functional groups of lagoon fish species in languedoc

8/14/2019 Functional Groups of Lagoon Fish Species in Languedoc

1/14

Functional groups of lagoon fish species in LanguedocRoussillon, southern France

O. D U M A Y , P . S . T A R I , J . A . T O M A S I N I A N D D. M O U I L L O T*

Laboratoire Ecosyste`mes Lagunaires, UMR CNRS-UMII 5119, UniversiteMontpellier 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 proposea 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 thismeasure as a single number (Chapinet al., 2000; Purvis & Hector, 2000). Numerousfacets 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 statisticsatisfies some theoretical criterion, but whether it allows meaningful inquiries aboutecosystem functioning or environmental factors. It is now generally accepted that

functional diversity, which is the value and range of functional traits of the organismspresent in a given ecosystem (Diaz & Cabido, 2001), rather than species diversity perse, is the key (Grime, 1997; Tilmanet al., 1997; Chapinet al., 2000; Diaz & Cabido,2001; Naeem, 2002a, b; Naeem & Wright, 2003). Species richness is practically alwaysused as an explanatory variable for ecosystem function because it is easy to estimateand assumed to be a good estimator for functional diversity (Lawton et al., 1998;Tilman, 1999). Nevertheless, Diaz & Cabido (2001) theoretically showed that speciesrichness (species number per se) will only be an adequate surrogate for functionaldiversity if there is a linear increase in niche space coverage as species richness

*Author to whom correspondence should be addressed. Tel.: 33467143926; fax: 33467143719;

email: [email protected]

Journal of Fish Biology (2004) 64, 970983

doi:10.1111/j.1095-8649.2004.00365.x, availableonlineat http://www.blackwell-synergy.com

970# 2004The Fisheries Society of theBritish Isles


2/14

increases. For Petchey & Gaston (2002), functional diversity could be strongly relatedto richness only if species traits were equally complementary. These two assumptionsare summarized in Fig. 1 with different fish assemblages containing more or less

functionally redundant or similar species. When species are added with similarfunctions in an ecosytem, functional diversity is not linearly related to richness andthus increases at a lower rate than richness. Indeed, many authors argue thatfunctional diversity rather than species richness determines ecosystem functioningand must be estimated (Grime, 1997; Tilmanet al., 1997; Chapinet al., 2000; Diaz &Cabido, 2001; Naeem, 2002a,b).

The introduction of functional groups was an important step in estimatingfunctional diversity, with species being grouped by similar function, similar effectson ecosystem processes or similar responses to environmental pressures (Diaz &Cabido, 1997; Lavorelet al., 1997, 1999; Walkeret al., 1999; Wilson, 1999; Walker

& Langridge, 2002). These functional groups or types have been used to investigatethe 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 tostudying assembly or coexistence rules, trophic interactions, species redundancy orsimilarity and environmental or perturbation influences on the system.

Worldwide, lagoon systems represent 13% of the coastline (Knoppers, 1994) andtogether with other coastal ecosystems contribute a large part of the ecologicalrichness of the biosphere (Costanza et al., 1997). Due to their location between thecontinent 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 verysensitive to both climatic and human impacts. In the Languedoc-Roussillon region(southern France, Mediterranean Sea), lagoons comprise 50% of the coastline. They

Functionaldiversity

Species richness

Increasing functionalredundancy in fish

assemblage

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.

F U N CT I O N AL G R O U PS O F L A G O ON F I S H ES 971

# 2004 The Fisheries Society of theBritish Isles, Journal of Fish Biology 2004, 64, 970983


3/14

are subject to many human impacts, in particular aquaculture, tourist activities andagriculture in the watershed. For instance, in Languedoc-Roussillon, some lagoonsare used intensively for aquaculture (20% of the Thau Lagoon area) (Bacheret al.,1997; Fiandrinoet al., 2003). It is important to study the impact of these activities onthe different biotic components of the lagoon ecosystem and on the different ecosys-tem processes,i.e. productivity, stability and resilience (Chapinet al., 1997; Tilmanet al., 1997; Loreau, 2000; Loreauet al., 2001; Bond & Chase, 2002).

Numerous studies have highlighted the influence of fish communities onecosystem 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. Tosimplify these systems or ecological compartments, functionally homogenousunits are needed (Simberloff & Dayan, 1991; Austen et al., 1994; Garrison &Link, 2000). Thus the aim of the present study was to propose functional groupsfor 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 andthe relation to the guild concept were also investigated.

MATERIALS AND METHODS

D A T A C O L LE C T IO N

Fishes were caught in four coastal brackish lagoons of southern France: Thau(43240 N; 3360 E), Mauguio (433402800 N; 40300000 E), Saint-Nazaire (424003900 N;30002400 E) and Salses-Leucate (425004300 N; 25904300 E) lagoons. These lagoons arevery different in their characteristics (e.g. surface, topography, depth, salinity andhuman impact level). Many fish species inhabit these water bodies. For instance, 72species were recorded in the Mauguio Lagoon, 20 were common and the others rare orvery rare (unpubl. data).

In order to obtain the best possible representation of the fish community of thelagoons, an active capture method, such as a drawnet, rather than a passive one suchas 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 columnfrom the bottom to the surface, both pelagic and benthic species were captured.

F U N C T I O NA L G R O U P S

The definition of functional groups and the classification of species must be donecarefully. The selection of which functions are of interest, which traits can be measured asan index of these functions and the multivariate analysis chosen to classify species intothese groups all influence the final result. Following Fonseca & Ganade (2001), buildingfunctional groups involved the following five main steps.

Defining functional groups

Functional groups can be seen under different facets, depending on whether groupsare defined as a set of species exhibiting a similar response to environmental conditionsor have similar effects on the dominant ecosystem processes (Blondel, 2003). Here, the

972 O . D U M AY E T A L .

# 2004 The Fisheries Society of the British Isles, Journal of Fish Biology 2004, 64, 970983


4/14

principal aim was not to measure a response of the community to disturbances such asglobal change or human impact but to define groups of species acting in the same way inthe system.

Species inclusion criteria

Many kinds of communities (e.g. macrophytes, plankton and bacteria) within thelagoon, are all potentially of interest. In this study the fish component was focused on.

Selecting the functions of interestTo 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. pelagicor benthic) and method of food acquisition.

Choosing the traitsIt 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 betweentheir relevant interest and ease of measurement were chosen. Most of the functional traitswere relevant for several functions of interest but some others could be associated withdiet, habitat and the food acquisition method.

Following these criteria, 10 functional traits were selected (Fig. 2): (i) mass (M) was thefirst trait to be estimated because body size is related to the amount of food intake byindividuals 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. Masswas measured on each individual with a precision balance; (ii) ratio of standard length

Pos

Og

D

pL

pd

Pro

LS90

45

100

10

4590

1

0

2

Horiz.

horizontal

cL

Bdcd

dGr

+1

+2

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, gillraker depth; cL, caudal fin length; cd, caudal fin depth (trait cL : cd); pL, pectoral fin length; pd,

pectoral fin depth (trait pL : pd).




5/14

(LS) to body depth (Bd; LS : Bd), which is related to the hydrodynamic ability of fishspecies (Sibbing & Nagelkerke, 2001); (iii) ratio between length (pL) and depth (pd) ofthe 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) decreasesas the swimming ability of the fish declines (Sibbing & Nagelkerke, 2001). Benthic fishestend 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 thespecies (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 capturemode or benthic character (Sibbing & Nagelkerke, 2001). Five classes were defined(Fig. 2):10 to10; 1 for 10 to 45 and 2 for 45 to 90; (vii) protrusionlength (Pro) allows a reduction of the distance between the fishes and their prey to limitenergetic cost (Sibbing & Nagelkerke, 2001). An ambush mode of prey capture or adigger activity is usually linked to this protrusion; (viii) gill raker depth (dGr) is highwhen 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 preyand influences the impact of the fish on the food web (Sibbing & Nagelkerke, 2001); (x)gut length (GuL) is strongly related to fishs diet (Kramer & Bryant, 1995, Elliott &Bellwood, 2003). The ratio of GuL to LS is between 07 and 10 in carnivorous fishesand >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 studieshave highlighted the robust relationship between morphological or metabolic rates andbody mass (West et al., 1997; Enquist & Niklas, 2001; Niklas & Enquist, 2001). Theexception to this was gut length which was standardized by LS(Kramer & Bryant, 1995;Cleveland & Montgomery, 2003). If the allometric relationship between a trait (X) andmass (M) isX aMb and the exponent coefficient is invariant between scales or species,

[ln(X 1)][ln(M 1)]1 could be expected to be constant or robust for the same popula-tion. So, this transformation was choosen.

Building a classificationFactorial discriminant analysis (FDA) was used to extract variables (functional traits)

discriminating fish species. FDA was applied to the original data set: a rectangularmatrix crossing fish individuals and functional traits. This analysis is based on linearmodels such as multiple linear regression to seek linear combinations of variables (herefunctional traits) that best discriminate among the groups (fish species) (Legendre &Legendre, 1998). The factorial form of this analysis is able to provide factorial axes withinertia defining planes where individuals and species are distributed. When all individualsare perfectly represented by a factorial axis, its inertia is 100%. Thereafter, a clusteranalysis based on Euclidean distance and the Ward linkage method was used to buildfunctional groups of fish species. This distance was the best cut-off distance to distinguish10 relevant functional groups. These analyses were computed with ADE-4 (v 2001) andPC Ord (Mc Cune & Mefford, 1999).

RESULTS

S P EC I E S C O L LE C T E D

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 Pomatoschistusmicrops(Kryer), the marbled goby Pomatoschistus marmoratus (Risso) and the

974 O . D U M AY E T A L .



6/14

TABLEI.Mean

S.E.ofthedifferen

tfunctionalvariablesforea

chlagoonfishspecies.n,numberofindividualsmeasured;M,mass;

LS,sta

ndardlength;Bd,

bodydept

h;D,eyediameter;Og,oralgape;Pro,protrusionlength

;Pos,oralgapeposition;dGr,gillraker

depth;

GuL,gutlength;cL:cd,asp

ectofratiocaudalfin(lengthtodepth),pL:pd,ratiobetweenlengthanddepthofpectoralfinor

pectoral

finaspectratio

Species

Species

code

n

M

(g)

LS

(mm)

Bd

(mm)

D

(mm)

Og

(mm)

Pro(mm)

Pos

dGr

(mm)

GuL

(mm)

cL

:cd

pL:pd

Anguilla

angu

illa

Aan

1

3

10

2650

160

40

45

00

10

01

1160

05

14

Atherina

boyeri

Abo

42

31

13

627

35

107

17

50

09

67

12

29

09

20

00

20

06

358

31

11

05

22

07

Atherina

hepsetus

Ahe

19

51

12

794

28

118

11

57

06

75

09

52

08

00

32

06

496

26

11

04

20

05

Cal

lionymuspusi

llus

Cpu

1

32

550

80

15

50

20

10

01

660

20

15

Chelonlabrosus

Cla

2

148

10

925

08

230

12

63

06

73

06

38

06

10

00

22

06

3550

53

16

03

24

08

Dicen

tra

rchu

sla

brax

Dla

3

45

06

650

14

160

00

60

00

80

00

30

00

10

00

30

04

543

20

13

03

26

04

Diplo

dus

sargus

Dsa

1

1

18

650

340

70

60

20

10

11

750

07

24

Ech

iichthy

svipera

Evi

1

1

93

1010

250

50

100

40

20

32

690

14

19

Gam

busiaaf

finis

Gaf

4

04

04

255

18

56

11

20

06

24

08

19

05

10

00

14

07

144

18

15

04

19

04

Gobusn

iger

Gni

4

69

16

645

29

138

15

51

08

89

12

19

09

20

00

06

05

728

39

20

06

23

08

Lizaaurata

Lau

25

102

13

907

22

175

11

56

06

58

08

38

06

09

05

22

04

2972

71

11

04

24

07

Pomatoc

histusm

icropsPmc

4

04

02

296

07

53

05

20

00

30

06

13

07

10

00

00

00

180

20

25

00

34

09

Pomatoc

histusm

inutusPmn

3

18

09

490

25

77

14

37

08

63

11

18

05

20

00

00

00

523

43

23

06

26

04

Pomatos

chistussp.

Psp

69

16

08

467

26

75

12

37

08

58

12

08

07

20

03

01

04

306

31

17

06

19

06

Salar

iapavo

Spa

1

59

700

170

30

30

00

00

00

400

12

23

Sarpasa

lpa

Ssa

7

188

26

899

33

303

18

74

08

59

09

13

09

10

16

09

2383

66

08

03

21

04

Scoph

thalmusrhom

busSrh

1

4

66

1240

90

70

160

25

00

34

1180

11

21

Soleaso

lea

Sso

1

5

66

1580

120

60

50

40

00

00

2700

14

25

Sparusa

urata

Sau

4

265

26

1020

29

375

17

91

05

48

05

21

05

05

08

12

05

805

37

09

03

32

07

Syngnat

husabas

ter

Sab

55

04

04

928

36

34

08

20

05

18

06

00

00

20

00

00

00

286

28

20

08

13

05

Syngnat

hus

typh

le

Sty

16

05

05

1036

36

31

07

21

06

24

08

00

00

20

00

00

00

354

27

24

09

11

05




7/14

sand goby Pomatoschistus minutus (Pallas) could not be easily distinguished,they were combined as Pomatoschistus sp. Only four P. microps and threeP. minutus specimens, from Mauguio Lagoon, were determined by stainingcanals, pores and papillae (Sanzo, 1911) by the Iljin method (Iljin, 1930).

The FDA discriminated fish species based on functional traits. The first threeaxes represented 82% of the total inertia (Figs 3 and 4). Axis 1 clearly con-

trasted the black-striped pipefishSyngnathus abaster Risso and the broad-nosedpipefish Syngnathus typhle L. with the other fish species. The Syngnathus grouphad high values for the standard length to body depth ratio, caudal fin length todepth ratio, eye diameter and oral gape, oral gape position >45, and low

-11

-1 1-11

-1 1-11

-1 111

1 1

Cla

LauSty

Sab

Aan

Pmn Gni Abo

Evi

Dsa

DlaPmc

Gaf

Ssa

Sau

Spa

Ahe

Srh

Sso

Cpu

Psp

LS

:

Bd

D*cL:cd

Og* cd*

Pos

pL:pd

ProdGr*

GuL*

(a) (b)

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.

SsaCla

-11

-1 1-11

-1 1

AanSab

-11

-1 111

1 1

Sty

Psp

Pmn

Pmc Sso

SpaDsa

GniSrh

EviDla

Ahe

Abo

SauLau

Gaf

cL:cd

Pos

cd*

LS:BdOg*

D*

dGr*

Pro*

pL:pd

GuL*

(a) (b)Cpu

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 TableI for abbreviations.

976 O . D U M AY E T A L .



8/14

values in pectoral fin length to depth ratio, gut length and protrusion. Axis 2divided species into two opposite groupings. One group, with the sand smeltAtherina boyeri Risso, the lesser weever Echiichthys vipera (Cuvier) and thegobies Pomatoschistus sp., P. minutus and the black goby Gobius niger L.,

displayed an oral gape axis >45

while this variable was between 10

and45 in the group with the sand smelt Atherina hepsetus L., the peacock blennySalaria pavo (Risso) and the common sole Solea solea (L.) and the brillScophthalmus rhombus (L.). Axis 3 highlighted the special position of themosquitofish Gambusia affinis (Baird & Girard). This species had high gillraker depth and protusion values. The same tendency was observed forA. 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 eelAnguilla 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 Atherinagenus plusD. labrax. Species with a flatbody shape were in the same group 7. Groups 2 and 4 included various speciestaxonomically unrelated.

DISCUSSION

This study aimed to test the possibility of using multivariate analyses toseparate functional groups based on morphological and anatomical traits in

Habitat Diet Capture 0 10 20 30 40 50

10

8

9

7

6

5

4

3

2

Atherina hepsetus

Dicentrarchus labrax

Atherina boyeri

Echiichthys vipera

Gobus niger

Pomatoschistus sp.

Pomatoschistus minutus

Pomatoschistus microps

Sarpa salpa

Liza aurata

Chelon labrosus

Anguilla anguilla

Diplodus sargus

Sparus aurata

Solea solea

Scophthalmus rhombus

Salaria pavo

Callionymus pusillus

Syngnathus abasterSyngnathus typhle

Gambusia affinis

Filtration/Hunting

Ambush

Ambush/Hunting

Digger/Grazer

Hunting

Hunting

Digger

Digger

Gulping

Filtration/Gulping

Carnivorous/Planctonophagous

Carnivorous (medium prey)

Carnivororous (small prey)

Omnivorous/Herbivorous

Carnivorous

Carnivorous

Carnivorous

Carnivorous

Planctonophagous

Omnivorous

Benthic

Benthic

Benthic

All depths

Benthic

All depths

Benthic episubstratum



All depths 1

Ward distance

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.




9/14

fishes. It allowed discrimination of 10 coherent groups based on diet, habitatand 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 Iwere used. Some functional traits are common among some groups discrimi-nated by cluster analysis, but each group is characterized by its own and uniquecombination 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 ismore fusiform than fish species from groups 4 and 6 which tend to move nearerthe bottom; the standard length to body depth ratio values are higher in the firstgroup than in the other two groups. Fish species (from the Sparidae andMugilidae) 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 ofaquatic plants. Species from groups 1 and 6 are mainly carnivorous, but can eatplants (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 1and 6. In group 1, Atherina sp. and juveniles D. labrax eat planktonic food byfiltration and small bottom-living prey (Labourg & Ste quert, 1973; Aprahamian& Barr, 1985; Trabelsi et al., 1994; Laffaille et al., 2000). These species showhigh gill raker depth for filtration and large protrusion length to ingest smallprey. 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 teethlaterally to crush prey.

With the exception of the special case ofG. affinis, functional groups 2, 3, 5, 7and 8 include more or less bottom-living, mainly carnivorous, species. Groups 2and 3 are close, so in both of them, fishes display an oral gape axis 45. Itcan be noticed that G. niger is more linked to E. vipera than to Pomatoschistussp. Indeed, G. niger and E. vipera show larger body size, protrusion and oralgape than Pomatoschistus sp. The prey spectrum of G. niger and E. vipera isgreater than Pomatoschistus sp., the two first species can feed on larger preysuch as small fishes (Joyeux et al., 1991). Salaria pavo and the flatfishes aresurprisingly placed in the same group (7) and the next group (8) consists ofC. 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 carnivorousbottom-living species is particularly well adapted for entering holes, swimmingthrough aquatic plant beds and burrowing into soft bottoms.

TheSyngnathidae, group (9), stands far apart from the other groups in FDA(Figs 3 and 4) because of the unusual pipefish characteristics. Their colourationand their long and slender body shape mimic aquatic plants among which theylive. They did not show protrusion, but their tubelike mouth allows them toingest tiny prey from some distance, which may compensate for their slowswimming, 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

978 O . D U M AY E T A L .



10/14

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 toshore 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 bylong 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 alarge 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 fishspecies. The choice was driven by their relevant interest and the easiness of theirestimation (about 1015 min are required to measure all the variables for eachindividual). This study is in the context of diversity-ecosystem function.Lagoons in Languedoc-Roussillon are highly impacted by humans. The fishcomponent is an important part to study in the functional processes in coastalecosystems (Mathiesonet al., 2000; Angeler et al., 2002; Baldo & Drake, 2002).Before investigations can be undertaken about the influence of the functionaldiversity of the fish community on lagoon stability, productivity or resilience,the first step was to classify these fish species into functional groups. Manystudies 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 moreoften used than functional groups for vertebrates, it refers more to the mechan-isms of resource sharing by species in a competitive context. Within the contextof biodiversity and ecosystem functions, a wide range of ecosystem functionsfrom the fishes are required and the functional groups seem more appropriatethan the guilds. For example, the gill raker depth is directly linked to aresource use (plankton) and thus to the guild concept whereas the swimmingabilities (fin variables) are more related to the place in the water column, habitatand 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 notcomplete to speculate about fish compartment functioning in lagoon ecosystemsand data on reproduction modes, abundances and migratory behaviour andmore generally life-history traits are required. Moreover, for seven of the 21species the various traits are measured in one specimen per species, so thesefunctional groups are far from being a final classification of lagoon fishes withindifferent 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 helpfulcomments. This work was supported by the grant 002420 from University of MontpellierII on functional diversity of lagoon fish species.




11/14

References

Adite, A. & Winemiller, K. O. (1997). Trophic ecology and ecomorphology of fishassemblages in coastal lakes of Benin, West Africa. Ecoscience4, 623.

Alatalo, R. V. (1981). Problems in the measurement of evenness in ecology. Oikos 37,199204.

Angeler, D. G., Rodrigo, M. A., Sanchez-Carrillo, S. & Alvarez-Cobelas, M. (2002).Effects of hydrologically confined fish on bacterioplankton and autotrophicpicoplankton in a semiarid marsh. Aquatic Microbial Ecology 29, 307312.

Aprahamian, M. W. & Barr, C. D. (1985). The growth, abundance and diet of 0-groupsea bass, Dicentrarchus labrax, from the Severn Estuary. Journal of the MarineBiological Association of the United Kingdom65, 169180.

Arthington, A. H., McKay, R. J. & Milton, D. A. (1986). The ecology and managementof exotic and endemic freshwater fish in Queensland. In Fisheries Management:Theory and Practice in Queensland(Hundloe, T. J. A., ed.), pp. 224245. Brisbane:Griffith University Press.

Austen, D. J., Bayley, P. B. & Menzel, B. W. (1994). Importance of the guild concept tofisheries research and management. Fisheries 19, 1220.

Bacher, C., Millet, B. & Vaquer, A. (1997). Modelling the impact of cultivatedfilter-feeders on phytoplanktonic biomass of the Thau Lagoon (France). ComptesRendus de lAcademie des Sciences 320,7381.

Baldo, F. & Drake, P. (2002). A multivariate approach to the feeding habits of small fishin the Guadalquivir Estuary. Journal of Fish Biology 61 (Suppl. A), 2132.

Bellwood, D. R. & Wainwright, P. C. (2001). Locomotion in labrid fishes: implicationsfor habitat use and cross-shelf biogeography on the Great Barrier Reef. CoralReefs 20,139150.

Bellwood, D. R., Wainwright, P. C., Fulton, C. J. & Hoey, A. (2002). Assembly rulesand functional groups at global biogeographical scales. Functional Ecology 16,557562.

Bence, J. R. (1986). Feeding rate and attack specialization: the role of predator experience

and energetic trade-offs. Environmental Biology of Fishes 16, 113121.Bence, J. R. & Murdoch, W. W. (1982). Ecological studies of insect predators and

Gambusiain rice field : a preliminary report. Proceedings of the California Mosquitoand Vector Control Association 50,4850.

Blondel, J. (2003). Guilds or functional groups: does it matter? Oikos 100, 223231.Bond, E. M. & Chase, J. M. (2002). Biodiversity and ecosystem functioning at local and

regional spatial scales. Ecology Letters 5, 467470.Bulla, L. (1994). An index of evenness and its associated diversity measure. Oikos 70,

167171.Carrasson, M. & Cartes, J. E. (2002). Trophic relationships in a Mediterranean deep-sea

fish community: partition of food resources, dietary overlap and connectionswithin the benthic boundary layer. Marine Ecology Progress Series 241, 4155.

Chapin, F. S., Walker, B. H., Hobbs, R. J., Hooper, D. U., Lawton, J. H., Sala, O. E. &Tilman, D. (1997). Biotic control over the functioning of ecosystems.Science277,500504.

Chapin, F. S., Zavaleta, E. S., Eviner, V. T., Naylor, R. L., Vitousek, P. M., Reynolds, H. L.,Hooper, D. U., Lavorel, S., Sala, O. E., Hobbie, S. E., Mack, M. C. & Diaz, S.(2000). Consequences of changing biodiversity. Nature405, 234242.

Clarke, K. R. & Warwick, R. M. (2001). A further biodiversity index applicable to specieslists: variation in taxonomic distinctness. Marine Ecology Progress Series 216, 265278.

Cleveland, A. & Montgomey, W. L. (2003). Gut characteristics and assimilation efficien-cies in two species of herbivorous damselfishes (Pomacentridae: Stegastesdorsopunicansand S. planifrons).Marine Biology 142, 3544.

Costanza, R., Darge, R., Degroot, R., Farber, S., Grasso, M., Hannon, B., Limburg, K.,

Naeem, S., Oneill, R. V., Paruelo, J., Raskin, R. G., Sutton, P. & Vandenbelt, M.(1997). The value of the worlds ecosystem services and natural capital.Nature387,253260.

980 O . D U M AY E T A L .



12/14

Courtenay, W. R. & Meffe, G. K. (1989). Small fishes in strange places: a review ofintroduced poeciliids. In Ecology and Evolution of Livebearing Fishes (Poeciliidae)(Meffe, G. K. & Nelson, F. F., Jr, eds), pp. 319331. New Jersey: Prentice Hall.

Davoren, G. K., Montevecchi, W. A. & Anderson, J. T. (2002). Scale-dependent associ-ations of predators and prey: constraints imposed by flightlessness of common

murres.Marine Ecology Progress Series 245,259272.Diaz, S. & Cabido, M. (1997). Plant functional types and ecosystem function in relation toglobal change. Journal of Vegetation Science 8, 463474.

Diaz, S. & Cabido, M. (2001). Vive la difference: plant functional diversity matters toecosystem processes. Trends in Ecology and Evolution 16, 646655.

Elliott, J. P. & Bellwood, D. R. (2003). Alimentary tract morphology and diet in threecoral reef fish families. Journal of Fish Biology 63, 15981609.

Enquist, B. J. & Niklas, K. J. (2001). Invariant scaling relations across tree-dominatedcommunities.Nature 410,655660.

Farley, D. G. (1980). Prey selection by the mosquito fish, Gambusia affinis, in FresnoCounty rice field. Proceedings of the California Mosquito and Vector ControlAssociation45, 8794.

Fiandrino, A., Martin, Y., Got, P., Bonnefont, J. L. & Troussellier, M. (2003). Bacterialcontamination of Mediterranean coastal sea water as affected by riverine inputs:simulation approach applied to a shellfish breeding area (Thau Lagoon, France).Water Research 37, 17111722.

Fonseca, C. R. & Ganade, G. (2001). Species functional redundancy, random extinctionsand the stability of ecosystems. Journal of Ecology 89, 118125.

Garrison, L. P. & Link, J. S. (2000). Dietary guild structure of the fish community in theNorth-east United States continental shelf ecosystem. Marine Ecology ProgressSeries 202, 231240.

George, J. P. & Ne de lec, C. (1991).Dictionnaire des engins de peche. Rennes: IFREMER(Ouest-France).

Goulding, M. (1985). Forest fishes of the Amazon. In Key Environments of Amazonia(Prance, G. T. & Lovejoy, T. E., eds), pp. 267276. New York: Pergamon Press.

Greenwood, J. J. D., Gregory, R. D., Harris, S., Morris, P. A. & Yalden, D. W. (1996).Relations between abundance, body size and species number in British birds andmammals.Philosophical Transactions of the Royal Society of London Series B 351,265278.

Grime, J. P. (1997). Biodiversity and ecosystem function: the debate deepens.Science277,12601261.

Grossman, G. D. (1986). Food resource partitioning in a rocky intertidal fish assemblage.Journal of Zoology, London 1,317355.

Harrington, R. W., Jr & Harrington, E. S. (1961). Food selection among fishes invadinga high subtropical saltmarsh : from onset of floading trough the progress ofmosquito brood.Ecology 42, 646666.

Harrison, T. D. & Whitfield, A. K. (1995). Fish community structure in three temporarily

open/closed estuaries on the natal coast.Ichthyological Bulletin of the J. L. B. SmithInstitute of Ichthyology 64, 180.

Helfman, G. S., Colette, B. B. & Facey, D. E. (1997). The Diversity of Fishes. Oxford:Blackwell Science.

Hill, M. O. (1997). An evenness statistic based on the abundance-weighted variance ofspecies proportions. Oikos 79, 413416.

Hubbs, C. (1971). Competition and isolation mechanism in the Gambusia affinis Gambusia heterochir hybrid swarm. Bulletin of the Texas Memorial Museum 19,146.

Huisman, J. & Weissing, F. J. (2001). Fundamental unpredictability in multispeciescompetition.The American Naturalist 157,488494.

Iljin, B. S. (1930). Le syste` me des gobiide s.Instituo Espanol de Oceanografia, Trabajos 2,

163.Jauffret, S. & Lavorel, S. (2003). Are plant functional types relevant to describe degrada-

tion in arid, southern Tunisian steppes? Journal of Vegetation Science 14, 399408.




13/14

Joyeux, J. C., Tomasini, J. A. & Bouchereau, J. L. (1991). Le re gime alimentaire deGobiusniger Linne , 1758 (Teleostei, Gobiidae) dans la lagune de Mauguio France.Annales des Sciences Naturelles, Zoologie 12, 5769.

Keast, A. & Webb, D. (1966). Mouth and body form relative to feeding ecology in the fishfauna of a small lake, Lake Opinicon, Ontario. Journal of the Fisheries Research

Board of Canada 23, 18451874.Knoppers, B. (1994). Aquatic primary production in coastal lagoons. In Coastal LagoonProcesses (Kjerfve, B., ed.), pp. 243286. Amsterdam: Elsevier Science.

Kramer, D. L. & Bryant, M. J. (1995). Intestine length in the fishes of a tropical stream : 2.Relationships to diet the long and short of a convoluted issue. EnvironmentalBiology of Fishes 42, 129141.

Labourg, P. J. & Stequert, B. (1973). Re gime alimentaire du bar Dicentrarchus labraxL.des re servoirs a` poissons de la re gion dArcachon. Bulletin dEcologie 4, 187194.

Laffaille, P., Lefeuvre, J. C. & Feunteun, E. (2000). Impact of sheep grazing on juvenile seabass,Dicentarchus labrax, in tidal salt marshes.Biological Conservation96,271277.

Lavorel, S., McIntyre, S., Landsberg, J. & Forbes, T. D. A. (1997). Plant functionalclassifications: from general groups to specific groups based on response todisturbance.Trends in Ecology & Evolution 12,474478.

Lavorel, S., Rochette, C. & Lebreton, J. D. (1999). Functional groups for response todisturbance in Mediterranean old fields. Oikos 84, 480498.

Lawton, J. H., Naeem, S., Thompson, L. J., Hector, A. & Crawley, M. J. (1998).Biodiversity and ecosystem function: getting the Ecotron experiment in its correctcontext.Functional Ecology 12, 848852.

Legendre, P. & Legendre, L. (1998). Numerical Ecology. Amsterdam: Elsevier.Loreau, M. (2000). Biodiversity and ecosystem functioning: recent theoretical advances.

Oikos91, 317.Loreau, M., Naeem, S., Inchausti, P., Bengtsson, J., Grime, J. P., Hector, A., Hooper, D. U.,

Huston, M. A., Raffaelli, D., Schmid, B., Tilman, D. & Wardle, D. A. (2001).Ecology Biodiversity and ecosystem functioning: Current knowledge and futurechallenges.Science294,804808.

Mancinelli, G., Costantini, M. L. & Rossi, L. (2002). Cascading effects of predatory fishexclusion on the detritus-based food web of a lake littoral zone (Lake Vico, centralItaly).Oecologia 133,402411.

Mathieson, S., Cattrijsse, A., Costa, M. J., Drake, P., Elliott, M., Gardner, J. & Marchand, J.(2000). Fish assemblages of European tidal marshes: a comparison based onspecies, families and functional guilds. Marine Ecology Progress Series 204,225242.

McCune, B. & Mefford, M. J. (1999).PC-ORD. Multivariate Analysis of Ecological Data,Version 4. Gleneden Beach, Oregon: MjM Software Design.

Miura, T., Takahashi, R. M. & Wilder, W. H. (1979). Habitat and food selection by themosquitofish,Gambusia affinis.Proceedings of the California Mosquito and VectorControl Association 47, 4650.

Morton, R. M., Beumer, J. P. & Pollock, B. R. (1988). Fishes of a subtropical Australiansaltmarsh and their predation on mosquitoes. Environmental Biology of Fishes 21,185194.

Motta, P. J., Clifton, K. B., Hernandez, P. & Eggold, B. T. (1995). Ecomorphologicalcorrelates in ten species of subtropical sea grass fishes : diet and microhabitatutilization.Environmental Biology of Fishes 44, 3760.

Moyle, P. B. & Cech, J. J., Jr (1988). Fishes: An Introduction to Ichthyology. New Jersey:Prentice Hall.

Naeem, S. (2002a). Disentangling the impacts of diversity on ecosystem functioning incombinatorial experiments. Ecology 83, 29252935.

Naeem, S. (2002b). Ecosystem consequences of biodiversity loss: The evolution of aparadigm.Ecology83, 15371552.

Naeem, S. & Wright, J. P. (2003). Disentangling biodiversity effects on ecosystemfunctioning: deriving solutions to a seemingly insurmountable problem. EcologyLetters 6, 567579.

982 O . D U M AY E T A L .



14/14

Niklas, K. J. & Enquist, B. J. (2001). Invariant scaling relationships for interspecific plantbiomass production rates and body size. Proceedings of the National Academy ofSciences of the United States of America 98, 29222927.

Norton, S. F. (1995). A functional approach to ecomorphological patterns of feeding incottid fishes. Environmental Biology of Fishes 44, 6178.

Petchey, O. L. & Gaston, K. J. (2002). Functional diversity (FD), species richness andcommunity composition. Ecology Letters 5, 402411.Piet, G. J. (1998). Ecomorphology of a size-structured tropical freshwater fish

community.Environmental Biology of Fishes 51,6786.Purvis, A. & Hector, A. (2000). Getting the measure of biodiversity.Nature405,212219.Rosecchi, E. (1985). Lalimentation de Diplodus annularis, Diplodus sargus, Diplodus

vulgaris et Sparus aurata (Pisces, Sparidae) dans le golfe du Lion et les laguneslittorales.Revue des Travaux de lInstitut des Peches maritimes 49, 125141.

Sanzo, L. (1911). Distributione delle papille cutanee (organi ciatiform) e suo valoresistematico nei Gobi. Mitteilungen aus der Zoologishen Station zu Neapel 20,251328.

Sibbing, F. A. & Nagelkerke, L. A. J. (2001). Resource partitioning by Lake Tana barbspredicted from fish morphometrics and prey characteristics. Reviews in FishBiology and Fisheries 10, 393437.

Simberloff, D. & Dayan, T. (1991). The guild concept and the structure of ecologicalcommunities.Annual Review of Ecology and Systematics 22, 115143.

Simpson, E. H. (1949). Measurement of species diversity. Nature 163, 688.Smith, B. & Wilson, J. B. (1996). A consumers guide to evenness indices. Oikos76,7082.Tilman, D. (1999). The ecological consequences of changes in biodiversity: a search for

general principles.Ecology 80, 14551474.Tilman, D., Knops, J., Weldin, D., Reich, P., Ritchie, M. & Siemann, E. (1997). The

influence of functional diversity and composition on ecosystem processes. Science277,13001302.

Trabelsi, M., Kartas, F. & Quignard, J. P. (1994). Comparaison du regime alimentairedune population marine et dune population lagunaire dAtherina boyerides cotes

tunisiennes.Vie Milieu 44, 117123.UNESCO (1986).Fishes of the North-eastern Atlantic and the Mediterranean , Vols II & III

(Whitehead, P. J. P., Bauchot, M.-L., Hureau, J.-C., Nielsen, J. & Tortonese, E.,eds). Paris: UNESCO.

Wainwright, P. C., Bellwood, D. R. & Westneat, M. W. (2002). Ecomorphology oflocomotion in labrid fishes. Environmental Biology of Fishes 65, 4762.

Walker, B. H. & Langridge, J. L. (2002). Measuring functional diversity in plant com-munities with mixed life forms: a problem of hard and soft attributes. Ecosystems5, 529538.

Walker, B., Kinzig, A. & Langridge, J. (1999). Plant attribute diversity, resilience, andecosystem function: the nature and significance of dominant and minor species.Ecosystems 2, 95113.

Walker, J. A. & Westneat, M. W. (2000). Mechanical performance of aquatic rowing andflying.Proceedings of the Royal Society of London Series B 267, 18751881.

Walter, L. L. & Legner, E. F. (1980). Impact of the desert pupfish, Cyprinodon macularisandGambusia affinis on fauna in pond ecosystems. Hilgardia 4, 18.

Warwick, R. M. & Clarke, K. R. (1995). New biodiversity measures reveal a decrease intaxonomic distinctness with increasing stress. Marine Ecology Progress Series 129,301305.

West, G. B., Brown, J. H. & Enquist, B. J. (1997). A general model for the origin ofallometric scaling laws in biology. Science 276, 122126.

Wilson, J. B. (1999). Guilds, functional types and ecological groups. Oikos 86, 507522.Winemiller, K. O. (1991). Ecomorphological diversification in lowland freshwater fish

assemblages from 5 biotic regions. Ecological Monographs61, 343365.



functional groups of lagoon fish species in languedoc

Documents