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Characterization of the ecological quality of the coastal Gulf of Lions (NW Mediterranean). A comparative approach based on three biotic indices Ce ´line Labrune a, * , Jean Michel Amouroux a , Rafael Sarda b , Eric Dutrieux c , Se ´bastien Thorin c , Rutger Rosenberg d , Antoine Gre ´mare a a Laboratoire d’Oce ´anographie Biologique de Banyuls, UMR 7621 CNRS—Universite ´ Pierre et Marie Curie, BP 44, F66651 Banyuls-sur-Mer, France b Centre d’Estudis Avancats de Blanes, CSIC, Cami de Santa Barbara s/n, 17300 Blanes, Girona, Spain c CREOCEAN—Agence de Montpellier, Les Athamantes, 740 avenue des Apothicaires, 34090 Montpellier, France d Department of Marine Ecology, Go ¨ teborg University, Kristineberg Marine Research Station, 450 34 Fiskeba ¨ ckskil, Sweden Abstract The ecological quality of the Gulf of Lions coast was assessed using three biotic indices (H 0 , AMBI and BQI). The three indices cor- related positively. The positive correlation between AMBI and BQI was surprising and was mostly due to the fact that the dominant species Ditrupa arietina featured a low ES50 0.05 but was classified in GI by AMBI. Both H 0 and BQI were efficient in distinguishing impacted from un-impacted sites but AMBI was not. Differences between H 0 and BQI were mainly due to the scale used to translate indices in terms of EcoQ. The three indices were able to detect the major changes in macrofauna composition, which occurred in the Bay of Banyuls-sur-Mer during the last 40 years. However, the interpretations of such changes in terms of EcoQ differed between indices. These results are discussed relative to the characteristics of the tested indices. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Biotic indices; Macrofauna; Ecological quality; Physical disturbances; Ditrupa arietina; Water framework directive 1. Introduction The European Water Framework Directive (WFD, 2000/60/EC) aims at achieving ÔGoodÕ ecological quality (EcoQ) for all European waters bodies by the year 2015. The first step towards this objective consists in assessing the current EcoQ of these water bodies. One approach rec- ommended for this assessment is the study of benthic mac- rofaunal species composition and abundance, since these parameters are known to respond in a predicted way to anthropic and natural stress (Pearson and Rosenberg, 1978). The interpretation of macrofaunal data for ecological quality assessment relies on a large set of methods (i.e., multivariate approaches, SAB curves, biotic indices), corre- sponding to different steps in the reduction of the initial information. The use of biotic indices constitutes an extreme in information reduction. It is however, the most straightforward and easy to present to potential end users, which explain that the utilization of biotic indices has been recommended within the WFD (Rosenberg et al., 2004). The assessment of the EcoQ of benthic habitats has been most often carried out within the framework of national projects (Rosenberg et al., 2004), which has led to the cre- ation of several biotic indices (e.g., Raffaelli and Mason, 1981; Warwick, 1986; Dauer, 1993; Weisberg et al., 1997; Borja et al., 2000; Rosenberg et al., 2004 and see Diaz et al., 2004 for a review). In spite of their diversity, most biotic indices are based on the Pearson–Rosenberg paradigm (Pearson and Rosen- berg, 1978), which stated that (1) species richness tends to 0025-326X/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.marpolbul.2005.08.005 * Corresponding author. E-mail address: [email protected] (C. Labrune). www.elsevier.com/locate/marpolbul Marine Pollution Bulletin 52 (2006) 34–47

Characterization of the ecological quality of the coastal Gulf of Lions (NW Mediterranean). A comparative approach based on three biotic indices

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Page 1: Characterization of the ecological quality of the coastal Gulf of Lions (NW Mediterranean). A comparative approach based on three biotic indices

www.elsevier.com/locate/marpolbul

Marine Pollution Bulletin 52 (2006) 34–47

Characterization of the ecological quality of the coastalGulf of Lions (NW Mediterranean). A comparative approach

based on three biotic indices

Celine Labrune a,*, Jean Michel Amouroux a, Rafael Sarda b, Eric Dutrieux c,Sebastien Thorin c, Rutger Rosenberg d, Antoine Gremare a

a Laboratoire d’Oceanographie Biologique de Banyuls, UMR 7621 CNRS—Universite Pierre et Marie Curie, BP 44, F66651 Banyuls-sur-Mer, Franceb Centre d’Estudis Avancats de Blanes, CSIC, Cami de Santa Barbara s/n, 17300 Blanes, Girona, Spain

c CREOCEAN—Agence de Montpellier, Les Athamantes, 740 avenue des Apothicaires, 34090 Montpellier, Franced Department of Marine Ecology, Goteborg University, Kristineberg Marine Research Station, 450 34 Fiskebackskil, Sweden

Abstract

The ecological quality of the Gulf of Lions coast was assessed using three biotic indices (H 0, AMBI and BQI). The three indices cor-related positively. The positive correlation between AMBI and BQI was surprising and was mostly due to the fact that the dominantspecies Ditrupa arietina featured a low ES500.05 but was classified in GI by AMBI. Both H 0 and BQI were efficient in distinguishingimpacted from un-impacted sites but AMBI was not. Differences between H 0 and BQI were mainly due to the scale used to translateindices in terms of EcoQ. The three indices were able to detect the major changes in macrofauna composition, which occurred in theBay of Banyuls-sur-Mer during the last 40 years. However, the interpretations of such changes in terms of EcoQ differed between indices.These results are discussed relative to the characteristics of the tested indices.� 2005 Elsevier Ltd. All rights reserved.

Keywords: Biotic indices; Macrofauna; Ecological quality; Physical disturbances; Ditrupa arietina; Water framework directive

1. Introduction

The European Water Framework Directive (WFD,2000/60/EC) aims at achieving �Good� ecological quality(EcoQ) for all European waters bodies by the year 2015.The first step towards this objective consists in assessingthe current EcoQ of these water bodies. One approach rec-ommended for this assessment is the study of benthic mac-rofaunal species composition and abundance, since theseparameters are known to respond in a predicted way toanthropic and natural stress (Pearson and Rosenberg,1978).

The interpretation of macrofaunal data for ecologicalquality assessment relies on a large set of methods (i.e.,

0025-326X/$ - see front matter � 2005 Elsevier Ltd. All rights reserved.

doi:10.1016/j.marpolbul.2005.08.005

* Corresponding author.E-mail address: [email protected] (C. Labrune).

multivariate approaches, SAB curves, biotic indices), corre-sponding to different steps in the reduction of the initialinformation. The use of biotic indices constitutes anextreme in information reduction. It is however, the moststraightforward and easy to present to potential end users,which explain that the utilization of biotic indices has beenrecommended within the WFD (Rosenberg et al., 2004).The assessment of the EcoQ of benthic habitats has beenmost often carried out within the framework of nationalprojects (Rosenberg et al., 2004), which has led to the cre-ation of several biotic indices (e.g., Raffaelli and Mason,1981; Warwick, 1986; Dauer, 1993; Weisberg et al., 1997;Borja et al., 2000; Rosenberg et al., 2004 and see Diazet al., 2004 for a review).

In spite of their diversity, most biotic indices are basedon the Pearson–Rosenberg paradigm (Pearson and Rosen-berg, 1978), which stated that (1) species richness tends to

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C. Labrune et al. / Marine Pollution Bulletin 52 (2006) 34–47 35

increase, (2) dominance tends to decrease, and (3) the pro-portion of sensitive species tends to increase during sec-ondary succession following disturbance. The Shannonindex H 0 (Pielou, 1975), the AMBI (AZTI Marine BioticIndex, Borja et al., 2000), the BENTIX (Simboura andZenetos, 2002) and the BQI (Rosenberg et al., 2004) areamong the most used and/or recent proposed biotic indi-ces. As a synthetic biodiversity index, H 0 accounts forchanges in both species richness and dominance patternduring secondary succession. Conversely AMBI, as wellas the related index BENTIX, accounts for the transitiontowards the dominance of mostly sensitive species duringsecondary succession. The recently introduced BQI is theproduct of two terms, one accounting for the relative dom-inance of tolerant versus sensitive species, and the secondone for species richness. In AMBI and BENTIX, thedegree of sensitivity/tolerance of a given species is discon-tinuous (5 and 3 Ecological groups, respectively) andbased on an analysis of the literature (Borja et al., 2000;Simboura and Zenetos, 2002). Conversely, in BQI thisparameter is continuous and based on a statistical methodapplied to the studied data set (Rosenberg et al., 2004).Another important difference between these three indicesis the use of an absolute (H 0 and AMBI) versus a localscale (BQI) to convert a biotic index in an EcoQ. Simplyput, the scale used for assessment of EcoQ from H 0 andAMBI values is unique and therefore independent of thestudied area. Conversely, the scale used for the assessmentof EcoQ from BQI values is based on the highest value ofBQI found in the studied area.

Regarding the WFD, there is a need for standardizationof the protocols and the procedures. A useful biotic indexneeds to be easy to compute, efficient in detecting distur-bances and usable for most European coasts. In May2001, a ‘‘common implementation strategy’’ was agreedupon to assist with the implementation of the WFD andit was stated that methods combining species composition,abundance and sensitivity of benthic fauna to disturbancewere the most promising (Vincent et al., 2002). AMBIand BENTIX have been tested for a large variety of com-binations of environments and disturbance sources, whichis not the case for BQI, which was introduced recently.AMBI has been tested and proven to be efficient for severalenvironmental impact sources (Borja et al., 2000; Borjaet al., 2003; Salas et al., 2004; Muxika et al., 2005). How-ever, Salas et al. (2004) reported some heterogeneity inthe response of AMBI and H 0 in given areas due to thedominance of certain species not being classified as toler-ant. BENTIX has been successfully tested on various ben-thic data as well (e.g., Simboura and Zenetos, 2002;Zenetos et al., 2004). Comparisons between BENTIX andAMBI showed a high correlation at six stations in Saroni-kos Gulf (Eastern Mediterranean) (Simboura, 2004).Marin-Guirao et al. (2005) also found a positive correla-tion between these two indices in Mar Menor Lagoon(Western Mediterranean). Conversely, these authorsreported no significant correlation between these two indi-

ces in Portman (Western Mediterranean). Moreover, theyalso reported that both AMBI and BENTIX failed to clas-sify stations according to predicted impact of metal con-taminations on benthic fauna in Mar Menor Lagoon.Thus, there is a need for assessing the potential of biolog-ical indices for environmental quality assessment withinthe WFD. Moreover, biological indices have been mostlytested in relatively localized areas under the influence of avariety of anthropogenic sources in view of assessing theirability to detect impacted areas (Borja et al., 2000; Borjaet al., 2003; Salas et al., 2004; Muxika et al., 2005). How-ever, in order to assess the EcoQ of European Waters, itis also essential to check the properties of these indiceswhen applied to larger areas (Rosenberg et al., 2004; Rog-ers and Greenaway, 2005).

In this study, we compare the H 0, AMBI and BQI indi-ces at 260 stations located in the Gulf of Lions (NorthwestMediterranean), some of them sampled since 1967. BEN-TIX was not used during the present study since it is closelyrelated to AMBI. Furthermore, the BENTIX groups ofsensitivity/tolerance species is only available as hard copy(Simboura and Zenetos, 2002) whereas AMBI can be com-puted using a free downloadable software (Borja et al.,2000). Our work constitutes the first comparison betweenAMBI and the recently introduced BQI. The WFD alsorecommends the use of reference sites to assess temporalchanges in the EcoQ of studied water types. This point isclearly beyond the scope of the present study, which isprimarily aiming at comparing biotic indices.

2. Material and methods

2.1. Macrofauna data set

The study area is the 270 km long portion of the Gulf ofLions coast located between the mouth of the Rhone Riverand the French–Spanish border. The whole studied waterbody thus clearly belongs to the category of coastal waters.Moreover, based on the degree of salinity and tidal range,it can be considered as a single water typology. The presentstudy was conducted based on quantitative data regardingthe composition and the abundance of macrofauna col-lected at 200 sites quantitatively sampled during 11 surveysbetween 1967 and 2003 (Fig. 1A). The range of samplingdepth was between 3.8 and 73.0 m. Some sites were sam-pled several times leading to a total number of 260 samples(stations). All these samples can be grouped into threemain categories. Ninety two samples were located on 21inshore–offshore transects sampled at 10, 20, 30, 40 and50 m during a boat campaign carried out in September–October 1998 along the coast between the Spain–Franceborder and the mouth of the Rhone River. Six stationslocated in the Bay of Banyuls-sur-Mer (sites 43, 31, 19,26, 178 and 183) were sampled in 1967–1968 and revisitedin 1994 and in 2003 (Fig. 1B), which allowed for a long-term comparison of indices as recommended in theWFD. The rest of the stations were sampled during several

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Fig. 1. Map of the sampling sites showing the localisation of the 260 sampled stations within the Gulf of Lions (A) and a close-up of the Bay of Banyuls-sur-Mer showing the location of the six sites (43, 31, 19, 26, 178 and 183) initially sampled in 1967–1968 and then revisited in 1994 and 2003 (B). Boldletters in (A) indicate impacted zones for which details are given in Table 1.

36 C. Labrune et al. / Marine Pollution Bulletin 52 (2006) 34–47

impact assessment studies. Some of the stations sampledduring these studies allowed to evaluate well-definedsources of disturbance (mostly sediment dumping andtrawling) and were considered impacted (Table 1), whileother stations were considered not impacted. Overall,impacted stations represented 16% of total sampled sta-tions and disturbance was mostly physical.

All samples were taken using a 0.1 m2 grab and sievedon a 1 mm mesh. The number of replicates from a givenstation was between 3 and 5 depending on surveys. Allmacrofaunal samples were identified by experienced andtrained experts to the lowest possible taxonomic level. Syn-onyms and names of species were checked following theEuropean Register of Marine Species (Costello et al.,

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Table 1Location and main characteristics of impacted sites

Location Number of stations Depth range (m) Main disturbance Disturbance type Disturbance periodicity References

Zone A 15 21–25 Sediment dumping Physical Semi-continuous Bornens et al. (2000a)Zones B and C 4 in B and 4 in C 16–31 Trawling Physical Continuous/intensive Canovas et al. (1998)Zone C 4 25–27 Bivalve aquaculture Organic

enrichment/physicalContinuous Canovas et al. (1998)

Zone D 15 25–30 Sediment dumping Physical Semi-continuous Bornens et al. (2000b)

Letters used for location refer to the zones indicated in Fig. 1.

C. Labrune et al. / Marine Pollution Bulletin 52 (2006) 34–47 37

2001). Total number of individual analysed was 110,521and the total number of taxa was 967. The granulometrydata used during the present study were restricted to anal-yses conducted using laser microgranulometry. This repre-sented a total of 164 stations out of 260.

2.2. Computation of indices

Macrofaunal data were used for the computation of H 0

(Pielou, 1975), AMBI (Borja et al., 2000) and BQI (Rosen-berg et al., 2004). H 0(log2) is the classical Shannon index.It was computed using the Primer� package. AMBIaccounts for the relative abundance of several ecologicalgroups of species (corresponding to different levels of sen-sitivity/tolerance) in a sample. It is computed as:

AMBI ¼ fð0�%GIÞ þ ð1:5�%GIIÞ þ ð3�%GIIIÞþ ð4:5�%GIVÞ þ ð6�%GVÞg=100

where %GI is the relative abundance of disturbance-sensitive species, %GII is the relative abundance of distur-bance-indifferent species, %GIII is the relative abundanceof disturbance-tolerant species, %GIV is the relative abun-dance of second-order opportunistic species, and %GV isthe relative abundance of first-order opportunistic species(Borja et al., 2000).

AMBI ranges between 0 and 6. Low AMBI are associ-ated with the dominance of sensitive species and thus highquality environments, whereas high AMBI are associatedwith the dominance of tolerant species and thus low qualityenvironments. During the present study, AMBI was com-puted using the AMBI software (http://www.azti.es).

BQI index accounts both for the relative abundance ofsensitive/tolerant species and for total species richness.Rosenberg et al. (2004) proposed to characterize the toler-ance/sensitivity of a given species based on its ES500.05.The concept of expected number of species (ES) was firstintroduced by Sanders (1968) but its computation wasmodified by Hurlbert (1971). The ES50 is the number ofspecies expected from a sub-sample of 50 individuals takenfrom the population of all the individuals present at a givenstation. It is computed as:

ES50 ¼ 1�Xsi¼1

ðN � NiÞ!ðN � 50Þ!ðN � Ni � 50Þ!N !

where N is the total abundance of individuals at the consid-ered station, Ni is the abundance of the ith species at the

considered station, and s is the number of species at theconsidered station.

Tolerant species are predominantly found in dis-turbed environments whereas sensitive species are mostlyrestricted to undisturbed or only slightly disturbed environ-ments. That means that, in theory, tolerant species mainlyoccur at stations with low ES50 whereas sensitive ones aremainly found at stations with high ES50. The ES500.05 of agiven species is defined as the ES50 corresponding to 5% ofthe total abundance of this species within the studied area.It is computed based on the distribution of total abundanceversus ES50 (Rosenberg et al., 2004).

BQI is then computed as:

BQI ¼Xsi¼1

Ai

totA� ES500:05i

� � !�10 logðS þ 1Þ

where Ai is the abundance of the ith species at the consid-ered station, ES500.05i is the ES500.05 of the ith species,totA is the total abundance of the individuals belongingto the species for which ES500.05 can be computed, and S

is the total number of species at the considered station.The first term of this equation refers to the predomi-

nance of tolerant or sensitive species and the secondone to species richness. As stated above the BQI thusaccounts for these two parameters. Conversely to AMBI,high BQI are associated with high environment quality(Rosenberg et al., 2004). As proposed by Rosenberget al. (2004), during the present study, we did not com-pute the ES500.05 of the species, which were present in lessthan 20 samples. It thus should be underlined that totAdiffers from the total abundance of macrofauna at theconsidered station.

2.3. EcoQ assessment

For H 0 and AMBI, an absolute scale composed of fiveclasses of EcoQ has been proposed. According to Molvaeret al. (1997), in Vincent et al. (2002), and Borja et al.(2004a), EcoQ is qualified as ‘‘High’’ if H 0 > 4 orAMBI 6 1.2, ‘‘Good’’ if 3 < H 0

6 4 or 1.2 < AMBI 6 3.3,‘‘Moderate’’ if 2 < H 0

6 3 or 3.3 < AMBI 6 4.3, ‘‘Poor’’if 1 < H 0

6 2 or 4.3 < AMBI 6 5.5 and ‘‘Bad’’ if H 06 1

or AMBI > 5.5 (Table 2). Conversely, the EcoQ assessedwith BQI is determined by taking the highest BQI valueas a reference value and by defining five classes of equal sizebetween 0 and this reference value. This categorization

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Table 2H 0 and AMBI classes associated with the different EcoQ status proposedwithin the WFD

EcoQ H 0 AMBI

High H 0 > 4 AMBIP 1.2Good 3 < H 0

6 4 1.2 < AMBI 6 3.3Moderate 2 < H 0

6 3 3.3 < AMBI 6 4.3Poor 1 < H 0

6 2 4.3 < AMBI 6 5.5Bad H 0

6 1 AMBI > 5.5

38 C. Labrune et al. / Marine Pollution Bulletin 52 (2006) 34–47

presents two main differences with those of H 0 and AMBI:(1) different scales must be constructed for each homoge-neous subgroups based on macrofauna composition, and(2) categorization is relative and assumes that the highestBQI constitutes a valid reference value. During the presentstudy, we divided the stations according to their depth(10 m range groups) to divide our whole data set intohomogeneous subgroups. A MDS was run on square roottransformed macrofaunal data to identify homogeneoussubgroups associated with particular depth ranges. Thedetermination of EcoQ based on BQI was carried out inde-pendently for each of these subgroups. According to theWFD, we have made the distinction between stations with‘‘High’’ or ‘‘Good’’ EcoQ on one hand and ‘‘Moderate’’,‘‘Poor’’ and ‘‘Bad’’ EcoQ (i.e., those stations needing tobe improved before 2015 according to the WFD) on theother hand.

Fig. 2. Frequency distribution of the three indices considered during the presstations P20 m.

3. Results

3.1. Analysis of the whole data set

The frequency distributions of H 0 and AMBI are pre-sented in Fig. 2A and B. The distribution of H 0 tended tobe unimodal and 46.1% of the stations were categorizedas ‘‘High’’ in terms of EcoQ. The distribution of AMBItended to be uniform with only few stations with AMBIhigher than 2 (categorized as ‘‘Good’’). The station withthe highest AMBI (3.3) was sampled in 1967 and was dom-inated by the polychaete Paraprionospio pinnata, whichbelongs to Group V (first order opportunistic species).

ES500.05 values of 30 common species are listed in Table3. The polychaetous annelid Ditrupa arietina featured anES500.05 of 2.0, which was the lowest value found duringthe present study. This species showed extremely high (upto 104 ind m�2) abundances at some stations. Conversely,the polychaetous annelid Prionospio dubia featured anES500.05 of 20.6, which was the highest value recorded dur-ing the present study. Correlation between the ES500.05found during the present study and those available forthe Swedish West Coast (www.marine-monitoring.se) wasnot significant (N = 48, r = 0.22, p = 0.13). It should how-ever be underlined that for most species, ES500.05 tended tobe within the same range in the Mediterranean and alongthe Swedish West Coast (Table 3).

ent study. (A) H 0, (B) AMBI, (C) BQI at stations <20 m, and (D) BQI at

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Table 3ES500.05 including lowest and highest values of 30 common species in theGulf of Lions

Taxa Present study Swedish studyES500.05 ES500.05

Ditrupa arietina 2.0Corbula gibba 3.5 4.7Turritella communis 4.1 12.0Scoletoma impatiens 4.8Chaetozone setosa 7.7 10.2Amphiura filiformis 8.2 9.5Pectinaria koreni 8.5 7.0Glycera unicornis 8.5Spisula subtruncata 8.6 7.2Ampelisca diadema 9.2 10.7Nephtys hombergii 9.3Glycinde nordmanni 9.6 10.7Phaxas pellucidus 9.9 9.1Nephtys incisa 10.0 9.0Nucula nitidosa 10.6Chone duneri 11.1 12.0Laonice cirrata 12.1 12.4Praxillella praetermissa 12.7 11.8Sternaspis scutata 14.6Myrtea spinifera 15.1 13.8Timoclea ovata 15.1Lumbrineris latreilli 15.2Levinsenia gracilis 15.2 9.2Ampelisca sarsi 15.5Siphonocetes neapolitanus 16.8Marphysa bellii 16.9Ampharete grubei 18.2Lumbrineris gracilis 19.5 14.7Magelona minuta 20.2 12.1Prionospio dubia 20.6

When available, the ES500.05 on the Swedish West Coast are also provided(www.marine-monitoring.se).

C. Labrune et al. / Marine Pollution Bulletin 52 (2006) 34–47 39

The positioning of the stations on the MDS plan is pre-sented in Fig. 3. MDS clearly separated stations relative totheir depths. The stations shallower than 20 m tended togroup on the lower left part of the MDS plan, whereas

Fig. 3. Positioning of the 260 sampled stations on the first plan of the MDS bsymbols correspond to the stations deeper than 20 m and the closed ones to t

those deeper than 20 m tended to group in the higher rightpart of the MDS plan. There was a significant difference inmacrofauna composition between these two subgroups ofstations (one-Way ANOSIM, p < 0.01). Moreover, therewas a significant difference in the average % of finesbetween the stations belonging to these two subgroups(Student�s t test, p < 0.01). Consequently, the transcriptionof BQI in terms of EcoQ was carried out separately for thestations shallower and deeper than 20 m. It should thus beunderlined that the distinction between the <20 m and theP20 m subgroups was not linked to water typology butrather to the conversion of BQI in terms of EcoQ.

The frequency distribution of BQI for these two depthgroups are presented in Fig. 2C and D. These two distribu-tions were significantly different (Kolmogorov–Smirnovtest, p < 0.01). BQI were between 1.7 and 24.8, andbetween 2.3 and 33.1 for the stations <20 m and P20 m,respectively. The five EcoQ classes were thus definedbetween 0 and 4.9, 9.9, 14.9, 19.8 and 24.8 for the stations<20 m, and between 0, 6.6, 13.3, 19.9, 26.5 and 33.1 for thestations P20 m depth. For both groups, most of the sta-tions were categorized as ‘‘Moderate’’ and the distributionsof BQI tended to be unimodal. However, in both cases,there were secondary peaks of stations categorized as‘‘Bad’’. The stations belonging to this category were mostlyimpacted and often largely dominated by the polychaetousannelid Ditrupa arietina. For the stations <20 m, only twostations were classified as ‘‘High’’. These two stations wereclear outliers in the overall distribution of BQI. Theyindeed corresponded to the same site, which was sampledin 2000 and 2001. The granulometry of this site was closeto those of deeper sites.

3.2. Comparison between indices

All the three tested indices correlated positively with oneanother (Fig. 4A–C). The best correlation was between H 0

ased on square root transformed macrofauna abundance data. The openhe stations shallower than 20 m.

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Fig. 4. Relationships between the three biotic indices considered duringthe present study. (A) H 0-BQI, (B) H 0-AMBI, and (C) BQI-AMBI.

Fig. 5. Relationships between the abundance of the polychaetous annelidDitrupa arietina and the three indices considered during the present study.(A) H 0, (B) AMBI, and (C) BQI.

40 C. Labrune et al. / Marine Pollution Bulletin 52 (2006) 34–47

and BQI using an exponential model. AMBI also corre-lated positively with both H 0 and BQI using simple linearregression models. This correlation was slightly higher forBQI than for H 0.

The average values of the three indices were significantlydifferent between impacted and un-impacted stations (Stu-dent�s t test, p < 0.01) with lower values for impacted thanfor un-impacted stations. This was surprising for AMBIsince this suggested a higher environmental quality atimpacted than at un-impacted stations. Species richness

was significantly lower at impacted than at un-impactedstations (14.0 ±1.5 and 47.8 ± 3.8 for impacted and un-impacted stations respectively, Student�s t test, p < 0.01).One of the obvious difference between AMBI on one sideand H 0 and BQI on the other side is the way they are deal-ing with dominance (Salas et al., 2004). In the studied area,macrobenthos is strongly (23.5 % of the total dominance)dominated by the polychaetous annelid Ditrupa arietina.The relationships between the density of Ditrupa arietina

and the three tested indices are presented in Fig. 5A–C.

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Fig. 6. Map showing the EcoQ status of the 200 sites sampled during thepresent study. Categorization is based on H 0 (A), AMBI (B), and BQI (C).The most recent sampling is plotted for each site.

C. Labrune et al. / Marine Pollution Bulletin 52 (2006) 34–47 41

When Ditrupa arietina was absent, the average of H 0 andBQI at impacted stations were significantly lower thanthose at un-impacted ones (Student�s t test, p < 0.01 in bothcases). Conversely, there was no significant difference inAMBI between impacted and un-impacted stations whenDitrupa arietina was absent (Student�s t test, p = 0.30).The stations where Ditrupa arietina was abundant alwayspresented low values ofH 0, AMBI and BQI. At the stationswhere Ditrupa arietina was present, the relationships link-ing the abundance of this species and: (1) H 0, (2) AMBI,and (3) BQI were all significant (p < 0.03 in all cases),except for BQI at impacted stations (p = 0.12). These rela-tionships significantly differed between impacted and un-impacted stations (ANCOVAs, p < 0.01 in all cases). Fora similar density of Ditrupa arietina, impacted stationstended to feature lower H 0 and BQI than un-impactedones. This was also the case, although less clearly, forAMBI.

The EcoQ status of the whole area was different depend-ing on the index used. The maps of the EcoQ statusobtained using each of the three indices considered duringthe present study are presented in Fig. 6. The use of AMBIresulted in the classification of the whole studied area as‘‘Good’’ or ‘‘High’’, whereas the use of BQI resulted in aclassification of most of the studied area as ‘‘Moderate’’.41.9% of stations were classified in the same category ofEcoQ by using H 0 and AMBI, 18.8% by using H 0 andBQI, and 16.5% by using AMBI and BQI. AMBI resultedin ‘‘High’’ or ‘‘Good’’ EcoQ whereas H 0 resulted in ‘‘Mod-erate’’, ‘‘Poor’’ or ‘‘Bad’’ EcoQ at 71 stations out of 200.AMBI resulted in ‘‘High’’ or ‘‘Good’’ EcoQ whereas BQIresulted in ‘‘Moderate’’, ‘‘Poor’’ or ‘‘Bad’’ EcoQ at 174 sta-tions out of 200. H 0 resulted in ‘‘High’’ or ‘‘Good’’ EcoQwhereas BQI resulted in ‘‘Moderate’’, ‘‘Poor’’ or ‘‘Bad’’EcoQ at 115 stations out of 200. Conversely, BQI resultedin ‘‘High’’ or ‘‘Good’’ EcoQ whereas H 0 resulted in ‘‘Mod-erate’’, ‘‘Poor’’ or ‘‘Bad’’ EcoQ at 12 stations out of 200.For H 0 and AMBI, the stations categorized as ‘‘High’’and ‘‘Good’’ spread all over the studied area. Conversely,when using BQI, the stations belonging to this categorywere mostly located in the Southern part of the studiedzone, with the important exception of a group of stationsoff Sete.

Using the three indices for the same data of impactedversus un-impacted sites did not show the same results.The relative proportions of the five EcoQ categories atimpacted and un-impacted stations, and based on thethree considered indices, are presented in Fig. 7. For bothH 0 and BQI, these proportions significantly differedbetween impacted and un-impacted stations (G test,p < 0.01 in both cases). Conversely, there was no signifi-cant difference in the proportions of these categories atimpacted and un-impacted stations while using AMBI asthe basis for the classification (G test, p > 0.25). The pro-portion of species belonging to the different ecologicalgroups involved in the computation of AMBI did notdiffer significantly between impacted and un-impacted

stations (G test, p > 0.25) (Fig. 8A). Conversely, the pro-portions of individuals belonging to the different ecolo-gical groups differed significantly between impacted andun-impacted stations (G test, p < 0.01). As opposed toexpected, the proportion of individuals belonging to GI(disturbance-sensitive species) tended to be higher atimpacted than at un-impacted stations (Fig. 8B). Thistrend was mostly due to a single species: the polychaetousannelid Ditrupa arietina.

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Fig. 7. Relative proportions of ‘‘High’’, ‘‘Good’’, ‘‘Moderate’’, ‘‘Poor’’and ‘‘Bad’’ stations at impacted and un-impacted stations. Categorizationsare based on H 0, AMBI and BQI.

Fig. 8. Percentage of each AMBI Ecological group at impacted and un-impacted sites. This percentage is based on species numbers (A) andindividuals numbers (B).

42 C. Labrune et al. / Marine Pollution Bulletin 52 (2006) 34–47

3.3. Temporal changes in the Bay of Banyuls-sur-Mer

Temporal changes of the three selected indices at the sixstations sampled in 1967–1968 and then revisited in 1994and 2003 are presented in Fig. 9. For all three indices, sta-tions 43 and 31 showed much lower values in 1994 than in1967–1968 and 2003. Here again, this pattern was surpris-ing for AMBI and due: (1) to the strong dominance of Dit-

rupa arietina in 1994, and (2) to its classification as a GIspecies by AMBI. This species sharply decreased between1994 and 2003, which together with an increase in speciesrichness resulted in an increase in H 0 and BQI between1994 and 2003.

All three indices tended to increase between 1967–1968and 2003 at station 19. BQI and AMBI showed similartemporal changes at station 26 with minimal value in1994, whereas H 0 tended to increase between 1967–1968and 2003 at the same station. The long term comparisoncarried out in 1994 (Gremare et al., 1998a) showed impor-tant changes at sites 19 and 26 as well. In 1967–1968,these two sites were dominated by the polychaetous anne-lids, Scoloplos armiger and Notomastus latericeus. The dis-appearance of Scoloplos armiger and the decrease ofNotomastus latericeus (Gremare et al., 1998a) resulted inan increase in both H 0 and BQI at site 19. The increasein AMBI at the same station was due to the apparition

of species from GII and GIII such as Myriochele daniel-

seni and Tharyx sp. The pattern was similar at site 26,except that the dominance of the gastropod Turritella

communis (ES500.05 = 4) resulted in a decrease in BQI in1994.

BQI increased between 1967–1968 and 2003 at station178, whereas there was a marked drop in AMBI between1967–1968, and 1994. This was due to the strong domi-nance of the polychaete Paraprionospio pinnata in 1967–1968. This species is classified in GIV by AMBI. It thuscontributed to the high AMBI and the low H 0 and BQIobserved at this site in 1967–1968. In 1994, the dis-appearance of Paraprionospio pinnata contributed to anincrease in H 0 and BQI and a decrease in AMBI. In2003, site 178 was highly dominated by the sipunculidAspidosiphon muelleri which contributed to decreasingH 0 and AMBI (because this species is classified in GI).The increase in BQI at this date partly resulted froman increase in species richness. The species newly foundat site 178 also featured higher ES500.05 than those pres-ent before 2003. Site 178 is the only one for whichAMBI and BQI were indicative of similar trends inEcoQ.

Finally, there was a strong increase in species richnessbetween 1967–1968 and 2003 at site 183. Conversely, thedominance pattern and the proportion of the different

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Fig. 9. Temporal changes in H 0 (A), AMBI (B) and BQI (C) at the six sites located in the Bay of Banyuls-sur-Mer, which were initially sampled in 1967–1968 and then revisited in 1994 and 2003. Vertical bars are standard deviations and different grey intensity backgrounds correspond to the different EcoQstatus.

C. Labrune et al. / Marine Pollution Bulletin 52 (2006) 34–47 43

ecological groups did not vary much during that period oftime. This resulted in an increase in H 0 and BQI and inthe absence of strong changes in AMBI.

When converted in terms of EcoQ, temporal changeswere much lower when based on AMBI than on H 0 andBQI.

4. Discussion

4.1. Relationships between H 0, AMBI and BQI

During the present study, we reported positive correla-tions between the three tested biotic indices. The best fits

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44 C. Labrune et al. / Marine Pollution Bulletin 52 (2006) 34–47

were obtained using an exponential model for H 0 and BQI,and linear ones for H 0 and AMBI and for BQI and AMBI.The positive relationship between H 0 and BQI was not sur-prising since both of these indices account for species rich-ness and dominance. This relationship was not linearbecause BQI integrates dominance both directly (throughthe weighing of ES500.05 by relative abundances) and indi-rectly (through the computation of ES500.05). The positivecorrelations between: (1) AMBI andH 0, and (2) AMBI andBQI were much more surprising although similar resultshave already been reported for H 0 and AMBI (Salaset al., 2004) and for AMBI and BQI (Grall, personal com-munication). Such positive correlations are surprisingbecause BQI and AMBI are constructed so that a worsen-ing of EcoQ should result in a decrease in BQI and anincrease in AMBI. An important difference between thesetwo indices is the way they are assessing the tolerance/sen-sitivity level of species. In AMBI, tolerance/sensitivity isassessed through a classification in five ecological groupswithin which species have been classified according to theirreported tolerance/sensitivity to disturbance. This classifi-cation is discrete and is supposed to be valid for all areas.Conversely, in BQI, the degree of tolerance/sensitivity ofspecies is continuous and assessed by the ES500.05 (Rosen-berg et al., 2004). The latter parameter is computed basedon each individual dataset. It is closely linked to domi-nance. Indeed, the stations largely dominated by one orfew species feature a low ES50, which most often resultsin a low ES500.05 value of dominant species. The two waysof assessing tolerance/sensitivity can lead to significant dis-crepancies. In the present study, the polychaete Ditrupa

arietina, which was highly dominant features an ES500.05of 2 while it is classified in GI (disturbance-sensitive spe-cies) in AMBI. Moreover, the gastropod Turritella commu-

nis featured an ES500.05 of 4.1, while it is classified in GII(disturbance-indifferent species) in AMBI. In the presentdataset, the dominant species were not opportunistic.Therefore, they were not classified as such by the AMBI.However, and because they were strong dominants, theyfeatured a low ES500.05. During the present study, thisresulted in a positive correlation between AMBI and BQIsince these two indices tended to correlate negatively withdominance. The same explanation also hold for the posi-tive correlation between H 0 and AMBI. In this case, a sim-ilar result has already been reported in the Mondegoestuary by Salas et al. (2004). These authors also attributedthis positive correlation to the dominance of certain spe-cies, which resulted in low diversity estimates although theybelonged to ecological groups usually related to non-pol-luted environments.

4.2. The ability of H 0, AMBI and BQI to differ between

impacted and un-impacted sites

A classic way to test the relevance of biotic indices is tocompare their results between un-impacted and impactedareas (Gray and Pearson, 1982; Warwick, 1986; Warwick

et al., 1987; Roberts et al., 1998; Borja et al., 2000, 2003;Rosenberg et al., 2004; Salas et al., 2004; Marin-Guiraoet al., 2005; Muxika et al., 2005). In the present study, therewere significant differences in H 0, AMBI and BQI betweenimpacted and un-impacted areas. These differences indi-cated a higher environmental quality at un-impacted sitesfor H 0 and BQI but a lower one for AMBI. Moreover,the average species richness was also lower in impactedthan in un-impacted stations. This supported that impactedstations indeed suffered from disturbance, and that H 0 andBQI were more efficient in classifying impacted stations as‘‘Bad’’, ‘‘Poor’’ and ‘‘Moderate’’ than AMBI. Conversely,it should be pointed out that H 0 and BQI also tend to clas-sify more un-impacted sites as ‘‘Bad’’, ‘‘Poor’’ or ‘‘Moder-ate’’ than AMBI (see also below).

As shown above, dominance has important effects onthe three tested indices. Moreover, these effects becomecontradictory, when dominant species are categorized asdisturbance-sensitive by AMBI. This was exactly the caseduring the present study, where the most common speciesDitrupa arietina was significantly more dominant atimpacted than un-impacted stations. This raises the ques-tion of the classification of species in AMBI as alreadypointed out by Salas et al. (2004). The AMBI classificationis mostly based on the literature data regarding organicenrichment (Grall and Glemarec, 1997; Borja et al.,2000). In this sense, it is not surprising that Ditrupa arietina

is classified in Group I since to our knowledge this specieshas never been reported in studies focusing on organicenrichment. However, the status of Ditrupa arietina relativeto other sources of disturbance is unclear and this species isfor example classified as tolerant in BENTIX (Simbouraand Zenetos, 2002). Peres and Picard (1957) considered thisspecies as primarily associated with unstable sediment andSarda et al. (2000) reported an increase in its abundanceafter dredging. Conversely, Gremare et al. (1998b) arguedthat the assemblages associated with sediment instabilityare reported to be restricted in time and space (Peres andPicard, 1957; Picard, 1965), which does not seem coherentwith the dramatic increase of this species in the whole Gulfof Lions. Moreover, the presence of Ditrupa arietina mayhave different meanings depending on communities. Thisspecies lives in sandy environments but not at shallowerdepths unless those sites are places for the accumulationof sand (Sarda, personal communication). That is whathappened at most of our impacted stations which were sub-mitted to sediment dumping and trawling. AMBI hasalready failed to detect the impact of sand extraction (Mux-ika et al., 2005). It thus seems clear that AMBI is notalways efficient in detecting physical disturbances and thatthis may partly result from an inappropriate classificationof key dominant species under some disturbances.

When considering only the stations where Ditrupa arie-

tina was absent, H 0 and BQI still showed significant differ-ences between impacted and un-impacted stations, whereasAMBI did not. This suggests that the dominance of thisspecies is not the only factor accounting for the differences

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C. Labrune et al. / Marine Pollution Bulletin 52 (2006) 34–47 45

in the ability of the three selected indices to detect distur-bance. Both H 0 and BQI are taking into account speciesrichness (which is significantly diminished at impactedsites), whereas AMBI is not. This is probably also account-ing for the inability of this last index to detect the (mostlyphysical) sources of disturbance considered during thepresent study. However, it should be pointed out that Borjaet al. (2004a) recommended not to use AMBI alone buttogether with other metrics such as species richness anddiversity. A similar approach constitutes the basis of themultimetric index recently proposed by Prior et al. (2004).

4.3. Current ecological quality status of the Gulf of Lions

Conclusions relative to the current EcoQ status of theGulf of Lions were highly depending on the index, whichwas used. AMBI resulted in the classification of the wholestudied area as ‘‘Good’’ or ‘‘High’’, whereas the two otherindices classified stations into the five classes of EcoQ pro-posed within the WFD. H 0 and BQI classified respectively31% and 69% of the stations as ‘‘Moderate’’ or lower.These proportions are higher than the 21%, which corre-sponds to the proportion of ‘‘known’’ impacted sites rela-tive to the 200 sites sampled during the present study andtaken into account in the assessment of the current EcoQof the Gulf of Lions. This suggests that BQI and H 0 mayhave the tendency to underestimate EcoQ. Differences inclassification by AMBI and the two other indices are partlyresulting from the sources of discrepancies presented in theprevious sections of the discussion. However, the use of H 0

resulted in a classification of most of the stations as ‘‘High’’while BQI classified them mostly as ‘‘Moderate’’. Thisresult is not linked to differences in absolute values of thesetwo indices since they were strongly correlated. The maindifference between the assessment of EcoQ based on thesetwo indices is the scale, which is used. This scale is fixed(i.e., not depending on the dataset) for H 0 and relative(i.e., depending on the dataset) for BQI. The scale usedforH 0 is not accounting for differences in the average diver-sity of studied areas. This could result in a shift of EcoQtowards ‘‘Good’’ and ‘‘High’’ in areas featuring high biodi-versity such as the Gulf of Lions (Guille, 1971). To solvethis problem, it is possible to not incorporate species rich-ness in the computation of the index (e.g., AMBI, with thedrawback mentioned above), or to use a relative scale toassess EcoQ as suggested by Rosenberg et al. (2004) forBQI. In order to do so, coastal typologies must be dividedinto homogeneous subgroups based on macrofauna com-position. During the present study, the studied typologywas divided into <20 m and P20 m according to macrofa-una composition and sediment characteristics. BQI werehigher at the stations P20 m than at the stations <20 m.The frequency distribution of BQI for <20 m sites showedthe presence of two outliers with high BQI, which corre-sponded to stations shallower than 20 m but presentinggranulometry and macrofauna compositions close to thoseobserved at deeper sites. Rosenberg et al. (2004) already

underlined the impact of such outliers in the assessmentof EcoQ. They suggested to set the upper limit of the clas-sification omitting outliers when they represent less than1% of the total number of stations. During the presentstudy, the removal of outliers indeed resulted in a shift ofthe peak of EcoQ from ‘‘Moderate’’ to ‘‘Good’’. However,the average EcoQ was still lower when based on BQI thanon H 0 (data not shown). Overall, the important differencesin EcoQ obtained using different biotic indices pinpointsthe importance of the careful selection of such indicesand associated procedures within the WFD.

4.4. Temporal changes of the different indices in the Bay

of Banyuls-sur-Mer

In the Gulf of Lions, quantitative historical data regard-ing the composition of macrobenthos are restricted to theCatalan Coast (Guille, 1971). Six of the sites initially sam-pled by Guille (1971) were revisited in 1994 (Gremare et al.,1998a) and then in 2003 (Labrune et al., unpublished). Thislong-term comparison showed important changes in mac-robenthos composition. Gremare et al. (1998a) alreadyreported the important changes that occurred between1967–1968 and 1994. The three indices accounted for suchdifferences. However, it should be underlined that the inter-pretation of those changes in terms of EcoQ differed for H 0

and BQI on one side and for AMBI on the other side.Overall, the use of AMBI resulted in little temporalchanges in EcoQ at all sites, whereas majors changes wereobserved at sites 43 and 31 using H 0 and BQI. Here again,this has important consequences since, one would have thetendency to conclude to the amelioration or the steadinessof EcoQ in the Gulf of Lions based on H 0 and BQI, andAMBI, respectively. The causes of the changes in macrofa-una composition which took place in the Bay of Banyuls-sur-Mer between the late 1960s and 1994 are not fullyunderstood yet (Gremare et al., 1998a,b) but currentlyattributed to natural changes. In this sense, AMBI thusappears to be less affected by natural changes than H 0

and BQI.

5. Conclusions

Our results clearly show that the EcoQ classification ofthe shallow bottoms of the Gulf of Lions greatly dependson the considered biotic index. Such a discrepancy is linkedto the main characteristics of biotic indices, namely: (1)their sensitivity to dominance, (2) their way of assessingsensitivity/tolerance (AMBI/BQI), and (3) the scales,which is used to translate the values of biotic indices interms of EcoQ. These characteristics are themselvesdepending on the aims of the indices. H 0 and AMBI bothaim at being applicable to any studied area. Consequentlythey are both using a fixed scale for the assessment ofEcoQ. These two indices nevertheless differ because AMBIis relying on dominance and sensitivity/tolerance and is notconsidering species richness, whereas H 0 is not considering

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sensitivity/tolerance. Both of these approaches may beinappropriate to compare areas featuring different biodi-versity levels (H 0), and may result in inappropriate assess-ment of EcoQ when dominant species are wronglyclassified (AMBI). BQI is highly empirical and is basedon the analysis of individual data sets. This hold both forthe assessment of sensitivity/tolerance through ES500.05and for the scale used to translate BQI in terms of EcoQ.BQI is highly sensitive to dominance and tends to classifydominant species as tolerant. Moreover, this can only beapplied to large data sets and assumes that they containa valid (i.e., fully un-impacted) reference station for eachhomogeneous subgroup (otherwise the EcoQ of the wholestudied area could be modified by further sampling). Over-all, and although useful, the use of single biotic index prob-ably constitute too much of a drastic reduction of the initialenvironmental information to come to definitive conclu-sion relative to the EcoQ of a given area. In this senseour results suggest that such indices should be used eitheras the basis for the computation of multimetric indices(Prior et al., 2004) or in association with other parameters(Dale and Beyeler, 2001; Borja et al., 2004b,c).

Acknowledgements

We thank Francois Charles for the sampling during theREDIT I campaign. We also thank the Languedoc-Rous-sillon region and the SMNLR for allowing us to use theirdata. This study was carried out within the framework ofthe SYSCOLAG project (Contrat Etat-Region 2000–2006). C. Labrune was supported by the ‘‘Conseil RegionalLanguedoc-Roussillon’’.

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