Macrograzers strongly influence patterns of epiphytic assemblages inseagrass meadows

Patricia Prado a,!, Teresa Alcoverro a, Begoña Martínez-Crego a, Adriana Vergés a,Marta Pérez b, Javier Romero b

a Centro de Estudios Avanzados de Blanes, C/Accés a la Cala St. Francesc, 14, 17300—Blanes, Girona, Spainb Departamento de Ecología, Facultad de Biología, Universidad de Barcelona, Avda. Diagonal 645, 08028—Barcelona, Spain

Received 17 May 2007; received in revised form 28 May 2007; accepted 29 May 2007

Abstract

The influence of factors, both abiotic (light and nutrients) and biotic (meadow structure, herbivory and seagrass shoot length) inthe abundance and distribution of epiphytes on the Mediterranean seagrass Posidonia oceanica was investigated by means of acorrelational approach over a spatial scale of ca. 500 km and at two different depths (5 and 15 m). Variability was examined fromthe double perspective of integrative community measures (biomass, species richness and alpha-diversity) and species composition.We assessed the influence of biotic and abiotic factors on integrative community measures using multiple correlation analyses. Theinfluence of these factors in the structure of the whole community was investigated using a distance-based RDA for a linear model.A total of 129 taxa, mostly epiphytic algae, were recorded across all sites and depths. A large part of the variability in speciescomposition (51%) was explained by the variables investigated. In particular, variability caused by differences in grazing pressurewas the most important (25%), followed by variables related to nutrient availability (11%), meadow structure (6%), light (5%) andseagrass shoot length (4%). Among integrative community variables investigated, species richness was also best explained bygrazing and nutrients.© 2007 Elsevier B.V. All rights reserved.

Keywords: Epiphytic assemblages; Large-scale; Macrograzers; Nutrients; Posidonia oceanica; Species richness

1. Introduction

Seagrass epiphytes are important functional elementsof seagrass meadows, contributing significantly to theoverall productivity of the system and to both vertical(food chain length) and horizontal (richness andheterogeneity within trophic levels; see review by

Borowitzka et al., 2006) tendencies. Epiphytic algaeare characterised by short generation times and rapidgrowth. Their photosynthetic rates can double those oftheir seagrass hosts, and productivity values can matchthose of seagrass leaves in some instances (Morgan andKitting, 1984; Williams and Heck, 2001). Seagrassepiphytes are also a fundamental food source for nu-merous taxa of vagile fauna (Buia et al., 1992; Gambiet al., 1992). In fact, the feeding habits of certain grazersclosely follow patterns of epiphyte distribution, pointingto the existence of well-differentiated niches basedon epiphytic resources (Mazzella and Russo, 1989).

Journal of Experimental Marine Biology and Ecology 350 (2007) 130–143www.elsevier.com/locate/jembe

! Corresponding author. Tel.: +34 972 33 6101; fax: +34 972337806.

E-mail address: patricia@ceab.csic.es (P. Prado).

0022-0981/$ - see front matter © 2007 Elsevier B.V. All rights reserved.doi:10.1016/j.jembe.2007.05.033

Additionally, epiphytes can also influence otherimportant ecosystem processes such as sedimentformation and nutrient cycling (Borowitzka et al.,2006). As a result, there has been a growing body ofresearch attempting to understand variation in epi-phytic communities in space and time (Vanderklift andLavery, 2000; Saunders et al., 2003; Johnson et al.,2005), particularly in order to discriminate betweennatural and human-induced sources of variability(Pardi et al., 2006).

The diversity, distribution and abundance of seagrassepiphytes are the result of multiple and interactingabiotic and biotic factors that operate at a variety ofscales. Among the abiotic factors, light, water motionand nutrients have a key influence. For instance,attenuated light intensity and altered quality of incidentlight can determine species replacement and epiphyticproductivity (Cambridge and Hocking, 1997; Dalla Viaet al., 1998; Robbins and Bell, 2000). Water motioncontrols several aspects related to epiphytic growth,such as leaf fouling in sheltered areas (Kendrick andBurt, 1997), and supply of algal propagules (Norton,1992), and food for filter-feeding epifauna (Ardissonand Bourget, 1992). However, nutrients are possiblythe most documented factor influencing epiphyticcommunities, with several observational and experi-mental studies having reported important increases inepiphytic biomass in response to nutrient loading(Tomasko and Lapointe, 1991; Borum, 1985; Mooreet al., 1996). In fact, the capacity of epiphytes toreflect changes in nutrient conditions makes themsensitive indicators of natural and anthropogenicdisturbances (Cambridge et al., 1986; Delgado et al.,1999; Ruiz et al., 2001).

Among the biotic factors that influence epiphyticcommunities, we can discern between those associatedwith the structural features of the host plant and thosethat involve trophic interactions between plants, herbi-vores and their predators. Structurally, the density of theseagrass canopy can significantly modify epiphyticbiomass, presumably due to effects of light penetration(Carruthers, 1994), whereas shoot morphology and leafage can influence epiphyte distribution and abundancedue to differences in the surface area that is available forepiphyte settlement (Casola et al., 1987; Knowles andBell, 1998; Lavery and Vanderklift, 2002). In terms ofbiotic interactions, herbivory is probably the most citedmechanism influencing epiphytic biomass and speciescomposition (Neckles et al., 1993; Jernakoff et al., 1996;Alcoverro et al., 1997a,b; Hays, 2005). However,different grazers can influence epiphytic algal commu-nities in contrasting ways. Mesoherbivores such as

copepods, isopods and amphipods directly removeepiphytic biomass (review by Borowitzka et al., 2006)representing up to 40% of epiphytic algal production(Peduzzi, 1987) and species-specific differences in thediet selectivity of different mesograzers can stronglyinfluence epiphyte species composition (Duffy andHarvilicz, 2001; Duffy et al., 2001). In contrast,macrograzers such as fish, sea urchins, sirenids, turtlesand waterfowl indirectly influence epiphyte commu-nities by removing the host substrate (review by Heckand Valentine, 2006). While much is known about theimpact of mesograzers on seagrass epiphytic commu-nities (reviews by Jernakoff et al., 1996; Borowitzkaet al., 2006), the significance of macrograzer consump-tion on epiphyte diversity, abundance and distribution isunclear.

A substantial part of the spatial variation in seagrassepiphytes can be attributed to depth-related verticalgradients in biotic and abiotic variables (Witman andDayton, 2001 and references therein). Such gradientsare decreased light and increased nutrient availability indeeper waters (Ballesteros, 1987; Alcoverro et al., 2001)and stronger herbivore pressure in shallow waters(Boudouresque and Verlaque, 2001; Tomas et al.,2005a). Additionally, horizontal gradients in variablessuch as wave exposure, water temperature, and geo-graphic distributions can also modify communitycomposition (Witman and Dayton, 2001). Althoughthe relevance of such gradients in explaining the dis-tribution patterns of seagrass epiphytic assemblages hasrepeatedly been evidenced (Vanderklift and Lavery,2000; Saunders et al., 2003; Johnson et al., 2005; Pardiet al., 2006), no attempt to assess these patterns againstthe potential biotic and abiotic factors that may bestructuring these communities has been made.

In this study we investigated the relative importanceof abiotic (light and nutrients) and biotic factors(meadow structure, macroherbivory and shoot mor-phology) in determining the patterns of spatialepiphyte species distribution and abundance. Wefocused on the epiphytic community growing on theMediterranean seagrass Posidonia oceanica, whichforms extensive meadows from the shallow sublittoralto about 30 to 40 m depth and is widely distributed inMediterranean coastal waters. The epiphytic commu-nity of this seagrass is among the most diverse andwell structured due to the longevity of P. oceanicaleaves of up to 300 days, the longest life-span knownin seagrasses (Hemminga and Duarte, 2000). Inaddition, leaf consumption by macrograzers onshallow P. oceanica represents 57% of the annualaboveground primary production (Prado et al., 2007).

131P. Prado et al. / Journal of Experimental Marine Biology and Ecology 350 (2007) 130–143

Multiple correlation analyses were used to investigateassociations between integrative community variables(species richness, alpha diversity and epiphytic biomass),biotic variables (seagrass shoot length, grazing andmeadow structure) and abiotic variables (light andnutrients). The influence of these variables in the structureof the whole community was assessed using multivariateanalyses.

2. Materials and methods

2.1. Study area and collection of samples

Eight sites were sampled along the Catalan Coast,in the North-East of Spain (see Fig. 1). Distances

varied between sites, but were at least 10 km apart,depending on the presence of P. oceanica meadows.Sites were chosen so as to encompass a maximumvariability of meadows. Two different depths (5 and15 m) were sampled in those sites where both shallowand deep meadows existed (Montroig, Coma-ruga,Fenals, Montjoi and Jugadora). In the remaining sites(Sitges, Mataró and Montgó), only deep meadows(15 m depth) were sampled because of the absence ofshallow ones.

Field sampling was conducted in October–No-vember 2002. At each site and depth, three zones ofabout 20 m diameter were selected. Within eachzone, six replicate shoots of P. oceanica wererandomly collected. Three of them were placed in

Fig. 1. Map of the Northeast Spanish coast (NW Mediterranean) showing the position of the study sites and sampling depths.

Table 1Results of one-way ANOVA on A) Species richness, B) Alpha diversity, and C) Epiphytic biomass on the oldest leaf of Posidonia oceanica(significant results are given in bold)

ANOVA A) Species richness B) Alpha diversity C) Epiphytic biomass

Source ofvariation

df MS F p MS F p MS F p

Site = S 12 284.71 23.181 0.0000 0.248 6.2031 0.0000 0.021 4.2143 0.0000Transf: !x; C=0.236 Transf: Arcsen x; C=0.19 Transf: !!x; C=0.186

132 P. Prado et al. / Journal of Experimental Marine Biology and Ecology 350 (2007) 130–143

plastic bags, with 95% seawater and 5% formalin inorder to preserve epiphytes for further taxonomicstudy. The three remaining shoots per zone werekept in an icebox and transported to the laboratoryfor morphological measures (shoot length andmacroherbivores' bite marks), epiphytic biomassand for determination of nutrient content of leavesand epiphytes.

2.2. Epiphytic composition and community measures

The most external leaf of the shoot (i.e. the oldestone) of approximately 20–40 cm was selected asrepresentative of mature epiphytic assemblages (Van-derklift and Lavery, 2000; Piazzi et al., 2004). In thelaboratory, leaf cover of encrusting species such asHydrolithon spp. and Titanoderma pustulatum, wasdetermined through visual estimation under the micro-scope prior to detachment with a razor blade. A cover of0.1% was assigned to rare and small species (erect orprostrated filaments in the order of 10s to 100s of !m)that were found only once in a leaf (e.g. Ballesteros,1987; Cormaci et al., 2004; Cebrian and Ballesteros,2004). Leaf cover values for the three collected leavesper zone were pooled in order to reach the minimumsampling area identified by Ballesteros (1987), andzones were used as replicates throughout the study.

Epiphytic biomass was measured as the mass inmg of DWof sessile organisms on the oldest leaf of eachshoot. Species richness was calculated as thetotal number of species found on that same leaf andalpha-diversity estimated from the Shannon index:

H V! –Xs

i!1

"pi "log2 pi#

Where s is the number of species and pi the relativecover of the species i.

2.3. Biotic factors

Meadow structure was assessed by measuring shootdensity in twelve random 40!40 cm quadrates per site(Alcoverro et al., 1995) and seagrass cover in twenty-seven 50!50 cm quadrates per site, placed at increasingdistances along radially oriented transects. Shoot length(cumulative length for all leaves within a shoot) wasmeasured to the nearest cm on nine replicate shoots persite.

Herbivore impact was estimated using two comple-mentary variables: (i) the number of grazing marks per

shoot (fish or sea urchin bite marks, Boudouresque andMeinesz, 1982) and (ii) the length of the oldest, mostexternal leaf. As the oldest leaf is the one exposed tograzers for the longest period, its length is signifi-cantly correlated to herbivore pressure in the study area(r="0.74; pb0.05; additional data from Prado et al.,2007).

Fig. 2. A) Species richness, B) Alpha diversity and, C) Epiphytebiomass (±SE) found in the oldest leaf of Posidonia oceanica at eachstudy site. Significantly different groups (SNK tests based ontransformed data; see Table 1) are indicated with letters.

133P. Prado et al. / Journal of Experimental Marine Biology and Ecology 350 (2007) 130–143

2.4. Abiotic factors

Yearly averaged Secchi disc data from Camp et al.(2001) were used to calculate the attenuation coefficientof light (K=1.7 /ZSD: Poole and Atkins, 1929) at eachsampling site and to estimate the proportion of surfacelight reaching the leaf canopy at each sampling site anddepth.

To evaluate differences in nutrient availabilityamong study sites two integrative plant variableswere used: (i) the nitrogen content of the secondyoungest leaf of each shoot clean of epiphytes. Thisleaf is usually largely developed, but has not yetsuffered the nutrient decline associated with ageing(Alcoverro et al., 2000), and thus is the one betterreflecting nutritional status of the shoot (Alcoverroet al., 2001). (ii) The nitrogen content of epiphytes

presents in the shoot. Leaves and epiphytes of thewhole shoot were dry-weighed separately (60 °C,48 h), reduced to powder and used in the determinationof carbon and nitrogen content with a Carlo-Erba CHNAuto-analyser.

2.5. Univariate analyses

Species richness, alpha diversity, epiphytic bio-mass and leaf cover values of epiphytic algae andepifauna were investigated with one-way ANOVAwith site as fixed factor. Data were first tested fornormality (Chi-square test) and homogeneity ofvariances (Cochran's test) and transformed whennecessary (square root, fourth root or arc sin x;transformations used in each case are indicated in thecorresponding tables) to satisfy ANOVA assumptions.For all analyses, the level of significance was fixed atp=0.05. Student–Newman–Keuls post hoc compar-isons were used to investigate significant differencesamong sites.

Multiple correlation analyses were used to investi-gate associations between integrative community vari-ables (species richness, alpha diversity and epiphyticbiomass) and biotic (shoot length, number of bite marks,length of the most grazed leaf, shoot density, meadowcover) and abiotic variables (light, nitrogen in leavesand epiphytes).

Fig. 3. Percent cover (±SE) of epiphytic algae and epifauna (per sample leaf) at each study site. Significantly different groups of algae are indicated inblack and those of animals in grey letters (SNK tests, animal data has been transformed; see Table 2).

Table 2Results of one-way ANOVA on percent cover of A) epiphytic algaeand B) epifauna found on the oldest leaf of Posidonia oceanica at thestudy sites (significant results are given in bold)

ANOVA A) Epiphytic algae B) Epifauna

Source ofvariation

df MS F P MS F P

Site = S 12 456.40 6.3343 0.0000 0.2715 3.3805 0.0000Transf: "; C=0.270 Transf: !!x; C=0.594

134 P. Prado et al. / Journal of Experimental Marine Biology and Ecology 350 (2007) 130–143

2.6. Multivariate analyses

Rare species present in very low abundance (less thanthree samples) were removed from the analyses. Theassumption that assemblages exhibit a linear response tothe environment was first tested with a DCA analysis(Hill and Gauch, 1980) in the CANOCO package (terBraak, 1987). Lengths of ordination axes were roughly2.5 SD, indicating that a linear approach was appropri-ate (data are non-linear when ordination lengths aregreater than about 3 SD; Hill and Gauch, 1980). Weused the MVSP multivariate statistical package(Kovach, 1998) to construct comparable metric MDSordinations (Torgerson, 1952) of species and biotic(shoot length, number of bite marks, length of the mostgrazed leaf, shoot density, meadow cover) and abioticvariables (light, nitrogen in leaves and epiphytes).

Related Metric Scaling (RMDS) was used to constructa new ordination, which combines the information of thetwo previous distance matrices, thus allowing assess-ment of possible redundant information (Cuadras andFortiana, 1995). The significance of the interactionbetween epiphytic assemblages and explicative vari-ables was investigated with a distance-based redundan-cy analysis (db-RDA) for a linear model (McArdle andAnderson, 2001) available in the DISTLM program(http://www.stat.auckland.ac.nz/~mja).

3. Results

3.1. Epiphytic taxa

A total of 129 taxa were observed growing on theoldest leaf ofP. oceanica (seeAppendix I). Taxa included:cyanobacteria (8 taxa), xanthophytes (1 taxon), rhodo-phytes (55 taxa), phaeophytes (18 taxa), chlorophytes(9 taxa), hydrozoans (13 taxa), bryozoans (23 taxa) andascidians (2 taxa). However, only 6 taxa had leaf coversaveraging more than 1%: encrusting coralline algaeincluding the complex of Hydrolithon farinosum andPneophyllum spp. (16.8%) and T. pustulatum (1.8%),phaeophytes including Sphacelaria cirrosa (3%) andDictyota linearis (1.2%), the bryozoanElectra posidoniae(3%) and the hydrozoan Sertularia perpusilla (1.3%).The rest of the taxa were formed by occasional and smallspecies which were, nonetheless, relevant to explainobserved differences among sites.

Fig. 4. MMDS of A) species and B) environmental variables, showingordination results for each location (shallow sites are expressed in greyand deep sites in black). Cumulative percentage of variance in the dataexplained by ordination axis I and II: A) 37% and B) 38.5%. Originalspecies data were ln (x+1) transformed and standardised by SDdivision. Environmental data were (x"mean /SD)+C standardised.Distance used was Bray–Curtis. Mr = Montroig; C = Coma-ruga; S =Sitges; Mt = Mataró; F = Fenals; Mg = Montgó; Mj = Montjoi; J =Jugadora.

Fig. 5. RMDS ordination from species and environmental dissim-ilarities matrices. Cumulative percentage of variance explained byordination axis I and II: 45%. Original species data were ln (x+1)transformed and standardised by SD division. Environmental datawere (x"mean /SD)+C standardised. Distance used for species datawas Bray–Curtis and Hellinger for the environmental data. Site namesas in Fig. 4.

135P. Prado et al. / Journal of Experimental Marine Biology and Ecology 350 (2007) 130–143

3.2. Spatial patterns

Species richness, alpha-diversity and epiphytic bio-mass in the oldest leaf displayed significant differencesamong sites (see Table 1). The range for species richnesswas highest in shallow sites, from 9.8±1.5 taxa in Fenalsto 27.1±1.1 taxa in Jugadora (Fig. 2A). In contrast, alpha-diversity seemed to vary the most at deep sites (1.4±0.05in Fenals to 2.6±0.34 in Montjoi; Fig. 2B). Epiphyticbiomass ranged from 5±0.3 mg DW leaf"1 (Fenals, 5 m)to 42±7.4 mg DW leaf"1 (Montroig, 15 m, Fig. 2C).

Cover by algal and animal epiphytes also differedsignificantly among study sites (Table 2). Cover by

epiphytic algae was consistently higher than by epifaunain all sites, but such differences were sharper in deepmeadows, with highest algal: animal ratios than inshallow ones (see Fig. 3). Leaf cover by epiphytic algaewas particularly high in deep meadows.

MMDS ordination of samples following speciescomposition showed similar groupings to those formedby observation of the above-mentioned variables (speciesrichness and leaf cover by epiphytic algae and epifauna).The two first axes explained 37% of the variance, andseparated shallow and deep sites, andwithin shallow sites,the two northernmost locations (Mj and J) from the rest(Fig. 4A). The N to S situation of the meadows was also

Table 3Multiple correlation results for biotic and abiotic variables influencingA) species richness, B) alpha diversity, and C) epiphytic biomass

A) Variables influencing species richnessMultiple R 0.926!!!

df 11, 18F 9.863β coefficientsLength most grazed leaf 0.778N Posidonia 0.60Seagrass cover 0.624

B) Variables influencing alpha diversityMultiple R 0.720df 11, 18F 1.769

C) Variables influencing epiphytic biomassMultiple R 0.693df 11, 18F 1.512

Significant R values are indicated (!pb0.05; !! pb0.01; !!! pb0.001).Significant partial correlation coefficients are indicated in bold.

Table 4Distance based Redundancy Analysis (db-RDA) on the basis of Bray–Curtis distance, according to a linear regression model using permutations

All variables Light Grazing Shoot length Nutrients Meadowstructure

df MS df MS df MS df MS df MS df MS

Regression 11 4015.51 1 4974.0 3 4317.84 1 5409.81 4 3571.57 2 3971.44Residual 27 2803.47 37 3285.0 35 3036.93 37 3145.89 34 3301.94 36 3294.71Total 38 1.3926 38 38 38 38 38Pseudo-F 1.5137 1.4217 1.719 1.0816 1.2054P 0.0010 0.0010 0.0010 0.0010 0.0010 0.0010

The biotic and abiotic variables included were: light, grazing (length of the most grazed leaf, fish and sea urchin bite marks), shoot length,nutrients (C and N content in seagrass and epiphytes) and meadow structure (seagrass cover and shoot density). Number of permutations used(full model) =999. Original species data were ln (x+1) transformed and double standardised by row and column sums. Significant results aregiven in bold.

Fig. 6. Pie-chart showing the proportion of variation in epiphyticassemblages explained by the biotic and abiotic variables (seeTable 4) using db-RDA multiple regression model (number ofpermutations under the full model = 999). Original species data wereln (x+1) transformed and double standardised by row and columnsums.

136 P. Prado et al. / Journal of Experimental Marine Biology and Ecology 350 (2007) 130–143

reflected in the ordination of the deep sites. Ordination ofsites was similar to that obtained with the compositionalabundance of species. Variance explained by the two firstaxis was 38.5%, and the ordination pattern was similar,although with less distinct groups (Fig. 4B). A jointrepresentation of species and biotic and abiotic variables(RMDS) resulted in only a slight improvement in thecumulative percentage of variance explained by axes I andII (45%) indicating that information given by both speciesabundances and biotic/abiotic variables was largelyredundant (see Fig. 5).

3.3. Influence of biotic and abiotic variables on epiphyticassemblages

Multiple correlation results were highly significantfor species richness (Table 3A; r=0.927, pb0.001).The highest and most significant partial correlationcoefficients were the length of the oldest, most grazedleaf, seagrass cover and nutrient availability (bothnitrogen content in seagrass and epiphytes). However,no significant multiple correlation were found foralpha-diversity or for epiphyte biomass (Table 3Band C).

From the perspective of the whole assemblage, allbiotic and abiotic variables investigated showed signif-icant contributions to observed differences in thestructure of epiphytic assemblages and explained up to51% of total variation (Table 4, Fig. 6). Among them,grazing-related variables (length of the most grazed leafand herbivore bite marks) emerged as the mostimportant explanatory variables (25% of variation),followed by variables related to nutrient availability(11%), meadow structure (6%), light (5%), and seagrassshoot length (4%; see Fig. 6). However, a large amountof variation (49%) remained unexplained by thosefactors.

4. Discussion

This study illustrate the importance of macroherbivoregrazing as a key factor controlling epiphytic communitycomposition in P. oceanica, accounting for ca. 25% of theobserved variability. Whilst the importance of mesogra-zers in structuring seagrass epiphytic assemblages is wellrecognised (Duffy et al., 2001; Duffy and Harvilicz,2001), this is the first study to show a direct effect ofmacrograzers on the taxonomic composition of thesecommunities. Nutrient availability was the secondexplanatory variable (11%), followed by structuralvariables of the meadow (i.e. shoot density and seagrasscover: 6%), light (5%) and seagrass shoot length (4%).

Species richness also displayed a highly significantassociation with the ensemble of biotic and abioticvariables investigated. Again those related to seagrassconsumption by grazers (i.e. length of the most grazedleaf) consistently showed the highest effects, suggestingthat the availability of leaf area influences the distributionand abundance of epiphytes (Alcoverro et al., 1997a;Tomas et al., 2005a).

The two main consumers of P. oceanica, the fishSarpa salpa and the sea urchin Paracentrotus lividusare macroherbivores that both have a distributionmarkedly skewed with depth, and exert their maximalpressure in shallow beds (0–10 m; Boudouresque andVerlaque, 2001; Tomas et al., 2005b). This unevenpressure was well reflected in the higher numbers ofherbivore marks and shorter length of the most grazedleaf observed in shallow meadows compared to deepones. The importance of seagrass leaf consumptionby macrograzers on shallow P. oceanica has onlyrecently been recognised by Prado et al. (2007), whofound rates of consumption in shallow meadowsaveraging 57% of the annual aboveground primaryproduction of this species. The present study furtheremphasises the importance of these herbivores, puttingforward the notion of their regulatory capacity on theepiphytic assemblage composition and biodiversity.The significantly shorter leaves found in shallowmeadows entail important differences in the surfacearea available for epiphytic settlement and develop-ment (Cinelli et al., 1984). Since herbivores mostlyconsume the older parts of the leaves (Cebrián et al.,1996) that are more heavily colonised by erect epi-phytic algae (Ben, 1969; Casola et al., 1987), dif-ferences in herbivory pressure may explain the loweralgae: animal cover ratio observed in most of theshallow seagrass meadows examined compared todeep ones. This is in opposition with previous studiesreporting higher abundance of animals than algae indeep meadows (Lepoint et al., 1999), possibly due tothe effect of irradiance penetration on sites subjectedto low herbivory.

Species composition of P. oceanica was similar tothat reported previously for the same season (Balles-teros, 1987). Leaf cover was dominated by Corallina-ceae and some zooepiphytes such as the hydrozoanS. perpusilla and the bryozoan E. posidoniae. Theabundant phaeophytes S. cirrosa and D. linearis wereprobably the remains of the summer community. Therewere distinctive compositional patterns between shallowand deep meadows, also in accordance with previousfindings (Battiato et al., 1982; Cinelli et al., 1984;Ballesteros, 1987).

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The importance of nutrients and light in accountingfor the variability in epiphytic assemblages was sur-prisingly low compared to evidence from other studies(e.g. Borum, 1985; Sand-Jensen, 1989; Neckles et al.,1993; Lapointe et al., 1997). In the Mediterranean,large-scale seasonal forcing resulting from changes inlight and nutrient conditions is a well-recognised sourceof variability for seagrass meadows (Alcoverro et al.,1995, 1997b). This may be due to the sampling time(autumn), in which the epiphytic community is not fullydeveloped.

The existence of a large amount of unexplainedvariation (49%) suggest the presence of unaccountedprocesses, and possibly the existence of environmentalheterogeneity at a range of spatial hierarchies not fullyassessed in this study (Vanderklift and Lavery, 2000;Lavery and Vanderklift, 2002; Piazzi et al., 2004;Johnson et al., 2005). Among them, some factors notinvestigated were general patterns of circulation, coastalgeomorphology and genetic continuity of populations,all of which may be a relevant source of variability forbiological communities (Underwood and Petraitis,1993; Pardi et al., 2006). Local hydrodynamics(Mazzella and Ott, 1984; Kendrick and Burt, 1997),salinity (Kendrick et al., 1988) and differences in tissueage and leaf productivity (Mazzella and Ott, 1984;Casola et al., 1987) may also contribute to unexplainedvariability in species composition. Additionally, epi-phytic composition may be influenced by mesograzers(Mazzella and Russo, 1989; Duffy et al., 2001; Duffyand Harvilicz, 2001). A substantial part of this un-explained variability can also be caused by differencesamong northern and southern meadows. However, ithas to be emphasized that such differences cannot besolely attributed to latitudinal gradients, as northernand southern meadows differed also in nitrogenconcentrations in leaves and epiphytes (minimum inthe north), probably caused by different degrees ofeutrophication, and contrasting habitat features. On theone hand, the existence of different climatic conditionsand higher water temperature in southern sites(MEDAR/MEDATLAS II database, 2004) may delaythe annual seasonal migration of the fish S. salpatowards deeper waters in the autumn (Harmelin-Vivienand Francour, 1992; Francour, 1997; Peirano et al.,2001; Tomas et al., 2005b). This delay may thus resultin higher herbivory pressure in southern sites duringthe study period (Prado et al., 2007). However,nitrogen availability has been shown to influence notonly epiphytic communities (Borum, 1985; Sand-Jensen, 1989; Neckles et al., 1993; Lapointe et al.,1997) but also macroherbivores behaviour (Ruiz et al.,

2001; Valentine and Heck, 2001; Goecker et al., 2005).In addition, higher habitat heterogeneity in theNorthern coast and the abundance of neighbouringrocky benthic communities could also influenceepiphytic community composition by enhancing thesupply of algal propagules (see van Elven et al., 2004for a similar links between seagrass meadows andmacroalgal reefs). In fact, the abrupt coastal topogra-phy of northern sites provides an adequate substratefor the development of benthic algal communities(Mestres et al., 1989; Buxó et al., 2002) in closecontact with the meadows. This contrasts with thesouthern meadows, most often located far away fromthe coastline (N500 m) and isolated in sandy bottoms.Consequently, the interaction between herbivory andlarge-scale supply of algal propagules may account, atleast in part, for the differences between shallow northernand southern meadows, and may also explain the higherextent of similarity between shallow and deep meadowsin the northern sites, particularly for species richness.

In short, we have identified the sources of animportant part (51%) of the variability in thecomposition of epiphyte communities on P. oceanicaleaves, at least at the sampling time. Biotic factorsplay a determinant role in structuring such commu-nities (35%), and in particular, grazing by macro-herbivores emerges as a central variable, accountingfor approximately 25% of the variation. Abioticfactors are responsible for 16% of the variation, andamong these, nutrient availability seems the mostimportant, contributing to 11% of the variation. Theunexplained variability (49%) also evidences thepresence of unaccounted processes, some of thempossibly related to N–S differences. Since someenvironmental variables such as nutrient availability,light and herbivory vary not only spatially but alsoseasonally, studies across a range of temporal scales arerecommended to assess the persistence of local patternsand evaluate the repercussions in the ecosystem as awhole.

Acknowledgement

We are grateful to E. Ballesteros for patience andassistance with identification of epiphytic algae and toT. García-Rubies for help with taxonomy of epifauna.This work was supported by a FI scholarship to PPfrom the Departament d'Universitats, Recerca iSocietat de la Informació (DURSI, Generalitat deCatalunya) and the REN2002-04020/MAR projectfrom the Spanish Ministry of Science and Technology.[SS]

138 P. Prado et al. / Journal of Experimental Marine Biology and Ecology 350 (2007) 130–143

Appendix A

Supplemental Table 1Species list of the macroalgae and sessile epifauna found growing over the oldest leaf of Posidonia oceanica in October–November 2002

5 m 15 m

Mr C F Mj J Mr C Mt S F Mg Mj J

CyanophyceaeAnabaena variabilis 0 0 0 0 0.011 0 0 0 0 0 0 0 0Calothrix confervicola 0 0 0 0.178 0.411 0.022 0 0 0 0 0 0.011 0Hydrocoleum sp. 0 0 0 0 0.011 0 0 0 0 0 0 0 0Lyngbya meneghiniana 0.044 0.044 0 0.056 0.089 0.1 0.011 0.044 0.067 0.067 0.089 0.056 0.1Lyngbya sordida 0.011 0 0 0.078 0.1 0.089 0.011 0.067 0.033 0.056 0.067 0.022 0.111Microchaete sp. 0 0 0 0 0.011 0 0 0 0 0 0 0 0Phormidium sp. 0 0 0.133 0.056 0.056 0.2 0.089 0.3 0.144 0.244 0.367 0 0.5Unidentified Hormogonales 0 0 0 0 0 0 0 0 0 0.011 0 0 0XantophyceaeNematochrysopsis marinum 0 0 0 0 0 0 0 0 0 0.022 0.011 0 0RodophyceaeAcrosorium venulosum 1.333 0 0 0 0 0 0 0 0 0 0 0 0Aglaothamnion brodiei 0 0 0 0.311 0 0.178 0 0 0.011 0.011 0.044 0.1 0.2Aglaothamnion byssoides 0.011 0.044 0 0.111 0.189 0.1 0.033 0.089 0.067 0.022 0.211 0.111 0.167Aglaothamnion tripinnatum 0.011 0.233 0 0.011 0.022 0.011 0 0.044 0.011 0.011 0 0.056 0.038Antithamnion cruciatum 0 0 0.156 0.278 0.4 0 0 0.1 0 0.233 0.078 0.078 0.211Antithamnion heterocladum 0 0 0 0.011 0.067 0 0 0 0 0 0.044 0 0.089Antithamnion ogdeniae 0 0 0 0 0 0 0 0 1.367 0 0 0 0Callithamniella tingitana 0 0 0 0.033 0.067 0.044 0.011 0 0.011 0 0.078 0.011 0.011Ceramium cingulatum 0 0 0 0.033 0.067 0.044 0.011 0 0.011 0 0.078 0.011 0.011Ceramium circinatum 0 0 0 0 0.056 0 0 0 0 0 0 0 0Ceramium codii 0 0 0 0 0.011 0 0.022 0.011 0.1 0 0.072 0 0.044Ceramium diaphanum 0 0.011 0 0.056 0.2 0 0 0 0 0 0 0 0Ceramium flaccidum 0.033 0.156 0.256 1.8 3.278 0.511 0.011 0.089 0.022 0.033 0.333 0.856 0.367Ceramium strictum 0 0 0 0 0 0 0 0.011 0 0.089 0 0 0Champia parvula 0 0 0.011 0 0 0.033 0.311 0 0.589 0 0 0 0Chondria capillaris 0 0 0 0.456 0.156 0.156 0 0 0 0.022 0.044 0.167 0.278Chylocladia verticillata 0 0 0 0.222 0.211 0.244 1.167 0.011 0.167 0.133 0 0.333 0.111Colaconema daviesii 0.1 0.1 0.078 0.078 0.078 0.044 0 0.022 0 0.022 0.056 0 0.022Colaconema leptonema 0.011 0 0 0.033 0 0 0 0 0 0 0 0.022 0Colaconema saviana 0 0 0 0.011 0 0 0 0 0 0 0 0 0Colaconema sp. 0.011 0.011 0 0.044 0.011 0 0 0 0 0 0 0.022 0Compsothamnion gracillimum 0 0 0.011 0 0 0 0 0 0 0 0 0 0Crouania attenuata 0 0 0 0.278 1.089 0.089 0.011 0.011 0.144 0.078 0.078 0.544 0.378Dasya corymbifera 0 0.022 0 0.133 0.5 0.011 0 0 0 0 0.022 0 0.033Dasya hutchinsiae 0 0 0 0 0.011 0.011 0 0 0 0 0 0 0.011Dasya ocellata 0 0 0 0.256 0 0.1 0 0.022 0.033 0.078 0.256 0.078 0.233Dasya sp. 0 0 0 0.011 0 0 0 0 0 0 0 0.011 0Erythrotrichia carnea 0.089 0.089 0.067 0.067 0.089 0.1 0.022 0.022 0.089 0.056 0.067 0.067 0.067Eupogodon spinellus 0 0 0 0 0 0 0 0 0 0 0.078 0 0Falkenbergia rufolanosa 0 0 0.022 0.022 0.078 0 0.033 0.044 0.011 0.056 0.044 0.122 0.089Herposiphonia secunda 0.011 0.089 0 0.011 0 0 0 0 0 0.022 0.011 0.111 0Heterosiphonia crispella 0.011 0 0 0 0 0 0 0 0.033 0.067 0 0 0Hydrolithon farinosum+

Pneophyllum spp.11.89 19.44 3.111 12.56 17.22 28.89 17.78 13.56 19.44 26.67 25.56 14.11 16.67

Laurencia chondrioides 0 0 0 0 0 0 0 0 0.278 0.056 1.856 1.522 0.767Laurencia minuta 0 0 0 0 0.1 0.044 0 0 0 0 0 0.022 0Laurencia sp1. 0 0 0 0 0.011 0 0 0 0 0 0 0 0Laurencia sp2. 0 0 0 0 0.022 0 0 0 0.011 0 0 0 0Lejolisia mediterranea 0 0 0 0.122 0.011 0.044 0 0.011 0.022 0 0.011 0 0.067Lomentaria clavaeformis 0 0 0 0 0 0.011 0 0 0.022 0 0.011 0 0Monosporus pedicellatus 0 0 0 0 0.011 0 0 0 0 0 0 0 0Nitophyllum micropunctatum 0 0 0.078 0.111 0.2 0.233 0.389 0.011 0.044 0.111 0.033 0.944 0.311

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139P. Prado et al. / Journal of Experimental Marine Biology and Ecology 350 (2007) 130–143

Appendix A (continued)

5 m 15 m

Mr C F Mj J Mr C Mt S F Mg Mj J

Osmundea gr. truncata 0 0 0 0 0 0.011 0.011 0 0.022 0 0.078 0 0Osmundea sp. 0 0 0 0 0.033 0.011 0.011 0 0.022 0 0.078 0 0Polysiphonia scopulorum 0 0.122 0.056 0.056 0 0 0.022 0.022 0.178 0 0.233 0 0.056Polysiphonia sp1. 0 0 0 0 0 0.033 0.289 0 0.2 0.044 0 0.133 0.033Polysiphonia sp2. 0.022 0.589 0 2.611 0.922 0.222 0 0 0.011 0.1 0.133 0.211 0.144Ptilothamnion pluma 0 0 0 0 0.011 0 0 0 0 0 0 0 0Rhodophyllis divaricata 0 0 0 0 0.022 0 0 0 0 0 0 0 0Spermothamnion flabellatum 0.1 0 0.011 0.478 0.322 0.178 0 0.3 0 0.1 0.078 0.944 0.356Spermothamnion repens 0.011 0 0 0.167 0.022 0.111 0 0.056 0 0 0 0.056 0.011Stylonema alsidii 0.056 0.089 0.022 0.022 0.044 0.056 0 0 0.011 0.011 0.067 0 0Stylonema cornu-cervi 0 0.022 0.033 0 0 0 0 0.011 0 0 0 0 0Titanoderma pustulatum 0.022 2.889 0 0.011 0.067 2 1.278 0.333 0.778 7.778 1.889 0 3.889Vickersia baccata 0 0 0 0 0 0 0 0 0 0 0 0.022 0Wrangelia penicillata 0 0 0 0.011 0.022 0.167 0 0 0 0 0.022 0.011 0PhaeophyceaeDictyopteris polypodioides 0 0 0 0 0 0 0 0 0.222 0 0 0 0Dictyota dichotoma+linearis

0 0 0 0 0.356 2.889 0.333 0 1.056 0 1.111 7 2.078

Ectocarpus fasciculatus 0 0 0 0 0.011 0 0 0 0 0 0 0 0Ectocarpus sp. 0 0 0 0 0.011 0 0 0 0 0 0 0 0Elachista sp. 0 0.022 0 0 0 0 0 0 0 0 0 0 0Feldmania sp. 0 0 0 0 0.011 0 0 0 0 0 0 0 0Giraudia sphacelarioides 0 0 0 0 0.011 0 0 0 0 0 0 0 0Halopteris scoparia 0 0 0 0.022 0 0 0 0 0 0 0 0 0Hincksia intermedia 0 0 0 0 0.056 0 0 0 0 0 0 0 0Hincksia mitchelliae 0 0 0 0 0.011 0 0 0 0 0 0 0 0Kuckuckia spinosa 0 0.056 0 0 0.033 0 0 0 0 0 0 0 0Kuetzingiella battersii 0.011 0 0 0 0 0 0 0 0 0 0 0 0Myriactula gracilis 0 0 0.011 0 0.011 0 0 0 0 0 0 0.011 0.011Myrionema magnusii 0.011 0 0 0.011 0 0 0 0 0.011 0 0 0 0Sphacelaria cirrosa 0.044 4.111 0.356 1.156 4.611 0.022 0.011 0.033 0.111 18.33 0.467 0.333 1.344Unidentified Dictyotales 0 0 0 0 0.011 0 0.022 0 1.033 0 0.011 0 0.144Unidentified Sphacelariales 0 0 0 0 0.011 0 0 0 0 0 0 0 0ChlorophycaeaChaetomorpha aerea 0.078 0 0.078 0.078 0.044 0.022 0 0.011 0 0.011 0.1 0.033 0.089Chaetomorpha gracilis 0 0 0 0 0.011 0 0 0 0 0 0 0 0Chaetomorpha sp. 0.011 0 0 0.011 0.044 0 0 0 0 0 0 0 0Cladophora dalmatica 0.967 0.256 0 0.044 0.411 0 0 0 0 0.011 0 0.011 0.033Cladophora sp. 0 0.011 0 0 0.011 0 0 0 0 0.022 0.011 0 0.011Cladophora socialis 0 0 0 0.122 0 0 0 0 0 0.011 0.022 0 0Enteromorpha multiramosa 0 0.011 0 0.011 0.078 0 0 0 0 0.011 0.022 0 0Ulvella sp. 0 0.011 0 0.011 0 0 0 0 0 0 0 0 0Unidentified Cladophorales 0 0 0 0 0.011 0 0 0 0 0 0 0 0HydrozoansAglaophenia harpago 0 0 0 0 0 0 0 0 0.778 0.833 0.233 0 0Campanularia asymmetrica 0 0.056 0.011 0 0 0 0 0 0 0.011 0 0 0Cladocoryne floccosa 0 0 0 0 0 0 0.011 0 0 0 0 0 0Clytia hemisphaerica 0.056 0.022 0.778 0.022 0 0.033 0.367 0 0.078 0.133 0.022 0 0.033Clytia linearis 0 0 0 0 0 0 0 0 0.022 0 0 0 0Halecium nanum 0.411 0 0.011 0 0 0.022 0 0 0 0.056 0 0 0Halecium pusillum 0.178 0 0.022 0 0 0 0.067 0 0.567 0 0 0.022 0Obelia geniculata 0 0.067 0 0 0 0 0.778 0 0.367 0 0 0 0Plumularia obliqua 0.822 2.289 0.233 0.056 0 0.478 1.278 0.389 0 0.067 0 0.089 0Sertularia perpusilla 0.3 3.844 1.967 0.011 0.033 0.911 5.944 2.367 1.8 0.133 0.033 0.222 0Sertularia distans 0.011 0 0 0 0 0 0 0 3.333 0 0 0 0Sertularella sp. 0 0 0 0 0 0 0 0 0.022 0 0 0 0Stylactis inermis 0 0 0.011 0 0 0 0 0.011 0 0 0 0.022 0

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140 P. Prado et al. / Journal of Experimental Marine Biology and Ecology 350 (2007) 130–143

Appendix A (continued)

5 m 15 m

Mr C F Mj J Mr C Mt S F Mg Mj J

BryozoansAetea sica 0 1.111 0.056 0.356 0.433 0.489 0.033 0.056 0.011 0.022 0.011 0.333 0.844Bowerbankia gracilis 0 0 0 0 0 0 0.167 0 0.689 0 0 0 0Bryozoan sp1. 0 0 0.022 0 0 0.011 0 0 0 0 0 0 0Bryozoan sp2. 0 0 0 0 0 0 0 0 0.667 0 0 0 0Bugula germanica 0 0 0 0 0 0.056 0 0 0 0 0 0 0Chorizopora brongniartii 0.367 0.422 0 0.333 0.489 0.256 0.867 0.056 3.522 0.256 0 0.222 0.156Collarina balzaci 0.022 0.022 0 1.111 0 0 0 0 0 0 0 0.056 0Crisia occidentalis 0 0 0 0 0 0.033 0.033 0 0 0 0 0 0Diaperoecia major 0 0 0 0 0.011 0 0 0 0 0 0 0 0Diaperoecia sp. 0 0.011 0 0.089 0.011 0.067 0.033 0.011 0 0 0 0.011 0Disporella hispida 0.078 0.456 0 0.022 0 0.033 0.056 0.022 0.056 0 0 0 0Electra pilosa 0.056 0 0 3.222 0.378 0.244 0 0 0 0 0.111 0.056 0.278Electra posidoniae 6.333 18.89 0 4.056 0.333 0.056 0 0.167 0 0 0.133 0 0.056Fenestrulina joannae 0.244 0.056 0 0.556 0.311 0.022 0 0.133 0 0.111 0 0.122 0Fenestrulina malusii 0 0.611 0 0 0 0 0 0 0 0 0 0 0Lichenophora sp. 0 0 0 0 0 0 0 0 0.056 0 0 0 0Microporella ciliata 0 0 0 0 0 0 0.033 3 0.333 0.167 0 0 0.1Mimosella gracilis 0 0 0 0 0 1.144 0 0 0 0 0 0 0Mimosella verticillata 0 0 0.056 0.222 0.422 0.156 2.333 0.311 0.111 0.356 0 1.8 1.111Puellina gattyae 0 0.011 0 0 0 0 0 0 0 0 0 0 0.022Scrupocellaria reptans 0 0 0.022 0 0 0.011 0 0 0 0 0 0 0Scrupocellaria scruposa 0 0 0.022 0 0.022 0.033 0 0 0 0 0 0 0Umbonula ovicellata 0 0 0 0 0 0 0 0 0.889 0.111 0 0 0AscidiansBotryllus schlosseri 0 0.111 1.111 0 0 0.44 0 0.078 0.056 0 0.167 0 0Unidentified Didemnidae 0 0 0 0.078 0 0.022 0 0 0 0 0 0 0.444

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