Journal of Fish Biology (2004) 64, 970–983 doi:10.1111/j.1095-8649.2004.00365.x,availableonlineathttp://www.blackwell-synergy.com
Functional groups of lagoon fish species in Languedoc Roussillon, southern France
O. DUMAY,P.S.TARI,J.A.TOMASINI AND D. MOUILLOT* Laboratoire Ecosyste`mes Lagunaires, UMR CNRS-UMII 5119, Universite´ Montpellier II Case 093, 34 095 MONTPELLIER Cedex 5, France
(Received 5 April 2003, Accepted 10 January 2004)
Ten functional traits of fish species were related to habitat, diet or food acquisition, to propose a classification of 21 lagoon fishes into 10 functional groups. The selection of traits was based on their functional interest and the ease of measurement. Some groups were taxonomically related containing species belonging to the same genus, e.g. Syngnathus, Atherina or Pomato- chistus. Species with a flat body shape constituted another group and three species (Anguilla anguilla, Gambusia affinis and Callionymus pusillus) formed individual groups. These results could be used to constitute functional units and to simplify such complex ecosystems and their interactions. # 2004 The Fisheries Society of the British Isles Key words: allometry; exotic species; functional traits; multivariate analysis.
INTRODUCTION A central aim of ecology is to measure biodiversity. It is not easy to ‘capture’ this measure as a single number (Chapin et al., 2000; Purvis & Hector, 2000). Numerous ‘facets’ of biodiversity have been already quantified using specific richness or even- ness, taxonomic and phylogenetic indices (Simpson, 1949; Alatalo, 1981; Bulla, 1994; Warwick & Clarke, 1995; Smith & Wilson, 1996; Hill, 1997; Clarke & Warwick, 2001). Nevertheless, the most important question is not whether a proposed statistic satisfies some theoretical criterion, but whether it allows meaningful inquiries about ecosystem functioning or environmental factors. It is now generally accepted that functional diversity, which is the value and range of functional traits of the organisms present in a given ecosystem (Diaz & Cabido, 2001), rather than species diversity per se, is the key (Grime, 1997; Tilman et al., 1997; Chapin et al., 2000; Diaz & Cabido, 2001; Naeem, 2002a, b; Naeem & Wright, 2003). Species richness is practically always used as an explanatory variable for ecosystem function because it is easy to estimate and assumed to be a good estimator for functional diversity (Lawton et al., 1998; Tilman, 1999). Nevertheless, Diaz & Cabido (2001) theoretically showed that species richness (species number per se) will only be an adequate surrogate for functional diversity if there is a linear increase in niche space coverage as species richness
*Author to whom correspondence should be addressed. Tel.: þ33 4 67 14 39 26; fax: þ33 4 67 14 37 19; email: [email protected] 970 # 2004 The Fisheries Society of the British Isles FUNCTIONAL GROUPS OF LAGOON FISHES 971
Functional Increasing functional diversity redundancy in fish assemblage
Species richness
FIG. 1. Relation between functional diversity and species richness in fish assemblages. When functional redundancy or similarity increases in a fish community, functional diversity increases at a slower rate than species richness whereas this relation is linear when species are functionally different. Thus, species richness is a good surrogate for functional diversity if new species add new functions or new functional groups. increases. For Petchey & Gaston (2002), functional diversity could be strongly related to richness only if species’ traits were equally complementary. These two assumptions are summarized in Fig. 1 with different fish assemblages containing more or less functionally redundant or similar species. When species are added with similar functions in an ecosytem, functional diversity is not linearly related to richness and thus increases at a lower rate than richness. Indeed, many authors argue that functional diversity rather than species richness determines ecosystem functioning and must be estimated (Grime, 1997; Tilman et al., 1997; Chapin et al., 2000; Diaz & Cabido, 2001; Naeem, 2002a, b). The introduction of functional groups was an important step in estimating functional diversity, with species being grouped by similar function, similar effects on ecosystem processes or similar responses to environmental pressures (Diaz & Cabido, 1997; Lavorel et al., 1997, 1999; Walker et al., 1999; Wilson, 1999; Walker & Langridge, 2002). These functional groups or types have been used to investigate the influence of climatic change (Diaz & Cabido, 1997) or species loss (Fonseca & Ganade, 2001; Naeem, 2002b) on ecosystem processes. In functional ecology, classifying species into groups based on similar function is a useful approach to studying assembly or coexistence rules, trophic interactions, species redundancy or similarity and environmental or perturbation influences on the system. Worldwide, lagoon systems represent 13% of the coastline (Knoppers, 1994) and together with other coastal ecosystems contribute a large part of the ecological richness of the biosphere (Costanza et al., 1997). Due to their location between the continent and the sea and their shallow depths, lagoons are among the most product- ive ecosystems (on average 300 g C m 2 year 1, Knoppers, 1994) but also very sensitive to both climatic and human impacts. In the Languedoc-Roussillon region (southern France, Mediterranean Sea), lagoons comprise 50% of the coastline. They
# 2004 The Fisheries Society of the British Isles, Journal of Fish Biology 2004, 64, 970–983 972 O. DUMAY ET AL. are subject to many human impacts, in particular aquaculture, tourist activities and agriculture in the watershed. For instance, in Languedoc-Roussillon, some lagoons are used intensively for aquaculture (20% of the Thau Lagoon area) (Bacher et al., 1997; Fiandrino et al., 2003). It is important to study the impact of these activities on the different biotic components of the lagoon ecosystem and on the different ecosys- tem processes, i.e. productivity, stability and resilience (Chapin et al., 1997; Tilman et al., 1997; Loreau, 2000; Loreau et al., 2001; Bond & Chase, 2002). Numerous studies have highlighted the influence of fish communities on ecosystem processes (Angeler et al., 2002; Baldo & Drake, 2002; Carrasson & Cartes, 2002; Davoren et al., 2002; Mancinelli et al., 2002) but these commu- nities remain complex systems with respect to functions and interactions. To simplify these systems or ecological compartments, functionally homogenous units are needed (Simberloff & Dayan, 1991; Austen et al., 1994; Garrison & Link, 2000). Thus the aim of the present study was to propose functional groups for the fish community of the Languedoc-Roussillon lagoons, based on func- tional traits which were related to diet, habitat or food acquisition methods (Keast & Webb, 1966; Goulding, 1985; Grossman, 1986; Motta et al., 1995; Norton, 1995; Piet, 1998). The limits of this method, its ecological interest and the relation to the guild concept were also investigated.
MATERIALS AND METHODS
DATA COLLECTION Fishes were caught in four coastal brackish lagoons of southern France: Thau (43 240 N; 3 360 E), Mauguio (43 3402800 N; 4 0300000 E), Saint-Nazaire (42 4003900 N; 3 0002400 E) and Salses-Leucate (42 5004300 N; 2 5904300 E) lagoons. These lagoons are very different in their characteristics (e.g. surface, topography, depth, salinity and human impact level). Many fish species inhabit these water bodies. For instance, 72 species were recorded in the Mauguio Lagoon, 20 were common and the others rare or very rare (unpubl. data). In order to obtain the best possible representation of the fish community of the lagoons, an active capture method, such as a drawnet, rather than a passive one such as ‘capetchade’ or trammel net seemed more appropriate (George & Ne´ de´ lec, 1991; Harrison & Whitfield, 1995). With a passive method there are always selectivity prob- lems, i.e. some species are more easily caught than others and thus the sampled community can be biased. In addition, as the drawnet covers the entire water column from the bottom to the surface, both pelagic and benthic species were captured.
FUNCTIONAL GROUPS The definition of functional groups and the classification of species must be done carefully. The selection of which functions are of interest, which traits can be measured as an index of these functions and the multivariate analysis chosen to classify species into these groups all influence the final result. Following Fonseca & Ganade (2001), building functional groups involved the following five main steps.
Defining functional groups Functional groups can be seen under different ‘facets’, depending on whether groups are defined as a set of species exhibiting a similar response to environmental conditions or have similar effects on the dominant ecosystem processes (Blondel, 2003). Here, the
# 2004 The Fisheries Society of the British Isles, Journal of Fish Biology 2004, 64, 970–983 FUNCTIONAL GROUPS OF LAGOON FISHES 973 principal aim was not to measure a response of the community to disturbances such as global change or human impact but to define groups of species acting in the same way in the system.
Species inclusion criteria Many kinds of communities (e.g. macrophytes, plankton and bacteria) within the lagoon, are all potentially of interest. In this study the fish component was focused on.
Selecting the functions of interest To define functional groups of fish species based on their influence on the system three functions of interest were selected: diet (e.g. herbivore or carnivore), habitat (e.g. pelagic or benthic) and method of food acquisition.
Choosing the traits It is necessary to select the traits which reflect the functions of interest but which are still possible to measure on a large number of individuals in a short time. Among all morphological characters available on fish species, those offering a trade-off between their relevant interest and ease of measurement were chosen. Most of the functional traits were relevant for several functions of interest but some others could be associated with diet, habitat and the food acquisition method. Following these criteria, 10 functional traits were selected (Fig. 2): (i) mass (M) was the first trait to be estimated because body size is related to the amount of food intake by individuals and to their impact on the food web (Greenwood et al., 1996; Niklas & Enquist, 2001). In addition, this variable is used to standardize other variables. Mass was measured on each individual with a precision balance; (ii) ratio of standard length
cL D
Pos pd Bd Og horizontal cd pL
° 90 L 45° S +2 dGr Pro +1 10° Horiz. 0° 0 –10° –1
–2 –45° –90°
FIG. 2. Different functional traits measured on lagoon fishes including the different classes of the oral
gape position (from Sibbing & Nagelkerke, 2001). LS, standard length; Bd, body depth (trait LS : Bd); D, eye diameter; Og, oral gape; Pro, protrusion length; Pos, oral gape position; dGr, gill raker depth; cL, caudal fin length; cd, caudal fin depth (trait cL : cd); pL, pectoral fin length; pd, pectoral fin depth (trait pL : pd).
# 2004 The Fisheries Society of the British Isles, Journal of Fish Biology 2004, 64, 970–983 974 O. DUMAY ET AL.
(LS) to body depth (Bd; LS : Bd), which is related to the hydrodynamic ability of fish species (Sibbing & Nagelkerke, 2001); (iii) ratio between length (pL) and depth (pd) of the pectoral fin, pectoral fin aspect ratio (pL : pd), which is strongly correlated to swim- ming performance for labrid species (Walker & Westneat, 2000; Bellwood & Wainwright, 2001; Bellwood et al., 2002; Wainwright et al., 2002). More generally, it appears to be related to manoeuvrability at slow speeds and efficiency of locomotion (Bellwood et al., 2002); (iv) aspect of ratio caudal fin length (cL) to caudal fin depth (cd; cL : cd) decreases as the swimming ability of the fish declines (Sibbing & Nagelkerke, 2001). Benthic fishes tend to have a high ratio whereas high-speed fishes have a low ratio; (v) eye diameter (D) is related to the detection of food and gives information about the visual acuity of the species (Piet, 1998). Hunting fishes need efficient visual acuity; (vi) oral gape position (Pos) is the angle of the oral gap with the body line, giving information about capture mode or benthic character (Sibbing & Nagelkerke, 2001). Five classes were defined (Fig. 2): 10 to þ10 ; 1 for 10 to 45 and 2 for 45 to 90 ; (vii) protrusion length (Pro) allows a reduction of the distance between the fishes and their prey to limit energetic cost (Sibbing & Nagelkerke, 2001). An ambush mode of prey capture or a digger activity is usually linked to this protrusion; (viii) gill raker depth (dGr) is high when food acquisition is by filtration which is related to a planktonic diet (Sibbing & Nagelkerke, 2001); (ix) oral gape (Og) is directly related to the maximal size of the prey and influences the impact of the fish on the food web (Sibbing & Nagelkerke, 2001); (x) gut length (GuL) is strongly related to fish’s diet (Kramer & Bryant, 1995, Elliott & Bellwood, 2003). The ratio of GuL to LS is between 0 7 and 1 0 in carnivorous fishes and >1 in herbivorous fishes. Because of size differences, fish species traits were standardized (Adite & Winemiller, 1997; Winemiller, 1991). The choice was to standardize biomass because recent studies have highlighted the robust relationship between morphological or metabolic rates and body mass (West et al., 1997; Enquist & Niklas, 2001; Niklas & Enquist, 2001). The exception to this was gut length which was standardized by LS (Kramer & Bryant, 1995; Cleveland & Montgomery, 2003). If the allometric relationship between a trait (X) and mass (M)isX ¼ aMb and the exponent coefficient is invariant between scales or species, [ln(X þ 1)][ln(M þ 1)] 1 could be expected to be constant or robust for the same popula- tion. So, this transformation was choosen.
Building a classification Factorial discriminant analysis (FDA) was used to extract variables (functional traits) discriminating fish species. FDA was applied to the original data set: a rectangular matrix crossing fish individuals and functional traits. This analysis is based on linear models such as multiple linear regression to seek linear combinations of variables (here functional traits) that best discriminate among the groups (fish species) (Legendre & Legendre, 1998). The factorial form of this analysis is able to provide factorial axes with inertia defining planes where individuals and species are distributed. When all individuals are perfectly represented by a factorial axis, its inertia is 100%. Thereafter, a cluster analysis based on Euclidean distance and the Ward linkage method was used to build functional groups of fish species. This distance was the best cut-off distance to distinguish 10 relevant functional groups. These analyses were computed with ADE-4 (v 2001) and PC Ord (Mc Cune & Mefford, 1999).
RESULTS
SPECIES COLLECTED In the four studied lagoons, 21 fish species, from 17 genera, were collected (Table I). All these species were not present in every lagoon; some were tem- porarily absent and others non-existent. As the common goby Pomatoschistus microps (Krøyer), the marbled goby Pomatoschistus marmoratus (Risso) and the
# 2004 The Fisheries Society of the British Isles, Journal of Fish Biology 2004, 64, 970–983 # 04TeFseisSceyo h rts Isles, British the of Society Fisheries The 2004
TABLE I. Mean S.E. of the different functional variables for each lagoon fish species. n, number of individuals measured; M, mass; LS, standard length; Bd, body depth; D, eye diameter; Og, oral gape; Pro, protrusion length; Pos, oral gape position; dGr, gill raker depth; GuL, gut length; cL : cd, aspect of ratio caudal fin (length to depth), pL : pd, ratio between length and depth of pectoral fin or pectoral fin aspect ratio
Species LS Bd D Og dGr GuL FISHES LAGOON OF GROUPS FUNCTIONAL Species code nM(g) (mm) (mm) (mm) (mm) Pro (mm) Pos (mm) (mm) cL : cd pL : pd
Anguilla anguilla Aan 1 31 0 265 016 04 04 50 01 00 1 116 00 51 4 Atherina boyeri Abo 42 3 1 1 362 7 3 510 7 1 75 0 0 96 7 1 22 9 0 92 0 0 02 0 0 635 8 3 11 1 0 52 2 0 7 Atherina hepsetus Ahe 19 5 1 1 279 4 2 811 8 1 15 7 0 67 5 0 95 2 0 80 03 2 0 649 6 2 61 1 0 42 0 0 5 Callionymus pusillus Cpu 1 3 255 08 01 55 02 0 1 00 166 02 01 5 Chelon labrosus Cla 2 14 8 1 092 5 0 823 0 1 26 3 0 67 3 0 63 8 0 61 0 0 02 2 0 6 355 0 5 31 6 0 32 4 0 8
ora fFs Biology Fish of Journal Dicentrarchus labrax Dla 3 4 5 0 665 0 1 416 0 0 06 0 0 08 0 0 03 0 0 01 0 0 03 0 0 454 3 2 01 3 0 32 6 0 4 Diplodus sargus Dsa 1 11 865 034 07 06 02 01 01 175 00 72 4 Echiichthys vipera Evi 1 19 3 101 025 05 010 04 02 03 269 01 41 9 Gambusia affinis Gaf 4 0 4 0 425 5 1 85 6 1 12 0 0 62 4 0 81 9 0 51 0 0 01 4 0 714 4 1 81 5 0 41 9 0 4 Gobus niger Gni 4 6 9 1 664 5 2 913 8 1 55 1 0 88 9 1 21 9 0 92 0 0 00 6 0 572 8 3 92 0 0 62 3 0 8 Liza aurata Lau 25 10 2 1 390 7 2 217 5 1 15 6 0 65 8 0 83 8 0 60 9 0 52 2 0 4 297 2 7 11 1 0 42 4 0 7 Pomatochistus microps Pmc 4 0 4 0 229 6 0 75 3 0 52 0 0 03 0 0 61 3 0 71 0 0 00 0 0 018 0 2 02 5 0 03 4 0 9 Pomatochistus minutus Pmn 3 1 8 0 949 0 2 57 7 1 43 7 0 86 3 1 11 8 0 52 0 0 00 0 0 052 3 4 32 3 0 62 6 0 4 2004, Pomatoschistus sp. Psp 69 1 6 0 846 7 2 67 5 1 23 7 0 85 8 1 20 8 0 72 0 0 30 1 0 430 6 3 11 7 0 61 9 0 6 Salaria pavo Spa 1 5 970 017 03 03 00 00 00 040 01 22 3 64, Sarpa salpa Ssa 7 18 8 2 689 9 3 330 3 1 87 4 0 85 9 0 91 3 0 9 1 01 6 0 9 238 3 6 60 8 0 32 1 0 4
970–983 Scophthalmus rhombus Srh 1 46 6 124 09 07 016 02 50 03 4 118 01 12 1 Solea solea Sso 1 56 6 158 012 06 05 04 00 00 0 270 01 42 5 Sparus aurata Sau 4 26 5 2 6 102 0 2 937 5 1 79 1 0 54 8 0 52 1 0 50 5 0 81 2 0 580 5 3 70 9 0 33 2 0 7 Syngnathus abaster Sab 55 0 4 0 492 8 3 63 4 0 82 0 0 51 8 0 60 0 0 02 0 0 00 0 0 028 6 2 82 0 0 81 3 0 5 Syngnathus typhle Sty 16 0 5 0 5 103 6 3 63 1 0 72 1 0 62 4 0 80 0 0 02 0 0 00 0 0 035 4 2 72 4 0 91 1 0 5 975 976 O. DUMAY ET AL.
(a) (b) 1 Cpu –1-1 1 –1-1 Sso Srh LS : Bd Ahe Spa D* GuL* Sty Aan Lau cL : cd dGr* Sau Pro Sab Cla Og* cd* Dla Ssa pL : pd Pmc Gaf Dsa
Pos Pmn Gni Abo Psp Evi
FIG. 3. Factorial discriminant analysis with the first two axes (total inertia of 69%) (a) for species and (b) for the variables (*, standardized). See Table I for abbreviations. sand goby Pomatoschistus minutus (Pallas) could not be easily distinguished, they were combined as Pomatoschistus sp. Only four P. microps and three P. minutus specimens, from Mauguio Lagoon, were determined by staining canals, pores and papillae (Sanzo, 1911) by the Iljin method (Iljin, 1930). The FDA discriminated fish species based on functional traits. The first three axes represented 82% of the total inertia (Figs 3 and 4). Axis 1 clearly con- trasted the black-striped pipefish Syngnathus abaster Risso and the broad-nosed pipefish Syngnathus typhle L. with the other fish species. The Syngnathus group had high values for the standard length to body depth ratio, caudal fin length to depth ratio, eye diameter and oral gape, oral gape position >þ45 , and low
(a)Pmc Sso Cpu (b) Pmn Cla 1 –1-1 1 Spa Ssa –1-1 Psp Dsa Lau Sau Sty Gni Srh Aan GuL* Sab Evi Ahe Dla Abo cL : cd pL : pd Pos LS : Bd Og* D* cd*
Pro* Gaf dGr*
FIG. 4. Factorial discriminant analysis with the first and the third axes (total inertia of 53%) (a) for species and (b) for the variables (*, standardized). See Table I for abbreviations.
# 2004 The Fisheries Society of the British Isles, Journal of Fish Biology 2004, 64, 970–983 FUNCTIONAL GROUPS OF LAGOON FISHES 977
Ward distance Habitat Diet Capture 0 10 20 30 40 50 Atherina hepsetus All depths Carnivorous/Planctonophagous Filtration/Hunting 1 Dicentrarchus labrax Atherina boyeri Echiichthys vipera Benthic – episubstratum Carnivorous (medium prey) Ambush 2 Gobus niger Pomatoschistus sp.
Benthic – episubstratum Carnivororous (small prey) Ambush/Hunting 3 Pomatoschistus minutus Pomatoschistus microps Sarpa salpa All depths Omnivorous/Herbivorous Digger/Grazer 4 Liza aurata Chelon labrosus Benthic Carnivorous Hunting 5 Anguilla anguilla Diplodus sargus All depths Carnivorous Hunting 6 Sparus aurata Solea solea Scophthalmus rhombus Benthic Carnivorous Digger 7 Salaria pavo Callionymus pusillus Benthic Carnivorous Digger 8 Syngnathus abaster Benthic Planctonophagous Gulping 9 Syngnathus typhle Gambusia affinis Benthic – episubstratum Omnivorous Filtration/Gulping 10
FIG. 5. Dendrogram from cluster analysis showing the habitat, diet and mode of capture similarities between the different functional group of fishes from 1 to 10. values in pectoral fin length to depth ratio, gut length and protrusion. Axis 2 divided species into two opposite groupings. One group, with the sand smelt Atherina boyeri Risso, the lesser weever Echiichthys vipera (Cuvier) and the gobies Pomatoschistus sp., P. minutus and the black goby Gobius niger L., displayed an oral gape axis >þ45 while this variable was between þ10 and 45 in the group with the sand smelt Atherina hepsetus L., the peacock blenny Salaria pavo (Risso) and the common sole Solea solea (L.) and the brill Scophthalmus rhombus (L.). Axis 3 highlighted the special position of the mosquitofish Gambusia affinis (Baird & Girard). This species had high gill raker depth and protusion values. The same tendency was observed for A. boyeri, A. hepsetus and the European sea bass Dicentrarchus labrax (L.), unlike the gobies and Syngnathus group. To propose functional groups of fish species, a cluster analysis was computed (Fig. 5). A Ward distance of 10 was chosen to discriminate 10 functional groups. Three functional groups had only one species each [group 5: the European eel Anguilla anguilla (L.); group 8: Callionymus pusillus Delaroche; group 10: G. affinis]. Two groups contained only co-generic species (group 3: three Poma- toschistus; group 9: two Syngnathus). Group 6 included two sparidae [the gilt- head sea bream Sparus aurata L. and the white sea bream Diplodus sargus (L.)] and group 1 two species of the Atherina genus plus D. labrax. Species with a flat body shape were in the same group 7. Groups 2 and 4 included various species taxonomically unrelated.
DISCUSSION This study aimed to test the possibility of using multivariate analyses to separate functional groups based on morphological and anatomical traits in
# 2004 The Fisheries Society of the British Isles, Journal of Fish Biology 2004, 64, 970–983 978 O. DUMAY ET AL. fishes. It allowed discrimination of 10 coherent groups based on diet, habitat and food capture abilities. To characterize each group, one main reference (UNESCO, 1986) and the results from Figs 3 and 4 and the data of Table I were used. Some functional traits are common among some groups discrimi- nated by cluster analysis, but each group is characterized by its own and unique combination of traits. Groups 1, 4 and 6 are composed of fish species swimming at all depths. Species from group 1 tend to move far from the bottom and their body shape is more fusiform than fish species from groups 4 and 6 which tend to move nearer the bottom; the standard length to body depth ratio values are higher in the first group than in the other two groups. Fish species (from the Sparidae and Mugilidae) of these two groups (4 and 6) have high pectoral fin aspect ratios, and they are well adapted for manoeuvring between rocks or in dense beds of aquatic plants. Species from groups 1 and 6 are mainly carnivorous, but can eat plants (Rosecchi, 1985) while those of group 6 are omnivorous or herbivorous. The relative size of the gut is often indicative of diet in fishes (Kramer & Bryant, 1995). The gut length to LS ratio values are higher in group 4 than in groups 1 and 6. In group 1, Atherina sp. and juveniles D. labrax eat planktonic food by filtration and small bottom-living prey (Labourg & Ste´ quert, 1973; Aprahamian & Barr, 1985; Trabelsi et al., 1994; Laffaille et al., 2000). These species show high gill raker depth for filtration and large protrusion length to ingest small prey. A protrusible mouth increases their prey capture ability and efficiency (Helfman et al., 1997). In group 6 species, the mouth is small with flat (D. sargus) or conical (S. aurata) teeth in front to catch and molar-like teeth laterally to crush prey. With the exception of the special case of G. affinis, functional groups 2, 3, 5, 7 and 8 include more or less bottom-living, mainly carnivorous, species. Groups 2 and 3 are close, so in both of them, fishes display an oral gape axis þ45 .It can be noticed that G. niger is more linked to E. vipera than to Pomatoschistus sp. Indeed, G. niger and E. vipera show larger body size, protrusion and oral gape than Pomatoschistus sp. The prey spectrum of G. niger and E. vipera is greater than Pomatoschistus sp., the two first species can feed on larger prey such as small fishes (Joyeux et al., 1991). Salaria pavo and the flatfishes are surprisingly placed in the same group (7) and the next group (8) consists of C. pusillus. The species in these two groups display several traits in common: small protrusion and oral gape, and oral gape axis between 45 and 10 . Group 5 consists only of A. anguilla. Body morphology of this carnivorous bottom-living species is particularly well adapted for entering holes, swimming through aquatic plant beds and burrowing into soft bottoms. The Syngnathidae, group (9), stands far apart from the other groups in FDA (Figs 3 and 4) because of the unusual pipefish characteristics. Their colouration and their long and slender body shape mimic aquatic plants among which they live. They did not show protrusion, but their tubelike mouth allows them to ingest tiny prey from some distance, which may compensate for their slow swimming, and the large size of their eyes is well adapted to precisely locate small prey. Gambusia affinis is also clearly separated from the other groups (Fig. 5). It is an exotic species, native in U.S.A. and Mexico but introduced into many
# 2004 The Fisheries Society of the British Isles, Journal of Fish Biology 2004, 64, 970–983 FUNCTIONAL GROUPS OF LAGOON FISHES 979 countries (Courtenay & Meffe, 1989) as a biological control agent for mosquitoes. This species cannot be defined as a bottom-living fish. Typically, it lives close to shore in calm shallow waters, among subsurface vegetation (Hubbs, 1971; Miura et al., 1979; Arthington et al., 1986). This aggressive fish is an opportu- nistic omnivore feeding on a large range of prey, from plankton, strained by long and closely spaced gill rakers, to small fishes and amphibian larvae (Harrington & Harrington, 1961; Farley, 1980; Walter & Legner, 1980; Bence & Murdoch, 1982; Bence, 1986; Morton et al., 1988). Gambusia affinis morpho- logy is well suited to capture prey from the water surface or in the water column (Moyle & Cech, 1988): the flattened head with an upward-pointing mouth has a large protrusion to ingest prey and the dorsal fin in a posterior position. In this study, the aim was not to examine all functional traits of lagoon fish species. The choice was driven by their relevant interest and the easiness of their estimation (about 10–15 min are required to measure all the variables for each individual). This study is in the context of diversity-ecosystem function. Lagoons in Languedoc-Roussillon are highly impacted by humans. The fish component is an important part to study in the functional processes in coastal ecosystems (Mathieson et al., 2000; Angeler et al., 2002; Baldo & Drake, 2002). Before investigations can be undertaken about the influence of the functional diversity of the fish community on lagoon stability, productivity or resilience, the first step was to classify these fish species into functional groups. Many studies have highlighted the complexity of ecological systems and their funda- mental unpredictability due to multiple interactions (Huisman & Weissing, 2001). One way to overcome this problem is certainly a simplification of com- munities through a partitioning of species into a variety of guilds, functional groups or functional types (Simberloff & Dayan, 1991; Mathieson et al., 2000; Blondel, 2003; Jauffret & Lavorel, 2003). If the guild concept has been more often used than functional groups for vertebrates, it refers more to the mechan- isms of resource sharing by species in a competitive context. Within the context of biodiversity and ecosystem functions, a wide range of ecosystem functions from the fishes are required and the ‘functional groups’ seem more appropriate than the ‘guilds’. For example, the gill raker depth is directly linked to a resource use (plankton) and thus to the guild concept whereas the swimming abilities (fin variables) are more related to the place in the water column, habitat and capture modes and thus to functional groups. These two concepts are sometimes used synonymously and clarification is needed (Simberloff & Dayan, 1991; Blondel, 2003). The variables proposed in the study are not complete to speculate about fish compartment functioning in lagoon ecosystems and data on reproduction modes, abundances and migratory behaviour and more generally life-history traits are required. Moreover, for seven of the 21 species the various traits are measured in one specimen per species, so these functional groups are far from being a final classification of lagoon fishes within different ecological functional groups.
We wish to thank B.J. Anderson and J.F. Craig, the Editor, for improving this manuscript and for English corrections. Two anonymous reviewers provided helpful comments. This work was supported by the grant 002420 from University of Montpellier II on ‘functional diversity of lagoon fish species’.
# 2004 The Fisheries Society of the British Isles, Journal of Fish Biology 2004, 64, 970–983 980 O. DUMAY ET AL.
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