Assessment of benthic trophic status of marine coastal ecosystems:Significance of meiofaunal rare taxa

Antonio Pusceddu*, Silvia Bianchelli, Cristina Gambi, Roberto Danovaro

Department of Marine Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy

a r t i c l e i n f o

Article history:

Received 21 July 2010

Accepted 10 May 2011

Available online 19 May 2011

Keywords:

trophic status

marine sediments

organic matter

meiofauna

Mediterranean Sea

a b s t r a c t

Eutrophication enhances organic C inputs to the sea bottom, so that the quantity and biochemical

composition of sedimentary organic matter are expected to change under different trophic status

conditions. In turn, changes in the trophic status are often associated with shifts in the abundance and

community structure of the benthos. We investigated the quantity and biochemical composition

(protein, carbohydrate, lipid and phytopigment) of sedimentary organic matter together with abundance

and community structure of meiofauna in two regions of the Mediterranean Sea characterized by

different levels of primary productivity. At each region, five transects were randomly selected along the

coastline. At each transect, three stations located at increasing distance from the shore and different

water depth were investigated. Uni- and multivariate analyses of variance revealed that the quantity and

biochemical composition of sediment organic matter displayed the most relevant differences between

stations, suggesting their potential use as descriptor of the benthic trophic state at the small spatial scale

(i.e. <2 km). The correlation analyses, corroborated by nMDS dispersion plots and cluster analyses

highlighted that the biopolymeric C content of the sediment and the algal fraction of sediment organic

matter were inversely related and able to discriminate the trophic status at the scale of region, transect

and station. Uni- and multivariate analyses on meiofaunal assemblages revealed that differences at

different spatial scales were less evident in terms of abundance and richness of meiofaunal taxa but were

more evident in terms of taxonomic composition. Furthermore, these differences were enhanced when

the analyses were restricted using the meiofaunal rare taxa (i.e. those taxa representing <1% of the total

meiofaunal abundance) as an input. The results of the multivariate multiple regression analyses revealed

that the taxonomic composition of meiofaunal assemblages was driven mostly by protein, biopolymeric

C and chlorophyll-a concentrations but also by the algal fraction of biopolymeric C. We conclude that, the

study of the quantity and biochemical composition of sediment organic matter coupled with an analysis

of the rare meiofaunal taxa allows an ecosystem-oriented assessment of the trophic status of marine

benthic environments.

! 2011 Elsevier Ltd. All rights reserved.

1. Introduction

Eutrophication, i.e. an increase in inorganic nutrient concen-

tration resulting in an enhancement in the ecosystem’s primary

productivity, is one of the most frequent and widely spread

phenomena associated with the human utilization of the coastal

ocean (Cloern, 2001). The recognition of coastal eutrophication as

a global problem is relatively recent and is thus attracting the

increasing attention from the scientific community as well as from

environmental managers and decision makers (Pinckney et al.,

2001; Karlson et al., 2002; Pusceddu et al., 2009; Ferreira et al.,

2011).

Studies on the assessment of the trophic status of marine coastal

ecosystems have been historically based on chemical measure-

ments (e.g., inorganic nitrogen and phosphorous) and/or surrogate

measurements of algal biomass (i.e., chlorophyll-a concentrations;

Zurlini, 1996; Vollenweider et al., 1998; Stefanou et al., 1999; Coelho

et al., 2007). However, shifts in the trophic status not only may

induce increases in primary production, but also exert conse-

quences at different hierarchical levels of the ecosystem organiza-

tion, including changes at the community level in terms of (1)

primary producers composition (e.g., from perennial macroalgae

and seagrasses, to ephemeral macroalgae, to pelagic microalgae);

(2) community size spectra; (3) biodiversity shifts; and (4) modi-

fication of length and structure of the food webs (Diaz et al., 1995;

Raffaelli et al., 1998; Gin et al., 1999; Feuerpfeil et al., 2004; Lotze

et al., 2006; Scavia and Bricker, 2006).* Corresponding author.

E-mail address: a.pusceddu@univpm.it (A. Pusceddu).

Contents lists available at ScienceDirect

Estuarine, Coastal and Shelf Science

journal homepage: www.elsevier .com/locate/ecss

0272-7714/$ e see front matter ! 2011 Elsevier Ltd. All rights reserved.

doi:10.1016/j.ecss.2011.05.012

Estuarine, Coastal and Shelf Science 93 (2011) 420e430

Although no single indicator can be employed to adequately

compare eutrophication state between different seas (McQuatters-

Gollop et al., 2009), to define synthetic trophic status indices, some

studies have integrated different approaches based on the analysis

of predictive and/or responsive variables of algal growth, such as

inorganic phosphorus, chlorophyll-a concentrations and water

column turbidity (e.g., Vollenweider et al., 1998). However, the

increase of primary production following increased inorganic

nutrient levels in the water column is far from representing

a general rule, so that it appears evident that the mere determi-

nation of inorganic nutrient and chlorophyll-a concentrations in

the water may be insufficient to provide complete information on

the trophic status of aquatic ecosystems (Izzo et al., 1997; Cognetti,

2001; Dell’Anno et al., 2002; Pusceddu et al., 2009). In fact,

predictive (i.e., nutrient concentrations) and responsive (e.g., algal

biomass measured as chlorophyll-a) variables are not always

effective in all ecosystems. For example, while water column vari-

ables can identify changes in the trophic status even at very large

spatial scales (e.g., Sarà et al., in press) in nutrient-enriched mix-

ohaline ecosystems (such as lagoons, ponds, and estuaries), the

fluctuations in the concentration of suspended chlorophyll-a are

often due to the microphytobenthos resuspension rather than to

increased primary production in the water column resulting from

enhanced inorganic nutrient availability (Conde et al., 1999;

Pusceddu et al., 1999; Lucas et al., 2000). Moreover, the complex

hydrodynamic forcing operating at shallow (i.e. <30 m) depths in

coastal ecosystems might lead to discrepancies between the

assessments of trophic status conditions based on water column

variables (in terms of inorganic nutrients and chlorophyll concen-

trations) vs. those based on sediment variables (Dell’Anno et al.,

2002), the latter being able to provide information also on

changes occurring after sediment resuspension induced by natural

and anthropogenic disturbance (Pusceddu et al., 2005).

The progressive accumulation of results rejecting the view of

eutrophication as a cascade of effects derived from enhanced

inorganic nutrient availability has thus stimulated new conceptual

models for the assessment of the trophic status of marine ecosys-

tems. Nixon (1995) proposed a new approach for the assessment of

the trophic status of marine systems based on the supply of total

organic C to the system (as g C m!2 y!1). This approach tentatively

moved the focus on the potential consequences of eutrophication

on benthic systems but, without taking into consideration the

differential reactivity of organic molecules within sediments, it still

appears to have a poor sensitivity (Pusceddu et al., 2009). In this

regard, it has been recently pointed out that benthic marine

ecosystems exhibiting putatively different trophic conditions in the

water column are characterized by relevant changes in the quan-

tity, biochemical composition and bioavailability of sediment

organic matter (Pusceddu et al., 2007a).

Alteration of benthic trophic conditions (i.e., changes in the

quantity and availability of food resources) may influence benthic

organisms directly altering their metabolic processes and mobility,

but also indirectly modifying community structure, biodiversity

and relationships among species and trophic groups (Diaz and

Rosenberg, 1995; Modig and Olafsson, 1998; Peterson et al., 2000;

Powers et al., 2005; Gambi et al., 2009; Mirto et al., 2010). Among

the different benthic compartments, meiofauna appear to be highly

sensitive to environmental disturbance including eutrophication

(Powers et al., 2005; Moreno et al., 2008; Gambi et al., 2009;

Balsamo et al., 2010; Mirto et al., 2010). In this regard, several

studies have addressed the response of meiofauna to hypoxic

conditions or benthic organic enrichment (Sandulli et al., 2004;

Pusceddu et al., 2007a; Steyaert et al., 2007; Sutherland et al.,

2007; Grego et al., 2009). Meiofauna, due to their relatively short

life cycles, high turnover rates and lack of larval dispersion, are in

fact expected to respond rapidly to environmental changes and

food availability (Modig and Olafsson, 1998; Danovaro et al., 2000,

2004; La Rosa et al., 2001; Danovaro and Gambi, 2002; Austen and

Widdicombe, 2006; De Troch et al., 2006), whereas macrofauna

respond more slowly (Austen and Widdicombe, 2006). Recent

studies have also identified meiofauna to be tightly respondent to

changes in the quantity and biochemical composition of sediment

organicmatter under different trophic conditions in coastal lagoons

(Pusceddu et al., 2009) and to eutrophication of marine sediments

subjected to organic wastes from aquaculture (Mirto et al., 2010).

For this reason the study of meiofauna is attracting an increasing

interest for their potential use as a ‘‘wide-spectrum’’ tool in envi-

ronmental monitoring (Mirto and Danovaro, 2004).

Very little information is available to date about the comple-

mentarity of signals provided by sedimentary biochemical

descriptors and the meiofaunal assemblage composition under

different conditions of trophic status. Some attempts have, for

instance, identified significant changes in the biodiversity of

nematode assemblages in response to changes in organic inputs to

the benthos (e.g., Mirto et al., 2002). However, the identification of

species, though of a single taxon, can be reliably conducted only by

specialized taxonomists and, especially for meiofaunal organisms,

this task is particularly time consuming. Moreover, it has been

recently shown that shifts in the organic inputs to the benthos

(such as those produced by fish farming) can produce significant

changes in the composition of meiofaunal community structure at

the highest taxonomic separation level (Mirto et al., 2010). Gener-

ally, nematodes represent more than 50% of the total meiofaunal

abundance in coastal sediments, whereas many other taxa often

represent less than 1% each. Based on these assumptions, in this

study we tested the hypothesis that the relative abundance of rare

meiofaunal taxa (i.e., each representing<1% of the total meiofaunal

abundance) can identify differences between sediments charac-

terized by variable trophic conditions. Moreover, we hypothesized

that such differences, on the one hand, are in good agreement with

the abovementioned biochemical approach, and, on the other hand,

provide a clearer figure than the one provided by changes in the

taxonomic composition of the whole meiofaunal assemblage.

To test such hypothesis, in this study we investigated the

quantity and biochemical composition of sedimentary organic

matter, as well as the abundance, richness of taxa and community

structure of meiofauna in two distinct regions of theMediterranean

Sea, characterized by different levels of primary productivity and

putative trophic conditions in the water column. At each region,

five transects were randomly selected along the coastline to assess

the mesoscale variability (i.e., within 10 km distance). Since the

quantity and biochemical composition of sediment organic matter

and benthic faunal variables can be also affected by the water

column depth, at each of the whole ten transects, three stations

were identified at an increasing distance from the shore and at

different water column depth.

2. Materials and methods

2.1. Study areas and sampling

Sediments were collected by means of box-corers in the

Northern Adriatic and Tyrrhenian Seas facing the shore of the

Veneto and Campania regions, respectively (Fig. 1). The use of box-

corers for meiofaunal sampling has been sometimes questioned,

especially for deep-sea studies (Bett et al., 1994; Shirayama and

Fukushima, 1995). In fact, the use of this kind of sampling device

can determine a certain bias on meiofaunal abundance estimates

because of the possible washout of the sediment during the (pro-

longed) retrieval of the device (Danovaro, 2010). In this study,

A. Pusceddu et al. / Estuarine, Coastal and Shelf Science 93 (2011) 420e430 421

sediment samples were collected at depths never exceeding 50 m

so that the possible bias due to bow-wave action on the sampled

sediment during retrieval of the corer may have been limited.

At each region, samples were collected along five transects

(transects 1e5 and 6e10 in the Veneto and Campania regions,

respectively) orthogonal to the coastline from three stations

located at increasing distance from the coastline (500, 1000 and

3000 m and different water depths, Table S1). Transects and

stations were selected to assess changes in the quantity and

biochemical composition of sediment organic matter as well as

meiofaunal community structure at the macro-scale (i.e., between

regions), at the mesoscale (i.e., between transects at few km

distance each other within the same region) and at the local scale

(i.e., between stations at increasing distance from the shore or

increasing water column depth within the same transect). The two

regions were selected because they are characterized by different

levels of trophic status in the water column, with chlorophyll-

a concentrations ranging from 0.3e2.5 to 0.6e10 mg m!3 in the

Campania and Veneto regions, respectively (data acquired from the

Ocean Productivity database in the month of sampling; http://

www.science.oregonstate.edu/ocean.productivity/index.php; Behr

enfeld and Falkowski, 1997). The two regions exhibit different

rates of supply of total organic C to the system: up to

273 g C m!2 y!1 in the Northern Adriatic Sea (Giani et al., 2001;

Giordani et al., 2002) and up to 100 g C m!2 y!1 in the Tyr-

rhenian Sea (Speicher et al., 2006), which, according to the Nixon’s

notation (1995), approximately correspond to mesotrophic and

oligotrophic conditions, respectively.

2.2. Biochemical composition of sediment organic matter

Chloroplastic pigments (chlorophyll-a and phaeopigments)

were analyzed fluorometrically according to Lorenzen and Jeffrey

(1980). Pigments were extracted with 90% acetone (24 h in the

dark at 4 "C). After centrifugation (800# g), the supernatant was

used to determine the functional chlorophyll-a and acidified with

0.1 N HCl to estimate the amount of phaeopigments. Total phyto-

pigment concentrations were defined as the sum of chlorophyll-

a and phaeopigment concentrations, and utilized as an estimate

of the organic material of algal origin, including the living (chlo-

rophyll-a) and senescent/detrital (phaeopigment) fractions

(Pusceddu et al., 2009).

Protein analyses were carried out after extractions with NaOH

(0.5 M, 4 h) and were determined according to Hartree (1972)

modified by Rice (1982) to compensate for phenol interference.

Concentrations are reported as albumin equivalents. Carbohydrates

were analyzed according to Gerchacov and Hatcher (1972) and

expressed as glucose equivalents. The method is based on the same

principle as the widely used method of Dubois et al. (1956), but is

specifically adapted for carbohydrate determination in sediments.

Lipids were extracted by direct elution with chloroform and

methanol and analysed according to Marsh and Wenstein (1966).

Lipid concentrations are reported as tripalmitine equivalents. For

each biochemical analysis, blanks were made with the same sedi-

ment samples as previously treated in a muffle furnace (450 "C,

2 h). All biochemical analyses were carried out (n ¼ 3) on the top

1 cm of the sediment.

Protein, carbohydrate and lipid concentrations were converted

to carbon equivalents by using the following conversion factors:

0.49, 0.40 and 0.75 mg C mg!1, respectively and the sum of protein,

carbohydrate and lipid carbonwas referred as biopolymeric carbon

(BPC, Pusceddu et al., 2000, 2009). Values of the carbon to

chlorophyll-a ratio can vary, depending on the source and ageing

of the algal material, from 10 to 100 (Banse, 1977). In the present

study, we converted sediment phytopigment concentrations into

carbon equivalents using a mean value of 40 mg C mg

phytopigment !1, which allowed the comparison with previous

works (Pusceddu et al., 1999, 2000, 2009). The fraction of bio-

polymeric C represented by relatively fresh algal material was then

assessed as the percentage contribution of phytopigment C to

biopolymeric C contents and referred to as the algal fraction of BPC

(Pusceddu et al., 2009).

Fig. 1. Sampling regions and location of the investigated transects and stations.

A. Pusceddu et al. / Estuarine, Coastal and Shelf Science 93 (2011) 420e430422

2.3. Meiofauna

For meiofaunal extraction, sediment samples were sieved

through a 1000-mmmesh, and a 30-mmmeshwas used to retain the

smallest organisms. The fraction remaining on the latter sieve was

re-suspended and centrifuged three times with Ludox HS40

(diluted with water to a final density of 1.18 g cm!3) according to

Heip et al. (1985). All meiobenthic animals from three independent

replicates per station were counted and sorted by taxa, under

a stereomicroscope and after staining with Rose Bengal (0.5 g L!1).

The rare taxa were defined as the taxa that represented <1% of the

total meiofaunal abundance of all investigated samples (Bianchelli

et al., 2010).

2.4. Statistical analyses

To assess differences in all investigated variables between

regions, transects and stations we applied either uni- or multivar-

iate analyses of variance. First, a three-way univariate analysis of

variance (3-way ANOVA) was carried out using region (RE, fixed

factor with 2 levels, Veneto vs. Campania), transect (TR, random

factor with 5 levels, nested in RE) and station (ST, random factor

with 3 levels, nested in RE and TR), as main sources of variance.

Prior to analyses, the homogeneity of variance was tested bymeans

of the Cochrans’ test and, when necessary, the data were appro-

priately transformed. For those data sets for which the trans-

formation did not allow to obtain homogeneous variances, a more

conservative level of significance was considered (Underwood,

1991). ANOVA and Cochran’s test were carried out using the

GMAV 5.0 software (University of Sydney). When significant

differences were observed between regions and stations, a Student-

Newman-Kuels (SNK) test was also applied. Although post-hoc tests

could not be applied on random factors (Underwood, 1997), we

forced their use to discriminate stations within the same transect.

Adistance-basedpermutationalmultivariate analysis of variance

(PERMANOVA, Anderson, 2001; McArdle and Anderson, 2001) was

also used to test for variation in organic matter biochemical com-

position. PERMANOVA is analogous to the multivariate analysis of

variance (MANOVA), but it is preferable since it allows to partition

the variability in the data according to a complex design or model

and to base the analysis on a multivariate distance measure that is

reasonable for ecological data sets (McArdle and Anderson, 2001).

PERMANOVA has been used already for assessing patterns of vari-

ation in the biochemical composition of sediment organic matter in

a variety of marine benthic ecosystems (e.g., Pusceddu et al., 2007b,

2010). Again, the design included three factors: region (RE, 2 levels,

fixed), transect (TR, random factor with 5 levels, nested in RE) and

station (ST, random factor with 3 levels, nested in RE and TR) with

n ¼ 3 for the combination of factors. The analysis included concen-

trations of proteins, carbohydrates, lipids, chlorophyll-a and phae-

opigments and was based on Euclidean distances of previously

normalizeddata, using999 randompermutations of the appropriate

units (Anderson and ter Braak, 2003).

The relationships between the algal fraction of sediment organic

matter, the concentrations of the different biopolymers and bio-

polymeric C in the sediment were investigated by using a Spear-

maneRank correlation analysis.

SIMPER analyses was also performed to assess the percentage

dissimilarity (sensu Gray, 2000) in the meiofaunal assemblage

composition between regions, transects within the same region

and stations within the same transect, separately for the entire

communities and rare taxa. After the data were square root trans-

formed a SIMPER analysis was also carried out for identifying

meiofaunal (rare) taxa discriminating regions. A ranked matrix of

BrayeCurtis similarities was used as input for this test.

ANOSIM analysis was then performed to test the presence of

statistical differences in the meiofaunal taxonomic composition

between grouped transects and/or grouped stations, for the whole

meiofaunal and for the rare taxa assemblages. Non-metric multidi-

mensional scaling (nMDS) bi-plots and cluster analysis were then

used to visualize the differences between stations and identify

threshold levels of trophic status, respectively. PERMANOVA,

SIMPER, nMDS, and ANOSIM analyses were performed using

PRIMER 6þ (Plymouth Marine Laboratory, UK; Clarke, 1993).

To assess if and to what extent the quantity and biochemical

composition of sedimentary organic matter explained changes in

meiofaunal assemblages characteristics in different regions, tran-

sects or stations a non-parametric multivariate multiple regression

analysis, based on Euclidean distances, was carried out using the

routine DISTLM forward (McArdle and Anderson, 2001). The

forward selection of the predictor variables was carried out with

tests by permutation. P values were obtained using 4999 permu-

tations of raw data for the marginal tests (tests of individual vari-

ables), while for all of the conditional tests, the routine uses 4999

permutations of residuals under a reduced model.

3. Results

3.1. Biochemical composition of sedimentary organic matter

Univariate analyses of variance revealed that almost all the

investigated variables and parameters displayed significant differ-

ences between stations, and, that lipid, biopolymeric C and phy-

topigment concentrations displayed also a significant effect of the

factor region (Table S2). This result partly reflected the results of the

multivariate analysis of variance, which revealed significant effects

of the factors station and transect on the biochemical composition

of organic matter, but no effects of the factor region (Table 1).

In the sediments facing the Veneto region, biopolymeric C (range

from 0.16 & 0.04 to 3.45 & 1.06 mg C g!1) and total phytopigment

(range from 0.63 & 0.09 to 12.6 & 2.33 mg g!1) concentrations dis-

played rather similar patterns with a clear increase with increasing

water column depth (SNK, p < 0.01), but only weak differences

between transects (Fig. 2A andB). In Campania, differences between

transects were clearly driven by the values found at transect 9

(facing the River Sarno, one of themost polluted coastal areas of the

entire Mediterranean Sea), exhibiting values up to one order of

magnitude higher than those in all other investigated stations.

In sediments facing the Campania region, concentrations of all

investigated variables displayed a clear increasing pattern with

increasing distance from the coast (i.e., water depth; SNK, p < 0.01)

at all transects, but not at transects 6 and 9, where concentrations of

biopolymeric C (ranging from0.5&0.2up to34.1&5.7mgCg!1) and

total phytopigments (ranging from 0.9 & 0.2 to 42.2 & 0.4 mg g!1)

werehighest at the shallowest stations (Fig. 2AandB; SNK,p<0.01).

Table 1

Output of the distance-based permutational multivariate analysis of variance

(PERMANOVA) carried out on the whole set of investigated variables dealing with

the organic matter concentration and composition. The data set included sedi-

mentary contents of protein, carbohydrate, lipid and phytopigments. df ¼ degree of

freedom, MS ¼ mean square, F ¼ ANOVA F statistic, P ¼ probability level.

** ¼P < 0.001, * ¼P < 0.05, ns ¼ not significant. RE ¼ Region, TR ¼ transect,

ST ¼ station.

Source df MS F P

RE 1 5094.42 2.81 ns

TR (RE) 8 1811.34 2.39 *

ST (TR # RE) 20 756.32 21.80 **

Residuals 60 34.70

Total 89

A. Pusceddu et al. / Estuarine, Coastal and Shelf Science 93 (2011) 420e430 423

Sediments of the Veneto region were characterized by the

overall dominance of carbohydrates (62% on average of all stations),

followed by proteins (20%) and lipids (18%), which contribution to

biopolymeric C displayed very limited differences between stations

(Fig. 3A). Sediments of the Campania region were characterized by

the dominance of carbohydrates (42% on average of all stations)

over proteins (33%) and lipids (25%) (Fig. 3B).

The SpearmaneRank correlation analysis revealed that

concentrations of all biochemical compounds, including their sum

as biopolymeric C, were significantly correlated with the algal

fraction of BPC (Table S3). Biopolymeric C concentrations were also

significantly correlated with total phytopigment concentrations

(Fig. 4A). Phytopigments explained more than 90% of biopolymeric

C concentrations variance. An exponential decrease in the phyto-

pigment contributions to the biopolymeric C pools with increasing

biopolymeric C concentration in the sediment was also observed

(Fig. 4B).

3.2. Meiofaunal assemblages

In sediments facing the Veneto region, total meiofaunal abun-

dance ranged from 144.0 & 26.6 ind. 10 cm!2 (transect 5 at 1000 m

from the coast) to 1104.3 & 113.2 ind. 10 cm!2 (transect 3 at 500 m

from the coast) (Fig. 5). In sediments facing the Campania region,

total meiofaunal abundance ranged from 0.9 & 0.8 ind. 10 cm!2

(transect 9 at 500 m from the coast) to 1299.8 & 258.7 ind. 10 cm!2

(transect 6 at 3000 m from the coast) (Fig. 5). In the Veneto region,

meiofaunal taxa richness ranged from 4 to 9, whereas in the

Campania region, richness of meiofaunal taxa ranged from 2 to 12

(Fig. 6). The lowest values of meiofaunal abundance and richness of

taxa were found at 500 m distance from the coast in the transect 9

(facing the highly polluted river Sarno).

In all the investigated stations the meiofaunal assemblage was

dominated by nematodes (33e96%), followed by copepods (1e67%)

and polychaetes (0e7%) (Fig. S1). In both investigated regions rare

taxa included oligochaetes, amphipods, cumaceans, bivalves,

kinorhynchs, gastrotrichs, and ostracods. In the Campania region

rare taxa included also isopods and tanaidaceans.

Univariate analyses of variance revealed that total meiofaunal

abundance, richness of taxa and abundance of each taxon displayed

Fig. 2. Biopolymeric C and total phytopigment concentrations in the sediments of the two investigated regions, transects and stations. Displayed are average & standard deviation.

Fig. 3. Biochemical composition (protein, carbohydrate and lipid percentage contri-

butions to biopolymeric C) of the sediments in the two investigated regions. Reported

are mean values obtained averaging values at all transects at 500, 1000 and 3000 m

from the shore.

A. Pusceddu et al. / Estuarine, Coastal and Shelf Science 93 (2011) 420e430424

significant differences at the local scale (i.e., between stations).

Only few taxa displayed also a significant effect of the factor Region

or Transect # Region (Table S4).

The multivariate analysis conducted considering all meiofaunal

taxa revealed significant differences between regions (ANOSIM,

p < 0.01; dissimilarity 40%) and transects (ANOSIM, p < 0.05,

Table 2). When the analyses were carried out considering only

meiofaunal rare taxa, differences between regions and transects

were even more evident (Table 2). Similar results were obtained

considering differences between stations (Table S5). The graphical

output of the nMDS confirmed that, removing the most abundant

meiofaunal taxa (i.e., nematodes, copepods and polychaetes),

differences between stations were more clearly identified and

associated to changes in the relative abundance of different rare

taxa (Fig. 7 A and B). The SIMPER analysis carried out on all

meiofaunal taxa revealed that differences between regions were

mostly explained by nematodes (35.4%), copepods (16.9%) and

polychaetes (9.7%). When the SIMPER was run only on the rare

meiofaunal taxa (i.e., after the removal of nematodes, copepods and

polychaetes), the taxa mostly responsible for the observed differ-

ences between regions were bivalves (21.5%), gastrotrichs (15.6%),

oligochaetes (13.2%), and kinorhynchs (13.1%).

The multivariate multiple regression analysis displayed that

protein, biopolymeric C and chlorophyll-a concentrations, and

the algal fraction of BPC, explained most of the variations in the

structure of the whole and rare taxa meiofaunal assemblages

(Table 3 A and B).

4. Discussion

4.1. Biochemical signatures of benthic eutrophication

The variables used so far for the analysis of marine ecosystems’

trophic status (e.g., nutrient concentrations, phytoplankton

biomass) are typically determined only in the water column, even

although the detrimental effects of eutrophication and dystrophic

(anoxic) events often begin and develop in the benthic domain

(Moodley et al., 2001). There is also evidence that differences in the

trophic conditions of surface waters do not necessarily match the

trophic conditions of the sea bottom even in coastal shallow waters

(Dell’Anno et al., 2002). Therefore, there is a strong need of iden-

tifying new and integrated descriptors of the trophic status of

benthic marine systems, where the eutrophication process is

primed and determines the worst effects. This can be pursued

effectively if we search for in situ variables related to the direct

consequences of eutrophication, rather than limiting our search

simply to potential precursor variables (e.g., inorganic nutrients in

the water column).

Primary production export, lateral advection of detrital C and in

situ organic C production are spatially and temporally integrated by

sediment records. In fact, the benthic domain, being a sink for

organic matter, acts as a “recorder” of processes occurring in the

entire ecosystem, at least when shallow water systems are

considered (Graf, 1992; Cornwell et al., 1996; Danovaro et al., 1999;

Pusceddu et al., 2009).

In all marine ecosystems, the largest fraction of organic matter

in the sediment is accounted for by organic detritus (i.e., non-living

organic material, Velimirov, 1991; Wetzel, 1991), which is often

represent by a dominant refractory fraction (Pusceddu et al., 2003,

2009). In fact, the response of consumers to increased organic

matter supply (i.e., the trophic response) is influenced more by

organic matter quality (e.g., bioavailability) rather than by bulkFig. 5. Meiofaunal abundance in the sediments of the two investigated regions,

transects and stations. Displayed are average & standard deviation.

Fig. 6. Richness of meiofaunal taxa in the sediments of the two investigated regions,

transects and stations. Displayed are average & standard deviation.

Fig. 4. Relationship between biopolymeric C and phytopigment sediment contents (A)

and between biopolymeric C concentration and its autotrophic fraction (B).

A. Pusceddu et al. / Estuarine, Coastal and Shelf Science 93 (2011) 420e430 425

concentration in the ecosystem (Cebrián et al., 1998; Huxel, 1999).

Thus, the assessment of the trophic status needs to be extended to

a more comprehensive description of the organic matter available

for heterotrophic nutrition, and should include descriptors of the

quantity and bioavailability of all (including detrital) resources

(Grall and Chauvaud, 2002; Pusceddu et al., 2009).

Previous studies demonstrated that biopolymeric C concentra-

tions in marine sediments are variably related with the inputs of

primary production (Dell’Anno et al., 2002; Pusceddu et al., 2000,

2009, 2010; Mincks et al., 2005; Dell’Anno et al., 2008; Bianchelli

et al., 2008). We show here that the quantity and biochemical

composition of sediment organic matter are highly responsive to

differences in the overall productivity of the investigated ecosys-

tems and that these changes are reflected at different spatial scales

(i.e., transects in the same region and stations along the coast-to-

offshore transects). The proved ability of the tested benthic vari-

ables and parameters to discriminate stations with putatively

different trophic conditions in the water column allowed us also to

investigate the relationships between the detrital and algal frac-

tions of sediment organic matter on the largest spatial scale (i.e.,

between regions).

Table 2

Dissimilarity in meiofaunal communities composition between different regions and transects within the same region for the entire meiofaunal assemblage and that of the

meiofaunal rare taxa (*** ¼P < 0.001, ** ¼P < 0.01, * ¼P < 0.05, ns ¼ not significant).

Total meiofaunal assemblage Rare taxa

ANOSIM SIMPER ANOSIM SIMPER

R P Average dissimilarity % R P Average dissimilarity %

Regions Veneto vs. Campania 0.059 ** 40.3 0.097 ** 81.9

Transects Veneto 1 vs. 2 0.046 ns 24.1 0.209 * 61.4

1 vs. 3 0.207 * 42.4 0.147 ns 66.9

1 vs. 4 0.028 ns 29.7 0.16 ns 71.8

1 vs. 5 0.056 ns 25.9 0.293 ** 76.1

2 vs. 3 0.195 * 39.9 0.325 ** 62.0

2 vs. 4 0.033 ns 28.2 0.436 ** 72.4

2 vs. 5 0.064 ns 28.4 0.424 ** 72.6

3 vs. 4 0.018 ns 39.1 0.203 * 70.8

3 vs. 5 0.147 ns 44.2 0.232 * 72.3

4 vs. 5 0.019 ns 33.5 0.454 *** 83.0

Campania 6 vs. 7 0.369 *** 32.8 0.527 *** 85.6

6 vs. 8 0.119 ns 30.3 0.664 *** 82.6

6 vs. 9 0.240 ** 66.7 0.517 *** 94.7

6 vs. 10 0.342 ** 39.1 0.588 *** 80.2

7 vs. 8 0.032 ns 24.3 0.254 ** 77.0

7 vs. 9 0.241 ** 63.8 0.324 ** 88.5

7 vs. 10 0.009 ns 23.8 0.206 ns 73.9

8 vs. 9 0.213 * 65.1 0.344 ** 88.0

8 vs. 10 0.065 ns 30.9 0.146 * 69.1

9 vs. 10 0.225 ** 66.5 0.404 ** 89.9

Fig. 7. Output of the nMDS carried out on (A) the whole meiofaunal and (B) the rare

taxa assemblages.

Table 3

Results of the multivariate multiple regression analysis carried out on the (A)

meiofaunal abundance and richness of taxa and (B) taxonomic composition. %

Var ¼ percentage of explained variance (SS ¼ sum of squares; F ¼ F statistic;

P ¼ probability level; ** ¼P < 0.001; * ¼P < 0.05; ns ¼ not significant).

A Variable SS (Trace) F P Var % Cumulative %

Protein 20002.6 26.0 ** 22.8 22.8

Algal fraction of BPC 7837.4 11.4 ** 8.9 31.8

Biopolymeric C 6402.8 10.3 ** 7.3 39.1

Chlorophyll-a 3113.8 5.3 * 3.6 42.6

Phaeopigment 975.5 1.7 ns 1.1 45.7

Lipid 834.4 1.4 ns 1.0 43.6

Total phytopigment 840.7 1.4 ns 1.0 44.5

Carbohydrate 580.1 1.0 ns 0.7 46.3

B Variable SS (Trace) pseudo-F P Var % Cumulative %

Protein 17182.2 19.4 ** 18.1 18.1

Algal fraction of BPC 7863.5 9.7 ** 8.3 26.3

Biopolymeric C 5825.4 7.8 ** 6.1 32.4

Chlorophyll-a 2636.9 3.6 * 2.8 35.2

Phaeopigment 1604.3 2.3 ns 1.7 39.4

Lipid 1428.6 2.0 ns 1.5 36.7

Total phytopigment 1002.7 1.4 ns 1.1 37.7

Carbohydrate 778.7 1.1 ns 0.8 40.3

A. Pusceddu et al. / Estuarine, Coastal and Shelf Science 93 (2011) 420e430426

Corroborating previous findings (Pusceddu et al., 2009), our

results pointed out that, in shallow coastal ecosystems, bio-

polymeric C is closely dependent on the inputs of fresh algal

material. However, since the determination of phytopigments in

the sediment does not allow discriminating between inputs from

the water column and microphytobenthic biomass, this result does

not provide any information on the actual significance of in situ

primary productivity vs. the export from the water column.

In the investigated sediments, the contribution of primary

organic matter (as total phytopigment C equivalents) to bio-

polymeric C was 4e34%, indicating that the investigated systems

were largely dominated (66e96%) by organic matter detrital or

heterotrophic in nature. The comparison among benthic systems

characterized by diverse primary producers and different produc-

tivities (including systems receiving huge terrestrial inputs such as

in the transect facing the Po and the Sarno Rivers in the Veneto and

Campania regions, respectively) clearly showed that increasing

biopolymeric C concentrations in the sediment are associated with

decreasing fractions of freshly produced algal material. This result

is consistent with a recent study that demonstrated such a rela-

tionship to occur on a global ocean scale (Pusceddu et al., 2009) and

indicates that systems characterised by increasing biopolymeric C

content are increasingly dominated by an accumulation of organic

matter of detrital (i.e., non-living) or heterotrophic (i.e., non-algal)

material. This relationship confirms that the eutrophication process

cannot be simply viewed as the result of enhanced inputs from

primary production, but further as an exacerbated alteration of

benthic C cycling linked to the accumulation of detrital organic

matter and associated benthic metabolism (Viaroli and Christian,

2003).

The nMDS analysis including all transects revealed that values

along the transect 9 of the Campania region were extremely

different from those encountered in all other transects (Fig. S2).

Thus the analysis was repeated after the stations of this transect

were removed. This new plot revealed that the biopolymeric C

sediment contents and the algal fractions of biopolymeric C

displayed opposite patterns (Fig. S3). By means of an additional

cluster analysis that was carried out including only the values of the

biopolymeric C concentrations and the percentage of its algal

fraction, we identified preliminary threshold levels of these two

descriptors for oligo-, meso- and eutrophic benthic systems (Fig. 8).

The issue of assessing threshold levels of organic C accumulation in

the sediment over which eutrophication determines undesired

ecosystem consequences still remains a difficult task (Nixon, 1995;

Pusceddu et al., 2009). However, our results provide evidence that

the analysis of the quantity and biochemical composition of bio-

polymeric C in marine sediments has the same potential as the

measurement of other predictive variables such as primary

production. Although our approach allowed us gathering a tool able

to discriminate quantitatively and qualitatively the trophic status of

sediments beneath aquatic systems characterized by putatively

different primary production levels, these results can be extrapo-

lated ex abrupto to other Mediterranean Sea coastal marine

ecosystems with much caution.

4.2. Meiofaunal communities associated with different benthic

trophic conditions

Meiofauna are highly sensitive to changes in environmental

conditions, so that this component of metazoan benthos can

provide useful information also about the changes in ecosystems’

quality (Warwick, 1988; Kennedy and Jacoby, 1999; Mazzola et al.,

1999; Danovaro and Gambi, 2002; Sutherland et al., 2007; Gambi

et al., 2009; Mirto et al., 2010). Generally, previous studies repor-

ted reduced meiofaunal abundance and richness of taxa in envi-

ronments strongly enriched in organic loads (Gambi et al., 2009

and citations therein). However, most of those studies were

focused mostly on nematodes, copepods and polychaetes, due to

the fact that such taxa, among the meiofauna, are considered the

most ubiquitous and resistant to different environmental distur-

bances (Mazzola et al., 1999; Gambi et al., 2009). Here, we show

that the analysis of the abundance and diversity of the entire

Fig. 8. Output of the cluster analysis discriminating sampling stations on the basis of biopolymeric C concentration in the sediment and the percentage contribution of phyto-

pigments to BPC.

A. Pusceddu et al. / Estuarine, Coastal and Shelf Science 93 (2011) 420e430 427

meiofaunal assemblages associated to different trophic status can

provide more reliable and clear results if we focus on those taxa

representing <1% of the total meiofaunal abundance (i.e., rare taxa;

Bianchelli et al., 2010; Mirto et al., 2010; Gambi et al., 2010).

Differences in the taxonomic composition of the investigated

meiofaunal assemblages were observed at all the investigated

spatial scales: between regions, between transects within the same

region and between stations within the same transects. The results

of the non-metric multidimensional scaling conducted on the

whole meiofaunal communities indicated nematodes and cope-

pods as the major responsible for the observed dissimilarities

(24e87%). However, the general dominance of nematodes and

copepods in the meiobenthic communities may mask the changes

in the relative importance of the other meiofaunal taxa (Bianchelli

et al., 2010). When the nMDS was restricted to the rare meiofaunal

taxa, the dissimilarities between regions, transects within the same

region and stationswithin the same transect resultedmore evident,

and different assemblages of rare taxa resulted responsible of the

observed dissimilarities (45e99%). As a consequence, even if the

richness of meiofaunal taxa did not display significant differences

between regions or transects, the investigated regions and tran-

sects within the same region were characterized by different

meiofaunal assemblages, which varied according to the differences

in the trophic status of the sediments. In particular, wherever high

sediment contents of biopolymeric C (associated with low photo-

trophic fraction of biopolymeric C) were observed, decreases in

meiofaunal abundance and richness of taxawere also observed (i.e.,

in the sediments facing the Sarno river, transect 9). This suggests

that strong accumulation of biopolymeric organic carbon, mostly

accounted for by material of detrital/heterotrophic origin, may lead

to profound modification of sediment distinctive features (e.g.,

oxygen availability; Pusceddu et al., 2009), which could in turn

affect negatively the meiofaunal assemblages (Gambi et al., 2009).

This result is in good agreement with the early predictions of the

effects of organic enrichment on marine benthic communities

(Pearson and Rosenberg, 1978) and provides compelling evidence

thatmeiofauna are a descriptor for investigating patterns of benthic

eutrophication as reliable as macrofauna, but with the advantage of

more prompt responses to trophic status changes, because of their

shorter life cycle.

In the present study, the tight linkage between the benthic

trophic state and the meiofaunal assemblages was confirmed by

the multivariate multiple regression analysis, that showed that

variations in the taxonomic composition of the whole or rare taxa

meiofaunal assemblages were mostly driven by chlorophyll-a,

protein and biopolymeric C sediment contents as well as by the

algal fraction of biopolymeric C, which altogether explained about

43% of the total variance. This result suggests that the presence and/

or abundance of different combinations of rare meiofaunal taxa are

influenced by the trophic conditions of the sediment and, as such,

their study provides the same results as the investigation of the

whole meiofaunal assemblage. We therefore not only confirm that

meiofauna are a useful and reliable descriptor of the trophic state of

marine coastal sediments (Pusceddu et al., 2007a) but provide also

evidence that the analysis restricted to rare taxa, i.e. excluding

nematodes, copepods and polychaetes, could be sufficiently reli-

able to provide an adequate assessment of the quality of the benthic

environments under different trophic state conditions, with the

advantage of counting a much lesser number of individuals per

sample.

Although based on a limited data set and a limited array of

trophic conditions, our study corroborates other recent investiga-

tions which showed that the composition of the rare meiofaunal

assemblage can respond similarly or even more clearly to several

ecosystem changes at different spatial scales and water depths.

Bianchelli et al. (2010) investigated meiofaunal abundance and

the richness of taxa along bathymetric gradients (from the shelf

break down to ca. 5000-m depth) in six submarine canyons and five

adjacent open slopes of three deep-sea regions. They showed that

at large spatial scales, differences in deep-sea meiofaunal abun-

dance are controlled by the region- or habitat-specific topographic

features which play also a key role in the distribution of rare

meiofaunal taxa.

Mirto et al. (2010) investigated meiofaunal assemblages in two

habitats (seagrass meadows of Posidonia oceanica and non-

vegetated soft bottoms) comparing sites receiving faeces and

uneaten food pellets from fish farms to control sites. They report

that meiofaunal abundance typically responded positively to fish-

farm effluents in both habitats and showed that taxa disappear-

ing below the fish cages always included rare taxa.

Gambi et al. (2010) investigated the spatial distribution of

meiofaunal abundance and community structure from 476 sites of

the deep Mediterranean Sea. They report that the differences in the

meiofaunal assemblage were evident when dominating taxa

(nematodes, copepods and polychaetes) were excluded and that

some rare taxa showed a clearly exclusive preference for a specific

habitat or basin.

Our approach, which for the first time takes into consideration

not only proxies of primary production, but includes the

measurement of the detrital fractions of sediment organic matter

and the associated meiofaunal communities, allowed character-

izing systems with putatively trophic conditions in terms of both

biogeochemical and faunal aspects. However, we are aware that,

because of the low-resolution spatial and temporal scales adopted

in this study, further large field studies are needed to expand the

observed shifts in the quantity and biochemical composition of

sediment organic matter and in rare meiofaunal taxa composition

to broader geographical and trophic state assets.

Acknowledgements

This study has been carried out in the frame of the PR/1 Project,

funded by the Italian Ministry of the Environment (MATT) and

coordinated by the Italian Agency for the Protection of the Envi-

ronment (APAT) and the NITIDA programme (PRIN2003) funded by

the Italian Ministry of University and Research. We are indebted

with M. Armeni (Ancona, Italy) for help in sampling and sediment

organic matter analyses, Prof. Mark Elliott and an anonymous

referee for useful suggestions that indeed helped to improve an

earlier version of the manuscript.

Appendix. Supplementary data

Supplementary data related to this article can be found online at

doi:10.1016/j.ecss.2011.05.012.

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