On the quantitative distribution and community structure of the meio and macrofaunal communities in...

Environ Monit Assess (2011) 180:325–344DOI 10.1007/s10661-010-1791-y

On the quantitative distribution and community structureof the meio and macrofaunal communities in the coastalarea of the Central Adriatic Sea (Italy)

Fabrizio Frontalini · Federica Semprucci ·Rodolfo Coccioni · Maria Balsamo ·Paolo Bittoni · Anabella Covazzi-Harriague

Received: 13 April 2010 / Accepted: 9 November 2010 / Published online: 1 December 2010© Springer Science+Business Media B.V. 2010

Abstract Many coastal areas have served as repo-sitories of different anthropogenic and naturallyinduced organic material and nutrients. The majorsources thereof are riverine inputs which stronglyinfluence the spatial and temporal distributionof benthic communities. In this study, the ben-thic foraminiferal, meiofaunal, and macrofaunalcolonies in front of three rivers in a poorly known,but environmentally valuable, area of the CentralAdriatic Sea have been examined concurrently.The physico-chemical parameters of bottom waterand sediment characteristics were determined in

Electronic supplementary material The online versionof this article (doi: 10.1007/s10661-010-1791-y)contains supplementary material, which is availableto authorized users.

F. Frontalini (B) · F. Semprucci · R. Coccioni ·M. BalsamoDipartimento di Scienze dell’Uomo, dell’Ambientee della Natura (DiSUAN), Università di Urbino‘Carlo Bo’, Campus Scientifico, loc. Crocicchia,61029 Urbino, Italye-mail: [email protected]

P. BittoniDipartimento Militare Marittimo di La Spezia,V.le Amendola, 1 La Spezia, La Spezia, Italy

A. Covazzi-HarriagueDipartimento per lo Studio del Territorio e delle sueRisorse (Dip.Te.Ris.), Università di Genova,C.so Europa, 26, 16132 Genova, Italy

order to characterize both the sediment–waterinterface and the benthic environments. Althoughchanges in the biota are neither univocal nor uni-directional, a moderate influence of riverine inputon the different communities’ components can beinferred. The most affected taxa are foraminiferaand copepods and, to a lesser extent, meiofau-nal polychaetes and platyhelminthes. These re-sults are also tested by the ABC curves, whichreveal that the macrofaunal communities closestto the river mouths are moderately disturbed. Thisintegrated investigation documents, for the firsttime, how benthic communities can be used as anearly warning indicator with which to monitor thehealth quality of a coastal ecosystem.

Keywords Foraminifera · Meiofauna ·Macrofauna · Riverine input · Adriatic Sea

Introduction

Coastal areas represent one of the most importantsources of nutrients for neighboring open seas.This is partly due to their enhanced productivityand the strong influence of riverine inputs. Nu-trient riverine discharge may stimulate primaryproduction, and increased amounts of organic ma-terial can consequently be deposited in the sed-iment (Deegan et al. 1986; Nixon et al. 1986).Biota living within and at the sediments’ interface

http://dx.doi.org/10.1007/s10661-010-1791-y

326 Environ Monit Assess (2011) 180:325–344

is, to some extent, controlled and structured bythese inputs or, at least, those which reach thesea floor (Moodley et al. 1998; Alberelli et al.1999; Danovaro et al. 2000). The abundance andbiomass of benthic infauna can increase whennutrient loading from river inputs is transformedinto food (Montagna and Yoon 1991; Montagnaet al. 2002; Semprucci et al. 2010).

The coastal nutrient budget may, however, beenriched by treated and untreated domestic andindustrial waste, or can otherwise be influenced byother human-related activities (i.e., recreation),resulting in trophic modification (Debenay et al.2006; Armynot du Châtelet and Debenay 2010).The enhanced organic content, which leads to hy-poxic/anoxic conditions, can drastically affect thebenthic populations, with a reduction of the mostsensitive components being the result (Kemp andBoynton 1992; Heip 1995; Ritter and Montagna1999). All marine benthic groups are affected bythe consequences of eutrophication if anoxia oc-curs, as documented by Stachowitz (1991) in thenorthern Adriatic Sea, where the macrofauna waseliminated after an event of summer anoxia.

The benthic community, therefore, represents asource of information at different food-web levels,and can be utilized to investigate and character-ize the habitat where the community exists. Asmeiofauna and macrofauna have different eco-logical roles in marine ecosystems (Coull andBell 1979; Coull and Palmer 1984), they may re-spond to inflow at different spatial and tempo-ral scales (Bell 1980). Indeed, with its planktoniclarval dispersal, macrofauna could be indicativeof effects over larger spatial and longer tempo-ral scales. On the other hand, with direct ben-thic development, and generation times as shortas 1 month, meiofauna (i.e., metazoan compo-nent) may indicate effects over smaller spatial andshorter temporal scales, although many speciesof benthic foraminifera might produce ‘propag-ules’, which can be widely dispersed over a rangeof habitats and conditions (Alve and Goldstein2002, 2010). Despite the numerous advantagesthat come with using meiofauna for assessing ma-rine environmental conditions (see Kennedy andJacoby 1999), it remains ‘the neglected benthiccomponent’ which might, nevertheless, be integra-ted into standardized methods of studying macro-

fauna (i.e., the marine biotic coefficient sensu(Borja et al. 2000), and the abundance biomasscomparison (ABC) method of Clarke (1990)).

Although integrated investigations may, po-tentially, increase our knowledge of the benthicresponse to environmental changes, only a fewstudies have simultaneously compared the benthiccomponents, including foraminifera, meiofauna,and macrofauna. Moreover, and, to our knowl-edge, similar studies have mainly been conductedin deep sea settings (Gooday et al. 2000; Galèronet al. 2001; Flach et al. 2002). Accordingly, syn-optic studies, which involve the consideration ofmore benthic components at the same time, arerather scarce along the Mediterranean coasts, andmost of them are focused on bacteria and the me-iofauna and macrofauna communities (Moodleyet al. 1998; Alberelli et al. 1999; Covazzi Harriagueet al. 2006; Papageorgiou et al. 2007; Semprucci etal. 2010). This is largely due to the methodologicaldifferences that exist in both the collection andenumeration of the different benthic communitiesand the taxonomical classification of small-sizedgroups.

In view of the general scarcity of integrated in-formation on benthic communities in the AdriaticSea, and given the vulnerability of the coastalsystem, a survey of the whole benthic size spec-trum was carried out along the Marches’ coast-line (Italy). Accordingly, this investigation isthe first attempt to document the compositionand structure of the entire benthic community(foraminifera, meiofauna, and macrofauna) in apoorly known coastal area of the Adriatic Sea(for a review, see Balsamo et al. 2010). The aimsof this study are to clarify the benthic commu-nity spatial distribution pattern and the effectsof seasonal variations, and to assess the potentialdisturbances caused by the three rivers upon thisbenthic community along the western coast of theCentral Adriatic Sea.

Materials and methods

Study area

The Adriatic Sea is an elongated NW/SE orien-tated basin located in the Central Mediterranean

Environ Monit Assess (2011) 180:325–344 327

Sea (Fig. 1). This basin is relatively shallow, es-pecially in the northern sector which has a gentleslope and an average water depth of about 35 m.The general circulation is cyclonic, with a flowtowards the northwest along the eastern side and areturn flow towards the southeast along the west-ern side (Franco et al. 1982). The mean circulationvaries seasonally in response to changing windsand thermal fluxes during the year.

The essentially low nutrient budget of the Adri-atic Sea is considerably enriched by the input ofnutrients, organic matter, and clay from the PoRiver and many other smaller Apennine rivers.Accordingly, the Po represents the main sourceof discharges and, along with the other north-ern Italian rivers, is believed to be responsiblefor about 20% of the total Mediterranean riverrunoff (Hopkins et al. 1992). Once the runoffproducts are introduced into marine ecosystems,their further distribution is mainly determined bythe surface circulation pattern (Artegiani et al.1997). The central and southern regions of theAdriatic Sea are characterized by a lower primaryproductivity, in comparison to the northern region(Zavatarelli et al. 2000). The investigated areais located in the northern part of the Marcheregion (Italy) and extends from Gabicce to Fano

(Fig. 1). It is characterized by the outflow ofthree rivers, the Tavollo, Foglia, and Metauro.These have been periodically monitored and theirquality evaluated by the Regional EnvironmentalAgency for the Marche (ARPAM) on the basisof physico-chemical, microbiological, biological,and chemical (selected dangerous substances) pa-rameters. The Tavollo River flows very close tothe small Cattolica harbor. At 15 km from its rivermouth the water quality has been described aspoor and unsuitable for fish. It is characterized bythe absence of a structured macrobenthic commu-nity, probably due to organic pollution. The 79-kmlong Foglia River is distinguished by a pluvial andtorrential regime, and is deeply affected by theanthropogenic pressure of both the city and har-bor of Pesaro, where the river mouth is located.Its water has been reported to be of low quality,particularly at the mouth, where an unstructuredmacrobenthic community and only a few highlytolerant taxa have been found. Moreover, its rivermouth has also been described as being unsuitablefor fish, in this case probably due to the high levelof ammonia. The 110-km long Metauro Riverflows to the south (∼3 km) of the Fano village.Its hydrographical basin is one of the widest in theMarche region. At its mouth, the water quality has

Fig. 1 Location map ofthe study area withsampling stations


been described as adequate and suitable for fish.Accordingly, the Metauro can be regarded as theleast polluted of the three rivers.

Sediment samples were collected during May(M) and July (J) 2002. Three transepts were laidoff the mouths of each river, and two stations at500 m (station 1, depth of ∼5 m) and 3,000 m(station 4, depth of ∼13 m) were sampled alongeach transect (Fig. 1).

Each sample was labeled according to its dis-tance from the coast (1 and 4), to which river it hadcome from (T, FO, and M), and to the month ofsampling (M and J). Sediment samples were col-lected using a Van Veen Grab (volume 15 l) andthen sub-sampled for the purpose of the analysisof total organic matter content (TOM), grain size,foraminifera, meiofauna, and macrofauna. For thestudy of foraminifera, a constant volume of 50 cm3

of sediment was taken from the upper centime-ters and immediately stained with buffered RoseBengal dye (2 g of Rose Bengal in 1,000 ml of ethylalcohol). For the meiofauna, three replicate cores(surface area 6 cm2) were taken down to a depthof 9 cm. In order to relax the fauna, 7% of MgCl2was added to the sample. Sediment was then fixedwith 4% neutralized formalin in seawater and wasfinally stained with Rose Bengal. The macrofaunasamples were sub-sampled using a manual corer(surface area 102 cm2), carefully washed througha 0.5 mm mesh sieve. Finally, 10% of neutralizedformalin in seawater was added to them.

Environmental parameters

Physico-chemical parameters of the water column,such as temperature, salinity, dissolved oxygenconcentration (DO%), and chlorophyll-a (Chl-a),were measured using a multi-parametric probe(IDRONAUT). The water samples were collectedin Niskin bottles at a depth of ∼0.5 m from the sur-

face. They were first filtered (except for the totalP and N analyses) with 0.45 μm pore size filters.Using the standard techniques indicated by theItalian Ministry of Environment and Land Pro-tection (Cicero and Di Girolamo 2001), and dataprovided by the Regional Environmental Agencyfor the Marches (ARPAM), nitrites, nitrates, am-monia, N-tot, and P-tot were measured in order todetermine the trophic state of the column water.The eutrophication intensity of the water can beevaluated either by using Chl-a, nutrients, and DOindividually, or by the TRIX index (Vollenweideret al. 1998). This index represents a linear combina-tion of four variables related to primary produc-tion (Chl-a and oxygen) and nutritional condition(dissolved inorganic nitrogen, inorganic phospho-rus), and can provide useful insight into the eu-trophication level. The TRIX index has beenincluded in Italian legislation (D.L.vo 152/1999)for the assessment of coastal water quality and, onthe basis of its values, four trophic states and theirrelative classes of water quality can be assessed(Table 1).

The TOM content was determined gravimetri-cally after loss on ignition (Buchanan and Kain1971). The sediment samples were first dried at60◦C for 6 h and weighed in a Scaltec SBC21 (ac-curacy 0.1 mg) in order to obtain the dry weight.They were then calcined in a muffle furnace(550◦C for 4 h) and weighed again to determinethe ash weight (inorganic fraction). The organicfraction content was calculated by deducting theash weight from the total weight. The samplesfor the grain size analysis were collected duringeach sampling and analyzed by the Earth ScienceInstitute of Urbino University and reported byColantoni et al. (2003). Samples for grain sizeanalysis were treated with H2O2 solution, thensieved and dried at 40◦C. Grain size analysis wascarried out to determine the percentage of silt and

Table 1 TRIX index andthe evaluation of theeutrophic state of water

TRIX value Trophic status Environmental significance Water qualityconditions

2–4 Low Low production High4–5 Medium Moderate production Good5–6 High Between moderate Bad

and high production6–8 Very high High production Poor


clay (<63 μm) by Sedigraph (Micrometrics 5100),sand fraction (63 μm to 2 mm) by means of amicro-sieve.

Benthic community analysis

Foraminifera

Samples for foraminiferal analysis were treatedwith standard techniques, largely following thework of Frontalini and Coccioni (2008). Sev-eral biocenotic parameters were calculated, in-cluding the foraminiferal density (herein reportedas foraminifera, defined as the total number ofliving specimens per gram of dried sediment)and the species richness (herein reported as S(Foraminifera)), which is the number of speciesper sample.

Meiofauna

The sediment samples were sieved through 45–500 μm mesh nets. In order to extract thespecimens, this fraction was centrifuged threetimes with Ludox HS 30 colloidal silica (den-sity 1.18 gcm−3), as described by McIntyre andWarwick (1984). The meiofauna were countedand identified at the major taxa level of tax-onomic discrimination using a stereomicroscope(Leica G26), and their density was recalculatedas abundance per 10 cm2. The Shannon indexH′ (ME) and the Pielou J (ME) indices, bothlog2-transformed, as well as the total meiofaunaldensity (TMED), were calculated to describe themeiofaunal assemblage structure.

Macrofauna

The macrofaunal sorting was carried out under abinocular microscope, and the specimens were iden-tified mainly to species level. The macrofaunaldensity was calculated as abundance (ind. m−2).Prior to this, the organisms were weighed to ob-tain the biomass value, and mollusks and echino-derms were treated with 30% HCl. The biomasswas expressed as organic carbon after the conver-sion (gC m−2) of the DW (dry weight, 60◦C for24 h), using the factor of 0.4 (Feller and Warwick1988). The Shannon H′ (MA) and Pielou J (MA)

indices, both log2-transformed, total macrofaunaldensity (TMAD) and total macrofaunal biomass(TMAB), were calculated to describe the macro-faunal (species level) assemblage structure.

Statistical analysis

A data matrix was created using the physico-chemical parameters of water (salinity, DO, Chl-a, ammonia, nitrates, nitrites, P-tot, N-tot, andTRIX), sediment characteristics (TOM, percent-ages of sand and mud), foraminiferal density(Foraminifera) and richness S (Foraminifera), themain meiofaunal index (TMED, S, J, and H’) andtaxa abundance (Nematoda, Polychaeta, Cope-poda, Oligochaeta, and Platyhelminthes), andmacrofaunal indices (TMAD, TMAB, S, J, andH’) and taxa abundance (Mollusca, Polychaeta,Crustacea, and Echinodermata). Since the prob-ability distribution of both the biotic and abioticraw data fails the Kolmogorov–Smirnov test fornormality, an additive logarithmic transformationlog(1+X) was performed prior to statistical analy-sis to remove the effects of orders of magnitudedifferences between variables, to normalize thedata, and to increase the importance of smallervalues such as the mid-range fauna (Manly 1991;Brakstad 1992).

The significant differences between the ben-thic communities (fourth-root transformed) withrespect to depth across the seasons (two-waycrossed ANOSIM, depth × season) have beenevaluated using PRIMER v.5.

In order to elucidate the relationships betweenbiotic and abiotic variables, a Spearman’s rho cor-relation analysis (p < 0.05) was used. Bivariate(correlation matrix) analysis and the multivariatestatistical techniques of cluster analysis (CA) andprincipal component analysis (PCA) were per-formed using Statistica 6.0.

The PCA was used to determine a community’srelationship to abiotic parameters at the sampledstations. This form of analysis attempts to identifythe underlying factors which explain the patternof correlation within a set of observed variables(all of the abiotic variables except TRIX). It isused to reduce data in such a way as to identifya small number of factors which explain most ofthe variance observed in a much greater number


of manifested variables. In PCA, it is possibleto compute additional variables (all of the fau-nal parameters) which do not contribute to theresults of the analysis. Additionally, abiotic pa-rameters were treated in a Q-mode hierarchicalcluster analysis, performed to examine similaritiesbetween the studied stations. The analysis is basedon Ward’s linkage method, which produces den-drograms with well-defined clusters (Parker andArnold 2000).

The abundance biomass comparison curvesproposed by Warwick (1986) for detecting pol-lution effects on marine zoobenthic communitieswere conducted using the PRIMER 5.0 softwarepackage. The numerical distribution of individualsamong species and the distribution of biomassamong species exhibit a differential response todisturbance. This difference is highlighted by adominance of r-selected species (opportunistic)in disturbed areas, in contrast to the competitivedominance of k-selected (specialized) species incommunities which are in equilibrium with a rela-tively stable environment. Accordingly, when thebiomass curve lies above the abundance curve,the macrofauna community is dominated by k-strategist species and is stable (the abundance hasgreater diversity than the biomass). In contrast,when the cumulative biomass curve intersects oroverlaps the cumulative abundance curve, themacrofauna community is disturbed and the levelof stability is lowered.

Results

Environmental variables

The physico-chemical characteristics of the studyarea during the sample period are summarizedin Appendix A (Electronic Supplementary Ma-terial). The temperature ranged between 19.6◦C(1MM and 4MM) and 25.5◦C (1TJ), while salin-ity varied from 32.2 (1TM) to 34.7 (1MM).The DO varied between 90% (1FOJ) and 107%(1MM). The pH was alkaline, ranging from 8.23(1FOJ) to 8.48 (4TM). Chlorophyll-a ranged from0.4 μg/l (4FOM) to 1.2 μg/l (1FOJ); ammoniafrom 8 μg/l (4MJ) to 53 μg/l (4FOM); nitrates

from 18 μg/l (4FOJ) to 59 μg/l (1TJ), and nitritesfrom 1 μg/l (4TJ and 4 FOJ) to 5 μg/l (1TJ).Total phosphorus ranged from 5 μg/l (4FOM) to15 μg/l (1TJ), while total nitrogen varied from102 μg/l (4FOJ) to 206 μg/l (1TM). The trophicstatus of the coastal area was determined byapplying the trophic index, TRIX (Table 1). Itsvalues varied from 3.3 (1FOM) to 4.4 (1FOJ).

The study area as a whole, and at differentsampling times, displayed higher TOM contentsseawards. The highest value (76.7 mg g−1) wasfound at the 4TM station, whereas the low-est (17.9 mg g−1) was at 1MM (Appendix A,Electronic Supplementary Material). Moreover,the mean TOM content was slightly higher in Maythan in July.

The sediments were, predominantly, fine sands.The coarser fraction (>2 mm), when present,was made up of gravels up to a maximum of6% (4FOJ). A main bipartition was present be-tween the sandy and clayey bottoms. Sand rangedfrom 4.1% (4TM) to 96.6% (1TJ), representingthe dominant fraction inshore. The mud frac-tion (<63 μm) varied from 3.3% (1TJ) to 95.7%(4TM), and sensibly increased seawards (Appen-dix A, Electronic Supplementary Material).

The benthic community structure

Benthic foraminifera

Most of the studied samples contained abundantand well-preserved living benthic foraminifera,which were generally associated with commonfragments of mollusks, ostracods, bryozoans, andannelids. A total of 19 benthic foraminiferalspecies (17 calcareous and two agglutinated), be-longing to 14 genera, have been identified in theliving assemblage. These living assemblages werelargely dominated by infaunal genera, such asAmmonia, Aubignyna, Bolivina, Eggerelloides,and Hopkinsina, as well as by a relatively lowoccurrence of epifaunal taxa belonging to theQuinqueloculina genus. The most abundant taxawere Ammonia parkinsoniana (28% in May and48% in July), Ammonia tepida (21% in Mayand 17% in July), Eggerelloides scaber (8% inMay and 15% in July), bolivinids-buliminids (12%


in May and 8% in July), and Quinqueloculinaseminulum (14% in May and 2% in July).

Ammonia parkinsoniana, Ammonia perlucida,Bolivina spp., Hopkinsina pacif ica, and Nonionel-la turgida were increasingly abundant seawards,whereas opposite trends have been highlightedfor A. tepida, E. scaber, Haynesina depressula,and Q. seminulum (Appendix B, Electronic Sup-plementary Material). The foraminiferal densityranged from 0.1 (1MM) to 25 (4TM) in May andfrom 0.1 (1TJ and 1MJ) to 60 (4TJ) in July. TheS (Foraminifera) varied from 6 (1TM and 1MM)to 16 (4MM) in May, and from 5 (1TJ) to 14(4FOJ and 4MJ) in July. Foraminiferal densityand diversity increased seawards (Appendix A,Electronic Supplementary Material).

Meiofauna

A total of 14 meiofaunal taxa was detected. TheTMED ranged from 96.4 ± 25 to 1,479.8 ± 522ind. 10 cm−2 (1TM and 1MJ, respectively) withhigher values in July (Appendix C, ElectronicSupplementary Material). The dominant taxonwas nematodes, with a mean density ranging from59.6 (1TM) to 1,272.5 (1MJ) ind. 10 cm−2, whichrepresented from 62% up to 92% of the totalmeiofauna (at 1TM and 1FOM, respectively). Thenext most abundant taxa were polychaetes (onaverage, 9%; range, 3–27%), copepods (on aver-age, 3%; range, 0.1–18%), oligochaetes (on av-erage, 2%; range, 0.3–9%), and platyhelminthes(on average, 2%; range, 0.3–8%). Overall, thecontribution of the other remaining taxa was lessthan 1% and has not been considered in the sta-tistical analysis. The three rivers had a generallysimilar meiofaunal composition, even if the Fogliaexhibited a greater dominance of nematodes thanthe Tavollo and the Metauro, while the great-est abundance of polychaetes was recorded inthe latter (Appendix C, Electronic Supplemen-tary Material). Higher abundances of polychaeteswere found inshore, while copepods, nematodes,and platyhelminthes were generally more plenti-ful offshore. H′ (ME) and J (ME) indices revealedhigher values at station 1TM (1.74 and 0.58, re-spectively), while lower values were recorded at

station 4TJ (0.61 and 0.22, respectively; AppendixA, Electronic Supplementary Material).

Macrofauna

A total of 48 macrofaunal taxa was recorded (Ap-pendix D, Electronic Supplementary Material).The TMAD ranged from 2,547 to 29,383 ind. m−2

(4TM and 1MJ, respectively), with a mean of12,716 ± 8,084 ind. m−2. The Foglia and theMetauro had higher values of TMAD than theTavollo. Polychaetes represented, on average, 61 ±20% of the TMAD, and Owenia fusiformis (theonly identified species) represented 37% of the to-tal polychaeta abundance. Mollusks were the sec-ond most abundant group (on average 22 ± 12%)and were represented by 23 species, of which Len-tidium mediterraneum, Chamelea gallina, Anadaradiluvii, and Corbula gibba were the dominant taxa(Appendix D, Electronic Supplementary Mater-ial). In particular, L. mediterraneum, C. gallina,Spisula sudtruncata, and Venerupis pullastra weremore abundant inshore (stations 1), while A. dilu-vii, C. gibba, Nucula sulcata, and Mysella bidentatadominate offshore (station 4). The crustaceans,consisting of 15 taxa, represented, on average,16 ± 11% of the TMAD. The general structureof the community was quite similar among therivers; the three principal groups represented 99%of the assemblages at the Tavollo and the Fogliaand 94% at the Metauro, where echinoderms,sipunculans, and nemerteans represented 6% ofthe taxa. S (MA) varied from seven (4MM) to 17species (1TM), while the H′ (MA) and J (MA)indices ranged from 1.5 (1MJ) to 3.0 (4FOM)and from 0.43 (1MJ) to 0.78 (4MM), respectively(Appendix A, Electronic Supplementary Mater-ial). Assemblages from the inshore stations werecharacterized by higher densities and richness, butlower Shannon diversity, than the stations thatwere offshore. On the contrary, the TMAB valuesincreased seawards (on average, 21.8 ± 9.1 and157.0 ± 194.8 gC m−2 for stations 1 and 4, respec-tively). The major contributor to the TMAB wasthe mollusks (54%), with the bivalve A. diluviiaccounting for 88% of its biomass, followed bypolychaetes (32%) and echinoderms (11%) (Ap-pendix E, Electronic Supplementary Material).


Tab

le2

Cor

rela

tion

mat

rix

Salin

ity

DO

Chl

-aA

mm

onia

Nit

rate

sN

itri

tes

P-t

otN

-tot

TR

IXT

OM

Sand

Salin

ity

1.00

DO

0.64

1.00

Chl

-a−0

.62

−0.3

91.

00A

mm

onia

0.55

0.66

−0.1

51.

00N

itra

tes

−0.3

3−0

.13

0.44

0.15

1.00

Nit

rite

s0.

060.

260.

410.

550.

761.

00P

-tot

−0.2

20.

020.

42−0

.05

0.51

0.30

1.00

N-t

ot0.

150.

37−0

.15

0.55

0.35

0.48

−0.3

21.

00T

RIX

−0.2

7−0

.34

0.55

−0.3

30.

540.

250.

62−0

.37

1.00

TO

M−0

.06

0.17

−0.2

4−0

.34

−0.5

5−0

.45

−0.2

7−0

.09

−0.3

71.

00Sa

nd0.

03−0

.26

0.17

0.36

0.37

0.41

−0.0

80.

150.

13−0

.89

1.00

Mud

0.06

0.23

−0.4

0−0

.38

−0.6

3−0

.59

−0.2

3−0

.20

−0.3

00.

95−0

.87

For

amin

ifer

a−0

.11

0.10

−0.3

1−0

.45

−0.5

7−0

.65

−0.1

3−0

.29

−0.3

10.

93−0

.90

S(F

oram

inif

era)

0.15

0.32

−0.4

2−0

.25

−0.6

6−0

.47

−0.2

2−0

.23

−0.4

20.

91−0

.77

TM

ED

−0.2

3−0

.01

0.36

−0.3

9−0

.10

−0.0

40.

35−0

.54

0.25

0.07

−0.1

5N

emat

oda

(ME

)−0

.03

−0.7

2−0

.05

−0.4

2−0

.28

−0.4

7−0

.30

−0.4

20.

07−0

.22

0.30

Pol

ycha

eta

(ME

)−0

.31

−0.7

20.

26−0

.23

0.42

0.05

0.06

−0.1

40.

48−0

.72

0.71

Cop

epod

a(M

E)

−0.4

3−0

.39

−0.3

2−0

.63

−0.2

8−0

.56

−0.4

7−0

.10

−0.2

60.

54−0

.29

Olig

ocha

eta

(ME

)0.

280.

22−0

.48

0.22

−0.0

6−0

.16

−0.0

4−0

.05

−0.2

4−0

.48

0.43

Pla

tyhe

lmin

thes

(ME

)−0

.40

−0.4

90.

05−0

.74

−0.3

4−0

.46

−0.1

0−0

. 55

0.08

0.33

−0.1

5S

(ME

)0.

210.

45−0

.36

0.01

−0.0

8−0

.07

−0.1

20.

29−0

.26

0.03

−0.1

3J′

(ME

)−0

.38

0.21

0.13

0.03

0.57

0.40

0.35

0.21

0.27

−0.1

10.

08H

′ (M

E)

−0.2

90.

310.

020.

030.

490.

340.

270.

270.

17−0

.08

0.04

TM

AD

0.10

−0.3

70.

170.

230.

210.

120.

090.

000.

37−0

.73

0.70

TM

AB

0.05

0.09

−0.3

40.

14−0

.57

−0.3

9−0

.51

−0.1

6−0

.52

0.44

−0.1

2M

ollu

sca

(MA

)0.

08−0

.22

−0.0

10.

200.

020.

030.

22−0

.12

0.21

−0.3

10.

40P

olyc

haet

a(M

A)

−0.0

5−0

.49

0.31

0.15

0.37

0.16

0.09

0.03

0.41

−0.7

80.

69C

rust

acea

(MA

)0.

510.

64−0

.27

0.60

−0.3

90.

13−0

.28

0.17

−0.4

2−0

.04

0.24

Ech

inod

erm

ata

(MA

)−0

.35

−0.3

9−0

.34

−0.7

0−0

.41

−0.7

5−0

.16

−0.4

9−0

.20

0.42

−0.3

3S

(MA

)−0

.38

−0.5

00.

330.

16−0

.01

−0.0

5−0

.13

−0.0

5−0

.15

−0.2

80.

44J′

(MA

)−0

.43

−0.4

20.

310.

11−0

.08

−0.0

9−0

.15

−0.0

4−0

.27

−0.0

90.

27H

′ (M

A)

−0.0

60.

33−0

.19

0.21

−0.3

5−0

.13

−0.1

7−0

.01

−0.4

60.

49−0

.26


Tab

le2

(con

tinu

ed)

Mud

For

amin

ifer

aS

(For

amin

ifer

a)T

ME

DN

emat

oda

Pol

ycha

eta

Cop

epod

aO

ligoc

haet

aP

laty

helm

inth

esS

(ME

)J′

(ME

)(M

E)

(ME

)(M

E)

(ME

)(M

E)

Salin

ity

DO

Chl

-aA

mm

onia

Nit

rate

sN

itri

tes

P-t

otN

-tot

TR

IXT

OM

Sand

Mud

1.00

For

amin

ifer

a0.

961.

00S

(For

amin

ifer

a)0.

950.

891.

00T

ME

D0.

140.

150.

241.

00N

emat

oda

(ME

)−0

.21

−0.1

4−0

.27

−0.2

21.

00P

olyc

haet

a(M

E)

−0.7

0−0

.63

−0.7

8−0

.23

0.66

1.00

Cop

epod

a(M

E)

0.55

0.57

0.48

−0.0

70.

200.

031.

00O

ligoc

haet

a(M

E)

−0.3

4−0

.31

−0.2

6−0

.05

0.15

0.26

−0.0

51.

00P

laty

helm

inth

es(M

E)

0.33

0.34

0.35

0.26

0.42

0.18

0.63

−0.0

21.

00S

(ME

)0.

160.

090.

160.

39−0

.41

−0.3

60.

030.

34−0

.26

1.00

J′(M

E)

−0.0

7−0

.09

−0.0

50.

19−0

.67

−0.0

10.

170.

130.

000.

251.

00H

′ (M

E)

−0.0

2−0

.06

0.00

0.27

−0.7

1−0

.11

0.17

0.20

−0.0

60.

480.

97T

MA

D−0

.69

−0.7

0−0

.73

−0.4

40.

530.

75−0

.39

0.17

−0.1

2−0

.47

−0.2

6T

MA

B0.

460.

450.

55−0

.12

−0.0

2−0

.31

0.45

0.00

0.14

−0.2

0−0

.05

Mol

lusc

a(M

A)

−0.2

4−0

.29

−0.1

8−0

.34

0.23

0.36

−0.1

4−0

.01

0.12

−0.5

6−0

.04

Pol

ycha

eta

(MA

)−0

.79

−0.7

3−0

.87

−0.4

00.

570.

83−0

.39

0.14

−0.2

5−0

.41

−0.2

9C

rust

acea

(MA

)0.

01−0

.16

0.22

0.05

−0.3

4−0

.38

−0.2

30.

35−0

.08

0.20

0.11

Ech

inod

erm

ata

(MA

)0.

530.

640.

490.

290.

28−0

.01

0.79

0.14

0.54

0.18

0.01

S(M

A)

−0.3

5−0

.22

−0.3

2−0

.14

0.30

0.34

−0.0

1−0

.11

−0. 1

5−0

.41

−0.2

3J′

(MA

)−0

.18

−0.0

4−0

.12

−0.0

20.

150.

140.

08−0

.18

−0.1

3−0

.31

−0.1

7H

′ (M

A)

0.51

0.48

0.65

0.16

−0.5

1−0

.60

0.31

−0.1

3−0

.01

0.07

0.29


Tab

le2

(con

tinu

ed)

H′ (

ME

)T

MA

DT

MA

BM

ollu

sca

Pol

ycha

eta

Cru

stac

eaE

chin

oder

mat

aS

(MA

)J′

(MA

)H

′ (M

A)

(MA

)(M

A)

(MA

)(M

A)

Salin

ity

DO

Chl

-aA

mm

onia

Nit

rate

sN

itri

tes

P-t

otN

-tot

TR

IXT

OM

Sand

Mud

For

amin

ifer

aS

(For

amin

ifer

a)T

ME

DN

emat

oda

(ME

)P

olyc

haet

a(M

E)

Cop

epod

a(M

E)

Olig

ocha

eta

(ME

)P

laty

helm

inth

es(M

E)

S(M

E)

J′(M

E)

H′ (

ME

)1.

00T

MA

D−0

.36

1.00

TM

AB

−0.0

9−0

.24

1.00

Mol

lusc

a(M

A)

−0.1

80.

710.

131.

00P

olyc

haet

a(M

A)

−0.3

70.

92−0

.34

0.42

1.00

Cru

stac

ea(M

A)

0.16

−0.0

10.

400.

20−0

.27

1.00

Ech

inod

erm

ata

(MA

)0.

05−0

.42

0.40

−0.1

8−0

.37

−0.3

11.

00S

(MA

)−0

.31

0.40

0.39

0.35

0.48

−0.0

80.

081.

00J′

(MA

)−0

.23

0.15

0.49

0.19

0.24

−0.0

70.

190.

961.

00H

′ (M

A)

0.29

−0.4

90.

810.

07−0

.62

0.46

0.31

0.26

0.43

1.00


The Foglia had higher values than the other tworivers.

Statistical analysis

A Spearman’s rho correlation matrix highlightsa significantly positive coefficient of correla-tions (0.95) between TOM and mud and a neg-ative coefficient with sand (−0.89; Table 2).Highly positive coefficients of correlations amongforaminifera, S (Foraminifera) and mud and TOMcontents are also documented, indicating a sim-ilar pattern of distribution and co-occurrence.On the other hand, there are significantly nega-tive correlation coefficients between the TMADand polychaetes (MA and ME) with mud andTOM. Nematodes are positively correlated withmeiofaunal polychaetes, whereas copepods arepositively correlated with both echinoderms andplatyhelminthes. Meiofaunal polychaetes are pos-itively correlated with macrofaunal polychaetes(0.83) and nematodes (0.66) but negativelywith foraminifera (−0.63). Negative correlationcoefficients have been found among ammoniaand copepods and platyhelminthes (Table 2). TheQ mode cluster analysis results in the groupingof samples into two separate clusters (I and II)according to their distance from the coast/waterdepth, influenced, in turn, by a set of parameters

(Fig. 2). Cluster I groups those stations closest tothe sea coast and with a low bathymetric depth,and can be defined as the shallower cluster. Onthe other hand, cluster II groups the stations far-thest from the coast and can be defined as thedeepest in terms of bathymetric depth. In order tounravel which parameters are behind the distancefrom the coast (water depth), a PCA has beenperformed to relate samples and faunal parame-ters to abiotic ones. Two principal components(factors) have been identified (eigenvalue >1),which together explain 64.9% of the data vari-ance, whereas the first and second factors explain38.3% and 26.6% of the total variance, respec-tively. Sand, mud, TOM, nitrates, and nitrites arethe predominant elements in the first factor, whilethe major contributors in the second are due tosalinity, DO, and, to some extent, ammonia andChl-a. The factor loadings of other parameters,including N-tot and P-tot, are almost equally dis-tributed between these two factors. This becomesclear as soon as the variables (which are the abi-otic parameters) are plotted on the factor-plane1 × 2 (Fig. 3). The foraminiferal, meiofaunal, andmacrofaunal parameters and their componentshave been projected onto the factor-plane as addi-tional variables without contributing to the resultsof the analysis. This can, however, provide insightinto the potential influence of abiotic parameters

Fig. 2 Dendrogramclassification of stationsproduced by Q-modecluster analysis usingEuclidean distance


Fig. 3 PCA ordinationdiagram of samplingbased on the selectedvariables

on the benthic community (Fig. 3). In particular,it appears that Foraminifera, S (Foraminifera),Copepoda, and Echinodermata have higher pos-itive values for factor 1, whereas macro and meio-faunal Polychaeta are confined between highly

negative values of factor 1, while a negative valuefor factor 2 is observed for Crustacea. All of thesampling stations have also been plotted on thePCA factor-plane 1 × 2, which grouped the sta-tions according to their environmental conditions.

Fig. 4 Scatter diagramplotting factors 1 and 2 ofsampling stations


This grouping is approximately the same as thatobtained by the Q mode CA (Fig. 4). Accordingly,two distinct groups (I and II, as also obtained bya CA) have been recognized and the two factorsinterpreted as the distance from the coast (the firstaxis) and seasonality (the second axis).

On the basis of density values, the two-waycrossed ANOSIM (depth × season) carried outon the foraminiferal assemblages was significantlydifferent only between the depths (R = 0.94; p =0.01), while the same analysis applied to meio-fauna revealed a significant difference in the as-semblage only between the seasons (R = 0.48;

p = 0.02). However, a significant difference in themacrofaunal assemblage was detected betweenboth depths (R = 0.93; p = 0.01) and seasons(R = 0.69; p = 0.01). The same kind of analysiswas applied to macrofaunal biomass, this timerevealing significant differences only with depth(R = 0.59; p = 0.01).

Applying the ABC method to the macrofaunalcommunities’ data (Fig. 5), the results indicatedthat the inshore stations in both sampling monthswere moderately disturbed (W statistic close to 0),while the offshore stations were undisturbed (Wstatistic values higher than 0).

Fig. 5 The abundance biomass comparison curves applied to the macrofaunal communities data


Discussion

Environmental parameters

The coastal area examined herein was charac-terized by quite stable physico-chemical waterconditions, and although the DO exhibited lowervalues in July than in May, this minor decreasemight indicate slightly higher oxygen consumptiondue to greater heterotrophic activity. Higher nu-trient loads were generally found at the inshorestations, where the river effects are enhanced.Accordingly, Chl-a, which can generally providea good indication of labile organic matter inputto sediments (e.g., Van Duyl and Kop 1994;Boon and Duineveld 1998), and P-tot had highervalues in July than in May. This might indicatean increased river water supply due to moderaterainfall (as registered in July 2002), and this isalso supported by lower salinity values in Julythan in May. These trends are comparable withthose found by Penna et al. (2004) for DO andnutrients in almost the same area. In the surfacewater, the TRIX values were generally low, sug-gesting poorly to moderately productive waterswith low trophic levels. Decreasing TRIX valueshave, however, been recorded seawards, and thehighest values found in stations closest to the coastwere, therefore, most likely to be as a result ofa direct influence of the nutrient loads from therivers that were enhanced in July.

Physical energy above the seafloor is an im-portant element which determines the spatial dis-tribution of different sediment types. This mayexplain the main bipartition of sand and mud sed-iment types encountered in the investigated area.The poorly sorted and deposited-fine-grained ma-terial offshore highlights that the hydrodynamicconditions predominately took place in the in-shore stations, where wave action is prevalent.This bipartition appears to influence the TOMcontents, revealing a marked seawards increase.This is also testified by the highly positive correla-tion coefficient. A strong relation between TOMand depth (in turn grain size) was also reportedin previous studies by Alberelli et al. (1999) andSemprucci et al. (2010). In contrast to the spatialdistribution, a temporal variation of TOM was notrecognized during the sampling period.

On the basis of the data, analyzed by PCAplot, the distance from the coast/depth gradientand the seasonality (month of collection) exerteda strong influence on several parameters. In par-ticular, sediment data (sand, mud, and TOM) andnutrient concentrations (nitrites and nitrates) ap-pear to be influenced only by the distance fromthe coast, being constrained in high (positive andnegative) values of factor 1. On the other hand,water parameters (salinity and DO) and nutrients(ammonia, Chl-a, P-tot, and N-tot) seem to bemainly related to seasonality.

Are there any relationships between the benthiccommunity and environmental parameters?

Several studies have highlighted the benthic com-munities’ sensitivity (foraminifera, meiofauna, andmacrofauna) to various kinds of anthropogenicdisturbances (e.g., Sandulli and De Nicola-Giudici1990, 1991; Austen et al. 1994; Barmawidjaja et al.1995; Danovaro et al. 1995; Alberelli et al. 1999;Duijnstee et al. 2004; Fraschetti et al. 2006;Akomianaki and Nicolaidou 2007; CovazziHarriague et al. 2007; Coccioni et al. 2009;Frontalini et al. 2009, 2010). The human influenceseems to alter the meiofaunal assemblages interms of composition, abundance, and diversity.The changes are not always univocal (increasingor decreasing the mean abundance in differentcases) and could determine dissimilar effects ondifferent taxa, i.e., increasing nematodes anddecreasing harpacticoid copepods (Sandulli andDe Nicola-Giudici 1990, 1991; Semprucci et al.2010).

The benthic community appears to be influ-enced, to some extent, by the riverine input. Inthe present study, the most affected taxa areforaminifera and copepods and, to a lesser degree,the meiofaunal polychaetes and platyhelminthes.The ABC curves demonstrate that the macrofau-nal communities closest to the river mouths weremoderately disturbed in both sampling periods. Inparticular, the lack of echinoderms and the lowerabundance of amphipods and sensitive taxa in theinshore stations could confirm the influence ofthe riverine input on the macrofaunal assemblages(Blanchard et al. 2002, 2003).


The foraminiferal assemblages reveal an evi-dent inshore–offshore gradient in species richnessand density, and this reflects the high mud andTOM contents. Changes in the benthic assem-blages in relation to the distance to the coast couldbe associated with either the modified structuralcomplexity of the substrate (i.e., sediment textureand food supply) or increased disturbance. Mostof the studies carried out in polluted environmentshave highlighted that a decrease in density anddiversity can be viewed as a measure of environ-mental stress on benthic foraminiferal communi-ties that is caused by pollution (e.g., Schafer 1973;Yanko et al. 1998). Increased pollution has alsobeen reported as the cause of a high number of in-dividuals belonging to a few opportunistic species(Murray 1973; Pearson and Rosenberg 1976;Ellison et al. 1986). It has been noted that asgreater concentrations of trace elements and otherchemicals are discharged, the population maydecrease, eventually leading to a barren area(Samir 2000; Elberling et al. 2003; Ferraro et al.2006). The recognized foraminiferal biocenosis,dominated by infaunal genera such as Ammonia,Aubignyna, Bolivina, Eggerelloides, and Hopkin-sina, and a relatively low occurrence of epifaunalbelonging to the Quinqueloculina genus, are typ-ical of shallow, oligotrophic, and moderately oxy-genized environments. Most of the biocenosis isconstituted of herbivore feeding forms with amarked preference for mud and/or fine sand sub-strates. In addition to the seawards increase ofdensity and species richness, a change in the as-semblages’ composition can also be documented.Accordingly, opportunistic taxa like H. pacif ica,Bolivina spp. and N. turgida display a simi-lar trend. As well as being regarded as themost opportunistic taxa by Jorissen et al. (1992)and Barmawidjaja et al. (1995), they have alsobeen viewed as being particularly stress toler-ant and bioindicators of nutrient load. In fact,Barmawidjaja et al. (1995) have documentedthat since 1880, a gradual replacement oftaxa with more stress tolerant versions (i.e.,N. turgida) occurred in a sediment core col-lected in front of the Po River. The same au-thors also regarded H. pacif ica as the moststress tolerant taxon. Greater abundances ofBolivina, Bulimina, Buliminella, and Hopkinsina

might generally be found in oxygen-depleted en-vironments. The genus Bolivina, with its flattenedelongated morphology, reported as an adapta-tion to low-oxygen conditions (Bernhard 1986), isknown to survive in oxygen-deficient environments(Murray 1991, 2006) and can often be dominantin upwelling zones (e.g., Debenay et al. 2001).Bolivina practices an opportunistic life strategy,and is able to tolerate periodic reductions in dis-solved oxygen contents by modifying its micro-habitat from infaunal to epifaunal (Jorissen et al.1992; Donnici and Serandrei Barbero 2002). Manyof the species tolerant to oxygen deficiency aretypical of muddy environments (Van der Zwaanet al. 1999), sometimes containing high amountsof organic carbon (Murray 1991, 2006). The genusAmmonia from the studied area consists mainlyof A. parkinsoniana and, albeit subordinated, theopportunistic species, A. tepida. Representativesof this genus dominate the shallow water envi-ronments all over the world. In particular, A.parkinsoniana, which is typical of relatively cleanenvironments (Seiglie 1975), is very common allalong the Italian coast between 10 and 20 m waterdepths, irrespective of the substratum type andpercentage of organic matter (Jorissen 1988). Onthe other hand, A. tepida is known for its greattolerance to all kinds of stressful conditions (e.g.,Setty and Nigam 1984; Yanko et al. 1994, 1999;Alve 1995; Debenay et al. 2001; Armynot duChâtelet et al. 2004). Due to the higher relativeabundances of A. tepida in shallow water stations,our results confirm the capacity of A. tepida totolerate stress, even that caused by riverine input.

Although significant differences between meio-faunal assemblages and distance from the coasthave not been found, harpacticoid copepods arenegatively correlated only with ammonia, andthey exhibit a clearly opposite trend to nutrients,as well as to TRIX. Nematodes, a taxon verytolerant to environmental disturbance, are able toexploit all of the adverse conditions (Vidakovic1983; Heip et al. 1985; Bongers et al. 1991). Theyrevealed a slight increase offshore, but not as ev-idently as in a previous investigation (Semprucciet al. 2010). Even though the nematode assemblageis represented mainly by deposit-feeding genera(Balsamo et al. 2003), a clear relationship withTOM is not found, while a significant increase of


nematodes with a reduction of DO percentage inthe water column is detected, confirming their tol-erance to oxygen depletion. The DO in the watercolumn cannot perfectly mimic the oxygenationcondition within the sediment, but it can provideuseful information about oxygen availability.

Among the macrofaunal polychaetes, O. fusi-formis represents almost 37% of this taxon. Thisspecies is quite tolerant, and typical of sandysubstrate and shallow waters corresponding tothe type of sediment found inshore (Simbouraand Zenetos 2002). The high abundance of O.fusiformis in the shallowest sites could be relatedto the sandy sediment. Indeed, according to Perésand Picard (1964), this species is characteristic ofwell-sorted and fine sandy biocoenosis.

Plausibly, the greater riverine influence thatoccurs inshore may have selected the meiofau-nal and macrofaunal assemblage favoring speciesthat are more tolerant inshore (polychaetes re-sulted parallel to increase to TRIX index), whilemore sensitive taxa were located offshore (i.e.,the echinoderms in macrofauna and copepods andplatyhelminthes in meiofauna).

The opposite trend of meiofaunal and macro-faunal abundances could be explained as a com-petition between the two benthic components.Despite the high organic load, the lack of any cor-relation between organic matter and Chl-a mightbe suggestive of the refractory nature of the or-ganic matter and, consequently, its low trophicvalue for the benthic organisms. Following this,the trophic source could become a limiting fac-tor for the benthic assemblages and, therefore, acause of competition between meio and macro-fauna. Furthermore, the inshore macrofaunalassemblages are constituted principally of sus-pension and suspension-deposit feeders. They en-trap the food particles before sinking to the seabottom, decreasing the quantity of the pelagichigh-quality food in the sediment for the deposit-feeders, and the meio and macrofauna.

The differences between inshore–offshore macro-faunal assemblages are, as is already known, re-lated to the food supply (Rosenberg 1995) andthe sediment grain size (Alberelli et al. 1999). Infact, the inshore stations, characterized by sandysediments and higher values of Chl-a concentra-tions (probably related to the higher inorganic

nutrient concentrations), are inhabited by speciesthat are typical of sandy bottoms and by sus-pension and deposit suspension-feeder feeding-types (such as L. mediterraneum, C. gallina, S.sudtruncata and O. fusiformis). The offshore sitesare characterized by muddy sediments and highsedimentary organic content. They are, conse-quently, inhabited by organisms typical of muddybiocoenosis and deposit-feeders (Amycolatopsisalba, Abra prismatica, N. sulcata, Harpinia crenu-lata, and Echinocardium cordatum) and depositsuspension-feeders (Corbula gibba and Anonyxsarsi).

The higher Chl-a concentrations in the in-shore stations, which are related to the higherorganic nutrient riverine input, have probablyinfluenced the macrofaunal assemblages. This canbe confirmed by the results of the ABC analysis,indicating the disturbed state of the inshore com-munities. Moreover, C. gibba has been regardedas an indicator of sediment instability (Perés andPicard 1964). Although its density was higheroffshore during July 2002 (corresponding to thehigher river runoff), a greater abundance of thisspecies was recorded inshore, supporting the ob-servations of a general riverine influence upon themacrobenthic communities. It is well known thatthe distribution of benthic communities varies inresponse to a complex array of variables. Cer-tainly, one of the main problems of environmentalmonitoring or field research lies in the difficultyin discriminating pollution gradients from naturalenvironmental gradients (like changes in sedimentgrain-size or food supply) which may have similareffects on the communities. A comparison withhistorical data could be an essential prerequisitein separating anthropogenic disturbance from thatof natural environmental variables.

Conclusion

Shelf systems are strongly influenced by changesin riverine input which play a major role inthe distribution of benthic communities. This in-tegrated investigation documents, for the firsttime, the benthic communities in a poorly knownbut environmentally valuable area of the CentralAdriatic Sea. Moreover, it simultaneously sheds


light on the temporal and spatial variations offoraminifera, meiofauna, and macrofauna in frontof three rivers. Although this area can be regardedas being poorly to moderately affected by anthro-pogenic activity, a clear inshore–offshore trend inthe benthic community has been reported. Thisis well documented by the foraminiferal assem-blages, which exhibit an evident gradient in theircomposition, species richness, and density. A sim-ilar pattern has been found for copepods. Thisis also well supported by the ABC curves, whichreveal that the macrofaunal communities closestto the river mouths are moderately disturbed.

Acknowledgements We warmly thank two anonymousreviewers, and the Editor in Chief Prof. G.B. Wiersma fortheir helpful comments that were material in improving themanuscript.

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