the nested ANOVA for species richness, density (number of individuals � 1000 m�2, Ln-transformed), biomass (g � 1000 m�2, Ln-transformed) and

diversity (Shannon-Weaver index) comparing the three locations (Mallorca, Formentera and Alacant) sampled in the western Mediterranean during the summer.

Degrees of freedom (DF), mean square (MS) and F-statistic are indicated. *P < 0.05, **P < 0.001

DF Species richness Density Biomass Diversity

MS F MS F MS F MS F

Location 2 25.72 2.79 1.98 1.53 0.84 2.01 0.24 1.57

Site (Location) 6 9.20 1.48 1.29 5.07** 0.42 1.63 0.15 2.76*

Error 45 6.24 0.25 0.26 0.05

588 J. Moranta et al. / Estuarine, Coastal and Shelf Science 68 (2006) 579e592

Fig. 5. Between-location comparison of community descriptors showing the mean values obtained in each site of each location: Species richness, diversity

(Shannon index), density (individuals � 1000 m�2) and biomass (Kg � 1000 m�2). Vertical bars denote the 95% confidence interval of mean values (taking

into account the nested structure of the sampling design).

Finally, for the between-location differences in the relativecontribution of the five trophic groups considered, the micro-phagous species made up the largest proportion of fish densityin Mallorca and Formentera, whereas in Alacant the micropha-gous and omnivores groups showed similar density values(Fig. 7). The ANOVA results show that the within-location dif-ferences were more important than between-location differ-ences (Table 5). The picture changed, however, when

Fig. 6. Normalized biomass spectra for each of the three studied locations.

Dark symbols represent those values included in the least squares regression

with data to the left of the mode excluded (white symbols and dotted lines).

biomass was considered. In this case, Alacant and Formenterashowed a large percentage of the macrophagous group,whereas in Mallorca the main trophic groups (all but herbi-vores) showed similar relative importance. In fact significantdifferences were detected for the macrofagus between-loca-tions with lower values in Mallorca than the other two loca-tions (Table 5, Fig. 7).

4. Discussion

Our results revealed that the composition of fish assem-blages associated with Posidonia oceanica seagrass meadowsof the western Mediterranean tend to show different species-specific relative abundances resulting in a spatial heterogene-ity at a large spatial scale. The differences observed betweenlocations 100 km apart are mainly due to changes in the rela-tive density of species rather than differences in species com-position. The variation at the smallest spatial scale betweenindividual transects was also not negligible (amounting tow60% of the variability), as expected for fishes given thatthe distance between individual sampling hauls was not largein relation to the high mobility range of many fish species in-cluded in this study (Anderson and Millar, 2004; Ordineset al., 2005).

The absence of variability for species-specific densities atthe intermediate scale (>10 km) from site to site within sam-pling locations is also noticeable. The high variability of reeffish communities found at this spatial scale has been

589J. Moranta et al. / Estuarine, Coastal and Shelf Science 68 (2006) 579e592

associated with local environmental gradients (Nunez-Laraet al., 2005) and habitat characteristics (Garcıa-Chartonet al., 2004; Chittaro, 2004; Anderson and Millar, 2004). Inour study the sites within locations were placed over Posido-nia oceanica meadows and sand. Posidonia oceanica cover-age ranged from 100 to 57% in Formentera and from 100 to67% in Mallorca. Therefore, it seems that this range of var-iability did not imply severe differences related to meadowstructure. In future analyses, different levels of P. oceanicacoverage should be tested because the effect of cover onseagrass fish fauna are evidenced when severely depauper-ated meadows are also considered, as in studies coveringbeds with different degrees of fragmentation (Vega Fernan-dez et al., 2005). In fact, fish requirements of heterogeneoussubstrate (e.g. seagrass, rocky and sand) have been de-scribed as an important factor determining the distributionand abundance of littoral fish species at a small spatial scale(Garcıa-Charton and Perez-Ruzafa, 1998; Garcıa-Chartonand Perez-Ruzafa, 2001; Letourneur et al., 2003; Garcıa-Charton et al., 2004). Furthermore, it should be consideredthat the ecotone between seagrass meadow and sand is par-ticularly exploited by the small-scale (trammel nets) andrecreational (angling) fisheries in these areas, which sug-gests that covers such as that observed in the current study

Fig. 7. Contribution of the different trophic groups to the total density and

biomass of the fish assemblage in each studied location. Columns indicate

the mean values and vertical lines indicate the standard error.

Tab

le5

Res

ults

of

the

nes

ted

AN

OV

Afo

rd

ensi

ty(n

um

ber

of

ind

ivid

ual

s�

10

00

m�

2,

Ln

-tra

nsf

orm

ed)

and

bio

mas

s(g�

10

00

m�

2,

Ln

-tra

nsf

orm

ed)

of

the

dif

fere

nt

tro

phi

cg

rou

psco

mp

arin

gth

eth

ree

loca

tion

s

(Mal

lorc

a,F

orm

ente

raan

dA

laca

nt)

sam

pled

inth

ew

este

rnM

edit

erra

nea

nd

uri

ng

the

sum

mer

.D

egre

eso

ffr

eed

om(D

F),

mea

nsq

uar

e(M

S)

and

F-s

tati

stic

are

ind

icat

ed.

*P<

0.0

5,

**P<

0.0

01

DF

Mic

rofa

gous

Mes

ofa

gous

Mac

rofa

gous

Om

niv

oro

us

SS

MS

FS

SM

SF

SS

MS

FS

SM

SF

Den

sity

Lo

cati

on

29

.61

4.8

02

.38

7.4

33

.72

0.9

64

.19

2.1

02

.99

3.7

91

.90

1.5

1

Sit

e(L

oca

tio

n)

61

2.0

92

.01

5.0

2**

23

.30

3.8

84

.42*

4.2

10

.70

1.6

57

.53

1.2

62

.94

*

Err

or

45

18

.06

0.4

03

9.5

20

.88

19

.15

0.4

31

9.2

10

.43

DF

Mic

rofa

gous

Mes

ofa

gous

Mac

rofa

gous

Om

niv

oro

us

SS

MS

FS

SM

SF

SS

MS

FS

SM

SF

Bio

mas

s

Lo

cati

on

22

.12

1.0

60

.87

1.1

40

.57

0.1

81

3.7

86

.89

13

.32

*2

.97

1.4

90

.97

Sit

e(L

oca

tio

n)

67

.34

1.2

22

.68*

19

.07

3.1

82

.50*

3.1

00

.52

1.0

89

.15

1.5

22

.41

*

Err

or

45

20

.57

0.4

65

7.2

11

.27

21

.48

0.4

82

8.5

00

.63

590 J. Moranta et al. / Estuarine, Coastal and Shelf Science 68 (2006) 579e592

are above the threshold from which significant effects ofcover would be detectable.

The differences in global assemblage descriptors (speciesrichness, density, biomass and diversity) between the threestudied locations were clearly not significant. The variabilityof these univarite community descriptors at an intermediatescale from site to site was significant only for density anddiversity. These differences are attributable to the very highnumber of small Diplodus annularis and Symphodus ocellatusfound in one site of Formentera with 100% Posidonia oce-anica cover, probably related to recruitment processes. Theopposite results were obtained by Vega Fernandez et al.(2005) when fragmented beds were considered with significantdifferences for biomass but not for abundance. However, ourresults are in accordance with their findings for smaller indi-vidual sizes in continuous seagrass rather than in fragmentedbeds. Considering that the system tends to maximize the bio-mass that can be maintained in a given area (i.e. carrying ca-pacity), P. oceanica meadows found in different locations ofthe western Mediterranean with similar cover tend to preservethe same carrying capacity, adapting the species and/or sizeswhich contribute to determining the upper limit of the bio-mass. However, direct estimation of the carrying capacity isdifficult to ascertain due to the difficulties in quantifying theavailability and quality of the enormous variety of food andhabitats required by all the species in a system (Edgar,1993). Alternatively, indirect measures for exploring thefood limitation such us the pelagic primary production(Garcıa-Charton et al., 2004) or cascade effects following pro-tection (Sanchez Lizaso et al., 2000) have been proposed inreef habitats. For P. oceanica meadows their primary produc-tion could be a possible indirect estimation of their carryingcapacity, although it seems to be very variable in the Mediter-ranean basin (Pergent-Martini et al., 1994; Pergent et al.,1997).

Spatial heterogeneity is especially relevant because loca-tions and sites differ in their meadow complexity (i.e. shootdensity). In the three locations analysed in this study, data cor-responding to a depth of 6 m (Marba et al., unpublished data)indicate that Posidonia oceanica meadows have a shoot densitygradient from Formentera (mean � sd, 666.6 � 14.5 shootsm�2), to Mallorca (562.6 � 54.7 shoots m�2) and Alacant(430.6 � 23.1 shoots m�2). Although no significant relation-ship was found between meadow structure and species-spe-cific densities or fish community descriptors in this study,when the spatial structure is considered in the analysis,denser beds generally host richer and more diverse fish as-semblages compared to sparser meadows and unvegetatedhabitats (Heck and Orth, 1980; Bell and Westoby, 1986b;Bell and Pollard, 1989; Jenkins and Wheatley, 1998; Grayet al., 1998; Guidetti, 2000). Therefore, the shoot density var-iability in the studied areas may be below any detectablethreshold of complexity that can eventually affect speciesrichness or the rest of the community descriptors consideredhere, or even the species-specific densities. It is important tonote that at the mesoscale other possible variables such asclimatic or hydrological differences, competition, predation,

recruitment dynamics or fishing pressure can also determinethe structure of littoral fish communities (Garcıa-Rubies andZabala, 1990; Garcıa-Rubies and Macpherson, 1995; Jenkinset al., 1997; Vigliola et al., 1998; Planes et al., 2000; Letour-neur et al., 2003; Garcıa-Charton et al., 2004).

The differences in the normalized biomass spectra (NBS)plots between the three locations studied can be related tothe higher meadow complexity of Formentera (i.e. highershoot density) which favours smaller sizes, since small speciesand/or individuals are known to find more shelter andfood there (Guidetti and Bussotti, 2000; Guidetti, 2000; andreferences cited therein). However, no differences betweenlocations appeared for large individuals with slopes equal to �1in the three locations and with a biomass tendency to increasewith size. Similar results were obtained by Macphersonet al. (2002) in a seagrass bed located in a protected area.These authors analyzed the biomass spectra in the demersalfish community in the Medes Island Marine Reserve (NWMediterranean) associated with protected and unprotectedareas and with different bottom types, including Posidoniaoceanica meadows. They also found significant regressionsfor the NBS but reported lower r2 values for the seagrassbed assemblages (0.71e0.86) than in this study (0.97e0.99).However, it must be taken into account that biomass spectraare influenced by the sampling technique. Visual censusesused by Macpherson et al. (2002) are biased towards largersizes, whereas in our study the beam trawl caught smaller spe-cies and/or specimens that are underestimated by visual cen-suses. Conversely, larger species or individuals are moreeasily recorded by visual censuses than by beam trawl sam-ples. This characteristic is clearly observed by comparingthe size class interval analysed by Macpherson et al. (2002)between size class 23 (8 g) and 213 (8 kg) and in our study be-tween size class 20 (1 g) and 210 (1 kg).

The microphagous species made up the most abundantgroup of the trophic structure both in Mallorca and Formentera(related to the highest densities of Chromis chromis, Sympho-dus ocellatus and Symphodus rostratus), whereas their densi-ties were much lower in Alacant, where omnivorous specieswere equally abundant. Most of the species belonging to thegenus Symphodus are microphagous, and they show morpho-logical adaptations for feeding on the invertebrate epifauna as-sociated with Posidonia oceanica. Therefore, it is possible thatthere is a relationship between the relative densities of fisheswith this feeding type at locations with high meadow complex-ity. The herbivores group (represented by Sarpa salpa) waspractically absent from the samples. Two explanations are sug-gested to explain this fact: (1) S. salpa mostly occurs in shal-low waters of less than 10 m (Bell and Harmelin-Vivien, 1983;Francour, 1997); and (2) adult specimens (not only of S. sarpabut also of other large sized species, such as Labrus spp.) showhigh net escape ability, thus being practically absent from thesamples. Moreover, the distribution and density of S. salpacould also be associated with heterogeneous habitats with P.oceanica, rocks and sand (Guidetti, 2000; Garcıa-Chartonet al., 2004). Macrophagous species were dominant in termsof biomass but not in density in all study sites, since larger

591J. Moranta et al. / Estuarine, Coastal and Shelf Science 68 (2006) 579e592

species or individuals are expected to feed at higher trophiclevels (Cohen et al., 1993). In this sense, although lowerthan other species, the relatively high density of macrophagusfeeding Serranus scriba and Scorpaena porcus resulted in thehighest biomass values in Formentera and Alacant but not inMallorca. These results differ from a previous study in PalmaBay using a similar methodology (Renones et al., 1995),which showed macrophagous as the main contributors to bio-mass. Our Mallorca study sites are placed in areas less im-pacted by humans and with little pollution, which indicatesheterogeneity in the trophic web.

In conclusion, spatial heterogeneity in the relative contribu-tion of the different species to the fish assemblages associatedwith Posidonia oceanica beds in the NW Mediterranean is no-ticeable at the mesoscale level. Other factors such as anthropo-genic pressure and environmental effects should be consideredin the future to determine the causes of the reported mesoscaleheterogeneity. The heterogeneity at a smaller scale is alsonoticeable and more significant than intermediate scale vari-ability. The local meadow characteristics or habitat structureseems to be the main factor determining the similarity or dis-similarity in fish assemblages associated with seagrassmeadows. However, it is worth noting that when the seagrassmeadows were in a good state of conservation (i.e. within thecover and shoot density ranges observed here), the meadowstructure was not responsible for a patchy fish distribution al-though it could determine the high proportion of small sizedindividuals, which probably favours recruitment.

Acknowledgements

This paper is a result of the Project POSICOST (1FD97/1654) and ‘‘Seguiment de l’evolucio dels recursos marins ide les poblacions de les especies de major interes pesquera les reserves marines de les Illes Balears: Badia de Palma,Nord de Menorca, Freus d’Eivissa i Formentera’’ from theDireccio General de Pesca del Govern Balear. Fishery surveyswere authorized by the local authorities (Govern de les IllesBalears and Generalitat Valenciana). We are grateful toB. Oliver, A. Roig, B. Artigues, R. Nicolau and F. Riera, whocontributed to the construction of the beam trawl and the sur-veys, and P. Tugores for providing Fig. 1. Thanks to the anon-ymous reviewers for their useful comments on the manuscript.

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