at SciVerse ScienceDirect

Marine Environmental Research 85 (2013) 64e75

Contents lists available

Marine Environmental Research

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

The assessment of environmental pollution along the coast of Beibu Gulf,northern South China Sea: An integrated biomarker approach in the clamMeretrix meretrix

Fanping Meng*, Zhifeng Wang, Fenglian Cheng, Xiuping Du, Wenchao Fu, Qun Wang, Xiaoyan Yi,Yongfu Li, You ZhouKey Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Ocean University of China, Qingdao 266100, PR China

a r t i c l e i n f o

Article history:Received 28 October 2012Received in revised form21 January 2013Accepted 24 January 2013

Keywords:Meretrix meretrixBeibu GulfIntegrated biomarker responseEnvironmental monitoringBiomarkerMetalsPolychlorinated biphenylsSediment

* Corresponding author. College of EnvironmentOcean University of China, Songling Road 238,Tel./fax: þ86 532 66782875.

E-mail address: fanpingm@tom.com (F. Meng).

0141-1136/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.marenvres.2013.01.003

a b s t r a c t

The clam Meretrix meretrix was used as a biomonitor to implement an environmental monitoring pro-gram along the coast of Beibu Gulf in October 2011. This program not only analyzed biomarkers includingacetylcholinesterase, glutathione peroxidase, glutathione S-transferase, catalase and superoxide dis-mutase activities, total glutathione content and lipid peroxidation level in M. meretrix but also adopteda multi-biomarker approach e integrated biomarker response (IBR) to assess the environmental qualityin this ecosystem. In addition, the metal (Hg, As, Cu, Pb, Zn, Cd and Cr) and polychlorinated biphenyls(PCBs) content in the surface sediment at the study area were also measured. The results showed that IBRindex was able to distinguish a space trend between sampling sites with different degrees of anthro-pogenic environmental stress. Integrated contamination degree were displayed in the form of star plotsand compared to IBR plots. There was a visual consistency between the pollution level and IBR variation.Based on the results, it was proved that the IBR method coupled with chemical analysis was quite usefulfor the assessment of environmental pollution in the coastal system.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Since coastal and intertidal areas are very productive ecosystemswith a high biodiversity, such areas are considered to be of greatecologic and economic value (Costanza et al., 1997). However, theseregions are suffering high anthropogenic pressure caused by urbandevelopment, industrialization and tourism (Monserrat et al., 2007;Cravo et al., 2009). Traditionally speaking, assessment and mon-itoring about the state of coastal areas have been based on themeasurement related to the pollutant concentration in sediment orwater column to a large extent, but the effects of contaminants onthe marine organisms and even the marine ecology haven’t drawnmuch attention (Lehtonen et al., 2006a). With respect to thedetection of effects of pollutants on marine organisms, the pastdecades has witnessed dynamic development in the aspect of mo-lecular, biochemical, cytological, immunological and physiological

al Science and Engineering,Qingdao 266100, PR China.

All rights reserved.

techniques, i.e., the so-called biomarkers (Depledge et al., 1995;Cajaraville et al., 2000; Raftopoulou andDimitriadis, 2010). Recently,analyses of the biochemical effects have been successfully applied toa number of environmental monitoring programs all over theworld,such as the European BIOMAR Program and the pan-European BEEPproject (Narbonne et al., 1999; Lehtonen et al., 2006b).

Compared with the use of a single biomarker, the application ofa battery of biomarkers may bemore useful to evaluate the effects ofcontaminant exposure and to assess environmental stress at last(Aarab et al., 2004). Thus, the integration of the biomarker responseswith a certain stress index has been increasingly important for thecorrect evaluation on the health status of marine organisms and thecontamination degree in recent years (Cajaraville et al., 2000;Mooreet al., 2006). For this purpose, the IBR index, a simple graphicmethod using star plots as away to summarize biomarker responsesto a single value reflecting the level of environmental stress at eachsite, was developed by Beliaeff and Burgeot (2002). This index caneffectively integrate various combinations of biomarkers of generalhealth, toxic effects and exposure to specific contaminants (Broegand Lehtonen, 2006), which has been applied to field studies onmussels (Damiens et al., 2007; Gagné et al., 2008; Fernández et al.,2010; Minguez et al., 2012), fish (Oliveira et al., 2010; Pereira et al.,

F. Meng et al. / Marine Environmental Research 85 (2013) 64e75 65

2010; Li et al., 2011; Wang et al., 2011a) and crabs (Jebali et al.,2011a; Pereira et al., 2011).

Beibu Gulf is a semi-closed gulf lying in the north of South ChinaSea, with the widest part reaching 180 nautical miles, an averagedepth of around 38 m and the maximum depth which is less than100 m (Chen et al., 2009). As a result of an accelerated industriali-zation process and rapid population growth in the coastal region inthe past two decades, it consequently suffers many environmentalproblems (Xia et al., 2011). However, there have been few chemicaland ecological data available in this region up to now, especially theinformation onmetal and PCB level; nevertheless the metal and PCBpollution in the surface sediment and organisms at the intertidalzone has been reported (Xia et al., 2008; Zhou et al., 2012). Ac-cording to Marine Environmental Quality Bulletin for Beibu Gulf,metal and PCB pollution in this region has remarkably increased inrecent 10 years, which may cause significant and permanent dis-turbances for the coastal ecosystems (Xia et al., 2011; Wang et al.,2012).

One of the objectives of the present study therefore was toevaluate the responses of several biomarkers in Meretrix meretrix,a marine bivalve, to the environmental pollution along the coast ofBeibu Gulf. Bivalves have been widely used as biomonitors inenvironmental assessment and monitoring programs. Because bi-valves are suspension feeders, they can not only respond to pollu-tant exposure and clams in particular but also accumulate thebioavailable fraction of contaminants deriving from water andsediment (Nasci et al., 2000; Cravo et al., 2012). The calmM. meretrix has a widespread distribution in Beibu Gulf in bothestuarine and inshore marine environments so that it is of greatecological and economical importance (Wu et al., 2012). In addi-tion, this species has also been used as a biomonitor to assess metalpollution in Arabian Gulf and Bengal Bay (Sarkar et al., 2008;Alyahya et al., 2011). In China, studies that focus on measuring thecontent of metals and PCBs in the soft tissue of M. meretrix to carryout pollution assessment have also been reported (Chen et al.,2002; Yatawara et al., 2010). As far as we know, there have beenno published papers that center on biochemical responses in thisclam for biochemical monitoring programs so far.

Multiple biomarkers reflecting contaminant exposure and/oreffects were assessed in the present research. It has been shownthat biotransformation phase II enzymes glutathione S-transferase(GST) activity responds to organic pollutants, for instance, PCBs(Wang et al., 2011b). Antioxidant defense systems comprise anti-oxidant enzymes like superoxide dismutase (SOD), catalase (CAT)and glutathione peroxidase (GPx), as well as non-enzymatic anti-oxidants (e.g. total glutathione e GSHt), have been widely used asbiomarkers of contaminant mediated oxidative stress, finding thattheir induction reflects they have a specific response to variouscontaminants (van der Oost et al., 2003; Lu et al., 2010). As a non-specific response associated with the disruption in the lipid com-ponent of cellular membranes, which reflects exposure and toxicityto pollutants, lipid peroxidation (LPO) was also measured (Viarengoet al., 2007). Acetylcholinesterase (AChE) was determined as a bio-marker of neurotoxicity indicating the exposure to organo-phosphorus and carbamate insecticides as well as metals (Galganiand Bocquené, 1989; Mora et al., 1999).

The successful application of the biomarker approach to envi-ronmental assessment depends on appropriate selection of bothbiomarkers and target tissue. Several researchers have recom-mended that the gills and digestive glands in bivalves can be usedto test and validate its usefulness in field studies (Gagné et al.,2008; Fernández et al., 2012). Gills are considered to be animportant route for uptake, bioconcentration and excretion oftoxicants as well as a prime target of pollutants, because of thewidesurface area in contact with the external medium and the reduced

distance between internal and external media (Jebali et al., 2011b).In this study, the gill was regarded as a target tissue for biomarkerresponse monitoring for the reason that many researches showedthat it was more sensitive compared with other tissues in manykinds of bivalve species (Cossu et al., 1997; Geret et al., 2003) andconfirmed in our lab experiment for M. meretrix (data not shown).

In addition to the above objective, another objective of this studywas to use the IBR approach and star plot to assess the environmentstatus at the study area. Although the use of a battery of differentbiomarkers enables a variety of responses to be assessed, it does notcompletely replace the chemical approach (Cravo et al., 2009).Therefore, the contamination degree characterized by themetal andPCB contents in sediment was also measured and related to theresults of the IBR index so that we could establish a possible cor-relation between the distribution of pollutants and their biologicaleffects in this study. Environmental factors (biotic and abiotic, suchas condition index, temperature, salinity, pH, dissolved oxygen (DO)of the water) were incorporated in this assessment to interpret thedata properly. The results of this study would contribute to theassessment of contaminant-induced stress over a large spatial scalein the coastal environment of Beibu Gulf.

2. Materials and methods

2.1. Study area and sampling

Wild clams M. meretrix (shell length 4.0 � 0.5 cm) were col-lected by grab from eight sites along the coast of Beibu Gulf aroundthe period of low tide in October 2011 (Fig. 1). It was decided thatthe sampling period was two months after the reproductive season(May to July in Beibu Gulf), i.e., the time when a sufficient numberof mature and healthy clams could be easily gathered so that theinterference of reproductive cycle, age and other non-pollutingfactors could be avoided. The sampling sites, selected accordingto different environmental characteristics, were influenced by dif-ferent types of anthropogenic activities, which are shown in Table 1.In detail, site 1 (S1) located in a small semi-closed bay and near anaquaculture farm; site 2 (S2) was in front of the quay of a local smallfishing village; site 3 (S3) and site 7 (S7) were near the main har-bors of Beibu Gulf and close to several sources of industrial sewagedischarge and urban effluent; site 4 (S4) was in a small river estuaryand a port of a small town nearby; both site 5 (S5) and site 6 (S6)located in Qinzhou Bay, which were close to aquaculture industryand industrial inputs, respectively; and site 8 (S8) was in a naturalbay and characterized by no apparent pollution source so that itwas regarded as a reference site. The surface sediment (0e10 cm)was sampled at the same time.

The physicalechemical characterization of the water, includingtemperature, salinity, pH and DO, was determined in situ at eachsampling site by using a multiparametric probe YSI 556MPS.

Regarding each site, about 200 clams were collected andtransported to the laboratory in insulated boxes with ice inside forbiomarker analysis on the premise that they were alive. Themoment the sample arrived, the dissection of the bivalves wasperformed. For the analysis of seven biomarkers, the gill tissues ofM. meretrix were carefully cut with a scalpel. Then, the sampleswere immediately enclosed in aluminum foil and stored at �80 �Cbefore the analysis.

2.2. Chemical analysis and contamination degree

The chemical characterization of sediment was based on theconcentration of several trace metals (Hg, As, Cu, Pb, Zn, Cd and Cr)and PCBs. The metal form measured in sediment was total. For themetal analysis of each station, triplicate surface sediment samples

108° E 109° E 110° E

20.5° N

21.0° N

21.5° N

22.0° N

Fig. 1. Map of the sampling sites along the coast of Beibu Gulf.

F. Meng et al. / Marine Environmental Research 85 (2013) 64e7566

were collected and immediately placed in decontaminated high-density polyethylene bags. Meanwhile, with respect to the sam-ples for the organic analysis of each station, they were placed inclean brown glass bottles. After being transported to the laboratoryin a refrigerated container, the samples were frozen at �20 �Cbefore the analysis.

2.2.1. Metal analysisThe sample preparation, pretreatment and analysis were con-

ducted according to the Specification for Oceanographic Survey ofChina GB17378-2007. The sediment samples were dried in an ovenat 105 �C and sieved by a 0.096mmmesh so that the effects of grainsize on metal distribution could be minimized. Then, such drysamples (0.2 g) were digested in PTFE microwave digestion vesselswith 8 mL of an acid mixture composed of concentrated HNO3: HCl(3:1, v/v) by using a microwave furnace (CEM MARS 5, USA). Inaddition, the atomic absorption spectrophotometry (M6 Series,Thermo Scientific, USA), whichwas combinedwith flame for Cu, Pb,Zn, and Cr and a graphite furnace for Cd, was used to measurecopper, lead, zinc, cadmium and chromium concentrations. Addi-tionally, mercury and arsenic was measured in sediment by aquaregia digestion in the water bath and analyzed by cold vapor atomfluorescence spectrometry (AFS-920, Beijing Titan InstrumentsCo.). Analytical determinations in each sample were repeatedlycarried out three times and the quality assurance was checked byusing a standard reference material (GBW 07314) provided by the

Table 1Type of anthropogenic impacts at the selected areas along the coast of Beibu Gulf.

Site Longitude andlatitude

Area Type of anthropogenic impact

S1 109�54044.700E Liusha Bay Agricultural, rural wasters andaquaculture practices20�26000.300N

S2 109�42013.000E Jianghongcoast

Shipping and rural wasters21�02009.700N

S3 109�34056.200E Tieshan Port Shipping, industrial inputs andaquaculture practices21�33050.100N

S4 109�26056.600E Yingpan Port Shipping and rural wasters21�27028.400N

S5 108�42044.300E Qinzhou Bay Rural wasters and aquaculturepractices21�40001.200N

S6 108�41046.000E Qinzhou Bay Shipping and rural wasters21�42011.900N

S7 108�20021.100E FangchengPort

Shipping, urban wasters andindustrial inputs21�35024.800N

S8 108�18043.600E Moon Bay Natural bay, absence of knownpollution sources21�34016.200N

Second Institute of Oceanography, SOA, China. All metal concen-trations were expressed in the form of mg per kg of dry weight.

2.2.2. PCB analysisThe procedure for the extraction and cleanup of PCBs from

sediment was modified according to the EPA 8082method and ‘TheMonitoring Specifications of the Ocean Environment GB17378-2007’. All freeze-dried samples were sieved (0.180 mm), groundand homogenized. 20 g sediment samples were mixed with 4 ganhydrous sodium sulfate and extracted for 12 h by using 150mL ofn-hexane/acetone (1:1, v/v) mixture in a soxhlet apparatus. Theresultant extract was reduced to 1 mL after a rotary evaporation.Next, two glass columns composed of 10 g deactivated florisil wereutilized to perform cleanup. Target analytes were eluted from thefirst column by using 100 mL of dichloromethane/n-hexane(3:7, v/v) and concentrated to 0.5 mL. Then, the analytes passedthrough the second column by adopting 50 mL n-hexane and wasconcentrated to 1 mL. The volume of eluant was concentrated toapproximately 0.5 mL under a gentle stream of nitrogen and thensettled to 1 mL with n-hexane until the analysis.

A gas chromatograph (GC 2010 AF, Shimadzu, Japan) equippedwith a splitless injector and coupled to a 63Ni Electrical CaptureDetector (ECD) was used to analyze PCBs as individual congeners(PCB28, PCB52, PCB101, PCB138, PCB153, PCB180 and PCB194).Quantitation of PCBs was performed by using procedural blank anda matrix sample spiked with standards (ISO6468, Accustandard,USA). None of the target compounds were detected in the blanks. Inaddition, each sediment sample was analyzed in triplicate. All ofthe relative standard deviations (RSD) were in the scope of 2.6%e13.5%. The spiked recoveries for PCBs in the surface sedimentranged from 70% to 111%.

2.2.3. Contamination degreeThe contamination degree related to the seven metals and PCBs

was expressed by the contamination factor (Cf) and the con-tamination degree (Cd) (Pekey et al., 2004; Raj and Jayaprakash,2008). A contamination factor (Cf) which described the pollutionlevel of a given toxic substance in a certain site was proposed byHåkanson (1980) and calculated as follows.

Cf ¼ C0=Cn

Where C0 referred to the mean substance content and Cn was thereference value of the substance. In this work, we chose the localbackground value reported by Wang et al. (2012) for the Cf calcu-lation of metal pollutants and selected the reference value

F. Meng et al. / Marine Environmental Research 85 (2013) 64e75 67

proposed by Ren et al. (2007) for PCBs. The reference values were0.1109 mg kg�1, 15.5 mg kg�1, 27.1 mg kg�1, 20.1 mg kg�1,59.7 mg kg�1, 0.0608 mg kg�1, 73.3 mg kg�1 and 0.424 mg kg�1 forHg, As, Cu, Pb, Zn, Cd, Cr and PCBs, respectively. The contaminationdegree (Cd) was defined as the sum of all contamination factors fora given site. The Cf and Cd were classified into four groups, as shownin Table 2.The methodology and classification were developed byHåkanson based on eight parameters (Hg, As, Cu, Pb, Zn, Cd, Cr andPCBs) included in this study.

2.3. Biochemical analysis

The whole procedure was conducted at 4 �C. The samples of thegills from each sampling station were homogenized (1:4, w/v) inchilled TriseHCl buffer (20 mM pH 7.8) by a XHF-D hi-speed dis-persator (Ningbo Scientific Biotechnology, Ningbo, China). Next,homogenates were centrifuged at 6000 g at 4 �C for 15 min and thesupernatant was used to measure the concentration of total glu-tathione and thiobarbituric acid reactive substances (TBARS). As forantioxidant enzyme and acetylcholinesterase assays, the homoge-nates were centrifuged at 13,000 g at 4 �C for 15 min. Regardingeach biochemical measurement, gill tissues collected from 10 in-dividuals were pooled, with three replicate samples for each site.The male and female proportion was 1:1 to avoid the situation thatthe possible gender difference existing in biomarker responsewhich may interference assessment results. AChE activity wasmeasured according to the colorimetric method proposed byEllman et al. (1961). All determinations were quantified as nmolesacetylthiocholine hydrolyzed by every gram of protein per minute.GSHt (mmol g�1 protein) content was estimated as the sum ofreduced and oxidized glutathiones which were determined by thefluorimetric method put forward by Hissin and Hilf (1976). GPxactivity was measured by a modification method proposed byHafeman et al. (1974) and expressed as nmoles of GSH used by everymilligram of protein per minute. GST activity was quantified by themethod developed by Habig et al. (1974) and expressed asnmolmin�1 mg�1 protein. CATactivity was analyzed by utilizing themethod described by Aebi (1974) and measuring the decrease inabsorbance at 240 nm because of the hydrogen peroxide con-sumption. Additionally, SOD activity was assayed by the methodinterpreted by McCord and Fridovich (1969) and the absorption ofthe reduction in cytochrome c by O2

�generated by the xanthineoxidase/hypoxanthine system at 550 nmwasmeasured as well. CATactivity was expressed as U g�1 of total protein concentration, whileSOD activity was expressed as Umg�1of total protein concentration.LPO was quantified in terms of TBARS (nmol mg�1 protein) by themethod described by Buege and Aust (1978). Protein concentrationwas measured spectrophotometrically by the method developed byBradford (1976) and consulting bovine serum albumin as a standard.

2.4. Condition index (CI)

To assess the physiological state of the organisms, the conditionindex (CI; not unit-based) which was equivalent to the ratio of

Table 2Terminology used to describe the contamination factor (Cf) and the contaminationdegree (Cd) as suggested by Håkanson (1980).

Cf Contaminationdegree

Cd Contaminationdegree

Cf < 1 Low Cd < 8 Low1 � Cf < 3 Moderate 8 � Cd < 16 Moderate3 � Cf < 6 Considerable 16 � Cd < 32 ConsiderableCf � 6 Very high Cd � 32 Very high

lyophilized dryweight of the soft tissues (g) to the dryweight of theshell (g) was measured for each pool consisted of 10 individuals(Moschino and Marin, 2006). Dry weight of soft tissues and shellswere obtained at �40 �C during a maximum period of 48 h untiltheir constant weight was achieved.

2.5. IBR index calculation

IBR was applied to each site by combining with the responses ofthe seven biomarkers in clam gills (AChE, GSHt, GPx, GST, CAT, SODand TBARS) according to Beliaeff and Burgeot (2002).

Firstly, data was standardized. After this, the scores of all thebiomarkers at a given station were expressed in the form of starplots. The basis of the data processing of each biomarker was brieflydescribed as follows. (1) Calculation of the mean and standarddeviation (SD) for each station. (2) Standardization of the data foreach station: Y ¼ (X � m)/S, where Y was the standardized value ofthe biomarker, X referred to the mean value of a biomarker fromeach station, m represented the mean value of the biomarker cal-culated for all the sites, and S stood for the standard deviationcalculated for the station-specific values of each biomarker. (3) Byusing standardized data, Zwas computed as Z¼þYor Z¼�Yon thecondition that the biomarker responds to contamination by acti-vation or inhibition, respectively. In this study, since it was expec-ted that GSHt, GPx, GST, CAT, SOD and TBARS would increase inresponse to environmental insult whereas AChE would decrease,the inverse values of the latter were used for calculations. Then, theminimumvalue (min) of Z for all stationwas obtained and the score(B) for a given station was computed in the equation B ¼ Z þ jminj,where B � 0 and jminj was an absolute value.

The seven selected biomarkers were introduced to the IBR cal-culation. The respective seven scores for each station (B1eB7) wereexpressed in the form of star plots. The IBR index for each stationwas calculated as the area of the star plot where the scores weredisplayed:

IBR ¼Xn

i¼1

Ai

where Ai represented the triangular area represented by two con-secutive biomarker scores (Bi, Biþ1) on the star plot, and n stood forthe number of biomarkers used in the IBR calculation. Since dif-ferent biomarker arrangements on the star plots generated differ-ent IBR values (Broeg and Lehtonen, 2006), biomarkers wereorderly represented in the seven axes of star plots according to theirability to distinguish non-impacted sites from impacted ones(Beliaeff and Burgeot, 2002), which was evaluated as discriminatepower in accordance with the calculation procedure described byNarbonne et al. (2005).

2.6. Statistical analysis

All data were expressed as mean � standard deviation (SD;n ¼ 3) and tested for normality and homogeneity of variance tocheck whether they meet statistical demands. For the imple-mentation of statistical analyses, the SPSS statistical package (ver.17.0, SPSS Co., USA) was adopted. At the same time, the variation ofeach biomarker was tested by one-way analysis of variance(ANOVA) procedure. When significant differences were found,post-hoc comparison tests for means were carried out by usingTurkey or GameseHowell test to determine which values differedsignificantly. Statistical significance was defined at P < 0.05. Pear-son’s correlation analysis was performed in order to verify therelationship among IBR values, contamination degree, biomarkers,

Table 3Environmental parameters measured in water and condition index values forM. meretrix collected from eight sites along the coast of Beibu Gulf. T e temperature,S e salinity, DO e dissolved oxygen, CI e condition index (mean � standard devi-ation; n ¼ 5 for T, S, pH and DO, n ¼ 10 for CI).

Site T (�C) S pH DO (%) CI

S1 25.2 � 0.3 27.9 � 0.5 7.8 � 0.2 73 � 6.6 9.7 � 0.5S2 24.2 � 0.2 29.7 � 0.6 8.0 � 0.1 115 � 7.5 11.4 � 1.2S3 27.5 � 0.4 30.6 � 0.3 8.2 � 0.3 126 � 10.2 9.8 � 0.9S4 27.2 � 0.1 30.4 � 0.2 8.0 � 0.2 85 � 5.8 9.9 � 1.4S5 26.4 � 0.2 28.8 � 0.2 7.9 � 0.3 94 � 8.1 11.1 � 2.1S6 26.1 � 0.1 28.7 � 0.5 8.1 � 0.1 92 � 6.0 11.3 � 0.8S7 27.1 � 0.3 29.9 � 0.7 7.9 � 0.4 88 � 11.3 9.5 � 1.7S8 25.5 � 0.5 30.8 � 0.2 8.1 � 0.2 131 � 4.8 12.3 � 0.7

Fig. 2. Mean concentrations of PCBs in surface sediments at eight sites along the coastof Beibu Gulf (n ¼ 3).

F. Meng et al. / Marine Environmental Research 85 (2013) 64e7568

pollutants and environmental parameters. Additionally, Excelsoftware (Microsoft, WA, USA) was used to obtain the star plots.

3. Results

3.1. Environmental parameters and condition index

The water features measured at each site are presented inTable 3. It could be found that the routine physicochemical pa-rameters of water at different sites did not change significantlyexcept DO. The temperature ranged from 24.2 (S2) to 27.5 �C (S3)and the salinity ranged from 27.9 (S1) to 30.8 (S8). The pH variedslightly among sites, ranging between 7.8 (S1) and 8.2 (S3). How-ever, the percentage of DO varied considerably among such sites,with the highest level in S8 (131%) and the lowest level in S1 (73%).

Being similar to the environmental parameters, the CI ofM. meretrix sampled at different sites also varied slightly and itsvalue ranged from 9.5% to 12.3% (Table 3). The highest CI was inclams collected in the reference site (S8), while the lowest valuewas found in S7.

3.2. Spatial distribution of pollutants and contamination degree

The mean concentration of metals and total PCBs in the surfacesediment at each site are depicted in Table 4. Seven metals (Hg, As,Cu, Pb, Zn, Cd and Cr) in sediment were measured. The concen-tration of Hg ranged from 0.008 (S8) to 0.109 (S4) mg kg�1, As from1.81 (S3) to 8.67 (S7) mg kg�1, Cu from 3.13 (S3) to 113.69(S4)mg kg�1, Pb from 13.68 (S3) to 65.30 (S7) mg kg�1, Zn from 6.99(S3) to 136.44 (S4) mg kg�1, Cd from 0.069 (S8) to 0.357(S7) mg kg�1, and Cr from 6.24 (S5) to 24.38 (S1) mg kg�1. Sedimentderiving from sites 1, 4 and 7 had generally higher metal concen-tration than that from the other sites, while S2, S3 and the referencesite (S8) showed lower levels of metal content. In addition, similarmoderate level was found in S5 and S6.

Total PCB concentration ranged from 0.69 (S4) to 6.54(S3) mg kg�1 dry weight. Seven congeners of PCBs were measured,whose results are displayed in Fig. 2. With respect to the sediment

Table 4Heavy metal contents and concentrations of total PCBs (mean values � standard deviatiosurface sediments at eight sites along the coast of Beibu Gulf.

Site Hg As Cu Pb

S1 0.107 � 0.002 5.96 � 0.59 60.79 � 0.37 36.58 � 1.82S2 0.061 � 0.002 2.30 � 0.35 4.74 � 0.83 14.69 � 3.15S3 0.061 � 0.004 1.81 � 0.20 3.13 � 0.40 13.68 � 3.85S4 0.109 � 0.002 4.00 � 0.20 113.69 � 8.40 64.69 � 3.96S5 0.079 � 0.002 8.51 � 0.28 8.62 � 0.81 23.47 � 4.58S6 0.075 � 0.002 6.71 � 0.32 8.35 � 0.41 21.01 � 2.26S7 0.020 � 0.005 8.67 � 0.28 21.27 � 2.66 65.30 � 2.56S8 0.008 � 0.005 5.36 � 0.46 3.83 � 0.53 16.37 � 2.93

from sites 1, 2, 6 and 8, the predominant PCBs were lower chlori-nated biphenyls, and the sum of PCB28, PCB52 and PCB101 excee-ded 50% of the total PCBs, while the other sites were predominatedby higher chlorinated biphenyls (form 52.2% to 69.0%). The sedi-ment from Tieshan Port (S3) presented the highest total PCB con-centration (6.54 mg kg�1 dry weight), while the lower concentrationwas found in the sediments from Yingpan Port (S4), Qinzhou Bay(S5) and Fangcheng Port (S7) (0.69, 0.76 and 0.71 mg kg�1 dryweight, respectively); and the other four sites (S1, S2, S6 and S8)showed a moderate PCB concentration (from 1.20 to 1.91 mg kg�1

dry weight).The values about the contamination factor (Cf) and con-

tamination degree (Cd) of the eight sampling sites are shown inTable 5. According to the table, it can be found that PCBs and Cd hadthe largest Cf values, while the values of Hg, As and Cr were low atall sites. With respect to PCBs, it was classified that the surfacesediment was suffering considerable contamination in S1, S6 andS8 and a very high contamination degree in S3. As for Cd, thecontamination factor was also high and the sediment was consid-erably contaminated in S1, S4 and S7. It was the Cf value of thesetwo contaminants (PCBs and Cd) that contributed most to the Cdvalue at all sampling sites. For Cu, Pb and Zn, their contaminationfactors were between low and considerable in S1, while betweenmoderate and very high in S4 except Zn. In addition, Pb and Zn alsopresented high Cf values in S7. As a result, it could be concluded thatthe contamination degree of the eight pollutants existed in theorder of PCBs > Cd > Pb > Zn > Cu > Hg > As > Cr in the wholestudy area. For different sampling sites, the results indicated that Cdlevels of site 1, 4, 6 and 7 reached up to moderate contaminationdegree, site 3 presented considerable contamination degree, whilethe other sites had low Cd values. The average Cd value for allsampling sites was 11.81, which indicated a moderate con-tamination degree according to Håkanson’s classification.

n, n ¼ 3; mg kg�1 dry weight for heavy metals and mg kg�1 dry weight for PCBs) in

Zn Cd Cr PCBs

123.01 � 1.84 0.267 � 0.005 24.38 � 1.48 1.48 � 0.0813.05 � 1.28 0.073 � 0.016 7.93 � 1.18 1.20 � 0.216.99 � 0.57 0.098 � 0.015 6.84 � 0.47 6.54 � 0.48

136.44 � 5.34 0.187 � 0.045 18.80 � 1.96 0.69 � 0.0833.04 � 1.56 0.101 � 0.008 6.24 � 0.27 0.76 � 0.0834.93 � 0.53 0.126 � 0.002 7.82 � 0.82 1.91 � 0.05

112.57 � 4.81 0.357 � 0.093 8.41 � 1.18 0.71 � 0.0238.44 � 0.65 0.069 � 0.003 6.37 � 0.94 1.71 � 0.23

Table 5Contamination factors (Cf) and contamination degree (Cd) of surface sediments at eight sites along the coast of Beibu Gulf.

Site Cf Cd Contaminationdegree

Hg As Cu Pb Zn Cd Cr PCBs

S1 0.97 0.39 2.24 1.82 2.06 4.39 0.33 3.49 15.69 ModerateS2 0.55 0.15 0.18 0.73 0.22 1.20 0.11 2.83 5.97 LowS3 0.55 0.12 0.12 0.68 0.12 1.61 0.09 15.43 18.72 ConsiderableS4 0.98 0.26 4.20 3.22 2.29 3.08 0.26 1.63 15.92 ModerateS5 0.71 0.55 0.32 1.17 0.55 1.66 0.09 1.79 6.84 LowS6 0.68 0.43 0.31 1.05 0.59 2.07 0.11 4.51 9.75 ModerateS7 0.18 0.56 0.79 3.25 1.89 5.87 0.12 1.68 14.34 ModerateS8 0.07 0.35 0.14 0.81 0.64 1.14 0.09 4.03 7.27 LowMean 0.59 0.35 1.04 1.59 1.05 2.63 0.15 4.42 11.81 Moderate

F. Meng et al. / Marine Environmental Research 85 (2013) 64e75 69

3.3. Biomarker responses

GSHt content, AChE, GPx, GST, CAT, SOD activities and TBARSlevel in gills ofM. meretrix collected at the eight sites are presentedin Fig. 3. In general, the biomarker responses displayed a largerange of variation at different monitoring sites.

Considering the biomarkers individually, GSHt was significantlyhigher at S1, S3 and S6 compared with the reference site (S8),which ranged from 1.23 to 1.27 fold higher. AChE and GPx showeda similar pattern of response among the sampling sites as bothenzymes revealed higher activity in S3, S4, S5 and S6, comparedwith the reference site. Moreover, GPx activity in clam obtained atsite 2 and site 7 was significantly much lower than site 8. GSTpresented significantly higher activity at S4, S5 and S6 comparedwith the reference site, with highest GST activity was observed atS4, which was 2.00 fold higher than S8. CAT activity was sig-nificantly higher in clam collected at S1, S6 and S7, compared withthe reference site, which ranged from 1.22 to 1.56 fold higher. Thelowest CAT activity was found at S4, while the highest CAT valuewas shown at S7. SOD activity was presented significantly higher atS3, S5, S6 and S7 compared with the reference site. The highestSOD activity was also found at S7. TBARS presented a higher levelat S1, S2, S3 and S7 compared with the reference site, while itdisplayed the lowest content at S5, which was significantly lowerthan S8.

3.4. Integrated biomarker response (IBR)

The IBR index was applied to the seven biomarkers and indi-cated as star plots (Fig. 4A), which enabled it to visualize differencesamong such studied sites. Generally speaking, the IBR values spa-tially change markedly at different monitoring sites. IBR values forS2, S5 and the reference site (S8) were lower than those at theother sites. S3 located at Tieshan Port, showing the highest IBRvalue. According to this index, the rank of the site according tothe degree to which they were affected could be ordered asS3 > S7 > S6 > S1 > S4 > S5 > S8 > S2, which was nearly the sameas the order obtained in the aspect of contamination degree. Thestar plot for Cd is shown in Fig. 4B according to which we could findthere was a good consistency between Cd gradient of the sedimentand the IBR variation. The conclusion could also be proved bycorrelation analysis displayed in Table 6, which indicated a positivecorrelation between the two parameters (r ¼ 0.848, P < 0.01).However, single pollutant concentration was not correlated withthe IBR index significantly, although there was the largest corre-lation coefficient for PCBs (r¼ 0.610, P> 0.05) in all eight pollutantsand for Cd (r ¼ 0.426, P > 0.05) in metals. The transformed data ofall the studied biomarkers are presented as star plots for each site inFig. 4C. In view of the extent and shape of the gray area, it can befound that S2, S5 and S8 suffered less impacts but the other sitesshowed larger areas and site-specific shapes.

4. Discussion

In general, there were no significant changes in the routinephysicoechemical parameters of water and the CI of clams at dif-ferent sites along the Beibu Gulf apart from DO. However, thepollution profiles of metals and PCBs showed spatial variation, andit could be concluded that the contamination level varied remark-ably, as shown in Tables 4 and 5.

Some researches have shown that non-pollution factors liketemperature, salinity, pH and DO of the seawater have impacts onbiomarker responses, so it is necessary to try to avoid the distur-bances of these factors in environmental monitoring (Ringwoodand Keppler, 2002; Santovito et al., 2005; Menezes et al., 2006).As the sampling sites in this study had similar physicochemicalfeatures of seawater in aspects of temperature, salinity and pH etc.,it could prevent the biomarker responses of the clam from beingdisturbed by these environmental factors excessively. However, thedifference of DO among sites was significant, with the lowestcontent at S1. The reason for this might be that the condition of thehydrodynamic force was poor and the environmental pollutionwasserious at this site. Santovito et al. (2005) studied the responsefeatures of biomarkers of mussel (Mytilus galloprovincialis) at twosites with different DO features in Lagoon of Venice and they foundthat antioxidant enzyme activity had correlation with water DO.Nevertheless, in this research, the correlation analysis showed thatDO and the seven biomarkers had no significant correlation, whichimplied that the different in DO among different sites had no sig-nificant impacts on the biomarker responses of M. meretrix.

As an index indicating the health status of animals, the CI ismainly influenced by the nutritional and reproductive statusleading to weight variation and is generally in accordance with thetrophic characteristics of the sampling sites (Tsangaris et al., 2011).In this research, the CI value of each station was similar, with thehigh value in the calms collected at S8, which not only indicatedthat the that food availability was higher at S8 compared to that atother sites but also stated that the reference site suffered few im-pacts of anthropogenic activities and its environmental quality wasrelatively good. At site 1, site 3, site 4 and site 7 where the inte-grated contamination degree was serious, CI values were low,which showed that the environmental pollution would have neg-ative impacts on the growth of organisms. In the transplanting testscarried out by Turja et al. (2013) for mussels (Mytilus trossulus) atGulf of Finland, they also found similar relationship between CI andchemical contaminant gradient so that they predicted that seriouspollution might have negative effects on the growth of individuals.

According to the measurement on the eight typical pollutants inthe sediment and the application of classic sediment quality eval-uation method to the assessment of the environmental pollution, itwas found that the result basically accord with the actual con-tamination degree at the local place. Among the four sites withthe highest Cd value, S3 became the site with the highest

S1 S2 S3 S4 S5 S6 S7 S80

15

30

45

60

ACC

D

ACBC

DE

AB

D

Sites

GS

Ht c

onte

nt

( µm

ol/g

pro

t)

S1 S2 S3 S4 S5 S6 S7 S80

2

4

6

8

AB

BC

D

CC

AA

C

Sites

AC

hE a

ctiv

ity

(nm

ol/m

in/m

g pr

ot)

S1 S2 S3 S4 S5 S6 S7 S80

7

14

21

28

B

A

D

C

D

CD

A

B

•

•

Sites

GP

x ac

tivi

ty

(nm

ol/m

in/m

g pr

ot)

S1 S2 S3 S4 S5 S6 S7 S80

150

300

450

600

BAB

CC

D

ABC

AB

Sites

ABG

ST

act

ivit

y (n

mol

/min

/mg

prot

)

S1 S2 S3 S4 S5 S6 S7 S80

25

50

75

100

B

D

C

B

A

BB

C

Sites

CA

T a

ctiv

ity

(U/g

pro

t)

S1 S2 S3 S4 S5 S6 S7 S80

20

40

60

80

A

D

C

BABC

C

AAB

Sites

SO

D a

ctii

vity

(U

/mg

prot

)

S1 S2 S3 S4 S5 S6 S7 S80

1

2

3

4

B

CDE

AB

A

BC

E

CDDE

Sites

TB

AR

S

(nm

ol/m

g pr

ot)

Fig. 3. Response of GSHt, AChE, GPx, GST, CAT, SOD and TBARS measured in gills of M. meretrix sampled at eight sites along the coast of Beibu Gulf in October 2011 (n ¼ 3). The barswith the same superscript are not significantly different (P > 0.05).

02468

10S1

S2

S3

S4

S5

S6

S7

S8

IBR

0

5

10

15

20S1

S2

S3

S4

S5

S6

S7

S8

Cd

0

1

2

3GPx

GST

CAT

AChESOD

LPO

GSHt

S1

0

1

2

3GPx

GST

CAT

AChESOD

LPO

GSHt

S2

0

1

2

3GPx

GST

CAT

AChESOD

LPO

GSHt

S3

0

1

2

3GPx

GST

CAT

AChESOD

LPO

GSHt

S4

0

1

2

3GPx

GST

CAT

AChESOD

LPO

GSHt

S5

0

1

2

3GPx

GST

CAT

AChESOD

LPO

GSHt

S6

0

1

2

3GPx

GST

CAT

AChESOD

LPO

GSHt

S7

0

1

2

3GPx

GST

CAT

AChESOD

LPO

GSHt

S8

(A) (B)

(C)

Fig. 4. Star plots of integrated biomarker response (IBR), contamination degree (Cd) and biomarkers. A, IBR; B, Cd; C, biomarker star plots for each site. GPx, glutathione peroxidase;GST, glutathione S-transferase; CAT, catalase; AChE, acetylcholinesterase; SOD, superoxide dismutase; LPO, lipid peroxidation; GSHt, total glutathione.

F. Meng et al. / Marine Environmental Research 85 (2013) 64e75 71

contamination degree due to it had high PCB content, while thepollution level at S2, S4 and S7 also reached the moderate levelbecause the metal content was high. S1 was situated at the inlet ofa semi-closed bay where the condition of the hydrodynamic forcewas poor as well as the long-term rural wastewater which had notbeen dealt with and the discharge from small-scale industries wereapparent so that the metal concentration in sediment at this sitewas increased (Zhang et al., 2011a). S4 was located at an estuarywhere there was a medium-sized dockyard at Yingpan Townnearby and sewage disposal from the metallurgy activities at theupstream of the river (Xia et al., 2008), so many sources of metalpollution caused serious stress for this site. S7 was at FangchengPort, one of the three great ports in Guangxi Province. According tofield investigations, it was found that there were a number of e-waste recycling corporations on the shore of the site, which gen-erated and discharged a great deal of tail water withmetals into thegulf so that such metals deposited in sediment and caused highpressure for organisms (Tang et al., 2010). In accordance with thedata about S3, it was shown that, although the metal content in thesediment at this site was quite low, its PCB content was the highestso that its contamination degree was considerable in general. At thesame time, based on the analysis of the various congeners of PCBs, it

Table 6Pearson’s correlation coefficient (r) between the IBR values, contaminant concentrations inof Beibu Gulf (**P < 0.01).

Hg As Cu Pb Zn

IBR 0.161 �0.079 0.117 0.249 0.178

was found that hepta-PCB and octa-PCB were the prevailing ho-mologues at this site. In consideration of the situation that themajor congeners produced and used in China was tri-PCB and thentetra-PCB, the appearance of this site with abundant higherchlorinated biphenyls implied that there might be a source ofpollution nearby (Sprovieri et al., 2007; Yang et al., 2009). Ac-cording to field investigations, there was a Tieshan Port which wasa busy oil wharf near the site and a great many of petroleumrefining industries on the shore, which were proved to be majorsources of PCB pollution by some reports (Chen et al., 2011). For theclean site S8, although its PCB content reached considerable con-tamination, which made the Cd value of this site not be the lowestamong all the sites, the biomarkers of clam were not significantlyaffected by pollution and no induction or inhibition was found. Inaddition, CI value of organisms at this site was high, which sug-gested that the organisms at this site stayed at a quite healthy state,which was also proved by IBR evaluation.

A key problem about the sediment quality evaluation methodadopted in this research involved the selection of the backgroundvalue. In order to reflect the environmental characteristic in a spe-cific area, it’s not recommended to adopt the large-scale meanreference values but use the background value with strong zonality

sediments and contamination degree (Cd) of sediments at eight sites along the coast

Cd Cr PCBs Metal Cd

0.426 0.146 0.610 0.178 0.848**

F. Meng et al. / Marine Environmental Research 85 (2013) 64e7572

according to the study area (Wang et al., 2012; Zhao et al., 2012). Asfor metals, this research adopted the background value in localsediment. Compared to Sediment Quality Guidelines (SQGs)developed by NOAA (Long et al., 1995), the local background valuesof Hg, Cu, Pb, Zn and Cr were lower than the Effect range-low (ERL)(0.15 mg kg�1 for Hg, 34 mg kg�1 for Cu, 46.7 mg kg�1 for Pb,150 mg kg�1 for Zn, 81 mg kg�1 for Cr). Moreover, Cd value wasmuch lower than ERL (1.2 mg kg�1) and As was a little higher thanERL (8.2mg kg�1) while lower than the Effects range-median (ERM)(70 mg kg�1), which indicated that the background values of themetals at the local place had regional features. For PCBs, as it hadsimilar migration and distribution laws in sediment and soil andheld the same order of magnitudes in many researches as well asthere were insufficient information about the background value ofPCBs in the sediment of Beibu Gulf (Cornelissen et al., 2005; Nakataet al., 2005; Wang et al., 2011b), this study adopted the mean valueof samples for sites in Guangxi Province in the investigation onPCBs in Chinese soil, which was carried out by Ren et al. (2007). Thebackground value is much lower than the ERL (22.7 mg kg�1), whichindicated that few production and small usage amount of PCBs inthe Southwest of China caused light degree of the overall con-tamination, according with the research conclusion of Nakata et al.(2005) and Pan et al. (2010). The result showed the contaminationdegree in whole area of Beibu Gulf was moderate. Compared withother bays all over theworld (Table 7), the average Cd value in BeibuGulf was much lower than regions with developed industries andeconomy, such as _Izmit Bay in Turkey and the coast of Bengal Bay inthe southeast of India, and was a little lower than Qunzhou Bay inFujian, China, Jacarepaguá Lagoon in Brazil; while it was higherthan that at Yundang Lagoon in Xiamen, China.

As an enzymatic biomarker of neurotoxicity, AChE is responsiblefor the degradation of acetylcholine in the process of the trans-mission of an impulse in nervous tissue, whose activity is inhibitedby the presence of pesticides, such as organophosphorus com-pounds and carbamates, and some metals in mussels (Galgani andBocquené, 1989; Mora et al., 1999). In this study, this biomarker hadlower values at site 1 and site 7, where the metal pollution wasserious. However, site 2 and site 8 also exhibited AChE activity in-hibitions although they were relatively clean, which might beresulted from the clam that was exposed to diverse pesticides usedin the adjacent agricultural lands that run into Beibu Gulf in thetyphoon season (Ren et al., 2002). Moreover, it has been reportedthat AChE is directly affected by temperature (Dellali et al., 2001;Pfeifer et al., 2005). In this research, no significant correlation wasfound between this biomarker and temperature (P > 0.05) butdiscovered the lower AChE activity was at S1, S2 and S8, where thetemperature was also lower compared with other sites.

Exposure to hazardous chemical substances stimulates the for-mation of oxygen species (ROS) (Lima et al., 2007). In order to dealwith the potential oxidative damage ensued, antioxidative defensemechanisms were developed in the organisms and antioxidant

Table 7The contamination degree (Cd) in sediments of Beibu Gulf and other coastal areas.

Area Cd Reference

Range Mean

Quanzhou Bay (China) 11.3e18.0 14.5 Yu et al., 2010Xiamen Bay (China) 7.68e9.85 8.95 Chen et al., 2010Bengal Bay (India) 46.00e75.10 65.81 Raj and Jayaprakash,

2008_Izmit Bay (Turkey) 51.3e78.3 65.6 Pekey et al., 2004Jacarepaguá lagoon

(Brazil)e 17.58 Fernandes, 1997

Beibu Gulf (China) 5.97e18.72 11.81 This study

enzyme was usually induced. SOD catalyzes the transformation ofsuperoxide radicals to H2O2, which is subsequently degraded bytwo types of enzymes, that is, CAT and GPx (Kappus, 1985; Cossuet al., 1997). In addition, it is necessary to use GSH as a substrateand oxidize it into GSSG when GPx exerts its function. An increasedCAT activity has been reported in many kinds of marine inverte-brate species in response to high H2O2 levels, while the GPxpathway is preferred in lower intracellular H2O2 concentration(Orbea and Cajaraville, 2006). In this study, correlation analysesshowed that there was no significant correlation among bio-markers. However, the correlation coefficients also justified theconnection, such as the coefficients of SOD and CAT (r ¼ 0.515,P > 0.05) indicated that the two had cooperativity in the aspect offunctions and the coefficients of CAT and GPx (r ¼ �0.411, P > 0.05)indicated that the two had complementarity to a certain extent.This was obviously reflected in S7. Under the high pollution stress atthis site, both the SOD and CAT activity in the gill ofM. meretrixwashigh while the GPx activity was low, which showed that the gen-erated ROS had caused associated response of antioxidant enzymeand CAT played a major role in the process of decomposing high-concentration H2O2. Zhang et al. (2011b) studied the response ofantioxidant enzyme like SOD, CAT and GPx in grasshopper (Oxyachinensis) under Cd pollution stress and discovered the similarphenomenon.

The environmental stress would also lead to the generation oforganic hydroperoxides (ROOH), a species of ROS, which could bedecomposed by GPx and GST, consumed GSH and generate GSSGwith an oxidation state simultaneously (Richardson et al., 2008).The correlation analysis showed that GPx and GST had significantlypositive relationship (r ¼ 0.798, P < 0.05), which indicated theyplayed a cooperative role in the process of clearing ROOH. In thisstudy, the highest value of both GST and GPx appeared at S4, whichmight have relationship with the metal pollution stress at this sitesince several studies have shown that the exposure to metals couldlead to an increase in GST and GPx in bivalve gills (Canesi et al.,1999; Franco et al., 2006; Einsporn et al., 2009). Additionally, asa kind of phase II biotransformation enzyme, GST could also con-jugate xenobiotics and metabolites produced by phase I metabo-lism (Wang and Ballatori, 1998). The reason why the GST activity atS6 was high might be that the PCB content at this site was thesecond highest, since it had been reported that elevated GST ac-tivity in mussel gills responded to organic contamination numer-ous times (Turja et al., 2013).

In this research, no significant correlations were found betweenbiomarkers and pollutants. On the one hand, the reason for thismight be that the amount of contaminants were not high enough topromote clear and strong biomarker responses and/or biomarkersdid not give special responses to these pollutants. On the otherhand, other factors such as abiotic environmental factors mayimpact biomarker responses (Cravo et al., 2012). However, from theperspective of the contamination degree, the research showed thatGSHt and TBARS had significant correlation with Cd (r ¼ 0.746,P < 0.05; r ¼ 0.781, P < 0.05), which proved that the two bio-markers in this research tended to reflect the integrated con-tamination stress rather than reflect the influence of a certainpollutant only. GSH is involved in processes which are essentialfor the synthesis and degradation of proteins, formation of de-oxyribonucleotides, regulation of enzymes, and protection of cellsagainst ROS (Wang and Ballatori, 1998). Generally, oxidation con-sumption of GSH accompanied with the process of antioxidantdefense. When the organisms consume excessive GSH, they willinduce living organisms to generate more GSH as the adaptation tothe environmental stress, which causes an increase in the amountof total glutathione (van der Oost et al., 2003; Oliveira et al., 2009).At S3 and S6, there was high GPx and GST activity which made

F. Meng et al. / Marine Environmental Research 85 (2013) 64e75 73

a great deal of GSH be consumed and led to high requirements andas a consequence of a physiological adjustment involving the syn-thesis of new GSH (Dickinson et al., 2004). Being different from theantioxidant enzyme whose induction was just an indication ofexposure, TBARS gave indications on an actual damaging/toxic ef-fect and reflected the degree to which the organisms were dam-aged under the continuous stress of pollution and was usuallyaccompanied with the activity decrease of the oxidation stressbiomarker (Nita et al., 2001; Oliveira et al., 2009). In this research,the highest TBARS level was found at S3, which indicated that thehigh-concentration PCB contamination at this site had causedoxidative damage for organisms. Meanwhile, the GST and CAT ac-tivity at this site was low but the GPx and SOD activity was stillhigh, showing the antioxidant defense systems of the clam stillwork. At S1, the GSHt content and TBARS level were high, whichindicated that the pollution stress had exceeded the antioxidantdefense capacity of the organisms accompanied with more GSHsynthesis to repair damage.

The relevant choice of biomarkers is a key issue for the appli-cation of multi-biomarker approach to biological monitoring pro-grams. According to Broeg and Lehtonen (2006), when biomarkersare applied to IBR calculations, the selection of several parametersthat respond to the same type of pollution more or less will over-emphasize the importance of the presence or absence of certainclasses of pollutants in the overall stress assessment. Thus in thepresent study, we chose seven biomarkers according to the objec-tives andmain contaminants at the local place, including AChE, fourtypes of antioxidant enzyme and one non-enzymatic antioxidantin the antioxidant defense system as well as LPO which was anindicator of oxidative damage. The oxidative stress biomarkersincluding antioxidant enzyme, GSHt and LPO could reflect the in-tegrated contamination stress rather than respond to a certainpollutant specifically so that the overemphasis on a typical con-taminant can be avoided even if all of them are applied to IBRcalculation (van der Oost et al., 2003; Fernández et al., 2010; Turjaet al., 2013). Doing so, the IBR index enabled the level of stressamong sites to be distinguished, showing that S1, S3, S4 and S7where the contamination degree was serious had high IBR values.However, the contamination degree of S6 did not have consistencywith IBR evaluation results. The reason for this might be that higherPCB content caused serious contamination stress for organisms andthe clam at the site might also be affected by other undeterminedpollutants. In addition, fewer adverse biological effects were foundat S2, S5 and S8, where the concentrations of contaminants werelower and the health degree of the clam was favorable, which wasconsistent with the conclusions of the previous analyses.

The IBR index was regarded as a practical tool which could beapplied to examine the stress response of different populations bythe combination of different biomarkers and to compare the stresslevels related to pollution degree. Several studies which applieddifferent combinations of biomarkers to the IBR calculation showedthe consistency between IBR and certain pollutants (Broeg andLehtonen, 2006; Damiens et al., 2007; Pytharopoulou et al., 2008;Lu et al., 2010; Tsangaris et al., 2011; Wang et al., 2011a). In mussels(M. galloprovincialis) caged at an area polluted by metals in the Gulfof Patras (Greece), IBR showed the consistency with Cu concen-tration in the digestive gland (Pytharopoulou et al., 2008). Ingoldfish (Carassius auratus) transplanted in Taihou Lake (China), itwas found that there was a visual correlation between IBR and OCPgradient in sediment (Wang et al., 2011a). Although no similarphenomenon was found in this study, the similarity between Cd ofthe sediment and IBR star plot (Fig. 4) proved that IBR could reflectthe integrated pollution level. This also confirmed that the IBR indexbased on biomarkers of sensitive species could not only respond toa single pollutant but reflected the integrated environment stress in

such a large-scale marine environmental system with various con-taminants. Though a single pollutant had no significant correlationwith IBR, the correlation coefficients between IBR and Cd, PCBswerethe highest, which indicated that the higher the contaminationdegree of a certain contaminantwas, the higher pollution pressure itmay caused for organisms as shown by the IBR index.

On the whole, though it was difficult to explain the response ofa single biomarker in this research, the integrated environmentalstress reflected by IBR had consistency with the chemical methodsand the practical conditions at the local place, which proved theusefulness of IBR. However, the index still hasmany drawbacks, oneof which is the fact that all of the responses assume the sameimportance. Actually, the response of different biomarkers shouldhave different significance undoubtedly. Therefore, when the pro-cess of the IBR calculation is improved in future, it may be necessaryto design a process which will be standardized and weighted tohighlight the effects of biomarkers, which reflect the degree towhich organisms are damaged, for example, LPO. This is a difficultproblem which need be explored in the next step. In addition,different seasons should be taken into consideration in futurestudies because it is possible that toxic effects will be changed withthe natural characteristics of the water/sediment and the repro-ductive cycle or other parameters reflecting the physiological stressand these non-pollution factors usually have significant seasonalvariation.

5. Conclusions

In conclusion, the integration of the measurement of biologicaleffects and the chemical analysis of sediment suggested that stresslevels were overall correlated with the contamination degree.Consequently, the multi-biomarker approach could be adopted toassess the environmental pollution and interpret biomarkerresponse to both environmental managers and decision-makers.The IBR values had good consistency with the results of a classicchemical approach on the basis of the eight typical pollutants insediment. The evaluation results also confirmed the usefulness ofthe clam M. meretrix as a good candidate species for the studies onthe environmental monitoring programs about chemical mixturecontamination in a coastal region. The IBR index proved to bea useful tool for the assessment of contaminant-induced stress overa large spatial scale along the coastal environment of Beibu Gulf.

Acknowledgments

This work was financially supported by Ocean Public ServiceFoundation of China (No. 201005012-2). We gratefully acknowl-edge all the members of the Key Laboratory who participated in thecampaign. Special gratitude goes to Zhifeng Wang for his veryexcellent work during this study and article preparation. We sin-cerely thank Heng Hu and Xianglei Li for their assistance in thetissue preparation. Also, many thanks to the referees for theirencouraging comments and constructive criticisms which finallyimproved the work. For improving the style of the manuscript weare very thankful to Dr. Xiaoshan Zhu.

References

Aarab, N., Champeau, O., Mora, P., Daubeze, M., Garrigues, P., Narbonne, J.-F., 2004.Scoring approach based on fish biomarkers applied to French river monitoring.Biomarkers 9, 258e270.

Aebi, H., 1974. Catalase. In: Bergmeyer, H.U. (Ed.), Methods of Enzymatic Analysis.Chemic Academic Press Inc., Verlag, pp. 673e685.

Alyahya, H., El-Gendy, A.H., Farraj, S.A., El-Hedeny, M., 2011. Evaluation of heavymetal pollution in the Arabian Gulf using the clam Meretrix meretrix Linnaeus,1758. Water Air and Soil Pollution 214, 499e507.

F. Meng et al. / Marine Environmental Research 85 (2013) 64e7574

Beliaeff, B., Burgeot, T., 2002. Integrated biomarker response: a useful tool for eco-logical risk assessment. Environmental Toxicology and Chemistry 21,1316e1322.

Bradford, M.M., 1976. A rapid and sensitive method for the quantitation of micro-gram quantities of protein utilizing the principle of protein-dye binding. Ana-lytical Biochemistry 72, 248e254.

Broeg, K., Lehtonen, K.K., 2006. Indices for the assessment of environmental pol-lution of the Baltic Sea coasts: integrated assessment of a multi-biomarkerapproach. Marine Pollution Bulletin 53, 508e522.

Buege, J.A., Aust, S.D., 1978. Microsomal lipid peroxidation. Methods in Enzymology52, 302e310.

Cajaraville, M.P., Bebianno, M.J., Blasco, J., Porte, C., Sarasquete, C., Viarengo, A.,2000. The use of biomarkers to assess the impact of pollution in coastal envi-ronments of the Iberian Peninsula: a practical approach. The Science of theTotal Environment 247, 295e311.

Canesi, L., Viarengo, A., Leonzio, C., Filippelli, M., Gallo, G., 1999. Heavy metals andglutathione metabolism in mussel tissues. Aquatic Toxicology 46, 67e76.

Chen, C., Lu, Y., Hong, J., Ye,M.,Wang, Y., Lu, H., 2010.Metal andmetalloid contaminantavailability in Yundang Lagoon sediments, Xiamen Bay, China, after 20 yearscontinuous rehabilitation. Journal of Hazardous Materials 175, 1048e1055.

Chen, W., Zhang, L., Xu, L., Wang, X., Hong, L., Hong, H., 2002. Residue levels ofHCHs, DDTs and PCBs in shellfish from coastal areas of east Xiamen Island andMinjiang Estuary, China. Marine Pollution Bulletin 45, 385e390.

Chen, Z., Cai, W., Xu, S., Huang, Z., Qiu, Y., 2011. Risk assessment of coastal ecosystemin Beibu Gulf, Guangxi of South China. Chinese Journal of Applied Ecology 22(11), 2977e2986 (in Chinese with English abstract).

Chen, Z., Xu, S., Qiu, Y., Lin, Z., Lin, Z., Jia, X., 2009. Modeling the effects of fisherymanagement and marine protected areas on the Beibu Gulf using spatial eco-system simulation. Fisheries Research 100, 222e229.

Cornelissen, G., Gustafsson, Ö., Bucheli, T.D., Jonker, M.T.O., Koelmans, A.A., vanNoort, P.C.M., 2005. Extensive sorptionof organic compounds toblack carbon, coal,and kerogen in sediments and soils: mechanisms and consequences for distri-bution, bioaccumulation. Environmental Science & Technology 39, 6881e6895.

Cossu, C., Doyotte, A., Jacquin, M.C., Babut, M., Exinger, A., Vasseur, P., 1997. Gluta-thione reductase, selenium-dependent glutathione peroxidase, glutathionelevels, and lipid peroxidation in freshwater bivalves, unio tumidus, as bio-markers of aquatic contamination in field studies. Ecotoxicology and Environ-mental Safety 38, 122e131.

Costanza, R., d’Arge, R., de Groot, R., Farber, S., Grasso, M., Hannon, B., Limburg, K.,Naeem, S., O’Neill, R.V., Paruelo, J., Raskin, R.G., Sutton, P., van den Belt, M., 1997.The value of the world’s ecosystem services and natural capital. Nature 287,253e260.

Cravo, A., Lopes, B., Serafim, Â., Company, R., Barreira, L., Gomes, T., Bebianno, M.J.,2009. A multibiomarker approach in Mytilus galloprovincialis to assess envi-ronmental quality. Journal of Environmental Monitoring 11, 1673e1686.

Cravo, A., Pereira, C., Gomes, T., Cardoso, C., Serafim, A., Almeida, C., Rocha, T.,Lopes, B., Company, R., Medeiros, A., Norberto, R., Pereira, R., Araújo, O.,Bebianno, M.J., 2012. A multibiomarker approach in the clam Ruditapes decus-satus to assess the impact of pollution in the Ria Formosa lagoon, South Coast ofPortugal. Marine Environmental Research 75, 23e34.

Damiens, G., Gnassia-Barelli, M., Loquès, F., Roméo, M., Salbert, V., 2007. Integratedbiomarker response index as a useful tool for environmental assessmentevaluated using transplanted mussels. Chemosphere 66, 574e583.

Dellali, M., Barelli, M.G., Romeo, M., Aissa, P., 2001. The use of acetylcholinesteraseactivity in Ruditapes decussatus and Mytilus galloprovincialis in the bio-monitoring of Bizerta lagoon. Comparative Biochemistry and Physiology, Part C130, 227e235.

Depledge, M.H., Aagaard, A., Györkös, P., 1995. Assessment of trace metal toxicityusing molecular, physiological and behavioural biomarkers. Marine PollutionBulletin 31, 19e27.

Dickinson, D.A., Levonen, A., Moellering, D.R., Arnold, E.K., Zhang, H., Darley-usmar, V.M., Forman, H.J., 2004. Human glutamate cysteine ligase gene regu-lation through the electrophile response element. Free Radical Biology &Medicine 37, 1152e1159.

Einsporn, S., Bressling, J., Koehler, A., 2009. Cellular localization of lead using anantibody-based detection system and enzyme activity changes in the gills anddigestive gland of the blue mussel Mytilus edulis. Environmental Toxicology andChemistry 28, 402e408.

Ellman, G.L., Courtney, K.D., Andres Jr., V., Featherstone, R.M., 1961. A new and rapidcolorimetric determination of acetylcholinesterase activity. Biochemical Phar-macology 7, 88e95.

Fernandes, H.M., 1997. Heavy metal distribution in sediments and ecological riskassessment: the role of diagenetic processes in reducing metal toxicity inbottom sediments. Environmental Pollution 97, 317e325.

Fernández, B., Albentosa, M., Viñas, L., Franco, A., González, J.J., Campillo, J.A., 2010.Integrated assessment of water quality of the Costa da Morte (Galicia, NWSpain) by means of mussel chemical, biochemical and physiological parameters.Ecotoxicology 19, 735e750.

Fernández, B., Campillo, J.A., Martínez-Gómez, C., Benedicto, J., 2012. Antioxidantresponses in gills of mussel (Mytilus galloprovincialis) as biomarkers of envi-ronmental stress along the Spanish Mediterranean coast. Aquatic Toxicology 99,186e197.

Franco, J.L., Trivella, D.B.B., Trevisan, R., Dinslaken, D.F., Marques, M.R.F.,Bainy, A.C.D., Dafre, A.L., 2006. Antioxidant status and stress proteins in the gillsof the brown mussel Perna perna exposed to zinc. Chemico-Biological In-teractions 160, 232e240.

Gagné, F., Burgeot, T., Hellou, J., St-Jean, S., Farcy, É., Blaise, C., 2008. Spatial varia-tions in biomarkers of Mytilus edulis mussels at four polluted regions spanningthe Northern Hemisphere. Environmental Research 107, 201e217.

Galgani, F., Bocquené, G., 1989. A method for routine detection of organophosphatesand carbamates in sea water. Environmental Technology Letters 10, 311e322.

Geret, F., Serafim, A., Bebianno, M.J., 2003. Antioxidant enzyme activities, metal-lothioneins and lipid peroxidation as biomarkers in Ruditapes decussatus?Ecotoxicology 12, 417e426.

Habig, W.H., Pabst, M.J., Jakoby, W.B., 1974. Glutathione S-transferases: the firstenzymatic step in mercapturic acid formation. Journal of Biological Chemistry249, 7130e7139.

Hafeman, D.G., Sunde, R.A., Hoekstra, W.G., 1974. Effect of dietary selenium onerythrocyte and liver glutathione peroxidase in the rat. Journal of Nutrition 104,580e587.

Håkanson, L., 1980. An ecological risk index for aquatic pollution control e a sed-imentological approach. Water Research 14, 975e1001.

Hissin, P.J., Hilf, R., 1976. A fluorometric method for determination of oxidized andreduced glutathione in tissues. Analytical Biochemistry 74, 214e226.

Jebali, J., Ben-Khedher, S., Ghedira, J., Kamel, N., Boussetta, H., 2011a. Integratedassessment of biochemical responses in Mediterranean crab (Carcinus maenas)collected from Monastir Bay, Tunisia. Journal of Environmental Sciences 23,1714e1720.

Jebali, J., Ben-Khedher, S., Kamel, N., Ghedira, J., Bouraoui, Z., Boussetta, H., 2011b.Characterization and evaluation of cholinesterase activity in the cockle Cera-stoderma glaucum. Aquatic Biology 13, 243e250.

Kappus, H., 1985. Lipid peroxidation: mechanisms, analysis, enzymology and bio-logical relevance. In: Sies, H. (Ed.), Oxidative Stress. Academic Press Inc., Lon-don, pp. 273e310.

Lehtonen, K.K., Leiniö, S., Schneider, R., Leivuori, M., 2006a. Biomarkers of pollutioneffects in the bivalves Mytilus edulis and Macoma balthica collected from thesoutherncoastof Finland (Baltic Sea).MarineEcologyProgress Series 322,155e168.

Lehtonen, K.K., Schiedek, D., Köhler, A., Lang, T., Vuorinen, P.J., Förlin, L., Bar�sien _e, J.,Pempkowiak, J., Gercken, J., 2006b. The BEEP project in the Baltic Sea: overviewof results and outline for a regional biological effects monitoring strategy.Marine Pollution Bulletin 53, 523e537.

Lima, I., Moreira, S.M., Osten, J.R., Soares, A.M.V.M., Guilhermino, L., 2007.Biochemical responses of the marine mussel Mytilus galloprovincialis to pet-rochemical environmental contamination along the north-western coast ofPortugal. Chemosphere 66, 1230e1242.

Li, Z.H., Zlabek, V., Turek, J., Velisek, J., Pulkrabova, J., Kolarova, J., Sudova, E.,Berankova, P., Hradkova, P., Hajslova, J., Randak, T., 2011. Evaluating environmentalimpact of STPs situated on streams in the Czech Republic: an integrated approachto biomonitoring the aquatic environment. Water Research 45, 1403e1413.

Long, E.R., Macdonald, D.D., Smith, S.L., Calder, F.D., 1995. Incidence of adversebiological effects within ranges of chemical concentrations in marine andestuarine sediments. Environmental Management 19, 81e97.

Lu, G.H., Ji, Y., Zhang, H.Z., Qin, J., Wang, C., 2010. Active biomonitoring of complexpollution in Taihu Lake with Carassius auratus. Chemosphere 79, 588e594.

McCord, J.M., Fridovich, I., 1969. Superoxide Dismutase: an enzymic function forerythrocuprein (hemocuprein). Journal of Biological Chemistry 244, 6049e6055.

Menezes, S., Soares, A.M.V.M., Guilhermino, L., Peck, M.R., 2006. Biomarkerresponses of the estuarine brown shrimp Crangoncrangon L. to non-toxicstressors: temperature, salinity and handling stress effects. Journal of Exper-imental Marine Biology and Ecology 335, 114e122.

Minguez, L., Buronfosse, T., Beisel, J., Giambérini, L., 2012. Parasitism can be a con-founding factor in assessing the response of zebra mussels to water con-tamination. Environmental Pollution 162, 234e240.

Monserrat, J.M., Martínez, P.E., Geracitano, L.A., Amado, L.L., Martins, C.M.G.,Pinho, G.L.L., Chaves, I.S., Ferreira-Cravo, M., Ventura-Lima, J., Bianchini, A.,2007. Pollution biomarkers in estuarine animals: critical review and new per-spectives. Comparative Biochemistry and Physiology, Part C 146, 221e234.

Moore, M.N., Allen, J.I., McVeigh, A., 2006. Environmental prognostics: an integratedmodel supporting lysosomal stress responses as predictive biomarkers of ani-mal health status. Marine Environmental Research 61, 278e304.

Mora, P., Fournier, D., Narbonne, J.-F., 1999. Cholinesterases from the marine mus-sels Mytilus galloprovincialis Lmk. and M. edulis L. and from the freshwaterbivalve Corbicula fluminea Müller. Comparative Biochemistry and Physiology,Part C 122, 353e361.

Moschino, V., Marin, M.G., 2006. Seasonal changes in physiological responses andevaluation of “well-being” in the venus clam Chamelea gallina from the NorthernAdriatic Sea. Comparative Biochemistry and Physiology, Part A 145, 433e440.

Nakata, H., Hirakawa, Y., Kawazoe, M., Nakabo, T., Arizono, K., Abe, S., Kitano, T.,Shimada, H., Watanabe, I., Li, W., Ding, X., 2005. Concentrations and composi-tions of organochlorine contaminants in sediments, soils, crustaceans, fishesand birds collected from Lake Tai, Hangzhou Bay and Shanghai city region,China. Environmental Pollution 133, 415e429.

Narbonne, J.F., Aarab, N., Clérandeau, C., Daubéze, M., Narbonne, J., Champeau, O.,Garrigues, P., 2005. Scale of classification based on biochemical markers inmussels: application to pollution monitoring in Mediterranean coasts andtemporal trends. Biomarkers 10, 58e71.

Narbonne, J.F., Mora, P., Michel, X., Budzinski, H., Garrigues, P., Lafaurie, M.,Salaun, J.P., Berge, J.B., Den Besten, P., Pagano, G., Porte, C., Livingstone, D.,Hansen, P.D., Herbert, A., 1999. Biological markers of environmental con-tamination in marine ecosystems: Biomar Project Coordinating Group. Journalof Toxicology: Toxin Reviews 18, 205e220.

F. Meng et al. / Marine Environmental Research 85 (2013) 64e75 75

Nasci, C., Da Ros, L., Nesto, N., Sperni, L., Passarini, F., Pavoni, B., 2000. Biochemicaland histochemical responses to environmental contaminants in clam, Tapesphilippinarum, transplanted to different polluted areas of Venice Lagoon, Italy.Marine Environmental Research 50, 425e430.

Nita, D.A., Nita, V., Spulber, S., Moldovan, M., Popa, D.P., Zagrean, A., Zagrean, L.,2001. Oxidative damage following cerebral ischemia depends on reperfusion e

a biochemical study in rat. Journal of Cellular and Molecular Medicine 5, 163e170.

Oliveira, M., Ahmad, I., Maria, V.L., Pacheco, M., Santos, M.A., 2010. Monitoringpollution of coastal lagoon using Liza aurata kidney oxidative stress and geneticendpoints: an integrated biomarker approach. Ecotoxicology 19, 643e653.

Oliveira, M., Maria, V.L., Ahmad, I., Serafim, A., Bebianno, M.J., Pacheco, M.,Santos, M.A., 2009. Contamination assessment of a coastal lagoon (Ria deAveiro, Portugal) using defence and damage biochemical indicators in gill ofLiza aurata e an integrated biomarker approach. Environmental Pollution 157,959e967.

Orbea, A., Cajaraville, M.P., 2006. Peroxisome proliferation and antioxidant enzymesin transplanted mussels of four Basque estuaries with different levels of poly-cyclic aromatic hydrocarbon and polychlorinated biphenyl pollution. Environ-mental Toxicology and Chemistry 25, 1616e1626.

Pan, J., Yang, Y., Geng, C., Yeung, L.W.Y., Cao, X., Dai, T., 2010. Polychlorinated bi-phenyls, polychlorinated dibenzo-p-dioxins and dibenzofurans in marine andlacustrine sediments from the Shandong Peninsula, China. Journal of HazardousMaterials 176, 274e279.

Pekey, H., Karakas, D., Ayberk, S., Tolun, L., Bako�glu, M., 2004. Ecological riskassessment using trace elements from surface sediments of _Izmit Bay (North-eastern Marmara Sea) Turkey. Marine Pollution Bulletin 48, 946e953.

Pereira, P., de Pablo, H., Subida, M.D., Vale, C., Pacheco, M., 2011. Bioaccumulationand biochemical markers in feral crab (Carcinus maenas) exposed to moderateenvironmental contaminationdthe impact of non-contamination-related var-iables. Environmental Toxicology 26, 524e540.

Pereira, P., de Pablo, H., Vale, C., Pacheco, M., 2010. Combined use of environmentaldata and biomarkers in fish (Liza aurata) inhabiting a eutrophic and metal-contaminated coastal system e gills reflect environmental contamination.Marine Environmental Research 69, 53e62.

Pfeifer, S., Schiedek, D., Dippner, J.W., 2005. Effect of temperature and salinity onacetylcholinesterase activity, a common pollution biomarker, in Mytilus sp.from the south-western Baltic Sea. Journal of Experimental Marine Biology andEcology 320, 93e103.

Pytharopoulou, S., Sazakli, E., Grintzalis, K., Georgiou, C.D., Leotsinidis, M.,Kalpaxis, D.L., 2008. Translational responses of Mytilus galloprovincialis to envi-ronmental pollution: integrating the responses to oxidative stress and otherbiomarker responses into a general stress index. Aquatic Toxicology 89, 18e27.

Raftopoulou, E.K., Dimitriadis, V.K., 2010. Assessment of the health status of musselsMytilus galloprovincialis along Thermaikos Gulf (Northern Greece): an integra-tive biomarker approach using ecosystem health indices. Ecotoxicology andEnvironmental Safety 73, 1580e1587.

Raj, S.M., Jayaprakash, M., 2008. Distribution and enrichment of trace metals inmarine sediments of Bay of Bengal, off Ennore, south-east coast of India.Environmental Geology 56, 207e217.

Ren, F., Gleason, B., Easterling, D., 2002. Typhoon impacts on China’s precipitationduring 1957e1996. Advances in Atmospheric Sciences 19, 943e952.

Ren, N., Que, M., Li, Y.-F., Liu, Y., Wan, X., Xu, D., Sverko, E.D., Ma, J., 2007. Poly-chlorinated biphenyls in Chinese surface soils. Environmental Science & Tech-nology 41, 3871e3876.

Richardson, B.J., Mak, E., De Luca-Abbott, S.B., Martin, M., McClellan, K., Lam, P.K.S.,2008. Antioxidant responses to polycyclic aromatic hydrocarbons and organo-chlorine pesticides in green-lipped mussels (Perna viridis): do mussels ‘‘inte-grate” biomarker responses? Marine Pollution Bulletin 57, 503e514.

Ringwood, A.H., Keppler, C.J., 2002. Water quality variation and clam growth: is pHreally a non-issue in estuaries? Estuaries 25, 901e907.

Santovito, G., Piccinni, E., Cassini, A., Irato, P., Albergoni, V., 2005. Antioxidantresponses of the Mediterranean mussel, Mytilus galloprovincialis, to environ-mental variability of dissolved oxygen. Comparative Biochemistry and Physi-ology, Part C 140, 321e329.

Sarkar, S.K., Cabral, H., Chatterjee, M., Cardoso, I., Bhattacharya, A.K., Satpathy, K.K.,Alam, M.A., 2008. Biomonitoring of heavy metals using the bivalve molluscs inSunderban mangrove Wetland, northeast coast of Bay of Bengal (India): pos-sible risks to human health. Clean e Soil, Air, Water 36, 187e194.

Sprovieri, M., Feo, M.L., Prevedello, L., Manta, D.S., Sammartino, S., Tamburrino, S.,Marsella, E., 2007. Heavy metals, polycyclic aromatic hydrocarbons and

polychlorinated biphenyls in surface sediments of the Naples harbour (south-ern Italy). Chemosphere 67, 998e1009.

Tang, X., Shen, C., Shi, D., Cheema, S.A., Khan, M.I., Zhang, C., Chen, Y., 2010. Heavymetal and persistent organic compound contamination in soil from Wenling:an emerging e-waste recycling city in Taizhou area, China. Journal of HazardousMaterials 173, 653e660.

Tsangaris, C., Hatzianestis, I., Catsiki, V., Kormas, K.A., Strogyloudi, E., Neofitou, C.,Andral, B., Galgani, F., 2011. Active biomonitoring in Greek coastal waters:application of the integrated biomarker response index in relation to con-taminant levels in caged mussels. Science of the Total Environment 412e413,359e365.

Turja, R., Soirinsuo, A., Budzinski, H., Devier, M.H., Lehtonen, K.K., 2013. Biomarkerresponses and accumulation of hazardous substances in mussels (Mytilus-trossulus) transplanted along a pollution gradient close to an oil terminal in theGulf of Finland (Baltic Sea). Comparative Biochemistry and Physiology, Part C157, 80e92.

van der Oost, R., Beyer, J., Vermeulen, N.P.E., 2003. Fish bioaccumulation and bio-markers in environmental risk assessment: a review. Environmental Toxicologyand Pharmacology 13, 57e149.

Viarengo, A., Lowe, D., Bolognesi, C., Fabbri, E., Koehler, A., 2007. The use of bio-markers in biomonitoring: a 2-tier approach assessing the level of pollutant-induced stress syndrome in sentinel organisms. Comparative Biochemistryand Physiology, Part C 146, 281e300.

Wang, C., Lu, G., Wang, P., Wu, H., Qi, P., Liang, Y., 2011a. Assessment of environ-mental pollution of Taihu Lake by combining active biomonitoring and inte-grated biomarker response. Environmental Science & Technology 45, 3746e3752.

Wang, J., Caccamise, S.A.L., Wu, L., Woodward, L.A., Li, Q.X., 2011b. Spatial distri-bution of organochlorine contaminants in soil, sediment, and fish in Bikini andEnewetak Atolls of the Marshall Islands, Pacific Ocean. Chemosphere 84, 1002e1008.

Wang, W., Ballatori, N., 1998. Endogenous glutathione conjugates: occurrence andbiological functions. Pharmacological Reviews 50, 335e356.

Wang, Z.F., Wang, J.C., Cheng, F.L., Meng, F.P., Yang, F.F., Du, X.P., Li, X.L., Wang, J.,2012. Distribution and ecological risk assessment of heavy metals and poly-chlorinated biphenyls in intertidal sediments along the Beibu Bay. Environ-mental Chemistry 31 (9), 1293e1302 (in Chinese with English abstract).

Wu, X., Jia, Y., Zhu, H., 2012. Bioaccumulation of cadmium bound to ferric hydroxideand particulate organic matter by the bivalve M. meretrix. Environmental Pol-lution 165, 133e139.

Xia, P., Meng, X.W., Yin, P., Cao, Z.M., Wang, X.Q., 2011. Eighty-year sedimentaryrecord of heavy metal inputs in the intertidal sediments from the Nanliu Riverestuary, Beibu Gulf of South China Sea. Environmental Pollution 159, 92e99.

Xia, P., Meng, X.W., Yin, P., Liu, L.J., 2008. Heavy metal pollution and its potentialecological risk in the sediments from the Beihai intertidal zone of GuangxiProvince. Advances in Marine Science 26 (4), 471e477 (in Chinese with Englishabstract).

Yang, Z., Shen, Z., Gao, F., Tang, Z., Niu, J., 2009. Occurrence and possible sources ofpolychlorinated biphenyls in surface sediments from the Wuhan reach of theYangtze River, China. Chemosphere 75, 1522e1530.

Yatawara, M., Qi, S., Owago, O.J., Zhang, Y., Yang, D., Zhang, J., Burnet, J.E., 2010.Organochlorine pesticide and heavy metal residues in some edible biota col-lected from Quanzhou Bay and Xinghua Bay, Southeast China. Journal ofEnvironmental Sciences 22, 314e320.

Yu, R., Hu, G., Wang, L., 2010. Speciation and ecological risk of heavy metals inintertidal sediments of Quanzhou Bay, China. Environmental Monitoring andAssessment 163, 241e252.

Zhang, J., Liu, J., Zhang, Y., Chen, C., Sun, X., 2011a. Variation features and potentialecological assessment of heavy metals in Liusha Bay. Environmental Science &Technology 34 (12H), 352e356 (in Chinese with English abstract).

Zhang, Y., Sun, G., Yang, M., Wu, H., Zhang, J., Song, S., Ma, E., Guo, Y., 2011b. Chronicaccumulation of cadmium and its effects on antioxidant enzymes and malon-dialdehyde in Oxya chinensis (Orthoptera: Acridoidea). Ecotoxicology andEnvironmental Safety 74, 1355e1362.

Zhao, S., Feng, C., Yang, Y., Niu, J., Shen, Z., 2012. Risk assessment of sedimentarymetals in the Yangtze Estuary: new evidence of the relationships between twotypical index methods. Journal of Hazardous Materials 241e242, 164e172.

Zhou, Y., Meng, F.P., Cheng, F.L., Du, X.P., Li, X.L., Bai, W.N., 2012. Distribution andpollution assessment of total petroleum hydrocarbon and polychlorinatedbiphenyls in the intertidal clam Paphia undulata along the Beibu Gulf. Envi-ronmental Chemistry 31 (6), 814e822 (in Chinese with English abstract).