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This article was downloaded by: [Felline, Serena] On: 7 September 2010 Access details: Access Details: [subscription number 926279981] Publisher Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 3741 Mortimer Street, London W1T 3JH, UK Italian Journal of Zoology Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t741771159 Effects of marine cage aquaculture on macrofauna assemblages associated with Posidonia oceanica meadows A. Terlizzia; G. De Falcob; S. Fellinea; D. Fiorentinoa; M. C. Gambic; G. Cancemid a Dipartimento di Scienze e Tecnologie Biologiche ed Ambientali, Università del Salento, CoNISMa, Lecce, Italy b Istituto per l'Ambiente Marino Costiero - IAMC-CNR, Torregrande-Oristano, Italy c Stazione Zoologica Anton Dohrn, Laboratorio di Ecologia Funzionale ed Evolutiva, Napoli, Italy d EVEMar, Etude et Valorisation de l'Environnement Marin - Porto-Vecchio, Corse, France First published on: 15 April 2010 To cite this Article Terlizzi, A. , De Falco, G. , Felline, S. , Fiorentino, D. , Gambi, M. C. and Cancemi, G.(2010) 'Effects of marine cage aquaculture on macrofauna assemblages associated with Posidonia oceanica meadows', Italian Journal of Zoology, 77: 3, 362 — 371, First published on: 15 April 2010 (iFirst) To link to this Article: DOI: 10.1080/11250000903464075 URL: http://dx.doi.org/10.1080/11250000903464075 PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Italian Journal of Zoology, September 2010; 77(3): 362–371 Effects of marine cage aquaculture on macrofauna assemblages associated with Posidonia oceanica meadows TIZO A. TERLIZZI1*, G. DE FALCO2, S. FELLINE1, D. FIORENTINO1, M. C. GAMBI3, & G. CANCEMI4 Aquaculture impact on macrofauna of Posidonia oceanica Dipartimento di Scienze e Tecnologie Biologiche ed Ambientali, Università del Salento, CoNISMa, Lecce, Italy, 2Istituto per l’Ambiente Marino Costiero - IAMC-CNR, Torregrande-Oristano, Italy, 3Stazione Zoologica Anton Dohrn, Laboratorio di Ecologia Funzionale ed Evolutiva, Napoli, Italy, and 4EVEMar, Etude et Valorisation de l’Environnement Marin - Porto-Vecchio, Corse, France Downloaded By: [Felline, Serena] At: 13:09 7 September 2010 1 (Received 21 July 2009; accepted 27 October 2009) Abstract Marine cage aquaculture has the potential to severely impact Posidonia oceanica seagrass meadows and its associated fauna. In order to assess the impact of fish farming in a littoral bay of Corsica, France, physico-chemical (mud and organic matter) and biological (density and compactness of P. oceanica beds and associated macrofauna) variables have been examined in two stations putatively impacted to different degrees (St1 and St2) and in two unimpacted stations (Controls: C1 and C2). Principal Component Analysis of meadow structural variables (shoot density and compactness of matte) and abiotic variables (mud and organic matter percentage into sediment) highlighted differences among stations and, particularly, differences between impacted stations and controls. Results from C1 and C2 totally overlapped. St1 was the station which differed the most from controls. Compared with control stations, St1 and St2 were characterized by higher values of organic matter and mud and by lower values of shoot density and matte compactness. Permutational multivariate analysis of variance (PERMANOVA) did not show significant differences between C1 and C2 in the structure of macrofauna assemblages, whereas significant differences between the two impacted sites and between these and the control conditions emerged. Differences in assemblages were well correlated with the measured abiotic variables. The analysis showed that the species most responsible for difference among stations were typical of muddy sediment with high organic matter content. These species had higher mean abundance values at impacted stations than at controls. This study suggests fish farming determines an increase of organic matter and sedimentation, which resolve in changes in structural properties of the seagrass meadows and, consequently, changes in the associated macrofauna assemblages. Keywords: Aquaculture, seagrasses, organic enrichment, environmental impact assessment, biodiversity Introduction Boat anchoring, dredging or other destructive fishing methods, coastal engineering and spoil disposal are all examples of human impacts that affect the structure and the functioning of marine habitats (Boström et al. 2006). Aquaculture (fish and shellfish farming) is a further activity, which is growing rapidly to meet high demand of resources and to face the parallel collapse of natural fish populations. It can determine major environmental problems and impacts which could be much more severe when habitat-forming species, such as seagrass meadows, are involved (Karakassis et al. 1999; Pergent et al. 1999; Holmer et al. 2003; Pergent-Martini et al. 2006; Pusceddu et al. 2007). The impact of fish farming ranges through a variety of disturbances, often acting in a synergistic way, such as deterioration of water column and sediments, shading and physical damage (Cancemi et al. 2003; Sarà 2007). The presence of fish cages increases by 2–3 times the input of organic matter at the bottom and adjacent areas by accumulation of uneaten food and faecal pellets (Karakassis et al. 2000; Holmer et al. 2003; Pergent-Martini et al. 2006). Organic matter is mineralized and then starts to release nutrients *Correspondence: A. Terlizzi, Dipartimento di Scienze e Tecnologie Biologiche ed Ambientali, Università del Salento, CoNISMa, 73100 Lecce, Italy. Email: [email protected] ISSN 1125-0003 print/ISSN 1748-5851 online © 2010 Unione Zoologica Italiana DOI: 10.1080/11250000903464075 Downloaded By: [Felline, Serena] At: 13:09 7 September 2010 Aquaculture impact on macrofauna of Posidonia oceanica (e.g. nitrogen and phosphorus) to the surrounding waters (Delgado et al. 1999). Such organic matter input affects primarily oxygen availability in the benthos living beneath fish cages, leading eventually to anoxic conditions (Porrello et al. 2005) and proliferation of anaerobic sulphate-reducing bacteria (Holmer & Kristensen 1992; Heijs et al. 2000; Kristensen 2000) with a toxic effect for seagrasses and consequent below-ground organ mortality which are fundamental for plant survival (Delgado et al. 1999). Nutrients in the water column boost phytoplankton, epiphyte and macroalgal growth, thus causing a reduction in water transparency. This reduction, in combination with the mere presence of the fish cage (Holmer et al. 2003), affects the photosynthetic capacity of plants, resulting in a decrease of shoot density and biomass (Delgado et al. 1999; Holmer et al. 2003). After farming cessation, the decrease of rhizome growth reduces the expansion capability of P. oceanica meadows, thus affecting the recolonization in the previously impacted area (Holmer et al. 2003). Food supply attracts macrobenthic predators, fishes and sea urchins (D’Amours et al. 2008) and the increase in herbivore pressure leads to a reduction in shoot size, resulting in a further decrease in photosynthetic capability (Holmer et al. 2003). Such conditions imply low diversity of benthic macro- and meiofauna (Clarke 1993; Borja et al. 2000; Terlizzi et al. 2005b) and increase of abundance and dominance of opportunistic species (Karakassis et al. 2000; La Rosa et al. 2001; Mirto et al. 2002; D’Amours et al. 2008). The extent of the impact is determined by the size of fish farming area, by the adopted techniques, by the site-specific features (e.g. bottom topography, water exchange) and by the distance between cages and seabed (Håkanson et al. 1988; Sarà 2007). Actually, a tall water column between cages and the seabed and high current speeds increase waste dispersion and determine a lesser degree of sedimentation. Moreover, highspeed currents increase oxygenation, thus accelerating aerobic decomposition of organic matter and preventing sulfides formation (Black & McDougall 2002; Porrello et al. 2005). Posidonia oceanica meadows are facing a widespread regression in the Mediterranean with a consequent degradation of the services they provide to marine ecosystems and, indirectly, humans. The aim of this study is to investigate the response of macrofauna assemblages associated with Posidonia oceanica meadows to the disturbance caused by cage aquaculture activities. These may have, in fact, far-reaching cascade effects on the associated fauna composition and abundance via reduction of shoot density and 363 increasing local patchiness of the bed, and the load of organic matter and fine fractions on the sediment. Materials and methods Study area and sampling design The study area is situated within the Bay of Figari (41°28′13″N, 9°44′09″E) along the southwestern coast of Corsica (France). The bay is a typical ria, a narrow fluvial valley submerged by sea level rise. A river (Carcerone) carries water and sediments in the inner sector of the bay, forming a delta system. The cross-profile of the bay is typically V-shaped with a maximum depth not exceeding 15 m. Sediments of Figari Bay are mainly fine-grained with high values of mud content. Sediments are sandier in the inner sector of the bay, close to the mouth of the river. The transition from sandy to muddy sediments is associated with an abrupt increase of water depth corresponding to the delta front. In the central sector of the Bay, in the proximity of the fish farm cages, sediments are fine-grained, with mud content exceeding 90%. Toward the outer sector of the Bay, sediments show a mixed sandy– muddy grain size composition (Figure 1). The Bay is part of the Natural Reserve of the Bouches of Bonifacio, with the exception of the Figure 1. Study area and positioning of investigated stations. C1, C2: control stations, St1, St2: impacted stations by marine cages. The mud percentage (<63 μm) in the sediments of the bay is also reported. The legend of mud percentage values is reported on the right. Downloaded By: [Felline, Serena] At: 13:09 7 September 2010 364 A. Terlizzi et al. inner part, which hosts a marina and the fish farm ‘A Dorada’. Fish farming is placed at about 200 m off the shore of the bay and it is made up of 30 floating cages measuring 25 m2, with an individual volume of 60 m3, grouped into six groups of five cages. Each group is separated by about 20 m and they float over a depth of 10 m (Cancemi et al. 2003). Annual production is estimated at approximately 20–30 tons of Dicentrarchus labrax (sea bass) and Sparus aurata (sea bream) and the amount of food distributed each year is about 38 tons (Pergent et al. 1999). Since fish farming was established in 1985, Posidonia oceanica beds, which represent the most widespread habitat in this area, have suffered a progressive regression in the bay (Cancemi et al. 2003). Four sampling stations were selected at the same depth (–10 m) and along the gradient of increasing distance from the fish farming facilities (Figure 1). St1 and St2 are located about 100 and 500 m from the cages, respectively. Station St1 is outside the marine protected area, whereas the others are inside. Control stations (C1 and C2) were placed where the P. oceanica meadow is in a pristine state of conservation and were randomly chosen among a set of possible locations representative of unimpacted conditions. Multiple controls were adopted to unconfound natural variability in assemblage pattern in undisturbed condition from the variability induced by disturbance under investigation (e.g. Underwood 1994; Terlizzi et al. 2005a). Sampling operations were carried out by SCUBA diving on May 2007. Sampling procedure The abiotic variables measured to represent P. oceanica meadows were: organic matter, expressed as LOI (Loss On Ignition), mud (fractions <63 μm), matte compactness and shoot density. For the estimation of LOI and mud content three replicate PVC core samples were taken at each station and immediately frozen until subsequent processing. Cores were 3 cm in diameter and 10 cm in length. The compactness of the matte was assessed through a penetrometer, following the method described by Francour et al. (1999). This parameter is a good indicator of the matte status and it can reveal a weakening of this structure and trend of erosion (Cancemi et al. 2003). At each of the four sampling stations the measurement was repeated five times at randomly selected sites. Compactness was defined as strong (penetration < 50 cm), medium (50 cm < penetration < 100 cm) and weak (penetration > 100 cm). Ten measures of density (shoots for m2; Giraud 1977) were performed at each site using a quadrate of 40 cm × 40 cm (1600 m3 of surface that is optimal for an assessment of P. oceanica density; Panayotidis et al. 1981; Buia et al. 2004). At each station, macrobenthic fauna was sampled by SCUBA divers by means of an air lift sampler (Terlizzi & Russo 1996; Buia et al. 2004) with a 0.4-mm mesh bag held by a 40 × 40 cm of metal frame and in three replicates. After collection samples were fixed in buffered 7% formalin. Abiotic data analysis In the laboratory, the sediment cores, after defrosting, were placed in an oven at 50°C for 24–48 h (depending on granulometric size) and cut into three fractions, then pulverized and homogenized. To evaluate sedimentary organic matter, about 1.5 g of sediment were sieved to obtain a finer fraction (<500 μm), oven-dried for a further hour and then weighed before and after a period of 3 h at 500°C; the loss of dry weight was expressed as a percentage of organic matter (Carver 1971; De Falco et al. 2004). In order to determine the mud fraction, about 100 g of dry sediment were dry-sieved by a set of sieves with a mesh from 4000 to 500 μm to get sediment fraction inferior to 500 μm. This fraction was oxidized in 10% H2O2 to remove organic matter and wet-sieved at 63 μm to obtain the mud fraction (Lorenti & De Falco 2004). Principal Component Analysis (PCA) was employed using mean values for each variable at each station, highlighting the differences among stations compared with structural features of meadow (matte compactness and shoot density) or characteristics of sediment (organic matter and mud content percentage). Taxonomic identification and macrofaunal analyses In the laboratory, samples were sorted under magnification and macrofauna separated into main taxonomic groups and stocked in 70% ethanol for further identification by expert taxonomists. Specimens of Mollusca, Isopoda, Decapoda, Tanaidacea and Amphipoda were all identified at species level, whereas Polychaeta were identified mainly at higher taxonomic levels (families, genera). Data were organized in a species vs. abundance matrix and analysed by multivariate and univariate techniques to quantify potential impact of source of disturbance on structure of assemblages associated with P. oceanica meadows. Given the presence of non-replicated stations for each of the two distances from the Downloaded By: [Felline, Serena] At: 13:09 7 September 2010 Aquaculture impact on macrofauna of Posidonia oceanica source of disturbance (i.e. St1 and St2) and the use of multiple controls, this is an asymmetrical design (sensu Glasby 1997). Distance-based permutational multivariate analysis of variance (PERMANOVA; Anderson 2001; McArdle & Anderson 2001) was employed to test the null hypothesis of no significant differences among stations. The analysis was based on Bray–Curtis dissimilarities (Bray & Curtis 1957) calculated on untransformed data (12 samples × 158 taxa) and each term of the analysis was tested using 999 random permutations of appropriate units (Anderson & ter Braak 2003). The analysis was done in two steps. First, the four stations were considered as separate units, investigating with pair-wise comparisons the difference between C1 and C2 with the PERMANOVA statistic and 999 permutations. The lack of differences between two controls indicates that assemblages belong to the same statistical population and they represent comparable conditions of faunal assemblages in the P. oceanica meadows. A more powerful statistical test was therefore done using a unique control condition employing a further PERMANOVA to analyse the difference between St1 and St2, and between these and C (Terlizzi et al. 2005a). Multivariate patterns of variation among stations were visualized by non-metric multidimensional scaling (nMDS) (Kruskal & Wish 1978) of sites’ centroids. The SIMPER procedure (Clarke 1993) was employed to analyse the percentage contribution of each variable to the Bray–Curtis dissimilarities among samples, allowing the identification of taxa most affected by the impact. A cut-off criterion was applied to allow identifying a subset of species whose cumulative percentage contribution to the observed value of dissimilarity reached 80%. The relationships between multivariate patterns of assemblage structure and patterns of environmental variables were examined by superimposing bubble plots, representing the values of this variable as a circle of different size, on the biotic ordination of the corresponding station. Diversity profiles at each station were visualized by plotting k-dominance curves displaying the cumulative proportion abundance against the log species rank (Lambshead et al. 1983). Multivariate analyses were repeated for the amphipod and mollusc data set separately to test whether a single group can be used as a surrogate in fish farming impact studies on diversity of macrofauna assemblages associated to P. oceanica meadows. Given that, for polychaetes, the taxonomic resolution was, for most taxa, at levels higher than species, no attempt was made to reanalyse the performances of the polychaetes data set. The use of polychaetes only in the assessment of environmental impacts can 365 be in some cases problematic if the analyses are conducted at rough levels of taxonomic resolution (Musco et al. 2009). On the other hand, lower taxonomic resolution (genus level) has been proven to still be useful to highlight differences in polychaete composition along a depth gradient on a Posidonia oceanica bed (Gambi et al. 1995). PERMANOVA was also employed to test, in a univariate context, the same hypothesis tested using multivariate analyses. The analysis was conducted on the mean number of taxa (S), mean number of individuals (N), Simpson’s diversity (1 – l′) and evenness (J′). All statistical analyses were performed using the computer program PRIMER v6 (Clarke & Gorley 2006), including the add-on package PERMANOVA+ (Anderson et al. 2008). Results Meadow features Matte compactness was 110 cm (± 0.0 SE) at St1, 97 cm (± 8.0) at St2, 71.7 cm (± 5.0) at C1 and 75.8 cm (± 7.7) at C2. According to Francour et al. (1999), St1 was classified as ‘weak’, St2, C1 and C2 as ‘medium’. Following Pergent et al. (1995), shoot density at St1 (132 ± 28.9 shoot/m2) and St2 (216.4 ± 33.1) was classified as ‘anomalous’, sub-normal values for that specific depth. Control stations C1 and C2 were classified as ‘normal’ with 361.5 ± 23.9 shoot/ m2 and 390.6 ± 38.8 shoot/m2, respectively. Univariate statistical analyses A total of 3041 specimens of benthic invertebrates were collected and characterized as 158 taxa of Mollusca (951 individuals, 81 species), Amphipoda (1052 individuals, 26 species), Decapoda (127 individuals, 14 species), Isopoda and Tanaidacea (85 individuals, 9 species) and Polychaeta (826 specimens belonging to 28 taxa, of which 16 families and the others recognized at genus and species level). Permutational analysis of variance on mean number of individuals revealed an overall significant difference among stations (Table I). Pair comparisons of these differences revealed that differences occurred only between C vs. St1. No differences were detected among other pairs of stations (Table I; Figure 2). There were no significant differences among stations in the mean number of species (Table I). The mean value of the evenness index (J′), instead, significantly differed (Table I), with the lowest value occurring at St1 (0.70 ± 0.007 SE; Figure 2). Diversity, expressed as Simpson’s diversity index (1 – l′), also varied significantly across stations, with the lowest 366 A. Terlizzi et al. Table I. Permutational analysis of variance testing differences among the three conditions (St1, St2 and C) in terms of number of individuals (N), number of species (S), evenness index (J´) and Simpson’s index (1 – l). Results of pair-wise tests are reported for significant differences among stations. N Source df Impact 2 Residual 9 Pair-wise comparisons St1 vs. C St2 vs. C St1 vs. St2 S MS 59480 16315 F 3.65 t 2.3875 1.8367 0.9329 p * ns ns p * MS 281.42 195.80 J´ F 1.44 p ns MS 0.03 0.00 F 50.07 t 9.61 2.80 8.66 p *** ** *** 1-l´ p *** MS 0.0045 0.00016 t 6.74 0.57 7.59 F 28.27 p ** p * ns ns Downloaded By: [Felline, Serena] At: 13:09 7 September 2010 *p < 0.05; **p < 0.01; ***p < 0.001; ns: not significant (p > 0.05). Figure 2. Mean (± SE, n = 3) values of variables analysed at each of four stations studied. value occurring at St1 (0.89 ± 0.006). Pair-wise comparisons of St1 and St2 vs. C revealed the only significant test to occur between St1 and the average of controls (Table I; Figure 2). Patterns of evenness index were reflected by plotting k-dominance curves for species abundance at four sampling stations (Figure 3), which showed that St1 was characterized by nine species accounting for 80% of total abundance value. Although in a weaker way, St2 was also characterized by few dominant species. Curves referring to control stations had a different shape with a greater number of species for the same abundance values than St1 and St2. The curves at C1 and C2 were overlapping, indicating a comparable pattern of species equitability between controls. Multivariate analysis Principal Component Analysis of meadow structural variables (shoot density and compactness of matte) Figure 3. K-dominance curves for species abundances at four study stations (x-axis logged). St1 = black squares; St2 = black triangles; C1 = white squares; C2 = white circles. and abiotic variables (mud and organic matter percentage into sediment) highlighted differences among stations and, particularly, differences between impacted stations and controls (Figure 4). Aquaculture impact on macrofauna of Posidonia oceanica 367 Figure 4. Biplot of principal component analysis ordination displaying differences among four stations in relation with abiotic variables. PC1 explained 98% of total variability. Downloaded By: [Felline, Serena] At: 13:09 7 September 2010 Table II. PERMANOVA testing differences between St1, St2 and C based on Bray–Curtis dissimilarities data for the whole data set (158 taxa × 12 samples) and for amphipods and molluscs data analysed separately. Results of pair-wise tests were also reported. All data set Source Impact Residuals Pair wise tests St1 vs. St2 St1 vs. C St2 vs. C Molluscs d.f. 2 9 MS 5348.9 1477.5 F 3.6203 t 1.8129 2.0881 1.764 p * ** * p *** Amphipods MS 7448.3 2215.8 F 3.3614 t 2.0491 1.6831 1.6684 p ns ** * p ** MS 4348.1 1181.1 F 3.6815 t 2.2935 1.2206 2.2032 p * ** ns p ** *p < 0.05; **p < 0.01; ***p < 0.001; ns: not significant (p > 0.05). The first axis explained 98% of total system variability. Considering environmental variables, C1 and C2 were virtually overlapping and St1 was the most different station. The PCA plot confirmed the controls as characterized by higher values of shoot density and matte compactness and by lower values of LOI and mud than St1 and St2. Like St1 but in a weaker way, St2 was characterized by lower compactness of matte and by high values of LOI and mud content (Figure 4). Permutational multivariate analysis of variance performed on the whole data set (158 variables × 12 samples) did not show significant differences between C1 and C2. Based on this result, a further PERMANOVA was carried out, considering a single control condition (C), in order to test for differences in total assemblage structure between St1 and St2 and between these and C. The analysis showed significant differences between the two impacted sites, and between these and the control condition (Table II). These differences were well portrayed by nMDS plot of the 12 samples, which showed samples at St1 grouped and separated from other samples (Figure 5A). St1 showed a lesser scattering among Figure 5. A, Non-metric multidimensional scaling ordinations (nMDS) on the basis of the Bray–Curtis dissimilarities measure of individual replicates comparing macrofauna assemblages from impacted (St1 and St2) and control stations (C1 and C2). 䊐 = C2; 䉫 = C1; ▲ = St1; = St2. B, macrofauna MDS plot of stations’ centroids with values of LOI at four stations superimposed as circles of differing sizes. replicate units than control sites. The same space arrangement was found at St2 group. This indicates that impact determined changes in the spatial heterogeneity among replicate units both at St1 and St2. Control sites showed similar condition of spatial heterogeneity among replicates. The plot of mean assemblage for each station (the centroids of three replicates) with superimposed abiotic variable mean value, showed clearly that the 368 A. Terlizzi et al. Downloaded By: [Felline, Serena] At: 13:09 7 September 2010 differences between control and impacted stations were heavily influenced by the values of LOI. Similar patterns (data not reported) were obtained plotting the differences in assemblage structure of macrofauna related to other variables such as mud and shoot density (Figure 5B). As suggested by the test for differences in the J index, SIMPER showed that St1 and St2 were characterized by few abundant species. These species were also found at the control condition, but with lower abundances. Some species (e.g. the amphipod Pereionotus testudo) were found only at St1, other species characterized St1 and St2 (e.g. molluscs Retusa truncatula and Loripes lucinalis and the tanaid Leptochelia dubia). The mollusc Rissoina (Rissoina) bruguieri and the amphipod Metaphoxus simplex were absent at St1 and present at St2 and C (Table III). SIMPER also showed a gradient for species most responsible for difference among stations. For example, mean abundance values of gastropod Rissoella inflata (living in mud with high organic matter content) were 91.6 at St1, 33.3 at St2 and 2.3 at C. The same pattern was showed by the amphipod Caprella acanthifera. The opposite pattern was observed for other species that characterize P. oceanica leaf stratum, as Syllinae spp. which had mean abundance values of 4.3 at St1, 6.6 at St2 and 9.0 at C (Table III). PERMANOVA performed separately on mollusc and amphipod assemblages showed similarly that C1 and C2 did not differ and thus they were analysed as a single control condition (Table II). PERMANOVA on mollusc assemblages did not show significant difference between St1 and St2, but revealed St1 and St2 as differing significantly from Table III. SIMPER analysis of species contributing the most (%) to dissimilarity between pairs of stations. The average dissimilarity between each pair of stations was reported in parentheses. For each species the average abundance (Avg. ab.) at each of the three conditions (St1, St2 and C) are provided. For each comparison only species up to 80% cumulative percentage are reported. Taxa St1 St2 C Avg. ab. Avg. ab. Avg. ab. Rissoella inflata Caprella acanthifera Apherusa veratri Aora spinicornis Sunamphithoe pelagica Prionospio spp. Exogoninae (Exogone spp./Sphaerosyllis spp.) Gouldia minima Protodorvillea kefersteini Paraonidae Scissurella costata Caecum trachea Pholoe minuta Pereionotus testudo Venericardia antiquata Retusa truncatula Phtisica marina Loripes lucinalis Dexamine spinosa Perioculoides aequimanus Lumbrineridae Lucinella divaricata Rissoina bruguieri Mysella bidentata Synchelidium haplocheles Alvania geryonia Syllinae Cymodoce hanseni Leptochelia dubia Parvicardium exiguum Capitellidae Metaphoxus simplex 91.67 46.33 50.67 36 22.33 5 36 9.67 13.33 8.67 0.67 3 1 5 1.67 3.67 0.67 1 3 3.67 0.67 1.33 0 0.67 1 0 4.33 5 2.67 2.67 0.67 0 33.33 5.33 20 11.33 1.67 18.67 39.33 15.33 15 2.33 6 4.67 5.33 0 5 2 3.67 3.33 2 5 3.33 3 2.67 3.33 3.33 2.33 6.67 3.33 1 3 3 2 2.33 1.83 24 8.83 0.67 2.67 9.5 0.67 1.17 1.67 3.67 0 5.17 0 1.33 0 0.83 0 5.33 1 0.5 0.17 1.67 0.33 0.33 0.5 9 5.33 0 0.17 0.5 3.33 St1 vs. St2 53.36 St1 vs. C 76.52 St2 vs. C 68.13 Contrib % Contrib % Contrib % 15.2 10.85 8.98 7.21 4.68 3.9 3.65 3.16 2.08 1.78 1.51 1.31 1.25 1.18 1.06 0.9 0.9 0.85 0.82 0.78 0.78 0.73 0.72 0.71 0.68 0.68 0.66 0.64 0.63 0.63 0.62 0.59 21.4 10.56 8.11 7.43 3.97 1.05 6.4 1.98 2.69 1.88 0.79 0.5 0.91 1.01 0.46 0.72 0.22 0.21 1.13 0.69 0.18 0.39 0.35 0.21 0.34 0.1 1.45 1.19 0.73 0.59 0.2 0.77 7.21 1.4 5.2 2.29 0.48 5.52 10.33 4.88 4.82 0.62 1.93 1.48 1.07 0 1.31 0.62 0.97 1.01 1.25 1.47 0.95 1 0.92 1 1.03 0.81 2.08 1.43 0.37 0.98 0.89 0.83 Aquaculture impact on macrofauna of Posidonia oceanica the control condition C (Table II). PERMANOVA on amphipod assemblage showed significant differences between St1 and other stations, but St2 did not differ from C. Downloaded By: [Felline, Serena] At: 13:09 7 September 2010 Discussion This study highlighted a significant effect of the aquaculture cages in modifying the assemblage structure of mobile invertebrates associated with P. oceanica meadows as a likely consequence of changes in sediment features and meadow structure (matte compactness and shoot density). The impact was revealed in terms of: an increase in mean abundance values at the station closest to the fish farming (St1); a selection of few abundant species in the same station; changes in the mean values of univariate diversity indexes at the St1 station compared with controls; a drastic change in assemblage structure in St1 and St2, which differed from those characterizing the controls; a higher small-scale variability among replicate units in the controls respect to the two impacted stations. One of the more striking aspects of the obtained results is that studies related to diversity changes have to be carried out defining biodiversity itself under its many aspects. Wrong inferences about effects of an environmental impact on biodiversity can be done when it is expressed simply as a number of species. Analyses carried out on the other variables (e.g. Simpson and J′ indexes) showed significant differences between St1 and C. Therefore, impact was revealed by a change in biodiversity (species identity and evenness) and not just by species number. The analysis of evenness (analysis of variance on J′ index and graphic inspection of quantitative dominance curves) related to impact showed controls stations (C1 and C2) as overlapping. The significant differences among St1, St2 and controls are consistent with a gradient of the perturbation caused by fish farming activities. This outcome is also supported by multivariate analysis, which showed significant differences in the whole assemblage structure between St1 and St2 and between these two and the control conditions. When analysing mollusc data only, significant differences resulted between St1 vs. C and between St2 vs. C, but there were no differences between St1 vs. St2. This result widens the range of habitats in which the use of molluscs only has been demonstrated to act as a valid surrogate in the detection of environmental impacts (Bevilacqua et al. 2009) and suggests that, at least in Posidonia beds, molluscs could be used in routine procedures of environmental monitoring for the assessment of the impact of fish farms. 369 By detecting only difference between St1 and C and not between St2 and C the use of amphipods only demonstrates a less affordability in the detection of impact by fish farming. There are likely multiple causal mechanisms, possibly acting interactively, underlying the observed differences in assemblages between the impacted and control stations. The identification and quantification of these mechanisms would require more detailed manipulative experiments than the correlative approach we used. In addition, the lack of temporal replication in the study and the consideration of seasonality that characterizes vagile fauna associated to P. oceanica meadows (e.g. Gambi et al. 1992; Scipione et al. 1996) limit the basis for any general inferences concerning the impact. Nonetheless, on the basis of the outcome of this study, some hypotheses regarding specific ecological mechanisms operating through the considered stations can be formulated and some general tentative ideas offered. Figari Bay is not characterized by significant urbanization and the presence of the Carcerone river cannot justify the organic enrichment of the bay given that percentages of organic matter recorded in the pro-delta (3–13%) are lower than those near the cages and exhibit a marked decline (from 25.0 to 5.6%) with distance from fish farm facilities (Cancemi et al. 2007). The massive presence of species indicating organic enrichment can be therefore reasonably assumed as an effect of fish farming. For example, the polychaetes Protodorvillea kefersteini and Prionospio spp. were among the most abundant species at St1 and St2, and emerged by the SIMPER analysis as responsible for differences between those stations and the control condition. Also, the abundance of the amphipod Caprella acanthifera at St1 in comparison with St2 and C can reasonably be interpreted as an effect of organic increase. This species is known to tolerate stressed habitats characterized by high rates of sedimentation and strong inputs of organic matter (Guerra-García & García-Gómez 2001). The increased sedimentation and organic load of the impacted stations could also explain the different pattern of small-scale variability among replicate units observed among stations, with control sites showing a higher scattering in the nMDs ordination model. Similar results have been highlighted by Borg et al. (2006) with invertebrate fauna associated with dead and alive P. oceanica matte off the Malta coast, suggesting that sediment properties and other features of the dead as more homogeneous than those occurring in the living meadow. Sediment features and shoot density values in the impacted Downloaded By: [Felline, Serena] At: 13:09 7 September 2010 370 A. Terlizzi et al. stations of our study may suggest some interesting parallelisms and analogies with those occurring in a dead Posidonia matte. Analysis of species mainly responsible for changes in assemblages across stations supports the hypothesis that changes of sedimentation rates induce major changes in benthic assemblages. For example, species living in muddy substrates as Retusa truncatula, Loripes lucinalis and Leptochelia dubia were exclusively recorded at St1 and St2. Sedimentation can influence mean shoot density (Delgado et al. 1999; Pergent et al. 1999; Ruiz et al. 2001; Cancemi et al. 2003) and indirectly increase the size of patches of dead matte. Instead, species typical of P. oceanica leaf stratum like, namely the polychaetes Syllinae spp., Chrysopetalum debile, Pholoe minuta, the gastropods Rissoina (Rissoina) bruguieri and Alvania geryonia and the amphipods Dexamine spinosa and Metaphoxus simplex characterized the control stations and contributed the most to characterize difference in assemblage between C and the impacted stations. Particularly, Alvania geryonia, R. bruguieri and M. simplex were not found at St1. Therefore, aquaculture facilities modify biodiversity patterns of fauna associated to P. oceanica meadows and also determine changes in the meadows living into the Marine Protected Area boundaries as suggested by data about St2. Marine reserves are not isolated from all critical impacts (Allison et al. 1998). Our results confirm that marine reserves offer no protection from important threats such as the spread of contaminants. That is, protected communities can be strongly impacted by human activities acting outside the reserve boundaries. Conserving P. oceanica is a target to be pursued not only for the ecosystem functions performed by the seagrass, but also for protecting a highly diversified biotope and is recognized as a priority habitat in the frame of the European Habitat Directive. 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