Application of biotic and taxonomic distinctness indices in assessing the Ecological Quality Status of two coastal lakes: Caprolace and Fogliano lakes (Central Italy)

)

f

)

.

t

-

.

Case study

Application of biotic and taxonomic distinctness indices inassessing the Ecological Quality Status of two coastal lakes:Caprolace and Fogliano lakes (Central Italy)

S. Prato a,*, J.G. Morgana a, P. La Valle b, M.G. Finoia b, L. Lattanzi b,L. Nicoletti b, G.D. Ardizzone c, G. Izzo a

aENEA Casaccia. Via Anguillarese 301, 00123 Rome, Italyb ICRAM, Via di Casalotti 300, 00166 Rome, ItalycUniversity of Rome ‘‘La Sapienza’’, Vle. dell’Universita 32, 00185 Rome, Italy

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3

a r t i c l e i n f o

Article history:

Received 27 August 2007

Received in revised form

7 June 2008

Accepted 11 June 2008

Keywords:

AMBI

BENTIX

Distinctness indices

Fogliano

Caprolace

EcoQS

a b s t r a c t

Marine biotic indices (AMBI, BENTIX) and the statistical tool M-AMBI (Multivariate AMBI

were applied as a comparative approach in assessing the Ecological Quality Status (EcoQS) o

two Mediterranean coastal lakes (Caprolace and Fogliano lakes) situated in the Circeo

National Park (Central Italy). The macrobenthic community was analysed using univariate

indices (community structure), correspondence analysis (CA) and taxonomic distinctness

indices (D+ and L+). The community composition showed a dominance of lagoonal species in

both coastal lakes, while in Caprolace lake marine taxa were also found. Diversity index (H0

complies to ranges found in Mediterranean lagoons and taxonomic distinctness indices

demonstrated that taxonomy structure is in accordance with natural variability ranges

Principal component analysis (PCA) on chemical parameters of water and sediment showed

that both coastal lakes differ mainly in their organic matter composition. In fact, the protein

fraction of bio-polymeric carbon prevails in Fogliano lake, while the ‘refractory’ componen

represented by carbohydrate fraction is predominant in Caprolace lake. The difference

between the two coastal lakes was also demonstrated by co-inertia analysis (COIA) per

formed using abundance of species and concentrations of chemical parameters. The results

from the application of the three biotic indices do not highlight a clear distinction between

the two lagoons. However, the AMBI index provided a more suitable evaluation of EcoQS

corresponding to ‘slightly polluted’ lagoons while M-AMBI and moreover BENTIX indices

indicated a worsening situation. The biotic indices are widely used in assessing the EcoQS in

marine environments, but their proper application in transitional waters would depend on a

resettlement; thresholds established in the biotic index scale values need to be modified

according to natural variability of transitional waters referring to abiotic conditions and

abundance of tolerant species.

# 2008 Elsevier Ltd. All rights reserved

avai lable at www.sc iencedi rec t .com

journal homepage: www.e lsev ier .com/ locate /ecol ind

* Corresponding author. Fax: +39 06 30484554.E-mail address: [email protected] (S. Prato).

1470-160X/$ – see front matter # 2008 Elsevier Ltd. All rights reserved.doi:10.1016/j.ecolind.2008.06.004

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3 569

1. Introduction

Several methodologies have been applied in European

countries in order to achieve the assessment of the Ecological

Quality Status (EcoQS) as required by the Water Framework

Directive (WFD). Accordingly, guidelines defining typologies,

reference conditions and classifications of coastal and transi-

tional waters have been drawn up (EC, 2003) and a series of

concepts, terminologies and tools were developed for the WFD

implementation (Andersen et al., 2004; Heiskanen et al., 2004;

Borja and Heinrich, 2005). Recent outcomes are highlighted in

volume 55 of Marine Pollution Bulletin (Devlin et al., 2007) and

volume 8 of Ecological Indicators (Borja and Dauer, 2008). Marine

biotic indices play an important role in regard to the ecological

status assessment of aquatic ecosystems (Diaz et al., 2004), for

example AMBI (Borja et al., 2000, 2003, 2004a,b,c; Muxika et al.,

2005, 2007a), M-AMBI (Muxika et al., 2007a) and BENTIX

(Simboura and Zenetos, 2002) are widely used. AMBI was

validated in areas involving a large set of impact sources

(domestic waste, heavy metals, submarine outfalls, drilling

cuts with ester-based mud, industrial and mining waste) in

accordance with community structure measures and multi-

variate methods used in assessing anthropogenic impacts

(Borja et al., 2003, 2004b; Muxika et al., 2005); M-AMBI is a

derived statistical tool which combines AMBI, diversity and

richness for the EcoQS assessment of previous classification of

water bodies and typologies, together with the definition of

reference conditions (Muxika et al., 2007a). BENTIX was tested

in Eastern Mediterranean through the application on three

habitat types (muddy sand, sandy mud, mud) in the presence

of different levels of organic pollution and compared to

community structure measures commonly used (Simboura

and Zenetos, 2002). These three indices were widely applied in

European marine areas (Salas et al., 2004; Simboura et al., 2005;

Marın-Guirao et al., 2005; Reiss and Kronke, 2005; Albayrak

et al., 2006; Labrune et al., 2006; Dauvin et al., 2007; Pranovi

et al., 2007; Simboura and Reizopolou, 2007; Zettler et al., 2007).

Recently, the investigation of suitable biodiversity indica-

tors in coastal and marine environments has been developed

(Feral et al., 2003) and the application of taxonomic distinct-

ness indices based on biodiversity measures has been

illustrated in several studies (Clarke and Warwick, 1998;

Rogers et al., 1999; Warwick and Light, 2002; Ellingsen et al.,

2005). These indices have been shown to detect anthropogenic

perturbation on communities (Brown et al., 2002; Warwick and

Clarke, 1995, 1998; Warwick et al., 2002; Terlizzi et al., 2005;

Leonard et al., 2006) and recently their effectiveness has been

evaluated for monitoring in transitional waters (Arvanitidis

et al., 2005; Moulliot et al., 2005a,b; Munari and Mistri, 2008).

A current approach to the EcoQS assessment tends towards

the application and the comparison of a set of methodologies

rather than the use of a single indicator (Dale and Beyeler,

2001; Borja and Muxika, 2005; Magni et al., 2005; Prior et al.,

2004; Muxika et al., 2007a) in conjunction with the definition of

reference conditions of habitat typologies (Nielsen et al., 2003;

Andersen et al., 2004; Bald et al., 2005; Mangialajo et al., 2007;

Muxika et al., 2007a).

On-going intercalibrations of classification metrics of

benthic macroinvertebrates in coastal and transitional

ecosystems are in fact performed in order to better under-

stand and analyse outputs and results achieved in different

European eco-regions (Borja et al., 2007; Labrune et al., 2006;

Reiss and Kronke, 2005; Simboura and Reizopoulou, 2008).

Therefore, ecological quality classification, and their respec-

tive threshold, has been analysed according to typologies,

considering the ecological assessment in coastal and

transitional waters (Quintino et al., 2006; Dauvin, 2007;

Ruellet and Dauvin, 2007; Blanchet et al., 2008; Borja and

Dauer, 2008).

This paper reports the results from the application of biotic

and taxonomic distinctness indices and univariate and

multivariate indices analyses as a comparative approach in

the Ecological Quality Status of two Mediterranean coastal

lakes located in the Circeo National Park in Central Italy.

2. Materials and methods

2.1. Study sites and data sets

The study was carried out at Caprolace and Fogliano lakes, two

coastal lakes situated in the Circeo National Park in Latium,

Central Italy. Both transitional water systems have been

included in the Ramsar List of Wetlands of International

Importance since 1978. In order to avoid water pollution,

freshwater input coming from watercourses, mainly from

drainage channels of agriculture land, was rejected and for

this reason the salinity of coastal lakes often exceeds 35 PSU,

especially during the summer. There is no excessive environ-

mental pressure on these areas, however, there are a few areas

nearby used for extensive agriculture activity and cattle

breeding.

The studies regarding these coastal lakes were concerned

with their biogeochemical state (Izzo et al., 1998, 2005, in

press), models for trophic and detrital dynamics (Hull et al.,

2000; Cioffi and Gallerano, 2001) and relationships between

sediment and macrophytes (Izzo et al., 1998, in press).

Regarding the zoobenthic communities, special attention

was paid to the structure analysis in relation to the trophic

conditions of these lakes (Ardizzone et al., 1982–1984, 1991;

Gravina, 1986; Gravina et al., 1989; Nicoletti et al., 2006). Recent

studies were carried out at these coastal lakes ichthyofauna

and its feeding habit (Tancioni et al., 2003; Mariani, 2001, 2006;

Mariani et al., 2002; Costa and Cataudella, 2007).

Caprolace lake with an area of 2.26 km2 and a maximum

depth of 2.9 m is connected to the Tyrrhenian Sea via the ‘San

Niccolo’ channel. The salinity is variable (32.3–42.4 PSU) and

the bottom is almost entirely covered by the phanerogam

Cymodocea nodosa. There are also several patches of Ruppia

cirrhosa and Zostera noltii (Izzo et al., in press).

Fogliano lake is connected to the sea via the ‘Foce del Duca’

channel. The salinity is very variable (28.5–48.9 PSU) during

the year. It is larger than Caprolace lake with an area of

4.08 km2, and a maximum depth of 2 m, and still shows higher

nutrient levels in spite of the closure of nutrient sources from

freshwater inlets. Widespread prairies of R. cirrhosa cover

almost entirely the bottom while C. nodosa is present only in a

few patches in the central area of the coastal lake (Izzo et al., in

press). Both coastal lakes are mainly characterized by sandy

sediment (Varrone, Pers. Com.).

Fig. 1 – Zoobenthos sampling sites at Caprolace and Fogliano lakes (Circeo National Park).

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3570

In this study, benthic macroinvertebrate communities were

analysed at nine soft-bottom sampling stations, five at

Caprolace lake, denominated Ca1, Ca2, Ca3, Ca4 and Ca5, and

four at Fogliano lake, denominated Fo6, Fo7, Fo8, Fo9 (see Fig. 1).

Samples were collected during 2004 in February, May, Septem-

ber and November utilizing a Van Veen grab (0.05 m2); two

replicates were collected at each station (total area = 0.1 m2).

Samples weresieved (Ø = 1 mmmesh) in thefieldand preserved

utilizing a buffered solution of formaldehyde (4% in brackish

water). Specimens were identified to the lowest possible taxon

(Castelli et al., 2003) and their abundance was quantified as

number of individuals per sample.

2.2. Data analyses

The macrobenthic community was examined using abun-

dance, species richness (Margalef’s d index), diversity (Shan-

non’s H index) and evenness (Pielou’s J index). Mean values of

the indices were calculated for each sampling site in relation

to the whole study period. A two-way table of abundance

(n.ind./0.1 m2) per sampling site was analysed by multivariate

correspondence analysis (CA) (Benzecri, 1973).

A principal component analysis (PCA) (Legendre and

Legendre, 1984) utilizing a two-way table of chemico-physical

parameters (Izzo et al., 2005) and sampling stations was

performed. The parameters used were sulphate reduction,

acid volatile sulphides (AVS), total, organic and inorganic

phosphorous, orthophosphates, nitrites, ammonia, proteins

(PRT), % PRT, carbohydrates (CHO), % carbohydrates, lipids, %

lipids, bio-polymeric carbon (BPC), total carbon (TC), total

nitrogen (TN), autotrophic organic carbon, % autotrophic

organic carbon, PRT/CHO, organic carbon (OC), BPC/OC, total

nitrogen (TN), proteinic nitrogen (N-PRT), N-PRT/TN. The bio-

polymeric fraction of Carbon (BPC) (sensu Fabiano and

Danovaro, 1994) represents the sum of equivalents of carbon

of the main biochemical classes (carbohydrates, proteins and

lipids).

A co-inertia analysis (COIA) was carried out using the same

data of abundances and chemico-physical parameters. This

multivariate method, that works on a covariance matrix,

identified co-relationships in multiple datasets which contain

the same samples, allowing the projection of the variables of

two datasets in the same space (named co-inertia plane)

(Doledec and Chessel, 1994; Doledec et al., 1996; Dray et al.,

2003). The co-inertia analysis, using the results of CA and PCA,

produced scores for each sampling site that incorporate

macrobenthic composition and abiotic features.

An approach to the EcoQS assessment of both coastal lakes

was performed by applying the indices BENTIX (Simboura and

Zenetos, 2002), AMBI (Borja et al., 2000, 2003; Muxika et al.,

2005) and its multivariate extension M-AMBI (Borja et al., 2007;

Muxika et al., 2007a). AMBI and BENTIX are based on the

tolerance of macrobenthic taxa towards pollution utilizing

their classification in ecological groups (EG) according to the

model of macrobenthic assemblages following gradients of

organic enrichment (Pearson and Rosenberg, 1978). Tolerant

species are weighted separately in AMBI while all tolerant

species are equally weighted in BENTIX. For the calculation of

AMBI and M-AMBI, AMBI version 4.1 with the species list

version of December 2007 (available at AZTI’s web page http://

www.azti.es) was utilized according to the guidelines from the

authors (Borja and Muxika, 2005). The statistical tool M-AMBI

involves a factorial analysis, associating AMBI values and

reference ranges of species richness and diversity, and a final

discriminant analysis (DA). The M-AMBI application requires

the definition of reference conditions related to the typology

under study (Muxika et al., 2007a; Borja et al., 2008a). In our

analysis we utilized historical data regarding benthic samples

collected from 1983 to 2000 (Ardizzone et al., 1982–1984, 1991;

Nicoletti et al., 2006) setting ‘high EcoQS’ reference conditions

with the highest richness and diversity values found during

that period (S = 23, H0 = 3.6) and AMBI = 0; while ‘bad EcoQS’

was fixed at the lowest possible richness and diversity values

(0) and the highest AMBI value (6).

For the BENTIX calculation we used the scores assigned to

species according to the methodology (http://www.hcmr.gr/

english_site/services/env_aspects/bentix.html) amending

some scores suggested by Dr. A. Zenetos (Pers. Comm.).

Two taxonomic distinctness indices based on the presence/

absence of species (Clarke and Warwick, 1998, 2001a) were

Table 1 (Continued )Caprolace Fogliano

Abarenicola claparedii *

Armandia cirrhosa * *

Phyllodocidae ind. * *

Glycera unicornis *

Glyceridae ind. *

Hesionidae ind. * *

Neanthes caudata *

Nereis ind. * *

Nereididae ind. * *

Aphroditidae ind. *

Lumbrineris coccinea *

Lumbrineris gracilis * *

Lumbrineris latreilli *

Ampharetidae ind. *

Terebellidae ind. *

Hydroides ind. *

Janua pagenstecheri * *

Serpulidae ind. *

Polychaeta ind. * *

Crustacea

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3 571

applied: the average taxonomic distinctness (D+) and the

variation in taxonomic distinctness (L+). The index D+ shows

the average degree in which the individuals are connected to

each other and has the capability to provide more information

than the measurement of species richness alone (Warwick

and Clarke, 1998). The index L+ reflects the unevenness of the

distribution of taxa across the hierarchical taxonomic tree.

The D+ and L+ statistics for Fogliano and Caprolace lakes

were tested for ‘departure from expectation’, referring to a

master taxonomy list of 177 species drawn up using historical

data of these coastal lakes (Ardizzone et al., 1982–1984, 1991;

Nicoletti et al., 2006) and considering five taxonomic levels

(species, genus, family, order, class and phylum). Therefore, a

simulated distribution of a random subset from this master list

was constructed. In this way a ‘funnel’ plot was obtained

indicating the predictable range in which the variability in

biodiversity due to natural environmental factors generally fell.

The statistical analysis was carried out using PRIMER 6

(Plymouth Marine Laboratory, UK) and ‘R’, The R Project for

Statistical Computing.

Leptochelia savignyi * *

Idotea chelipes *

Cymodoce spinosa * *

Microdeutopus bifidus * *

Microdeutopus gryllotalpa * *

Microdeutopus versiculatus *

Corophium insidiosum *

Dexamine spinosa *

Gammarus insensibilis * *

Gammarus ind. *

Ericthonius brasiliensis *

Elasmopus rapax *

Amphipoda ind. *

Palaemon elegans *

3. Results

3.1. Macrobenthic composition

The macrozoobenthic composition of the two coastal lakes is

characterized by a similar number of taxa. However, differ-

ences in community structure concerning taxa composition

(Table 1) and relative abundances were established to be

present. In total 50 taxa and 1930 individuals were found in

Caprolace lake while 49 taxa and 3482 specimens were found

in Fogliano lake.

Table 1 – Taxa collected (presence/absence) at Caprolaceand Fogliano lakes

Caprolace Fogliano

Mollusca

Heleobia stagnorum *

Nassarius reticulatus *

Haminoea hydatis *

Cerithium vulgatum *

Cyclope neritea * *

Loripes lacteus *

Mytilaster marioni *

Cerastoderma glaucum * *

Abra ovata * *

Tapes decussatus * *

Polychaeta

Orbinia cuvieri *

Phylo foetida * *

Scoloplos armiger *

Aonides oxycephala *

Spio decoratus *

Paraonidae ind. *

Cirratulidae ind. *

Capitella capitata *

Capitella ind. *

Dasybranchus caducus * *

Heteromastus filiformis * *

Notomastus ind. *

Palaemon longirostris *

Hippolyte leptocerus *

Hippolyte longirostris *

Liocarcinus arcuatus * *

Echinodermata

Amphipholis squamata * *

Ophiura ind. * *

Tunicata

Botryllus schlosseri *

Altri

Hydrozoa *

Actiniaria * *

Cnidaria *

Chironomidae * *

Nemertea *

Sipuncula * *

Nematoda * *

Bryozoa *

The Polychaeta species was found to dominate the

macroinvertebrate community of Caprolace lake during the

whole study period (58.7%). To this, Crustacea (12.9%),

Mollusca (11.5%), and typical marine taxa, like Actinaria

(10.9%) and Cnidaria (4.7%) were frequently collected. The

highest values of species number and abundance were found

at Ca3 station (Table 2). Polychaeta are represented mainly by

Heteromastus filiformis and Spio decoratus species. In particular,

Table 2 – Mean values of univariate indices (number of species, S; number of individuals, N; Margalef index, d; Shannonindex, H0 and Pielou index, J) concerning community structure at each sampling site during the study period

Stazioni S e.s. N e.s. d e.s. H0 e.s. J e.s.

Ca1 4.8 2.3 17.0 11.2 1.3 0.5 1.2 0.4 0.5 0.2

Ca2 6.3 1.9 34.5 24.9 1.8 0.3 1.9 0.1 0.8 0.1

Ca3 7.0 1.4 268.3 98.2 1.1 0.2 1.2 0.2 0.4 0.0

Ca4 5.0 1.3 21.5 2.7 1.3 0.4 1.6 0.5 0.7 0.1

Ca5 3.5 1.7 28.8 18.9 0.8 0.3 1.0 0.4 0.5 0.2

Fo6 7.3 1.9 355.7 139.2 1.1 0.3 1.4 0.6 0.5 0.2

Fo7 8.7 2.3 170.7 117.8 1.7 0.2 1.6 0.3 0.6 0.2

Fo8 10.8 1.4 242.0 175.6 2.0 0.1 2.5 0.1 0.7 0.1

Fo9 6.3 1.4 205.8 21.7 1.0 0.3 1.6 0.5 0.6 0.2

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3572

S. decoratus was found only at Ca3 station where the

macrophyte C. nodosa is abundant. Among Crustacea, above

all two amphipods were sampled, Microdeutopus gryllotalpa

and Microdeutopus bifidus, both sampled only at Ca2 and Ca5

Fig. 2 – Correspondence analysis (CA): (a) factor loading

stations, where C. nodosa is abundant. Among Mollusca, the

bivalve Loripes lacteus was chiefly found at Ca3 station.

High abundance values of both Chironomidae (32.8%) and

Mollusca (30.7%) were found in Fogliano lake during the whole

s (species) and (b) factor scores (sampling stations).

Fig. 3 – Principal components analysis (PCA): (a) factor loadings (chemical compounds) and (b) factor scores (sampling sites).

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3 573

Fig. 4 – Seasonal trend of ratios protein (PRT)/carbohydrates (CHO) and biopolimeric carbon (BPC)/organic carbon (OC) in

Caprolace and Fogliano lakes (from Izzo et al., 2005).

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3574

study period. High individual numbers were registered at Fo6

station while the highest number of species was found at Fo8

station (Table 2). Chironomidae were present in all sampling

sites but particularly abundant at Fo6 and Fo9 stations.

Mollusca were characterized by the brackish water bivalve

Abra ovata, present in all sampling sites (28.9%), but especially

abundant at Fo7 (November) and Fo8 (February). Another

bivalve found in Fogliano lake was Cerastoderma glaucum,

common in lagoonal ecosystems (Gravina, 1986). Several

specimens of polychaetes (H. filiformis, Abarenicola cleparedii

and Hydroides elegans), amphipods (M. gryllotalpa and Gam-

marus insensibilis) and isopods (Idotea chelipes) were also

collected.

Peaks in abundance were found in samples collected in

May and November at Caprolace lake, and in February and

November at Fogliano lake.

3.2. Univariate and multivariate analyses

Table 2 shows the mean values of univariate indices (number

of species, S; number of individuals, N; Margalef index, d;

Shannon index, H0 and Pielou index, J) concerning community

structure in both coastal lakes during the whole study period.

Multivariate correspondence analysis (CA) did not show

either a sharp distinction among sampling sites of the two

coastal lakes or a distinction based on taxa abundances (Fig. 2).

Low variability showed by axes 1 and 2 (25%) was probably

influenced by a great numbers of rare species.

The zoobenthic community of Fogliano lake is chiefly

composed of typical taxa of the Mediterranean brackish

waters, such as the bivalves A. ovata, C. glaucum, the

amphipods M. gryllotalpa, G. insensibilis, Corophium insidiosum

and the Chironomidae insects, and also by opportunistic

species found to be tolerant to organic pollution such as the

polychaetes H. filiformis and H. elegans. On the other hand, the

macrobenthic structure of Caprolace lake is quite different. In

fact, a large number of taxa distinctive of marine and semi-

enclosed coastal environments (Actinaria,Armandia cirrhosa, L.

lacteus, M. bifidus and Leptochelia savignyi), species tolerant to

organic enrichment (polychaetes Neanthes caudata and S.

decoratus) and species with a wide ecological range were

collected. In particular, some of these species are present in

areas where seawater exchange is reduced, often in conditions

of organic matter enrichment and of low dissolved oxygen

concentration.

The principal component analysis performed using phy-

sico-chemical parameters set a well-defined distinction

between the two coastal lakes. The results of PCA indicate

that our set of chemical-physical variables explained the 58%

of the variability along the first two axes (Fig. 3). Fig. 3

(correlation circle) shows a clear separation between the two

coastal lakes. Results are consistent with the respective

composition of organic matter on sediments (Fig. 4). In fact,

the sediment of Fogliano lake has a higher protein content, as

shown by high values of protein (% PRT), proteins/carbohy-

drate (PRT/CHO), proteinic nitrogen/total nitrogen (N-PRT/TN),

biopolymeric carbon/total organic carbon (BPC/OC), auto-

trophic carbon (% Carb.Autotr.); on the contrary, the sediment

of Caprolace lake is mainly represented by an high content of

carbohydrates (CHO), lipids, total organic carbon (OC), total

carbon (TC), total nitrogen (TN), bio-polymeric carbon (BPC),

proteinic nitrogen (N-PRT).

The co-inertia analysis showed a marked distinction

among the sampling sites (Fig. 5) on the basis of sediment

composition and macrobenthic assemblages of both coastal

lakes. The inertia projected on the first two axes represents

about the 80% of the total inertia. In fact, in the co-inertia

space, correlations between the organic fractions of sediment

(TC, TOC, BPC, %CHO, CHO, Porg) and distinctive macro-

zoobenthic species (L. lacteus, M. bifidus, Microdeutopus versicu-

latus, Dexamine spinosa) were found in Caprolace lake.

On the other hand sampling sites of Fogliano lake were

gathered specifically in relation to protein fractions of

sediment and dominance of brackish water taxa (Heleobia

stagnorum, A. ovata, G. insensibilis and Chironomidae).

3.3. AMBI, M-AMBI and BENTIX

The application of the indices AMBI, M-AMBI and BENTIX did

not highlight a clear distinction of the two coastal lakes

(Table 3). In only two samples of Caprolace lake the three

indices AMBI, M-AMBI and BENTIX were concordant on the

ecological status assessment. Comparing pairs of indices, a

higher number of matching among classes was found between

AMBI and M-AMBI (57% in Fogliano lake and 30% in Caprolace

lake, respectively).

Mismatch (A) and absence (B and C) of assignment of

ecological group (showed as percentage of individuals) are

reported in Table 3, while taxa involved in discordances on

assignment of ecological group are listed in Table 4.

Fig. 5 – Co-inertia analysis: (a) Correlation circle between CA factors and axes of the co-inertia ordination space; (b)

correlation circle between PCA factors and axes of the co-inertia ordination space; (c) Eigen values of co-inertia analysis; (d)

PCA plot in the co-inertia ordination space; (e) CA in the co-inertia ordination space and (f) sampling sites distribution in the

co-inertia ordination space.

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3 575

Table 3 – AMBI, M-AMBI and BENTIX values and respective classes of EcoQS

A: individuals (%) showing discordant EG assignment, B: individuals (%) without EG assignment by applying AMBI, C: individuals (%) without EG

assignment by applying BENTIX.

Table 4 – Disagreement on the assignment of Ecologicalgroups (EG) to taxa by BENTIX and AMBI methods

TAXA EG BENTIX EG AMBI

Amphipholis squamata T I

Cymodoce spinosa T I

Dasybranchus caducus S III

Gammarus insensibilis T I

Ericthonius brasiliensis T I

Ericthonius brasiliensis T I

Loripes lacteus T I

Lumbrineris latreilli T II

Phylo foetida T I

T: tolerant, S: sensible, I: very sensible to organic enrichment, II:

indifferent to organic enrichment, III: tolerant to excess of organic

enrichment.

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3576

In order to satisfy the WFD requirements it has been

referred to ‘acceptable’ (high or good classes) and ‘not

acceptable’ (moderate, poor or bad classes) EcoQS status: this

approach is useful to establish if restoration measures are

necessary to reach the ‘good’ status by 2015. In our study,

taking into account the threshold between the classes

‘moderate’ and ‘good’ it appears that the percentage of

samples classed as ‘acceptable’ EcoQS (high + good) are 75%

for AMBI, 50% for M-AMBI, 0% for BENTIX in Caprolace lake,

while the percentages of the same classes are 79% for AMBI,

64% for M-AMBI and 0% for BENTIX in Fogliano lake. These

results are summarized in Fig. 6 which shows the percentages

of samples for each classes of EcoQS according to the benthic

indices. If the sites with more than 20% of organisms with

missing EG are excluded, the percentages of acceptable EcoQS

in Caprolace lake decreases for BENTIX (BENTIX = 0) but the

worsening trends in the assessment of M-AMBI and BENTIX

was confirmed. In particular, BENTIX index has not ever

Fig. 6 – Percentages of samples from Caprolace and Fogliano lakes for each classes of EcoQS according to AMBI, M-AMBI and

BENTIX.

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3 577

assigned a better assessment as compared with AMBI and

BENTIX.

3.4. Taxonomic distinctness indices

Taxonomic distinctness indices (D+ and L+) computed using

data from Caprolace and Fogliano lakes showed that their

values fell inside the confidence limits of the 95% probability

‘funnel’ obtained from the simulations (Fig. 7), indicating that

the macrobenthic composition did not depart significantly

from the null expectation of a random selection from the

reference master list and therefore no anthropogenic dis-

turbance was detected by these measures in both coastal

lakes. Only Ca2 station fell below the limits of the ‘funnel’ with

the lowest value of D+ (58.33) in May and with the highest value

of L+ (351.47) in September.

4. Discussion

The macrobenthic communities found at Caprolace and

Fogliano lakes are well-diversified showing rich set of species

in wide taxonomic structures, and do not reflect highly

disturbed conditions on these transitional ecosystems. The

high seasonal variability of abundances is mainly due to

different life cycles of several taxa which dominate in both

coastal lakes, as the polychaeta S. decoratus and Actinaria in

Fig. 7 – Values of the average taxonomic diversity (D+) and valu

macrozoobenthos communities of Caprolace and Fogliano lakes

confidence funnel.

Caprolace lake and the mollusc A. ovata and Chironomidae in

Fogliano. Moreover, seasonal trends of the macrobenthic

communities of these two coastal lakes can be attributed to

the naturally fluctuating environmental conditions (Gravina

et al., 1989).

In both coastal lakes, the values of community structure

parameters (as specific richness and diversity) do not highlight

meaningful environmental perturbations (Table 2). The noted

differences between the two lakes mainly concern the species

composition.

Euryhalin and eurytherm species were found in Fogliano

lake, such as the amphipods G. insensibilis and typical brackish

water species such as A. ovata and M. gryllotalpa (Ardizzone

et al., 1991; Rossi et al., 1997), the latter species being

commonly associated to algal covering (Nicolaidou and

Kostaki-Apostolopoulou, 1988).

Other species, tolerant to organic enrichment and low

oxygen concentration, were also collected, such as the

polychaeta H. elegans (Lardicci et al., 2001) and Lumbrineris

latreilli, considered as ‘an indicator of instability and zones of

transitional pollution’ (Bellan, 1985; Pearson and Rosenberg,

1978).

Macrobenthic composition of Caprolace lake is featured by

the presence of several marine species (Actinaria, M. bifidus, L.

savignyi). Among these, some species, indicators of organic

enrichment, like the polychaetes S. decoratus and H. filiformis

were collected. The latter species is an opportunistic species

es of variation in taxonomic diversity (L+) for the

, plotted against the number of species on the 95%

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3578

frequently collected in semi-enclosed coastal areas (Nicoletti

et al., 2006) enriched with organic matter (Lardicci et al., 2001).

Mean values of Shannon–Weaver’s index (Table 2) fit

within the values found in Mediterranean lagoons according

to Simboura and Zenetos, 2002.

In Caprolace lake, Ca5 station shows lower values of H0, d,

and J indices, probably due to the distance from the channel

connecting it to the sea. In this case, communities could be

affected by the reduced ‘vivification’ of the inner area due to

lower seawater exchange. On the other hand, high values of

these indices were found in Fo8 station, located in front of the

‘Foce del Duca’ outfall of Fogliano lake, where the seawater

exchange is higher.

A clear distinction of the two coastal lakes is found through

the co-inertia analysis (Fig. 5) through the projection in a single

plain of results arises from PCA on chemical parameters

(Fig. 3) and CA on macrobenthic species composition (Fig. 2);

this differentiation could be related to the quality and

concentration of sediment organic matter. The BPC/OC ratio,

expressed as a percentage, is considered an index of ‘trophic

quality’, while the protein to carbohydrates ratio (PRT/CHO)

estimates the organic material ageing (Fabiano et al., 1997).

In Caprolace lake the organic matter is predominantly

refractory and ‘dated’; in fact the prevailing component of BPC

is related to carbohydrates which are poorly available to

benthic consumers. On the other hand, high values of PRT/

CHO and BPC/OC in Fogliano lake (Fig. 4) represent respectively

newly built organic substance and prevalence of labile fraction

(Fabiano et al., 1997; Cividanes et al., 2002; Dell’Anno et al.,

2002). The origin of this ‘newly created’ organic matter is

probably related to the processing of the detritus coming from

submerged seagrass meadows of the dominant species R.

cirrhosa which accumulate the amino acid proline in the

cytoplasm as a defence mechanism, to withstand and balance

high saline concentrations in vacuolar fluids (Izzo et al., in

press). The protein component is readily available for bacterial

mineralization enhancing the growth rate of macroinverte-

brates (Taghon and Greene, 1990). Co-inertia results also

highlighted that composition of sediment is correlated to the

presence of several tolerant macroinvertebrate taxa widely

represented in Fogliano lake, such as H. stagnorum, A. ovata, G.

insensibilis and Chironomids.

In order to define the EcoQ assessment it is necessary to

settle ‘type-specific reference conditions’ as required from the

WFD. There are different options for deriving reference

conditions: (i) comparison with an undisturbed site or a site,

with only very minor disturbance; (ii) historical data and

information; (iii) models; or (iv) expert judgement (WFD, 2000/

60/EC Annex II, 1,3[iii]). If reference conditions have to be

defined using modelling, either predictive models or hindcast-

ing using historical, paleolimnological, and other available

data can be applied (Heiskanen et al., 2004; Nielsen et al., 2003;

Andersen et al., 2004).

In this research, the references values for Shannon

diversity and species richness expected under undisturbed

conditions are establish on the base of pre-existing data of the

zoobenthos of Caprolace and Fogliano lakes measured from

1983 to 2001.

The EcoQS levels of the two coastal lakes obtained by

applying AMBI, M-AMBI and BENTIX (Table 3) were not

concordant. In particular BENTIX index always assigned a

‘not acceptable’ EcoQS, highlighting a very impacted situation.

There is no evidence of high environmental disturbance on

both coastal lakes, as shown by their chemical analysis and

zoobenthic community composition; therefore, AMBI seems

to be more appropriate than M-AMBI and BENTIX in reflecting

ecological status of these brackish water ecosystems.

Differences in EcoQS assessment with AMBI, M-AMBI and

BENTIX were explained by several factors, like

(a) D

species. Despite the recent efforts of the indices authors to

revise the libraries of the species list some taxa resulted as

‘sensitive’ according to AMBI, while are ascribed as

‘tolerant’ according to BENTIX. The assignment of EG to

species is often arguable since based on field remarks

rather than right knowledge of their autoecology (Ponti

et al., 2002) and may vary between scientist and geogra-

phical area (Rosenberg et al., 2004). Moreover, species react

differently depending on inter-species interaction and

environmental conditions (Dauvin, 2007). In our study, we

found nine species with discordant EcoQS assignment

(Table 4). As a consequence of this fact high percentages of

individuals were excluded by the computation of the

indices in some sites (Table 3 column A). In particular, the

difference in the rank of EcoQS assigned by the two indices

is largely attributed to differences in the scoring respec-

tively of the bivalve L. lacteus sampled in Caprolace lake,

particularly in Ca3 station and the amphipod G. insensibilis

in Fogliano lake, mainly in Fo8 and Fo9 stations. Therefore,

the assignment of ecological group to species is not a factor

to be underestimated when using these biotic indices for

these coastal lakes.

(b) T

lead to an exclusion of large number of individuals in

applying biotic indices. In this study 12/34 samples for

BENTIX showed more than 20% of organisms without

assignment of EG, with high percentages of individuals,

83.1% (Table 3 column B). In fact the assignment to an

ecological group is not fulfilled for taxa living in limited

geographical areas. However, the check lists of AMBI and

BENTIX are constantly up-to-date, even though the AMBI’s

one is more exhaustive (including more than 4400 taxa).

Anyway the lacking of species in the lists could impair the

assessment of ecological status of transitional waters

where dominance of one or few species is commonly

observed. Therefore, it would be necessary creating a

definitive version of the list, made public, in order to

minimize ‘the variability of the subjective expert judge-

ment’ (Ruellet and Dauvin, 2007).

(c) T

between AMBI and BENTIX owing to the differential

weight each index puts in the different ecological groups.

BENTIX tends to reveal extreme values in the EcoQS

because species are ascribed only to 2 EG rather than 5 EG

of AMBI (Borja et al., 2004c). In the case where commu-

nities are dominated by tolerant species, the BENTIX

index assesses a lower EcoQS rather than AMBI. In this

study, such a difference was found in a transitional

system (Fogliano lake, sites Fo6 and Fo9 in May, Fo7 in

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3 579

February, Fo7 in November and Fo8 in February) where

communities were dominated by the bivalve A. ovata

(assigned ‘EG III’ by AMBI and ‘2’ by BENTIX) and therefore

the EcoQS final assessments were always lower for

BENTIX index (see Table 3).

(d) F

among quality classes. A debatable topic concerns the

definition of the threshold between the ‘good’ status and

the ‘moderate’ one, namely what is an ‘acceptable’ status

or when it is necessary to spend resources for the

restoration of an ecosystem (Blanchet et al., 2008). In this

study, the highest number of ‘acceptable’ classes (good + -

high) of EcoQS were obtained by AMBI, followed by M-AMBI

and BENTIX (Fig. 6). In addition to previous factors, the

quite different scaling in AMBI, M-AMBI and BENTIX could

affect the EcoQS assessment. In fact, AMBI and M-AMBI set

a wider good class (1.2–3.3 for AMBI; 0.55–0.85 for M-AMBI)

compared to the moderate (3.3–4.3) and high (0–1.2) classes

of AMBI, and compared to the moderate (0.39–0.55) classes

of M-AMBI, while BENTIX sets the same distances for the

moderate (2.5–3.5) and good (3.5–4.5) classes. The applic-

ability of indices in relation to their thresholds values of

ecological classification are currently analysed (Quintino

et al., 2006; Simboura and Reizopolou, 2007), in transitional

systems (Dauvin, 2007; Ruellet and Dauvin, 2007), pointing

out that sometimes arbitrary thresholds between cate-

gories remains (Blanchet et al., 2008; Dauvin, 2007).

Transitional water is a naturally organic enriched envir-

onment and the use of indices based on the species

tolerance/sensitivity mainly due to organic pollution

might reduce their effectiveness. So the ‘paradox of

estuarine quality’ (Dauvin, 2007) should be extended to

the ‘paradox of transitional water’ as Munari and Mistri

(2008) argued. In fact, in these systems featured by low

diversity, low species richness and high abundance

community it is extremely difficult distinguish between

natural or anthropogenic stresses. The indices AMBI, M-

AMBI and BENTIX are widely utilized in assessing the

EcoQS in marine environments, but their right application

in transitional systems would depend on a resettlement.

As a matter of fact, thresholds settled in the biotic index

scale values need to be modified according to the natural

variability of transitional waters referring to abiotic

conditions and the abundance of opportunistic species

(Dauvin, 2007).

Regarding AMBI, its robustness is reduced under low

salinity conditions, i.e. inner areas of estuaries (Borja and

Muxika, 2005). The assignment of species to five groups would

render AMBI more suitable in assessing EcoQS compared with

an index based only upon two groups, which polarizes the

results in case of a high dominance of species.

Some authors criticized M-AMBI remarking that the new

way of defining classes of this index could involve ‘the risk of

losing the ecologically meaning of the former classification of

AMBI (Blanchet et al., 2008). Ruellet and Dauvin (2008) judged

M-AMBI ‘not adapted to objective of WFD’ pointing out that (i)

it ‘can change over time and is sensible to new data addition’

and that (ii) the software proposed ‘cannot treat more than 255

samples’. Borja et al. (2008b) replied that the changes occur

with small sample number (>50) and that these changes lie

within the range recommended by the ECOSTAT Group. In

addition the limitation of samples has been solved with a new

version of AMBI software (AMBI 4.1).

Our results concerning two ‘not heavily impacted’ transi-

tional waterbodies confirm that the AMBI scale works better

than BENTIX for slightly and moderately polluted lagoons as

well as Simboura and Reizopoulou (2008) asserted. Anyway in

Fogliano lake, where the H0 and S values are slightly higher

than in Caprolace lake (except for Ca2), M-AMBI is more

similar to AMBI, and than it seems to be more suitable in

assessing EcoQS than in Caprolace lake (Fig. 6).

Ruellet and Dauvin (2007) argued that the inclusion of

Shannon index (H0) and species number (S) in M-AMBI

computation gives too much weight to diversity and the

indices BENTIX and M-AMBI tend to underestimate the EcoQS

in slightly or moderately disturbed lagoons (Simboura and

Reizopoulou, 2008). In Caprolace coastal lake, the low values of

Margalef (d), Shannon (H0) index and species number (S) are not

necessarily a sign of degradation, being probably related to

natural condition of this transitional system.

In this study the distinction between the two coastal

lakes resulting from COIA and in particular related to the

different composition of organic matter of sediment did not

correspond with a significant biodiversity loss; the taxo-

nomic distinctness indices (D+ and L+) confirmed a good

degree of taxonomic stability in the communities of both

lakes according to the community structural analysis

(Fig. 7). This result is in accordance with the research of

Arvanitidis et al. (2005) of some Mediterranean lagoons

which includes Caprolace and Fogliano lakes. These authors

demonstrated on the base of diversity indices, multivariate

analyses and graphical methods that these lagoons are

‘naturally stressed ecosystem that are not experiencing

severe anthropogenic impacts’ and moreover they con-

firmed this outcome by applying D+ and L+ indices on the

most abundant faunal group (polychaetes, molluscs and

crustaceans). In this case, the information coming from the

species distribution of the dominant phylum resulted more

meaningfully than that one obtained from all taxa com-

bined. However, the use of only one phylum as surrogate for

others is arguable considering that the biodiversity of

different phyla can respond differently to environmental

gradient (Ellingsen et al., 2005).

In Fogliano lake community the L+ index did not show

higher values, not being sensitive enough to discriminate

the trophic levels arised from aquatic phanerogam and

macroalgae distribution. In fact Izzo et al. (2005) classified

Caprolace, characterized from the presence of C. nodosa

known as enrichment-sensitive species (Lloret et al., 2005), as

‘High’ and Fogliano lake, in which R. cirrhosa prevails as

‘Good’. This last macrophyte is considered as ‘transitional

species’ showing lower disturbance sensitiveness than C.

nodosa (Izzo et al., 2005). Therefore, the hypothesis of Moulliot

et al. (2005a,b) has not been confirmed. In fact the main result

obtained by these authors is the recognition of the variation in

taxonomic index (L+) as the best indicator of a lagoons

eutrophication level, observing a consistent trend of L+ along

the eutrophication gradient, namely L+ increased with the

increase in eutrophication level. Environmental disturbances

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3580

like eutrophication or wide salinity fluctuations would lead to

a disequilibrium in the taxonomic tree with a low presence of

species in more impacted lineages whereas in a more stable

environment the structure of the taxonomic tree is very

regular with a relatively homogeneous repartition of the

species (Moulliot et al., 2005b).

One of the advantageous features of the application of

taxonomic distance measures is represented by the possibility

of establishing a range of biodiversity ‘expected’ values for any

designated location: therefore, the values from undisturbed

habitats should fall within ‘the range’ and impacted locations

fall outside it, allowing the definition of a ‘reference condition’,

according to the requirement of WFD to assess the parameters

of a ‘good ecological condition’. This would enable the

establishment of a reference condition even in a region

entirely impacted to some degree, and where no appropriate

reference sites are available (Leonard et al., 2006). Other

favourable characteristics of these indices are the lack of

dependence on sample size and being founded in the

presence/absence of data, useful when comparing historical

data sets or when the sample effort is uncontrolled, unknown

or unequal (Clarke and Warwick, 1998, 2001a,b).

Salas et al. (2006) testing the robustness of taxonomic

distance measurements in different scenarios (estuarine

eutrophication, organic pollution, and re-colonisation after

physical disturbance) did not recognize their power of

discrimination in any case of environmental disturbance.

The average taxonomic distinctness showed the ability to

detect impacts despite possible natural environmental dis-

turbances, for example in salinity fluctuations, in an estuary or

in coastal lagoon. Somerfield et al. (1997) found no consistent

pattern between the decreasing taxonomy diversity of marine

macrofauna assemblages as a consequence of increasing

environmental impact. Nevertheless, there have been

attempts to apply these indices in marine environments

which still require wider testing and if possible should be

associated to other biodiversity measures (Clarke and War-

wick, 2001a).

These indices did not seem to be helpful alone in assessing

the Ecological Quality Status as required by the WFD, not being

able to identify the different levels of EcoQS. Their use in

transitional water might be encouraging since poor quality

stations felt below the confidence limits of the D+ probability

funnel, so establishing if a community is in a natural condition

or if is suffering an anthropogenic impact. Moreover, these

measures can be suitable in the evaluation of transitional

water ecosystem functioning (Munari and Mistri, 2008).

In this paper, the application of the biotic indices AMBI, M-

AMBI and BENTIX, recently utilized and compared in transi-

tional waters (Borja et al., 2008a; Ruellet and Dauvin, 2007;

Pranovi et al., 2007; Simboura and Reizopolou, 2007; Simboura

and Reizopoulou 2008), highlights their disagreement in the

evaluation of EcoQS and in particular, in the boundary

between ‘acceptable’ or ‘not acceptable’ quality status.

Recently, in order to obtain similar classification for water

bodies using different benthic indicators, intercalibrations are

actually carried out (Borja et al., 2007; Labrune et al., 2006;

Reiss and Kronke, 2005; Simboura and Reizopoulou, 2008) and

the possible modifications of thresholds of classes related to

different methods are analysed (Ruellet and Dauvin, 2007;

Blanchet et al., 2008). Their values in the biotic scale values

need to be adapted according to the natural variability of

transitional waters and abundance of opportunistic species

(Dauvin, 2007).

5. Conclusions

Over the years, the implementation of WFD has led to the

application of new methodologies for the assessment of

the EcoQS in transitional and coastal waters of European

countries.

With this goal in mind, some supporting evidence has been

highlighted, e.g. the assessment of physico-chemical status

and definition of references conditions. Besides, many biotic

indices have been tested in Mediterranean and Atlantic eco-

regions, but their application often shows discordances found

in EcoQS assessment. The achievement of Ecological Status of

water systems equal or higher than ‘Good’ by 2015 (WFD)

implies that the boundary Good/Moderate in the EcoQS

assessment is particularly relevant since sites in ‘Moderate’

conditions should be restored by 2015.

In this study AMBI, M-AMBI and BENTIX gave different

results regarding the boundary Good/Moderate indicating a

worse condition when applying M-AMBI and still more

applying BENTIX (Fig. 6). However, the index AMBI provided

a more suitable evaluation of EcoQS corresponding to ‘slightly

polluted’ lagoons in compliance with environmental para-

meters, univariate community indices, taxonomic distance

measurements.

The application of the taxonomic distinctness indices

showed their usefulness in determining the range of expected

natural variability. Nevertheless they are unsuitable for the

EcoQS assessment since five ecological levels as required by

WFD are not assigned.

Another recent approach concerns the development of

more pragmatic indices in respect of the ‘taxonomic suffi-

ciency’ principles (Ferraro and Cole, 1990) which minimizes

the number of identification errors and simplifies their

application, for example the BOPA (the Benthic Opportunistic

Polychaetes Amphipods Index) (Dauvin et al., 2007) or the BITS

index (Benthic Index based on Taxonomic Sufficiency) (Mistri

and Munari, 2008).

A proposal for the future concerns inter-calibration among

indices and the need to have shared standardized methods

based on multicriteria approaches which provide comple-

mentary information in order to reach the goal required by

WFD regarding the Good Ecological Status of water bodies by

2015.

Acknowledgements

The authors wish to thank A. Borja and A. Zenetos for the

updating pertaining to the assignment of ecological groups to

the macrobenthic taxa found in this research. The authors are

grateful to the ‘Circeo National Park’ for the technical support.

Thanks to C. Varrone, A. Signorini, G. Migliore for their

invaluable support regarding sediment analysis and field

assistance.

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3 581

r e f e r e n c e s

Albayrak, S., Balkis, H., Zenetos, A., Kurun, A., Kubanc, C., 2006.Ecological quality status of coastal benthic ecosystems inthe Sea of Marmara. Marine Pollution Bulletin 52, 790–799.

Andersen, J.H., Conley, D.J., Hedal, S., 2004. Paleoecology,reference conditions and classification of ecological status:the EU Water Framework Directive in practice. MarinePollution Bulletin 49, 283–290.

Ardizzone, G.D., Coen, R., Corsi, F., Gravina, F., Pelusi, P.,Scaletta, F., 1982–1984. Progetto laghi costieri. Relazionefinale. Amministrazione Prov.le Latina, Universita ‘LaSapienza’, Roma, 413 pp.

Ardizzone, G.D., Gravina, M.F., Coen, R., 1991. The ecology ofcoastal lagoons in Central Italy. Animal and Human Biology69–106.

Arvanitidis, C., Hatzigeorgiou, G., Koutsoubas, D., Dounas, C.,Eleftheriou, A., Koulouri, P., 2005. Mediterranean lagoonsrevisited: weakness and efficiency of the rapid biodiversityassessment techniques in a severely fluctuatingenvironment. Biodiversity and Conservation 14, 2347–2359.

Bald, J., Borja, A., Muxika, I., Franco, J., Valencia, V., 2005.Assessing reference conditions and physico-chemicalstatus according to the European Water FrameworkDirective: a case-study from the Basque Country (NorthernSpain). Marine Pollution Bulletin 50, 1508–1522.

Bellan, G., 1985. Effects of pollution and man-made modificationson marine benthic communities in the Mediterranean: areview. In: Moraitou-Apostolopoulou, M.,Kiortsis, V. (Eds.), Mediterranean Marine Ecosystems. NATO.

Benzecri, J.P., 1973. L’analyse des donnees. In: L’analyse decorrespondance, Dunod, Paris, 632 pp.

Blanchet, H., Lavesque, N., Ruellet, T., Dauvin, J.C. Sauriau, P.G.,Desroy, N., Desclaux, C., Leconte, M., Bachelet, G., Janson,A.L., Bessineton, C., Duhamel, S., Jourde, J., Mayot, S.,Simon, S., de Montaudouin, X., 2008. Use of Biotic Indices inSemi-Enclosed Coastal Ecosystems and Transitional WatersHabitats—Implications for the Implementation of theEuropean Water Framework Ecological Indicators, vol. 8,Issue 4, 360–372.

Borja, A., Franco, J., Perez, V., 2000. A marine biotic index toestablish the ecological quality of soft bottom benthoswithin European estuarine and coastal environments.Marine Pollution Bulletin 40 (12), 1100–1114.

Borja, A., Muxika, I., Franco, J., 2003. The application of a MarineBiotic Index to different impact sources affecting soft-bottom benthic communities along European coasts.Marine Pollution Bulletin 46, 835–845.

Borja, A., Valencia, V., Franco, J., Muxika, I., Bald, J., Belzunce,M.J., Solaun, O., 2004a. The water framework directive:water alone, or in association with sediment and biota, indetermining quality standards? Marine Pollution Bulletin49, 8–11.

Borja, A., Franco, J., Valencia, V., Bald, J., Muxika, I., Belzunce,M.J., Solaun, O., 2004b. Implementation of the Europeanwater framework directive from the Basque country(northern Spain): a methodological approach. MarinePollution Bulletin 48, 209–218.

Borja, A., Franco, J., Muxika, I., 2004c. The biotic indices and theWater Framework Directive: the required consensus in thenew benthic monitoring tools. Marine Pollution Bulletin 48,405–408.

Borja, A., Heinrich, H., 2005. Implementing the European WaterFramework Directive: the debate continues. MarinePollution Bulletin 50, 486–488.

Borja, A., Muxika, I., 2005. Guidelines for the use of AMBI(AZTI’s Marine Biotic Index) in the assessment of the

benthic ecological quality. Marine Pollution Bulletin 50,787–789.

Borja, A., Josefson, A.B., Miles, A., Muxika, I., Olsgard, F., Phillips,G., Rodriguez, G., Ryggs, J.G., 2007. An approach to theintercalibration of benthic ecological status assessment inthe North Atlantic ecoregion, according to the EuropeanWater Framework Directive. Marine Pollution Bulletin 55,42–52.

Borja, A., Dauer, D.M., 2008. Assessing the environmentalquality status in estuarine and coastal systems: comparingmethodologies and indices. Ecological Indicators 8 (July (4)),331–424.

Borja, A., Dauer, D.M., Dıaz, R., Llanso, R.J., Muxika, I., Rodrıguez,J.G., Schaffner, L., 2008a. Assessing estuarine benthicquality conditions in Chesapeake Bay: a comparison ofthree indices 8 (4) 331–424.

Borja, A., Mader, J., Muxika, I., German Rodrıguez, J., Bald, J.,2008b. Using M-AMBI in assessing benthic quality withinthe Water Framework Directive: Some remarks andrecommendations. Marine Pollution Bulletin 56 (7), 1377–1379.

Brown, B.E., Clarke, K.R., Warwick, R.M., 2002. Serial patterns ofbiodiversity change in corals across shallow reef flats in KoPhuket, Thailand, due to the effects of local (sedimentation)and regional (climatic) perturbations. Marine Biology 141,21–29.

Castelli, A., Lardicci, C., Tagliapietra, D., 2003. Il macrobenthosdi fondo molle. Manuale di metodologia di campionamentoe studio del benthos marino mediterraneo SIBM 10 (Suppl.),109–144.

Cioffi, F., Gallerano, F., 2001. Management strategies for thecontrol of eutrophication processes in Fogliano lagoon(Italy): a long-term analysis using a mathematical model.Applied Mathematical Modelling 25, 385–426.

Cividanes, S., Incera, M., Lopez, J., 2002. Temporal variabilita inthe biochemical composition of sedimentary organic matterin an intertidal flat of the Galician coast (NW Spain).Oceanologica Acta 25, 1–12.

Clarke, K.R., Warwick, R.M., 1998. A taxonomic distinctnessindex and its statistical properties. Journal of AppliedEcology 35, 523–531.

Clarke, K.R., Warwick, R.M., 2001a. Change in the MarineCommunities: An Approach to Statistical Analysis AndInterpretation, 2nd ed. PRIMER-E, Plymouth, 172 pp.

Clarke, K.R., Warwick, R.M., 2001b. A further biodiversity indexapplicable to species list: variation in taxonomicdistinctness. Marine Biology Progress Series 216, 265–278.

Costa, C., Cataudella, S., 2007. Relationship between shape andtrophic ecology of selected species of Sparids of theCaprolace coastal lagoon (Central Tyrrhenian sea).Environmental Biology of Fishes 78, 115–123.

Dale, V.H., Beyeler, S.C., 2001. Challenges in the developmentand use of ecological indicators. Ecological Indicators 1,3–10.

Dauvin, J.C., 2007. Paradox of estuarine quality: benthicindicators and indices, consensus or debate for the future.Marine Pollution Bulletin 55, 271–281.

Dauvin, J.C., Ruellet, T., Derroy, N., Janson, A.L., 2007. Theecological quality status of the Bay of Seine and the Seineestuary: use of biotic indices. Marine Pollution Bulletin 55,241–257.

Dell’Anno, A., Mei, M.L., Pusceddu, A., Danovaro, R., 2002.Assessing the trophic state and eutrophication of coastalmarine systems: a new approach based on the biochemicalcomposition of sediment organic matter. Marine PollutionBulletin 44, 611–622.

Devlin, M., Best, M., Haynes, D., 2007. Implementation of theWater Framework Directive in European marine waters.Marine Pollution Bulletin 55, 1–2.

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3582

Diaz, R.J., Solan, M., Valente, R.M., 2004. A review of approachesfor classifying benthic habitats and evaluating habitatquality. Journal of Environmental Management 73, 165–181.

Doledec, S., Chessel, D., 1994. Co-inertia analysis: an alternativemethod for studying species–environment relationships.Freshwater Biology 31, 277–294.

Doledec, S., Chessel, D., Ter Braak, C.J.F., Champely, S., 1996.Matching species traits to environmental variables: a newthree-table ordination method. Environmental andEcological Statistics 3, 143–166.

Dray, S., Chessel, D., Thioulouse, J., 2003. Co-inertia analysis andthe linking of ecological tables. Ecology 84, 3078–3089.

EC, 2003. Guidance on Typology, References Conditions andClassification Systems for Transitional and Coastal Waters.CIS Working Group 2.4 (Coast) Common ImplementationStrategy of the Water Framework Directive. EuropeanCommission, 116 pp.

Ellingsen, K.E., Clarke, K.R., Somerfield, P.J., Warwick, R.M.,2005. Taxonomic distinctness as a measure of diversityapplied over a large scale: the benthos of the Norwegiancontinental shelf. Journal of Animal Ecology 74, 1069–1079.

Fabiano, M., Danovaro, R., 1994. Composition of organic matterin sediments facing a river estuary (Tyrrhenian Sea):relationships with bacteria and microphytobenthicbiomass. Hydrobiologia 277, 71–84.

Fabiano, M., Chiantore, M., Povero, P., Cattaneo-Vietti, R.,Pusceddu, A., Misic, C., Albertelli, G., 1997. Short-termvariations in particulate matter flux in Terra Nova Bay, RossSea. Antarctic Science 9, 143–149.

Feral, J.P., Fourt, M., Perez, T., Warwick, R.M., Emblow, C., Heip,C., van Avesaath, P., Hummel, H., 2003. European MarineBiodiversity Indicators. Report on the European ConcertedAction: BIOMARE, Implementation and Networking ofLargescale, Long Term Marine Biodiversity Research inEurope, Yerseke, Netherlands: NIOO-CEME.

Ferraro, S.P., Cole, F.A., 1990. Taxonomic level and the samplesize sufficient for assessing pollution impacts on theSouthern California Bight macrobenthos. Marine EcologyProgress Series 67, 251–262.

Gravina, F., 1986. Lo zoobenthos dei laghi pontini: un esempio didiagnosi ecologica dei sistemi salmastri. Atti Conv. Asp.Faun. Probl. Zool. P.N. Circeo (Sabaudia, 1984), 117–131.

Gravina, M.F., Ardizzone, G.D., Scaletta, F., Chimenz, C., 1989.Descriptive Analysis and Classification of BenthicCommunities in Some Mediterranean Coastal Lagoons(Central Italy). Marine Ecology 10 (2), 141–166.

Heiskanen, A.S., van de Bund, W., Cardoso, A.C., Noges, P., 2004.Towards good ecological status of surface waters inEurope—interpretation and harmonization of the concept.Water Science and Technology 49 (7), 169–177.

Hull, V., Mocenni, C., Falcucci, M., Marchettini, N., 2000. Atrophodynamic model for the lagoon of Fogliano (Italy) withecological dependent modifying parameters. EcologicalModelling 134, 153–167.

Izzo, G., Signorini, A., Silvestri, C., Giordano, P., 1998. Studio deilaghi costieri pontini di Fogliano e Caprolace. BiologiaMarina Mediterranea 5 (3), 2112–2124.

Izzo, G., Signorini, A., Massini, G., Allegro, A., Tosoni, M.,Varrone, C., Migliore, G., Sbrana, M., Morgana, G., Prato, S.,Procacci, S., La Valle, P., Nicoletti, L., 2005. L’uso deisedimenti per la valutazione della qualita delle acque ditransizione: correlazione tra test fisici, chimici e biologici.In: Apat (Ed.), Metodologie per il rilevamento e laclassificazione dello stato di qualita ecologico e chimicodelle acque con particolare riferimento all’applicazione delD.Lgs 152/99; 345–377.

Izzo, G., Signorini, A., Massini, G., Migliore, G., Tosoni, M.,Varrone, C., in press. Sediment biogeochemical differencesin two pristine Mediterranean coastal lagoons (in Italy)

characterized by different phanerogam dominance. Acomparative approach. Aquatic Conservation: Marine andFreshwater Ecosystems. ID: AQC-07-0161.

Labrune, C., Amouroux, J.M., Sarda, R., Dutrieux, E., Thorin, S.,Rosenberg, R., Gremare, A., 2006. Characterization of theecological quality of the coastal Gulf of Lions (NWMediterranean): a comparative approach based on threebiotic indices. Marine Pollution Bulletin 52, 34–47.

Lardicci, C., Como, S., Corti, S., Rossi, F., 2001. Recovery of themacrozoobenthic community after severe dystrophic crisesin a Mediterranean coastal lagoon (Orbetello, Italy). MarinePollution Bullettin 42 (3), 201–214.

Legendre, L., Legendre, P., 1984. Ecologie numerique. T2. Lastructure des donnees ecologiques. Masson, Paris, 335 pp.

Leonard, D.P.R., Clarke, K.R., Somerfield, P., Warwick, R.M., 2006.The application of an indicator based on taxonomicdistinctness for UK marine biodiversity assessment. Journalof Environmental Management 78, 52–62.

Lloret, J., Marin, A., Marin-Guirao, L., Velasco, J., 2005. Changesin macrophytes distribution in a hypersaline coastallagoon associated with the development of intensivelyirrigated agriculture. Ocean & Coastal Management 48,828–842.

Magni, P., Hyland J., Manzella G., Rumhor H., Viaroli P., ZenetosA. (Eds.), 2005. Proceedings of the Workshop ‘Indicators ofStress in the Marine Benthos’, Torregrande, Oristano, Italy,October 8–9, 2004. IOC Workshop Reports, 195, 46 pp.

Mangialajo, L., Ruggieri, N., Asnaghi, V., Chiantore, M., Povero,P., Cattaneo-Vietti, R., 2007. Ecological status in the LigurianSea: the effect of coastline urbanisation and the importanceof proper reference sites. Marine Pollution Bulletin 55,30–41.

Mariani, S., 2001. Can spatial distribution of ichthyofaunadescribe marine influence on coastal lagoons? A CentralMediterranean case study. Estuarine, Coastal and ShelfScience 52, 261–267.

Mariani, S., 2006. Life-history- and ecosystem-driven variationin composition and residence pattern of seabream species(Perciformes: Sparidae) in two Mediterranean coastallagoons. Marine Pollution Bulletin 53, 121–127.

Mariani, S., Maccaroni, A., Massa, F., Rampacci, M., Tancioni, L.,2002. Lack of consistency between the trophicinterrelationships of five sparid species in two adjacentcentral Mediterranean coastal lagoons. Journal of FishBiology 61 (Suppl. A), 138–147.

Marın-Guirao, L., Cesar, A., Marın, A., Lloret, J., en Vita, R., 2005.Establishing the ecological quality status of soft-bottommining-impacted coastal water bodies in the scope of theWater Framework Directive. Marine Pollution Bulletin 50,374–387.

Mistri, M., Munari, C., 2008. BITS: A SMART indicator for soft-bottom, non-tidal lagoons. Marine Pollution Bulletin 56 (3),587–599.

Moulliot, D., Laune, J., Tomasini, J.A., Aliaume, C., Brehmer, P.,Dutrieux, E., Do Chi, T., 2005a. Assessment of coastal lagoonquality with taxonomic diversity indices of fish, zoobenthosand macrophyte communities. Hydrobiologia 550, 121–130.

Moulliot, D., Gaillard, S., Aliaume, C., Verlaque, M., Belsher, T.,Troussellier, M., Do Chi, T., 2005b. Ability of taxonomydiversity indices to discriminate coastal lagoonenvironments based on macrophyte communities.Ecological Indicators 5, 1–7.

Munari, C., Mistri, M., 2008. The performance of benthicindicators of ecological change in Adriatic coastal lagoons:throwing the baby with the water? Marine PollutionBulletin 56, 95–105.

Muxika, I., Borja, A., Bonne, W., 2005. The suitability of themarine biotic index (AMBI) to new impact sources alongEuropean coasts. Ecological Indicators 5, 19–31.

e c o l o g i c a l i n d i c a t o r s 9 ( 2 0 0 9 ) 5 6 8 – 5 8 3 583

Muxika, I., Borja, A., Bald, J., 2007a. Using historical data, expertjudgement and multivariate analysis in assessing referenceconditions and benthic ecological status, according to theEuropean Water Framework Directive. Marine PollutionBulletin 55 16-29. 0.

Nicolaidou, A., Kostaki-Apostolopoulou, M., 1988. Growth ofAbra ovata in a brackish-water lagoon. Vie Marine 9,7–10.

Nicoletti, L., La Valle, P., Lattanzi, L., Ardizzone, G.D., 1983-2000.Il popolamento zoobentonico dei laghi pontini: 1983–2000.Biology of Marine and Mediterranean 13 (1), 124–131.

Nielsen, K., Somod, B., Ellegaard, C., Krause-Jensen, D., 2003.Assessing reference conditions according to the EuropeanWater Framework Directive using modelling and analysis ofhistorical data: an example from Randers Fjord, Denmark.Ambio 32, 287–294.

Pearson, T.H., Rosenberg, R., 1978. Macrobenthic succession inrelation to organic enrichment and pollution of the marineenvironment. Oceanography and Marine Biology: an AnnualReview 16, 229–311.

Ponti, M., Casselli, C., Abbiati, M., 2002. Applicazione degli indicibiotici all’analisi delle comunita bentoniche degli ambientilagunari costieri: la ‘Pialassa Baiona’. In: Atti XII CongressoSITE, Urbino, p. 51.

Pranovi, F., Da Ponte, F., Torricelli, 2007. Application of bioticindices and relationship with structural and functionalfeatures of macrobenthic community in the lagoon ofVenice: an example over a long time series of data. MarinePollution Bulletin 54, 1607–1618.

Prior, A., Miles, A.C., Sparrow, A.J., Price, N., 2004. Developmentof a classification scheme for the marine biotic component,Water Framework Directive: Phase I&II-Transitional andcoastal waters. R&D Technical Report E1-116 & E1-132Environmental Agency, Bristol, 83 pp.

Quintino, V., Elliott, M., Rodrigues, A.M., 2006. The derivation,performance and role of univariate and multivariateindicators of benthic change: case studies at differentspatial scales. Journal of Experimental Marine Biology andEcology 330, 368–382.

Reiss, H., Kronke, I., 2005. Seasonal variability of benthicindices: an approach to test the applicability of differentindices for ecosystem quality assessment. Marine PollutionBulletin 50, 1490–1499.

Rogers, S.I., Clarke, K.R., Reynolds, J.D., 1999. The taxonomicdistinctness of coastal bottom-dwelling fish communitiesof the North-east Atlantic. Journal of Animal Ecology 68,769–792.

Rosenberg, R., Blomqvist, M., Nilsson, H.S., Cederwall, H.,Dimming, A., 2004. Marine quality assessment by use ofbenthic-abundance distributions: a proposed new protocolwithin the European Union Water Framework Directive.Marine Pollution Bulletin 49, 728–739.

Rossi, F., Rizzi, L., Lardicci, C., 1997. Struttura delle comunitabentoniche di fondo molle della laguna di Orbetello dopoestese crisi distrofiche. Biologia Marina Mediterranea 4 (1),445–448.

Ruellet, T., Dauvin, J.C., 2007. Benthic indicators: analysis of thethreshold values of ecological quality classifications fortransitional waters. Marine Pollution Bulletin 54, 1707–1714.

Ruellet, T., Dauvin, J.C., 2008. Comments on Muxika et al.(2007).‘‘Using historical data, expert judgement andmultivariate analysis in assessing reference conditions andbenthic ecological status, according to the European Water

Framework Directive’’ Marine Pollution Bulletin 56 (6), 1234–1235.

Salas, F., Neto, J.M., Borja, A., Marques, J.C., 2004. Evaluation ofthe applicability of a marine biotic index to characterize thestatus of estuarine ecosystems: the case of Mondegoestuary (Portugal). Ecological Indicators 4, 215–225.

Salas, F., Patricio, J., Marcos, C., Pardal, M.A., Perez-Rufaza, A.,Marquez, J.C., 2006. Are taxonomic distinctness measurescompliant to other ecological indicators in assessingecological status? Marine Pollution Bulletin 52, 817–829.

Simboura, N., Zenetos, A., 2002. Benthic indicators to use inEcological Quality classification of Mediterranean softbottom marine ecosystems, including a new Biotic Index.Mediterranean and Marine Science 3/2, 77–111.

Simboura, N., Panayotidis, P., Papathanassiou, E., 2005. Asynthesis of the biological quality elements for theimplementation of the European Water FrameworkDirective in the Mediterranean ecoregion: the case ofSaronikos Gulf. Ecological Indicators 5, 253–266.

Simboura, N., Reizopolou, S., 2007. A comparative approach ofassessing ecological status in two coastal areas of EasternMediterranean. Ecological Indicators 7, 455–468.

Simboura, N., Reizopoulou, S., 2008. An intercalibration ofclassification metrics of benthic macroinvertebrates incoastal and transitional ecosystems of the EasternMediterranean ecoregion (Greece). Marine Pollution Bulletin56, 116–126.

Somerfield, P.J., Olsgard, F., Carr, M.R., 1997. A furtherexamination of two new taxonomic distinctness measures.Marine Ecology Progress Series 154, 303–306.

Taghon, G.L., Greene, R.R., 1990. Effects of sediment-proteinconcentration on feeding and growth rates of Abarenicolapacifica Healy et Wells (Polychaeta: Arenicolidae). Journal ofExperimental and Marine Biology and Ecology 136, 197–216.

Tancioni, L., Mariani, S., Maccaroni, A., Mariani, A., Massa, F.,Scardi, M., Cataudella, S., 2003. Locality-specific variation inthe feeding of Sparus aurata L.: evidence from twoMediterranean lagoon systems. Estuarine, Coastal and ShelfScience 57, 469–474.

Terlizzi, A., Scuderi, D., Fraschetti, S., Guidetti, P., Boero, F.,2005. Molluscs on subtidal cliffs: patterns of spatialdistribution. Journal of Marine Biological Association of UK83, 165–172.

Warwick, R.M., Clarke, K.R., 1995. New ‘biodiversity’ measuresreveal a decrease in taxonomic distinctenness withincreasing stress. Marine Ecology Progress Series 129,301–305.

Warwick, R.M., Clarke, K.R., 1998. Taxonomic distinctness andenvironmental assessment. Journal of Applied Ecology 35,532–543.

Warwick, R.M., Light, J., 2002. Death assemblages of molluscs onSt. Martin’s Flats, Isles of Scilly: a surrogate for regionalbiodiversity? Biodiversity and Conservation 11, 99–112.

Warwick, R.M., Ashman, C.M., Brown, A.R., Clarke, K.R., Dowell,B., Hart, B., lewis, R.E., Shillabeer, N., Somerfield, P.J., Tapp,J.F., 2002. Inter-annual changes in the biodiversity andcommunity structure of the macobenthos in Tees Bay andTees estuary, UK, associated with local and regionalenvironmental events. Marine Ecology Progress Series 234,1–13.

Zettler, M.L., Schiedek, D., Bobertz, B., 2007. Benthic biodiversityindices versus salinity gradient in the southern Baltic Sea.Marine Pollution Bulletin 55, 258–270.