Responses of Benthic Foraminifera to the 2011 Oil Spill in the Bohai Sea, PR China

Marine Pollution Bulletin xxx (2015) xxx–xxx

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Marine Pollution Bulletin

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Responses of benthic foraminifera to the 2011 oil spill in the Bohai Sea, PR China ⇑ Yan Li Lei a, Tie Gang Li a, , Hongsheng Bi b, Wen Lin Cui c, Wen Peng Song c,JiYeLic, Cheng Chun Li a a Department of Marine Organism Taxonomy & Phylogeny, Key Laboratory of Marine Geology and Environment, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, PR China b Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, Solomon, MD 20688, USA c The Organization of North China Sea Monitoring Center, SOA, PR China article info abstract

Article history: The 2011 oil spill in the Bohai Sea was the largest spill event in China. Nine sediment cores were taken Received 5 October 2014 near the spill site and environmental factors including Polycyclic Aromatic Hydrocarbon (PAHs), oils, sul- Revised 12 May 2015 fides, organic carbon were measured 6 months later. Benthic foraminifera were separated into >150 lm Accepted 12 May 2015 (large) and 63–150 lm (small) size fractions for 2-cm depth interval of each sediment core. Statistical Available online xxxx analyses suggested that the species composition of living foraminifera was impacted by oils, PAHs and sulfides. Large foraminifera were more sensitive to the oils than the small. Abnormal specimens were Keywords: positively correlated with oils or PAHs. Small forms, however, tended to have high reproduction and mor- Benthic foraminifera tality. Pollution-resistant and opportunistic taxa were identified to calculate a Foraminiferal Index of Biological response Ecological monitoring Environmental Impacts (FIEI). The FIEI increased from low to high oil-polluted station and from deep Indicator species layer to surface sediment reflects the impact of oil pollution in this area. The Yellow Sea Ó 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

1. Introduction oil and 2620 barrels (416 m3) of mineral oil-based drilling mud seeping into the Bohai Sea (http://www.soa.gov.cn/) and yet very Oil spills have a wide range of adverse impacts on the marine few studies have examined the potential environmental impact. environment at different temporal scales (Peterson, 2001). They The Bohai Sea is a half-closed sea and is only connected with the can have dire consequences on the survival of marine flora and Yellow Sea through the Bohai Strait. The residence water in the fauna including ecological and economically important fish and Bohai Sea has a mean age of >1.2–3.9 years (Liu et al., 2012). To mammals (Brody et al., 1996; Murphy et al., 1997; Wiens et al., examine and assess the potential impact of the ‘‘Penglai’’ oil spill 1996) and affect marine organisms by disrupting reproduction on the local marine environment, we investigated the potential (Andres, 1997; Lamont et al., 2012), development of using benthic foraminifera as biotic indicators. (Gonzalez-Doncel et al., 2008; Incardona et al., 2014), and feeding Benthic organisms are used extensively as biotic indicators of (Romero et al., 2012). Besides the direct impacts on marine organ- environment because they generally have limited mobility and isms and their habitats, the toxic substances can also affect human cannot avoid adverse environmental changes. Benthic foraminifera health through food webs (Aguilera et al., 2010; Gin et al., 2001; are particularly useful for environmental monitoring (Frontalini O’Rourke and Connolly, 2003). There is a large body of literature and Coccioni, 2011; Hallock et al., 2003; Foster et al., 2012). First, on large oil spills such as the 1978 ‘‘Amoco Cadiz’’ spill in France they are widely distributed and very diverse. Second, they can pre- (Dauvin, 1998; Mille et al., 1998), the 1989 ‘‘Exxon Valdez’’ spill serve historical information in their shells (>500 million years) in Alaska (Atlas and Hazen, 2011; Harwell et al., 2010; Payne which can be used to study the marine environments from ancient et al., 2008; Peterson, 2001) and the 2010 ‘‘Deepwater Horizon’’ (Cambrian) to present (Holocene). Therefore, their species compo- spill in the Gulf of Mexico (Kurtz, 2013; Lavrova and Kostianoy, sition and chemical elements reflect palaeoenvironment (Spero 2011). The 2011 ‘‘Penglai’’ oil spill in the Bohai Sea was the worst et al., 1997; Li et al., 2009; Nigam et al., 2009). Third, they are sen- oil spill in China. There were approximately 723 barrels (115 m3)of sitive to changes in marine environments such as water tempera- ture, salinity, pH, water mass, ocean current, marine geographical variables (Murray, 1991, 2006). Furthermore, their shells preserved

⇑ Corresponding author. at different depths in sediment can reﬂect environmental changes E-mail address: [email protected] (T.G. Li). including oil exploitation activities (Denoyelle et al., 2010; Sabean http://dx.doi.org/10.1016/j.marpolbul.2015.05.020 0025-326X/Ó 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Please cite this article in press as: Lei, Y.L., et al. Responses of benthic foraminifera to the 2011 oil spill in the Bohai Sea, PR China. Mar. Pollut. Bull. (2015), http://dx.doi.org/10.1016/j.marpolbul.2015.05.020 2 Y.L. Lei et al. / Marine Pollution Bulletin xxx (2015) xxx–xxx et al., 2009), which is particularly useful when no baseline data river runoff (Fig. 1). There are 16 rivers entering the Bohai Sea were available. including the Yellow River. The average residence time water in Previous studies showed that foraminifera could serve as biotic the Bohai Sea is 3 years (Liu et al., 2012). Current from the indicators to evaluate the impacts of oil spills (Casey et al., 1980; Yellow Sea entered the Bohai Sea from the bay mouth and flowed Armynot du Châtelet et al., 2004). Durrieu et al. (2006) and west towards inner Bay. The dominant circulation pattern is anti- Mojtahid et al. (2006) showed that benthic foraminifera could be clockwise (Chen, 2009). used to estimate the pollution from oil drill mud disposal. The Bohai Sea has significant hydrocarbon deposits and offshore However, Locklin and Maddocks (1982) found no negative effects oil exploration started in 1980s. The ‘‘Penglai’’ field is that biggest of petroleum operations on benthic foraminifera on the southwest oil field in this region, which is 51% owned by the China National Louisiana shelf. Offshore Oil Corporation (CNOOC), and 49% owned by the The general responses of benthic foraminifera to pollutants ConocoPhillips (COPC). The exploration of the ‘‘Penglai’’ Oilfield include decreased diversity and increased dominance of tolerant started in 1999 and the operation started on December 31, 2002. or opportunistic species, or alteration of species morphology and From June to July in 2011, at least two major leaks events occurred reproduction, but different species may show differential response. in the ‘‘Penglai’’ Oilfield, which became the largest oil spill accident For example, Morvan et al. (2004) conducted a laboratory culture in China. experiment and observed morphological abnormalities of benthic foraminifera (Ammonia tepida) and a reduction of reproduction rate 2.2. Sampling under oil pollution. But Ernst et al. (2006) found that the mortality of foraminiferal faunas increased in response to the presence of oils Nine sediment cores with a depth of 22–28 m to the surface in a laboratory microcosm experiment, but some species did were sampled on December 18–19, 2011 in the Bohai Sea (38°100 increase their density by increasing their reproduction. Although -39°000N, 119°300–120°10E). The locations of the oil spill and sam- the toxic hydrocarbon components appeared to be responsible pling sites were shown in Fig. 1. For detecting the impact of oil pol- for the observed changes in foraminiferal abundance and species lution, the sediments near the oil spill site were intensively composition (Armynot du Châtelet and Debenay, 2010; Mojtahid sampled. Station 14 was closest to the spill site, followed by et al., 2006), species-specific responses to environmental stress St22, St36, St31, St11, St19 and St6. Station 26 was furthest away induced by oil pollution were evident. Considering the from the spill site and was considered as a reference site. StA8 bio-geographical distribution of foraminifera and the different was considered as an intermediate station. Sediment samples were habitat may colonize different foraminiferal community domi- taken using a 0.1 m2 Gray–Ohara box corer. At each sampling sta- nated by different species, the foraminiferal responses to the oil tion, environmental variables (water depth, sediment type, sedi- pollution should vary among different foraminiferal communities ment color) and pollution factors including Polycyclic aromatic from different geographical regions. hydrocarbons (PAHs), oils, sulfides and organic carbon were mea- When compared to other regions, e.g., the temperate Atlantic sured from the surface sediment (Table 1). Sediment grain size regions (e.g. Brunner et al., 2013; Hallock et al., 2003), there is a analysis was based on Shepard (1954). The measurements for the lack of studies on monitoring and assessing environmental impact chemical contaminants of the sediments were based on the of oil spills using benthic foraminifera in the Western Pacific Chinese National Standards of GB/T 18668-2002 and GB/T region, Chinese continental shelf in particular (Li et al., 2009; Jian 17378.5-2007. et al., 2000). As offshore drilling increases, there is a growing need The sampled sediment cores were subsampled using a recently to identify suitable indicator species and develop local indices that developed Pushing-type Quantitative Layering Sampler with an could be used to assess environmental conditions. While there inner diameter of 6 cm, i.e., 28.26 cm2 sampling surface (Fig. 2). were a variety of foraminiferal indices have been developed, e.g., Each core was sliced every 2-cm interval until 12–16 cm depth. diversity indices, Foraminiferal Abnormality Index (FAI, Coccioni The sliced sediment stratums were immediately fixed using 95% et al., 2005) and Foraminiferal Index of Environmental Impact ethanol mixed with 1 g/L Rose Bengal such that live and dead spec- (FIEI, Mojtahid et al., 2006), all indices require baseline information imens could be distinguished. Samples were then stored in a dark, on local foraminiferal fauna and identification of indicator species. cooling box and transported to the laboratory within 24 h. In the But in the Bohai Sea, information on species composition and dis- laboratory, each sediment stratum was washed over a 63 lm tribution of recent benthic foraminifera is not available and how screen. The residues were dried in the oven below 50 °C for 24 h they respond to oil spills remains unknown. and weighted and sieved through 63 lm and 150 lm meshes. After the 2011 ‘‘Penglai’’ oil spill in the Bohai Sea, we started to Benthic foraminifera were picked and counted for two size frac- explore the potential of using foraminifera to evaluate the status of tions, >150 lm and 63–150 lm, respectively (Jian et al., 1999). oil pollution. The objectives of the present study are to: (1) inves- The volumes of sample were consistent with each other, i.e. tigate the horizontal distribution of living foraminiferal fauna and 56.55 cm3, but the dry weights varied from 31.3 g to 50 g among examine vertical distribution using their fossil records; (2) exam- stations. The foraminiferal specimens were concentrated by an ine how benthic foraminifera respond to oil spill and identify isopycnic separation technique using tetrachloromethane potential indicator species; (3) assess environmental status of the (D = 1.59) and the residues were also examined. survey area. The ultimate goal is to build a regional index based on indicator species to assess environmental stress and provide 2.3. Classification and analyses background information on local foraminiferal species composition and distribution. Foraminifera were enumerated under a Nikon SSZ1500 stere- omicroscope, with continuous zooming to a maximum amplifica- tion of 225. Specimens were observed and photographs were 2. Materials and methods taken under the microscope. Foraminifera were identified to species level based on Loeblich and Tappan (1987, 1992, 1994), 2.1. Study area and background information Hayward et al. (2014) and the relevant regional taxonomic literature (e.g. Wang et al., 1988). To investigate the spatial pattern, total The Bohai Sea is the innermost gulf of the North Yellow Sea of foraminiferal fauna were separated as living, dead and abnormal. China with an area 78,000 km2 and high sediment loadings from Individuals were picked and inventoried, and were separated into

Oils N 26 94 to 146 CHINA 146 to 158 158 to 239 239 to 419 Bohai Sea 419 to 487

Yellow A8 6 19 11 Sea 36 22 14 AB31

PAHs Sulfides Organic carbon 26 24 to 38 26 32 to 36 26 0.17 to 0.26 38 to 40 36 to 37 0.26 to 0.32 40 to 45 37 to 46 0.32 to 0.33 45 to 68 46 to 55 0.33 to 0.39 68 to 123 55 to 66 0.39 to 0.67

A8 6 A8 6 A8 6 19 19 19 11 11 11 36 36 36 22 22 22 14 14 14

CD31 31 E31

Fig. 1. Map of 9 sampling stations (A) and distributions of pollution factors (B–E). (A) Sampling sites were shown by black dots and the oil spill site was indicated by the open square. Arrows showing a schematic drawing of the general circulation pattern in the Bohai Sea. (B) Concentration of oils (lg/g); (C) concentration of Polycyclic Aromatic Hydrocarbon (PAH, ng/g); (D) concentration of sulﬁdes (lg/g) and (E) concentration of organic carbon (%).

was calculated as RPi ln(Pi), where Pi is the proportion of total Table 1 number of species made up of the ith species. Evenness (J0) was cal- Basic information and pollution parameters in the 9 sampling sites of the Bohai Sea. culated as J0 = H0/ln S. Species made up >15% of the total abundance The samples were taken from the upper 2-cm sediment layer. were considered as dominant species. Sampling Water Sediment Sediment Distance to oil Foraminiferal bioindicators were selected based on three crite- sites depth (m) color type spill site (km) ria: highly recognizable morphology, abundant and common in oil St26 26 Yellow Silt clay 100.40 contaminated regions, frequent occurrence in various depth layers StA8 28 Yellow brown Clay silt 35.42 which allows comparison over time. Based on our preliminary St6 28 Yellow Silt clay 24.14 analysis, we selected indicator species to construct the St19 28 Yellow Silt clay 18.46 St11 28 Yellow Silt clay 13.86 Foraminiferal Index of Environmental Impact (FIEI, Mojtahid St36 27 Yellow brown Clay silt 11.92 et al., 2006) to evaluate the pollution status among stations. St22 27 Yellow Silt clay 7.34 FIEI = (Nr + N0)/Ntot 100, where Nr is the total quantity of St14 24 Yellow Silt clay 6.28 pollution-resistant taxa, N0 is the number of individuals of oppor- St31 22 Yellow Silt 14.08 tunistic taxa and Ntot is the total number of individuals in the foraminiferal assemblage. In this study the pollution-resistant taxa two size fractions: large foraminifera (>150 lm) and small forami- were determined among the dominant species whose occurrence nifera (63–150 lm). Because the small size group mostly included was significantly positively correlated to the oils. While those were mainly juvenile or larva of large foraminifera and some small also frequent or abundant at some oil-polluted stations but were unidentified species, therefore only large foraminifera were chosen not significantly correlated to oils, were considered as opportunis- to investigate the vertical distribution. tic taxa. In general, whole sample was analyzed, but when foraminiferal density was too high, a riffle was used to subset samples with a 2.4. Statistical analysis minimum of 300–1000 individuals of total fauna examined from each sample. For each station, the abundance of total fauna, live Simple nonparametric Spearman correlation was used to evalu- fauna and abnormal fauna, species richness (number of species ate the relationship between biotic variables (the abundance of per sample), Margalef index (D), Shannon–Wiener diversity (H0) total, living and abnormal foraminifera, species richness, diversity and evenness (J0) were calculated. Margalef index (D) was calcu- indices and evenness) and the pollution parameters (PAHs, oils, lated as S 1/ln N, where S is the total number of species and N sulfides, and organic carbon). These analyses were performed using is the total number of individuals. Shannon–Wiener index (H0) the Statistical Package for the Social Sciences (SPSS, version 15.0).

sampling stations were mostly silt clay, but St36 was clay silt and St31 was silt. The sediment colors were most of yellow but St36 was yellow brown (Table 1). Oils’ concentration was highest at St22, followed by St11, St36, St14, St19, St26, St6, StA8 and St31 (Fig. 1). The PAHs concentration was highest at St31, followed by St22, St14, St19, St6, St36, St26, StA8 and St11 (Fig. 1). Concentration of sulﬁdes was highest at St26, followed by StA8, St22, St36, St19, St11, St6, St14 and St31 (Fig. 1). Organic carbon was highest at St26, followed by StA8, St36, St22, St11, St6, St14, St19 and St31. MDS analysis using the four pollution factors separated the 9 sampling stations into several different groups: the ﬁrst group comprised St26 and StA8. Other distinct groups included St6-St19-St14, and St36-St22. St31 and St11 were standing alone but in different directions (Fig. 3).

3.2. Horizontal distribution of foraminifera in surface stratum

3.2.1. Large group Both the abundances of total fauna and living fauna were lowest at St31: 150 and 72 individuals 10 cm2 respectively. High abundance of total and living foraminifera occurred at stations 11, 36 and 22 where concentrations of oil-pollutant were high and were close to the oil spill site (Table 2; Fig. 1). The highest abundance of total fauna was observed at St11 (488 individuals 10 cm2) and the maximum living abundance was at St22 (238 individuals 10 cm2). The percentage of living fauna ranged from 34.4% to 60.1% but there was no clear relationship with oil pollutants. High densities of living fauna sometimes occurred at stations with moderate pollution (e.g. St11, St36 and St22). Noteworthily, various morphological abnormal forms were observed including malformation in chambers, test with warts, diminution in the last chamber, color darken with dwarfism etc. (Plates 1 and 2). The percentage of abnormal specimens was higher Fig. 2. Schema diagram of the Pushing-type Quantitative Layering Sampler. 1. Push at polluted stations (e.g. St36, St22 and St31). The highest amount rod with scales; 2. Stainless steel sampling tube. of deformed specimens occurred at St22, up to 31%. In contrast, at Clusters were separated using the Ward method based on the St26, the reference station, the proportion of abnormal specimens species-abundance data. Canonical Correspondence Analysis was only 4.6% (Table 2). (CCA) was performed to test relationships between foraminiferal Species richness was highest at St26 with a value of 28, and species distribution and pollution factors, and was analyzed. Data lowest at St14 with a value of 18. Margalef index (D) and were log (x + 1) transformed to meet the assumptions of normality Shannon–Wiener index (H0) were both highest at St6 (4.59 and and homogeneity of variances. 2.57, respectively), but their lowest values were observed at St22 To examine the spatial variation of community structure, mul- (=3.12) and St26 (=1.88), respectively. Community evenness (J0) tidimensional scaling (MDS) ordination using Bray-Curtis similar- ranged from 0.97 (St22) to 0.89 (St14). ity matrices was performed in PRIMER v6.1 package (Clarke and Gorley, 2006). Stations-based pollution parameters and 3.2.2. Small group species-abundance data of foraminifera (>150 lm) were analyzed Similar to large foraminifera, the abundances of the total fauna separately. To detect how oil-pollution affects living foraminifera, and living fauna in this group were lowest at St31, 1935 vs. 45 indi- 2 multivariate biota-environment (BIOENV) analysis were per- viduals 10 cm , respectively, and were highest at St11, 6791 and formed by examining biotic and abiotic similarity matrices. The significance of biota-environment correlations was test using the routine RELATE (Clarke and Gorley, 2006). The spatial distribution of sampling sites and their pollution parameters were visualized in Surfer (version 8.0, Golden Software Inc., Golden, CO, USA). Small foraminiferal group mainly contains small specimens or juveniles of large foraminifera, due to their small size and difficulty in identification, especially in differentiation of abnormal forms from normal, statistical analyses were mainly based on large foraminiferal group.

3. Results

3.1. Environmental factors

Fig. 3. Multidimensional scaling (MDS) ordination for pollution factors using The oil spill site was at the inside of the entrance from the Euclidean distance among 9 sampling sites. To perform the MDS analysis, data were Yellow Sea to the Bohai Bay (Fig. 1). The sediment types of log (x + 1) transformed and Spearman rank correlations were calculated.

Table 2 Foraminiferal community parameters at the 9 sampling sites in the surface sediment layer, 0–2 cm.

St26 StA8 St6 St19 St11 St36 St22 St14 St31 >150 lm fraction Total abundance (inds. 10 cm2) 451 224 231 320 488 456 439 191 150 Living abundance (inds. 10 cm2) 181 103 88 110 221 172 238 115 72 Abnormal abundance (inds. 10 cm2) 21 34 50 75 89 124 136 46 41 Living ratio (%) 40.2 45.7 38.0 34.4 45.2 37.7 54.2 60.1 48.2 Abnormal ratio (%) 4.6 15.1 21.6 23.4 18.3 27.3 31.0 24.1 27.2 Species richness (S) 28 24 26 26 21 23 20 18 22 Margalef index (D) 4.42 4.25 4.59 4.33 3.23 3.59 3.12 3.24 4.19 Shannon–Wiener index (H0) 1.88 2.26 2.57 2.42 2.41 2.41 2.50 2.02 2.26 Evenness (J0) 0.57 0.71 0.79 0.74 0.79 0.77 0.84 0.70 0.73 Specimens examined 1278 636 657 457 361 687 318 544 430 63–150 lm fraction Total abundance (inds. 10 cm2) 2931 2716 2808 3916 6791 4255 2716 2275 1935 Living abundance (inds. 10 cm2) 181 113 181 566 815 113 91 79 45 Living ratio (%) 6.2 4.2 6.5 13.9 12.0 2.7 3.3 3.5 2.3 Species number (S) 16 14 18 17 12 20 22 18 16 Margalef index (D) 1.88 1.64 2.14 1.93 1.25 2.27 2.66 2.20 1.98 Shannon–Wiener index (H0) 1.59 1.70 1.85 1.37 1.63 1.37 1.72 1.36 1.43 Evenness (J0) 0.57 0.64 0.64 0.48 0.66 0.46 0.56 0.47 0.52 Specimens examined 259 121 124 173 76 188 241 201 171

815 individuals 10 cm2 respectively. Comparing to the large fora- frigida were dominant at St26, making up 13% and 10% of total minifera, the total abundances of small fauna were remarkably abundance, respectively. Several species appeared to be higher. It is noteworthy that living abundance was not that high, oil-philic: B. frigida showed a large increase in its abundance the ratio varied from 2.3% to 13.9% among stations, markedly lower near the oil spill site, making up to 19% at heavily polluted site than the living ratio of large fauna (Table 2). (St14). C. incertum was only 5% of total abundance at St26, and Species richness, Margalef diversity index (D) and Shannon– increased to 11–26% of total abundance near the oil spill site. Wiener index (H0) were all lowest at St11 with a value of 12, Species including E. macellum, Q. ungeriana, C. asiaticum, V. 2.61 and 2.47, respectively, and were all highest at St22, with a advena, A. tepida, R. annectens, R. compressiusculus were fre- value of 22, 4.76 and 3.05, respectively. But the three parameters quently observed at all stations and they usually accounted for were all lower than large size group. Community evenness (J0) 1–7% of total abundance (Fig. 4). among the nine stations was similar. 3.3.2. Small group 3.3. Species composition of foraminifera in surface layer and below A total of 37 species representing 27 genera within four orders surface (Textulariida, Miliolida, Lagenida and Rotaliida) was identified from sediment samples at different depths. C. magellanicum was A total of >100 foraminiferal species was identified from surface predominant species at the surface layer and it made up on average and below surface samples, and 53 species were observed in the 62% (ranged from 53% to 71%) of total abundance in small forami- surface layer (0–2 cm). Surface samples were different from below niferal group. V. advena was the second abundant species at the surface samples, e.g., some species did not occur in below surface surface layer, accounting for on average 6% (ranged from 1% to samples and some species increased their abundance. 14%) of total abundance in small foraminiferal group. Species such The species compositions of large and small groups were similar as A. globigeriniformis, C. incertum, B. frigida and C. asiaticum were in the surface layer (0–2 cm, Tables A1 and A2). Calcareous forami- often observed at all stations but with relatively low abundance nifera made up 80–90% of the total fauna, and agglutinated tests in this size spectrum (Fig. 4). made up 10–20%. Rotaliida species were predominant, followed by Textulariida and Miliolida. Astrorhizida and Lagenida were rel- 3.4. Linkage between foraminiferal community and pollution factors atively rare. In >150 lm fraction, simple nonparametric Spearman correla- 3.3.1. Large group tion analysis results showed several community parameters were A total of 41 species representing 27 genera and five orders significantly correlated to the oils. Living abundance and abnormal (Astrorhizida, Textulariida, Miliolida, Lagenida and Rotaliida) were abundance were positively correlated to oils (p < 0.05). In addition, identified in surface layers (Table A1). The common species the percentage of abnormal individuals was also positively corre- included Ammoglobigerina globigeriniformis, Cribrononion incertum, lated to PAHs (p < 0.05). Margalef index (D) negatively correlated Buccella frigida, Elphidium macellum, Cribroelphidium magellanicum, to oils. In contrast, no parameter of 63–150 lm fraction was signif- Quinqueloculina ungeriana, Cribrononion asiaticum, Verneuilinulla icantly correlated to oils, except that the total and living abun- advena, A. tepida, Ammonia inflata, Rotalidium annectens, dance of small foraminifera were negatively correlated to PAHs Rotalinoides compressiusculus, Ammonia pauciloculatus, Ammonia (Table 3). ketienziensis, Elphidium advenum. These species were also observed The BIOENV analysis results suggested that the composi- in samples below surface (Table A1). Among them, A. globigerini- tion/distribution of living foraminiferal species was related to the formis, C. incertum, B. frigida, E. macellum and C. magellanicum were combination of PAHs, oils and sulfides (R = 0.490; p=0.019). Note most frequent. that oils were included in all correlations. The foraminiferal biotic Species composition showed distinct variation among sur- variables were significantly correlated to several different combi- veyed stations. C. magellanicum accounted for up to 50% of total nations of pollution factors (Table 4). foraminiferal abundance at St26 but rapidly decreased to 17–30% MDS analysis was performed using the station based abundance at the stations near the spill site. A. globigeriniformis and B. of total foraminifera and large living foraminifera separately to

Plate 1. Microphotographs of dominant and common species of benthic foraminifera in the Bohai Sea, showing normal specimens and abnormal individuals (indicated by arrows). Scale bars = 200 lm. 1. Ammoglobigerina globigeriniformis (Park and Jones, 1865) showing normal (a–d) and abnormal (e and f) specimens. 2. Verneuilinulla advena (Cushman, 1922) showing normal (a and b) and abnormal (c) specimens. 3. Quinqueloculina ungeriana (d’Orbigny, 1846) showing normal (a–c) and abnormal (d) specimens. 4. Cribrononion asiaticum (Polski, 1959) showing normal (a–c) and abnormal (d and e) specimens. 5. Cribrononion incertum (Williamson, 1858) showing normal (a–c) and abnormal (d–f) specimens. 6. Elphidium macellum (Fichtel and Moll, 1798) showing normal (a–c) and abnormal (d and e) specimens.

examine the spatial patterns of the total and living foraminiferal 3.5. Identifying of foraminiferal bioindicators assemblages among stations (Fig. 5). Both St31 and St14 were separated from other stations. Stations near the spill site (St19, St11, To identify species could be used to evaluate the impact of oil St22 and St36) were clustered together. St26 and StA8 were pollution, a dendogram of the occurrence of different species was grouped together in Fig. 5A, but separated in Fig. 5B. Results constructed for large foraminifera (Fig. 6). The species were sepa- reﬂected the status of oil impact, but the total abundance was con- rated into two distinct clades (25% similarity level). Clade 1 consistent with the pollution factors (Fig. 3). tained 28 taxa which rarely occurred, or if they did occur, their

Plate 2. Continue. 7. Cribroelphidium magellanicum (Heron-Allen and Earland, 1932) showing normal (a and b) and abnormal (c–f) specimens. 8. Buccella frigida (Cushman, 1922) showing normal (a–c) and abnormal (d–f) specimens. 9. Ammonia inflata (Seguenza, 1862) showing normal (a–c) and abnormal (d–f) specimens. 10. Ammonia tepida (Cushman, 1926) showing normal (a and b) and abnormal (c–e) specimens. 11. Rotalidium annectens (Parker et Jones, 1865) with normal (a–c) and abnormal (d and e) specimens. 12. Rotalinoides compressiusculus (Brady, 1884) with normal (a–c) and abnormal (d and e) specimens. abundance tended to be low. Clade 2 had 13 common species with Based on Spearman correlations, cluster analysis and the CCA high occurring frequency and high abundance (Fig. 6; Table A1). along with the spatial and vertical distribution, 4 resistant and 3 The relationships among the distributions of large foraminiferal opportunistic species were selected as bioindicators. The total species were summarized by CCA (Fig. 7). Species was numbered and/or living abundance of B. frigida, E. macellum, C. asiaticum, V. and was consistent with Fig. 6. Many species distributed along advena were positively correlated to oils (Table 5), which were the oils axis, indicating strong influence by oils. In addition, several considered as pollution resistant taxa. The following three species species distributed along the axis of PAHs or sulfide or organic car- of A. globigeriniformis, C. incertum and Q. ungeriana were regarded bon, suggesting a close relationship to the corresponding environ- as opportunistic taxa because although they increased their abun- mental factor. dance at stations with high concentration of oils, no significant

100% 3.6. Foraminiferal Index of Environmental Impact (FIEI) in sediment 90% layers 80% 70% In order to comparing pollution status among stations and 60% between the present and the past times in the Bohai Sea, the FIEI 50% using selected bioindicators were calculated in surface sediment 40% layers and also in sediment depths (Table 6). In the surface layer, 30% the FIEI based on living fauna was lowest at St26 (=33.59) and 20% 10% highest St31 (=88.73). The FIEI based on living fauna was also high 0% at St11 (=72.44), and ranged from 40 to 60 at other stations. The A St26 StA8 St6 St19 St11 St36 St22 St14 St31 FIEI value based on total foraminifera was also lowest at St26 (=38.65). The FIEI based on total fauna was relatively high at A. globigeriniformis C. incertum St14 and St31 (64.51 and 66.74, respectively) and ranged from B. frigida E. macellum 40 to 60 at other stations. The high values of FIEI at stations near C. magellanicum Q. ungeriana the spill site (St14 and St31) were consistent with high abundance C. asiaticum V. advena of pollution-resistant or opportunist species and low abundance of A. tepida A. inflata sensitive species (Tables 6 and A1). R. annectens R. compressiusculus The depth-speciﬁc FIEI values (Table 6; Fig. 9) suggested that A. pauciloculatus A. ketienziensis FIEI increased from deep layer to surface layer. The FIEI values in E. advenum Others the deepest stratums, 14–16 cm, were lowest, under 40. Then the FIEI values slightly increased in upper stratums, varying between 100% 40 and 60 from 8 to 14 cm depth. The great increase of FIEI was 90% observed at 6–8 cm depth, 60 at St31. The FIEI values were sim- 80% ilar at 2–6 cm depth but with a slight increase. In the surface 0– 70% 2 cm layers the FIEI values at most stations reached to the maxi- 60% mum (Table 6). 50% 40% 30% 4. Discussion 20% 10% 4.1. Sediment environments among stations 0% B St26 StA8 St6 St19 St11 St36 St22 St14 St31 As one of the largest energy consumers and rapidly increasing demand, offshore drilling is becoming an important source for fos- Fig. 4. Percent composition of common foraminiferal species in >150 lm fraction sil fuel. In China, the Bohai Sea is the most important oil production (A) and in 63–150 lm fraction (B) at the 9 stations in the surface sediment, 0–2 cm. area since 1980s and the local marine environment is heavily Note that data were based on total foraminiferal fauna. impacted by oil pollution (Hu et al., 2013, 2011; Qin et al., 2011). By nature, the Bohai Sea is a half-closed sea with limited water exchange with the Yellow Sea. The general circulation pattern is correlations could be detected (Table 5). The spatial distribution of characterized by an east–westwards, north–southwards, anticlock- the selected bioindicators in surface layer of 0–2 cm was shown in wise currents from bay mouth to the inner (Chen, 2009). To prop- Fig. 8. Their total and living abundance had a similar tendency of erly understand the results, it is important to ﬁt the observed variations in the surface layer. In addition, the abundance of fora- biological changes in physical environment. miniferal indicator species tended to decrease with depth (Fig. 9). In the present study, the overall concentrations of pollutants in sediment samples were not so high with the highest PAHs

Table 3 Correlations (Spearman’s r values) between foraminiferal community parameters and environmental factors. Data were based on the data after log (x + 1) transformed from each sample of the 9 sediments taken from 0 to 2 cm surface layer. Because the same data were used in several analyses (pollution parameters), the a-level was reduced from 0.05 to 0.025. p-values (in the lower line parentheses) beneath 0.025 are marked in double asterisks.

PAHs Oils Sulﬁdes Organic carbon >150 lm fraction Total abundance 0.600(0.088) 0.683(0.042)⁄ 0.500(0.170) 0.519(0.152) Living abundance 0.267(0.488) 0.883(0.002)⁄⁄ 0.500(0.170) 0.527(0.145) Abnormal abundance 0.150(0.700) 0.800(0.010)⁄⁄ 0.083(0.831) 0.142(0.715) Living ratio (%) 0.383(0.308) 0.067(0.865) 0.233(0.546) 0.050(0.898) Abnormal ratio (%) 0.817(0.007)⁄⁄ 0.300(0.433) 0.433(0.244) 0.485(0.185) Species richness (S) 0.360(0.342) 0.502(0.168) 0.435(0.242) 0.248(0.520) Margalef index (D) 0.200(0.606) .700(0.036)⁄ 0.217(0.576) 0.092(0.814) Shannon–Wiener index (H0) 0.300(0.433) 0.067(0.865) 0.317(0.406) 0.075(0.847) Evenness (J0) 0.000(1.000) 0.667(0.050) 0.100(0.798) 0.033(0.932) 63–150 lm fraction Total abundance 0.686(0.041)⁄ 0.477(0.194) 0.343(0.366) 0.311(0.415) Living specimens 0.720(0.029)⁄ 0.226(0.559) 0.351(0.354) 0.227(0.557) Living ratio (%) 0.517(0.154) 0.083(0.831) 0.150(0.700) 0.025(0.949) Species richness (S) 0.571(0.108) 0.420(0.260) 0.025(0.949) 0.059(0.880) Margalef index (D) 0.683(0.042)⁄ 0.350(0.356) 0.167(0.668) 0.142(0.715) Shannon–Wiener index (H0) 0.233(0.546) 0.050(0.898) 0.283(0.460) 0.301(0.431) Evenness (J0) 0.583(0.099) 0.150(0.700) 0.233(0.546) 0.276(0.472)

Table 4 industrial discharges. Therefore oils and PAHs were low at St26 Summary of results from biota-environment (BIOENV) analysis showing the best station but sulfides and organic carbon were high. matches of pollution factors with spatial distribution of living foraminiferal species in In the present study, the impact was relatively clear at broad >150 lm fraction at 9 sampling sites. The a-level was ranked to 0.05. p-values beneath 0.05 were considered as significant and are marked in asterisks. scale. Oil contaminates were high at the stations near the spill site (St36, St22 and St14), and current could bring oil contaminates dif- Rank R Environmental variables p fused to the surrounding stations such as St6, St19, StA8 and St31. ⁄⁄ 1 0.490 PAHs, Oils, Sulfide 0.019 Another important factor is sediment type (Mojtahid et al., 2006). 2 0.469 PAHs, Oils 0.040⁄⁄ For example, the silty sediment type at St31 has strong impact on 3 0.423 Oils 0.006⁄⁄ 4 0.416 Oils, Sulfide 0.021⁄⁄ water exchange and degradation of oil containments. Although 5 0.408 PAHs, Oils, Sulfide, Organic Carbon 0.082 St14 was nearest to the spill site, statistical analysis based on envi- 6 0.385 PAHs, Sulfide 0.051 ronmental factors and foraminiferal abundance suggested St31 7 0.373 PAHs, Oils, Organic Carbon 0.108 was the most severely affected site. The measurements on pollu- 8 0.370 PAHs 0.106 9 0.364 Oils, Organic Carbon 0.097 tion factors among sampling sites indicated that St22, St11 and 10 0.310 Oils, Sulfide, Organic Carbon 0.111 St14 were heavily impacted by oils, but PAHs representing biological accumulation at St31 and St22 were highest. To understand the observed patterns, it requires detail information on near bottom currents and biological processes related to oil degradation.

4.2. Horizontal and vertical distribution of foraminiferal communities

To our best knowledge, we are not aware that any studies have investigated the relationship between benthic foraminifera and oil pollution in the Bohai Sea. The present study not only investigated the potential of using foraminifera to evaluate the environmental impact of oil spill, but also provide knowledge on species composition and potential indicator species which will provide baseline information for future studies. Studies have found that the abundance of benthic foraminifera was less than 200 individuals per 10 cm2 in >150 lm fraction in areas with oil drilling. For example, in Angola, northwestern of Africa, the abundance ranged from 20 to 200 individuals per 10 cm2 in sediments affected by oily cutting discharge (Jorissen et al., 2009). Another study in the outer continental shelf off Congo of central Africa found the abundance was <170 individuals per 10 cm2 at a station impacted by oily drill cutting disposal on the sea ﬂoor environment (Mojtahid et al., 2006). Additionally, a seasonal study carried out at a 550 m deep station in the Bay of Biscay in northwest of Atlantic showed the benthic foraminiferal abundance was from 35 to 200 individuals per 10 cm2 at a 550 m deep station, and from 25 to 90 individuals per 10 cm2 at a 1000 m deep two open slope stations (Fontanier et al., 2003, 2006). In the present study the abundance of total fauna was ranged from 150 to 488 individuals per 10cm2, living abundance varied from 72 to 238 individuals per 10 cm2 in >150 lm fraction. Overall, the density benthic foraminifera in the Fig. 5. Multidimensional scaling (MDS) ordination on abundance of total foraminiferal fauna (A), and abundance of living foraminiferal fauna (B) in >150 lm Bohai Sea appeared to be higher when compared to other regions. fraction using Euclidean distance among 9 sampling sites. To perform the MDS The species composition and abundance showed a distinct analysis, data were log (x + 1) transformed and Spearman rank correlations were uneven distribution as a result of oil spill. The lowest abundances calculated. of total fauna and living fauna, for both large and small foraminiferal assemblages, occurred at St31 (Table 2), suggesting heavy concentration of 123 ng/g, lower than the commonly referred impact from oil-pollution in the study area. St26 appeared to be effects range-low (ERL) concentration of 4022 ng/g (Long et al., in the best condition based on community parameters of large for- 1995), but comparable to the value reported by Denoyelle et al. aminiferal group, e.g., highest species richness and Margalef index. (2010) with sediment PAHs concentrations up to 160 g/kg close Furthermore, St26 also had the least proportion of abnormal indi- to the discharge point of oil polluted drill mud. The relative low viduals which indicated less environmental stress. Next to St26, concentrations of pollutants could be attributed to fact that sam- diversity parameters at St6 and at St19 were higher than other pling occurred 6 months after the spill and pollutants might be sites. Additionally, the lowest species richness was observed at degraded or transported away by near bottom currents. St14, and the highest percentage of abnormal specimens was In this study, the concentrations of oils tended to be high at sta- observed at St22, suggesting potential environmental stress at tions near the spill site except St31. Although sediment type in these stations. St31 was silt, which might not retain oils contaminants very well, The overall community structure was also consistent with envi- the concentration of PAHs, representing bioaccumulation of hydro- ronmental conditions. The results from MDS analysis on the abun- carbon was still high at St31. Meanwhile, in the contaminant based dance of individual species were consistent with the cluster analysis St31 was separated from other stations, indicating environmental conditions at different stations. Meanwhile, other its different environment characteristics. St26 was selected as the community parameters including the total, living, abnormal fauna, reference site because it was the farthest from the oil spill site, Margalef index (D) were all related to either oils or PAHs. Our but this station was located near coast, which often received results conﬁrmed that oil pollution have impact most benthic

Fig. 6. Cluster analysis on Bray–Curtis similarity matrices by Ward method for foraminiferal species, based on the abundance of individual species of total fauna in >150 lm fraction. Note that species were separated into two distinct clades. foraminiferal species and can further affect community parameters 4.3. Responses of benthic foraminifera to oil pollutant and species composition. The deposition of foraminifera in sediments could also provide Different foraminiferal species may show differential response historical information and allows a comparison between the pre- to oil pollution. Speciﬁcally, large foraminifera were more sensitive sent and the past time to examine the impact of oil pollution. In to the oils than the small foraminifera. For large foraminifera, their the present study, we utilized the vertical distribution of foramini- abundance, abnormality and Margalef index were negatively fera to select the bioindicator species, which offers an opportunity affected by oils. In contrast, small foraminifera did not show signif- to examine potential changes at individual stations. Our results icant response to oils. This result was consistent with the study revealed that the community structure was different at different conducted on continental margin off Africa by Jorissen et al. sediment layer, with a general trend of increasing proportion of (2009), which also showed that large-sized foraminiferal taxa arenaceous types and a reduction of hyaline forms from the bottom appeared more sensitive than small in sediments impacted by oily to the top layers. Using selected bioindicators of the foraminifera in cuttings discharged during oil exploration. In the same study, they each sediment depth, we established a local FIEI index which could also found that both species number and Shannon–Wiener index be used to investigate the historical changes in environmental con- were high at the distant station and decreased with increasing dis- ditions, oil pollution in particular, in the Bohai Sea. tance from the disposal site (Jorissen et al., 2009).

response to oil-induced pollution (Ernst et al., 2006). The foraminiferal density in some oil-treated mesocosms strongly increased by enhancing their production, on the other hand, they may expe- rience elevated mortality. In the present study, large volume of deformed foraminiferal specimens was observed in the samples, surface 0–2 cm layer in particular. The percentage of deformed individuals increased as concentration of oil pollutants increased (Table 2). Statistical analysis results showed that the abnormal specimens significantly increased as oils concentration increased, meanwhile, the abnormal ratio were significantly positively correlated with PAHs (Table 3). In other studies, Foraminiferal Abnormality Index (FAI), an index of percentage of abnormal specimens within the sample (Coccioni et al., 2005) has been used to evaluate the stress of environment from pollution contaminates (Armynot du Châtelet and Debenay, 2010). A laboratorial culture experiment documented that benthic foraminifera (A. tepida) responded to oil pollution by morphological abnormalities, cellular modification and a low rate of production (Morvan et al., 2004). Several studies (e.g. Vénec-Peyré, 1981; Yanko et al., 1992; Morvan et al., 2004) also observed very low foraminiferal abundance as well as morphological abnormalities. Our results were consistent with previous stud-

Fig. 7. Canonical Correspondence Analysis (CCA): plot of relationships between ies and demonstrated that both the abundance of abnormal foraminiferal species (in Arabic numbered) and pollution factors (PAHs, Oils, Sulfide individuals and abnormal ratio were significantly correlated with and Organic carbon). Data were based on total foraminiferal species in >150 lm oils, and PAHs, respectively (Table 3). Considering that the natural fraction and were transformed by log (x + 1). Each number of the species was background for the abnormality value is around 1–2%, values that concordant with that in Fig. 6. The species names in the figure were numbered as we observed are high (4.6–31.0%) and indicate that foraminiferal follows: 1, Ammoglobigerina globigeriniformis;2,Cribrononion incertum;3,Buccella frigida;4,Elphidium macellum;5,Cribroelphidium magellanicum;6,Protelphidium assemblages were affected by environmental stress, at a different sp1; 7, Polskiammina asiatica;8,Quinqueloculina ungeriana;9,Quinqueloculina extent, in all sampled stations (Frontalini and Coccioni, 2011; bellatula; 10, Cribrononion asiaticum; 11, Verneuilinulla advena; 12, Ammonia tepida; Morvan et al., 2004). 13, Pseudoeponides japonicas; 14, Ammonia inflate; 15, Rotalidium annectens; 16, The composition and faunal distribution of benthic foraminifera Rotalinoides compressiusculus; 17, Ammonia falsobeccarii; 18, Ammobaculites formosensis; 19, Nonionoides cf. grateloupii; 20, Fissurina lucida; 21, Fissurina cf. in the Bohai Sea have not been studied in detail before. However, marginata; 22, Lagenammina asymmetrica; 23, Psammosphaera fusca; 25, Ammonia different foraminiferal species showed different advantages in pauciloculatus; 26, Textularia foliacea; 27, Lagena spicata; 28, Amphicoryna proxima; assessing pollution status and several bioindicators were docu- 29, Nouria textulariformis; 31, Quinqueloculina polygona; 35, Textularia oceanica; 36, mented in different pollution environments. The foraminiferal Spiroloculina bohaiensis; 37, Lagena hispidula; 38, Nodosaria communis; 39, community was dominated by opportunistic species including Siphogenerina raphanus; 40, Rosalina globularis; 47, Ammonia sp.; 56, Spiroloculina planulata; 77, Ammonia ketienziensis; 78, Gyroidella planata; 80, Protelphidium sp2; Haynesina germanica, A. tepida and Cribroelphidium gunteri in heavy 89, Elphidium advenum. metal polluted sediments at the Goro lagoon in Italy (Luciani, 2007). In an African open marine slope affected by disposal of oil In the present study the abundance of small foraminifera was drill cuttings, the common foraminiferal taxa included about one order of magnitude higher than the large one, but the Chilostomella oolina and small-sized bolivinids and buliminids. living ratio was about one order of magnitude lower than that Sensitive species included Uvigerina peregrina, Cancris auriculus the large group (Table 2). It suggests that benthic foraminifera and Cribrostomoides subglobosus (Jorissen et al., 2009). Unlike may enhance their production to compensate their high mortality Italian and African sediments, the Bohai Sea is located in shallow in this area, and therefore small foraminifera responded to continental shelf in the north temperate zone. Therefore the fora- oil-pollution by high production and high mortality. This result miniferal assemblages in this region were characterized by cold was consistent with a laboratorial mesocosm study conducted in temperate and shallow water species dominating and were very an intertidal mudflat (Bay of Bourgneuf, France) where benthic for- different with the above studies. In addition, study conducted in aminifera exposed to oil-polluted seawater showed a dual an Italian Bagnoli Bay, which was heavily affected by industrial

Table 5 Spearman’s correlation between foraminiferal bioindicators and pollution factors. Data were based on total and living foraminiferal abundances in >150 lm fraction and were log (x + 1) transformed.

Species Abundance PAHs Oils Sulﬁde Organic carbon

Ammoglobigerina globigeriniformis Total 0.517(0.154) 0.567(0.112) 0.650(0.058) 0.778(0.014)⁄ Living 0.500(0.170) 0.633(0.067) 0.533(0.139) 0.561(0.116) Buccella frigida Total 417(0.265) 0.850(0.004)⁄⁄ 0.483(0.187) 0.410(0.273) Living 0.383(0.308) 0.533(0.139) 0.233(0.546) 0.301(0.431) Cribrononion asiaticum Total 0.367(0.332) 0.800(0.010)⁄⁄ 0.617(0.077) 0.594(0.092) Living 0.008(0.983) 0.866(0.003)⁄⁄ 0.227(0.557) 0.072(0.854) Cribrononion incertum Total 0.100(0.798) 0.633(0.067) 0.317(0.406) 0.276(0.472) Living 0.267(0.488) 0.417(0.265) 0.567(0.112) 0.427(0.252) Elphidium macellum Total 0.250(0.516) 0.683(0.042)⁄ 0.567(0.112) 0.678(0.045)⁄ Living 0.050(0.898) 0.717(0.030)⁄ 0.283(0.460) 0.477(0.194) Quinqueloculina ungeriana Total 0.267(0.488) 0.350(0.356) 0.200(0.606) 0.033(0.932) Living 0.067(0.865) 0.033(0.932) 0.167(0.668) 0.351(0.354) Verneuilinulla advena Total 0.126(0.748) 0.678(0.045)⁄⁄ 0.209(0.589) 0.118(0.763) Living 0.077(0.845) 0.928(0.000)⁄⁄ 0.162(0.678) 0.205(0.596)

Abundance (ind. 10cm-2) pollution tolerant and opportunistic taxa. This result is consistent 90 Ammoglobigerina globigeriniformis Living with Mojtahid et al. (2006) in which they observed the lowest ben- Total thic foraminiferal density at sites within the immediate vicinity of 45 oil-polluted, but high density at sites within the intermediate vicinity and then decreased. Alve (1995) pointed out the character- 700 istic features of foraminiferal assemblages in oil-polluted region Buccella frigida St26 StA8 St6 St19 St11 St36 St22 St14 St31 that proximal areas included decreased diversity and increased dominance of tolerant or opportunistic species compared to dis- 35 tant areas. In the present study, the pollutant resistant species and oppor- 400 Cribrononion asiaticum tunistic species were identified through cluster analysis and CCA. St26 StA8 St6 St19 St11 St36 St22 St14 St31 Cluster analysis grouped common and dominant species among 20 stations and CCA identified species affected the most by oil pollution. Among the dominant species, the sensitive taxon, C. magellan- 600 icum, showed a distinct decline from the reference site (St26) to Cribrononion incertum St26 StA8 St6 St19 St11 St36 St22 St14 St31 heavily polluted stations. The pollution resistant taxa B. frigida, E. 30 macellum, C. asiaticum, V. advena increased their abundance from the low to the high oil-polluted stations. Several opportunistic species including A. globigeriniformis, C. incertum and Q. ungeriana 300 Elphidium macellum were also abundant at oil spill region but there were not statistical St26 StA8 St6 St19 St11 St36 St22 St14 St31 significant correlations with oils (Table 5). Information at species 15 level provides critical information in understanding the spatial variation in community parameters, and furthermore the pollution 3600 tolerant and opportunistic taxa were selected to build FIEI index. Quinqueloculina St26ungeriana StA8 St6 St19 St11 St36 St22 St14 St31 18 4.4. Using foraminiferal indices to assess the oil pollution

140 0 There were several foraminiferal indices including FIEI St26Verneuilinulla StA8 St6 advena St19 St11 St36 St22 St14 St31 (Mojtahid et al., 2006), Foraminiferal Abnormality Index (AI, 7 Coccioni et al., 2005) and Foraminifera in Reef Assessment and Monitoring Index (FI, Hallock et al., 2003). Since oil pollution often 0 has severe biotoxicity and bioaccumulation and exerted compre- St26 StA8 St6 St19 St11 St36 St22 St14 St31 hensive impacts on marine organisms and ecosystem, it is difﬁcult

Fig. 8. Spatial distribution of the abundance (individuals 10 cm2) of bioindicators to assess pollution status among stations if only using single chem- at 9 stations. ical value. Therefore many studies attempted to selected suitable bioindicators to evaluate the pollution status of environments. The FIEI index is often region-specific because the index is based on the relative abundance of the selected indicator species, discharge documented several pollution tolerant benthic forami- i.e., pollution-tolerant and opportunistic taxa. According to niferal species, among them E. macellum is capable of tolerating Mojtahid et al. (2006) and Denoyelle et al. (2010), the the presence of PAHs (Bergamin et al., 2003). pollution-resistant taxa and opportunistic taxa were identified In the present study, the abundance of both total fauna and liv- based on their spatial patterns. FIEI index was therefore corre- ing fauna were high at stations with intermediate concentration of sponded to the accumulated percentage of opportunistic and oil pollutants (e.g. St11 and St22) but relatively low at the refer- stress-tolerant taxa. By using the cumulative percentage of ence site (St26), indicating an oil-philic property of benthic forami- pollution-tolerant and opportunistic taxa, the FIEI can also reflect nifera. High abundance could be attributed to the increase of pollution stress at an elevated level. Denoyelle et al. (2010) showed

Ammoglobigerina Buccella Cribrononion Cribrononion Elphidium Quinqueloculina Verneuilinulla globigeriniformis frigida asiaticum incertum macellum ungeriana advena 0-2 cm

2-4 cm

4-6 cm

6-8 cm

8-10 cm

Sediment depth 10-12 cm

12-14 cm

14-16 cm 00 25 2550 0 30 0 10 0 30 0 75 0 20 0 5 10 Mean abundance (ind. 10cm-2)

Fig. 9. Vertical distribution of foraminiferal indicator species (Ammoglobigerina globigeriniformis, Buccella frigida, Cribrononion asiaticum, Cribrononion incertum, Elphidium macellum, Quinqueloculina ungeriana, Verneuilinulla advena) in each sediment depth. Data were based on the average value of species abundances across 9 stations within the same sediment depth interval.

Table 6 Foraminiferal Impact of Environmental Index (FIEI) values in sediment depths based on the abundance of foraminiferal bioindicators in >150 lm size fraction. The Bioindicators included the following resistant taxa: Buccella frigida, Elphidium macellum, Cribrononion asiaticum, Verneuilinulla advena, and the following opportunistic taxa: Ammoglobigerina globigeriniformis, Cribrononion incertum, Quinqueloculina ungeriana. Note that 40 < FIEI was considered no polluted, 60 < FIEI < 80 was moderately polluted, FIEI > 80 was severely polluted.

Sediment depths (cm) Abundance of indicators St26 StA8 St6 St19 St11 St36 St22 St14 St31 0–2 Total individuals 38.65 58.65 50.99 47.26 49.17 52.84 53.46 64.51 66.74 Living individuals 33.59 64.83 60.08 60.90 72.44 64.61 57.14 60.19 88.73 2–4 Total individuals 21.04 49.14 41.79 – 35.56 44.59 48.88 – 57.67 4–6 Total individuals 28.64 44.13 41.50 – 37.37 41.94 47.84 – 64.81 6–8 Total individuals 26.79 45.08 42.34 – 41.90 46.06 43.32 – 59.85 8–10 Total individuals 27.27 – 37.09 – 42.01 37.61 35.74 – – 10–12 Total individuals 27.21 – 38.82 27.98 38.35 – 45.03 42.76 – 12–14 Total individuals – – 38.33 34.17 29.27 – – 43.49 – 14–16 Total individuals – – 33.76 32.93 – – – – –

that the FIEI index was effective in assessing oil-pollution. 80 However, constructing an FIEI index requires a detailed back- St26 StA8 St6 ground investigation of local fauna and selection of foraminifera 70 St19 St11 St36 as indicator species. In the present study, the study sites reﬂected St22 St14 St31 60 different levels of pollution and the spatial extent, both horizon- tally and vertically, of the samples provide adequate background 50 information for the selection of indicator species. Denoyelle et al. 40 (2010) suggested that an FIEI value within 40–50 indicated a low degree of environmental stress, and a value above 60 indicated a 30

strong environmental impact of oil pollution. In the present study, of Impact Foraminiferal Index Environmental based on the horizontal and vertical distribution of benthic forami- 20 nifera, we classified the pollution status in Bohai Sea using the 10 selected indicators into four categories: FIEI < 40 means unpolluted; 40 < FIEI < 60 means lightly polluted; 60 < FIEI < 80 means 0 0-2cm 2-4cm 4-6cm 6-8cm 8-10cm 10-12cm 12-14cm 14-16cm moderately polluted; FIEI > 80 means severely polluted. Although the classification based on FIEI is somewhat arbitrary, Fig. 10. Values of the Foraminiferal Impact of Environmental Index (FIEI) in the pollution status is consistent with the observed pollutant con- sediment depths based on resistant and opportunistic bioindicators of foraminifera centrations and other community parameters including density, at the 9 stations sampled in the Bohai Sea in 2011. diversity and species composition of the total and living fauna and abnormal specimens. Based on our FIEI calculation result (Table 6), St26 could be considered unpolluted (FIEI < 40), the fol- like any other indices, it is not an easy task to construct a lowing 6 stations including St6, St19, St11, St22, St36 and StA8 region-specific FIEI index, because it requires background informa- were lightly polluted (40 < FIEI < 60); St14 were moderately pol- tion on species composition and changes in abundance and it also luted (FIEI > 60). St31 could be considered moderately to severely needs to adjusted and verified over time to reflect local foraminif- polluted (FIEI > 60 based on total foraminifera, or FIEI > 80 based eral fauna. on living fauna). The most significant advantage using foraminifera as bioindicators is that this organism reflects sediment dynamics. They also 5. Conclusion records environmental information of ambient water and deposition in respective stratums, providing a dynamic archive of the The present study demonstrates the potential of utilizing ben- local environmental changes. Engle (2000) suggested that the ideal thic foraminifera to evaluate environmental changes using samples bioindicator would not only quantify the present environmental collected near the 2011 oil spill site in the Bohai Sea. Based on the status in ecosystems but also document the effects of anthro- horizontal and vertical distribution of foraminifera, large size pogenic and natural stressors on the organisms over time group (>150 lm) were more sensitive to oil pollutants than the (Hallock et al., 2003). In the study area, sediment deposition rate small size group (63–150 lm fraction). The abundances of total was reported about 0.2–0.4 cm/a (Li et al., 2002, 2003). If we fauna, living fauna and abnormal specimens were all significantly assume that every 3-cm sediment corresponds to 10 year’s depo- positively correlated to oils, suggesting the presence of oil-philic sition, the FIEI index reflected environmental conditions at each foraminiferal community in the Bohai Sea, but with decreased sediment depth (Fig. 10). The FIEI appeared to decrease from sur- diversity. The variation in species composition of living foramini- face strata to deep layer. The oil exploration in the Bohai Sea fera could attribute to a combination of oils, PAHs and sulfides. started in late 1960s, corresponding to the deposition 14–16 cm However, small foraminifera appeared to respond to oil pollution depth, where the FIEI values in sediments at 14–16 cm was within differently, with an enhanced production and high mortality. The 30–40. But oil drilling started in the 1980s, corresponding to 10-cm proportion of abnormal specimens tended to be more abundant sediment depth, where FIEI was within 40–50. The largest increase at high oil-polluted sites, and it was significantly correlated with of FIEI occurred at the 8–10 cm depth at most stations, but after- PAHs, indicating a negative effect of oil spill on foraminiferal wards the values remained stable. In the surface layer most sta- community. tions evidently had the highest FIEI values, and at some stations In the present study, benthic foraminiferal species showed dif- was as high as 70. Although this was only a rough assessment, ferential response to oil pollution, and therefore they could be used the FIEI index provided us a general picture of environmental as bioindicators. Four species including B. frigida, E. macellum, C. changing expressed by foraminifera in space and time. However, asiaticum and V. advena were pollution resistant taxa. Three species

Table A1 The occurrence of the foraminiferal taxa of >150 lm fraction in different sediment strata with respective abundance (individuals 10 cm2) at the 9 sampling sites in the Bohai Sea. Note that size was measured on 5–10 randomly selected individuals for each species. Both test length and width were measured for each individual. Mean values were presented here.

Species Size (lm) Distribution in sediment strata St26 StA8 St6 St19 St11 St36 St22 St14 St31 Astrorhizida Lagenammina asymmetrica 662 304 0–2 cm – – – 1.4 – – – – – Psammosphaera fusca 485 348 0–16 cm 0.4 – 1.8 1.4 2.8 3.5 – 0.4 0.7 Textulariida Ammobaculites formosensis 498 131 0–8, 10–12 cm 2.1 – 1.4 2.8 2.8 0.7 – – 0.4 Ammoglobigerina globigeriniformis 397 339 0–16 cm 58.0 37.1 15.2 29.7 53.8 76.4 43.9 34.0 22.6 Nouria textulariformis 356 242 0–2 cm 0.7 – – – – – – – – Polskiammina asiatica 365 310 0–14 cm – – – 1.4 – – – 0.4 – Textularia foliacea 1132 513 0–2, 4–8, 10–12 cm 2.5 – 0.4 – – – – – – Textularia oceanica 459 286 0–2, 8–12, 14–16 cm – – – – – – – – – Verneuilinulla advena 317 146 0–12 cm 1.8 5.3 4.6 7.1 7.1 12.7 8.5 3.5 2.1 Miliolida Quinqueloculina bellatula 378 215 0–4, 6–12, 14–16 cm 1.8 1.4 – 0.7 – – 1.4 – 1.8 Quinqueloculina polygona 620 423 0–2, 6–8, 8–10 cm 0.4 – – – – – – – – Quinqueloculina ungeriana 763 599 0–14 cm 8.8 5.7 19.5 14.2 31.1 4.2 24.1 – 5.3 Spiroloculina bohaiensis 960 776 0–2, 2–4 cm – 0.4 – – – – 1.4 0.4 2.5 Spiroloculina planulata 800 520 0–4, 10–12 cm – – 0.4 1.4 1.4 2.8 1.4 – 0.7 Lagenida Amphicoryna proxima 1100 290 0–2, 6–8 cm 0.4 – – – – – – – – Fissurina cf. marginata 273 207 0–4, 6–10 cm 1.8 – 0.7 1.4 2.8 – – – – Fissurina lucida 139 97 0–2, 12–14 m – – – 0.7 – – – – – Lagena hispidula 203 163 0–2, 2–4, 4–6 cm – – – – – – – – 0.4 Lagena spicata 280 174 0–10, 12–14 cm 1.1 0.4 – – 1.4 1.4 – – – Nodosaria communis 549 174 0–2, 4–6, 14–16 cm – – – – – – – 0.4 – Rotaliida Ammonia falsobeccarii 418 365 0–16 cm – 0.4 2.8 2.8 2.8 2.8 – – 0.7 Ammonia inﬂata 262 235 0–2, 4–16 cm 0.4 0.4 5.0 10.6 14.2 7.1 9.9 – – Ammonia ketienziensis 275 262 0–16 cm 0.4 0.4 – – – – – – – Ammonia pauciloculatus 250 220 0–16 cm 8.1 4.2 0.7 – – 6.4 11.3 1.8 2.8 Ammonia sp. 250 225 0–2, 4–8, 14–16 cm – 0.4 – – – – – – – Ammonia tepida 311 289 0–16 cm 6.4 1.8 7.8 9.2 14.2 7.8 8.5 4.2 4.2 Buccella frigida 295 264 0–16 cm 44.6 38.6 27.2 47.4 62.3 55.9 56.6 36.4 18.7 Cribroelphidium magellanicum 247 213 0–16 cm 224 58.7 56.9 97.6 132 109 97.6 50.9 26.2 Cribrononion asiaticum 269 227 0–16 cm 12.0 11.0 7.1 11.3 19.8 31.8 29.7 7.8 3.5 Cribrononion incertum 340 262 0–16 cm 21.6 23.7 26.2 33.3 55.2 51.6 49.5 28.3 40.0 Elphidium advenum 430 390 0–16 cm 1.4 0.4 1.4 1.4 1.4 1.4 1.4 – 0.4 Elphidium macellum 470 430 0–16 cm 27.9 10.6 18.7 9.9 21.2 24.1 28.3 13.4 9.2 Gyroidella planata 260 230 0–2, 8–10 cm 11.7 6.4 7.1 11.3 12.7 19.8 19.8 – 1.8 Nonionoides cf. grateloupii 246 168 0–4, 8–10, 12–14 cm 0.4 – 0.7 1.4 – – – – – Protelphidium sp.1 249 214 0–2, 4–6 cm 0.4 0.7 0.7 0.7 7.1 – – 0.4 0.4 Protelphidium sp.2 370 335 0–2 cm – – 7.4 – – 2.8 4.2 – – Pseudoeponides japonicus 239 222 0–12 cm – – 7.4 – – 0.7 – – – Rosalina globularis 262 239 0–2, 4–6 cm – 0.4 – – – – – – – Rotalidium annectens 510 457 0–16 cm 4.2 8.5 4.6 4.2 17.0 14.2 15.6 5.3 – Rotalinoides compressiusculus 362 335 0–16 cm 5.3 7.1 3.9 9.9 25.5 16.3 18.4 1.1 4.2 Siphogenerina raphanus 610 192 0–2 cm – – – – – – – 0.4 –

Table A2 The occurrence of the foraminiferal taxa of 63–150 lm fraction in sediment strata with respective abundance (individuals 10 cm2) at the 9 sampling sites in the Bohai Sea. Note that size was measured on 5–10 randomly selected individuals for each species. Both test length and width were measured for each individual. Mean values were presented here.

Species Size (lm) St26 StA8 St6 St19 St11 St36 St22 St14 St31 Textulariida Ammoglobigerina globigeriniformis 210 180 101.9 113.2 181.1 203.7 271.6 135.8 90.5 45.3 11.3 Ammoscalaria pseudospiralis 215 140 – – 45.3 – 90.5 22.6 22.6 – 11.3 Cribrostomoides jeffreysii 120 100 – – 90.5 22.6 – 45.3 22.6 – – Polskiammina asiatica 95 90––––––11.3 – – Textularia oceanica 245 205 11.3 – ––––––– Verneuilinulla advena 270 125 418.8 271.6 316.9 226.4 271.6 271.6 113.2 22.6 11.3 Miliolida Quinqueloculina bellatula 360 165 – – 22.6 –––––11.3 Quinqueloculina ungeriana 260 180 – – 45.3 – 181.1 – 11.3 – – Lagenida Fissurina cf. marginata 140 100 – 22.6 – 22.6 – – – – 11.3 Lagena substriata –––––––11.3 – Rotaliida Ammonia beccarii 165 125––––––34.0 – – Ammonia falsobeccarii 210 180 – 22.6 – – – 22.6 – – – Ammonia inﬂata 190 160 – – 45.3 22.6 – – 22.6 – – Ammonia ketienziensis 220 210 – 67.9 – 22.6 271.6 67.9 22.6 11.3 – Ammonia pauciloculatus 200 195 22.6 22.6 – 22.6 – 45.3 – 22.6 90.5 Ammonia sp. 170 160 271.6 181.1 113.2 226.4 452.7 158.5 147.1 135.8 237.7 Ammonia tepida 200 170 – – – – – 45.3 11.3 – – Bolivina robusta 280 160 45.3 – 22.6 – 90.5 22.6 – – – Bolivina striatula 290 130 34.0 – – – – 22.6 – 22.6 22.6 Buccella frigida 200 195 – 90.5 90.5 271.6 362.2 158.5 181.1 45.3 56.6 Bulimina marginata 170 145 22.6 – – 22.6 – – – – – Cribroelphidium magellanicum 205 180 1675 1517 1494 2626 3893 2988 1652 1607 1234 Cribrononion asiaticum 215 175 45.3 90.5 ––––22.6 22.6 – Cribrononion incertum 180 155 79.2 67.9 90.5 22.6 – 22.6 67.9 56.6 90.5 Elphidium advenum 225 190 67.9 67.9 – 22.6 181.1 22.6 56.6 34.0 – Elphidium macellum 330 280––––––––11.3 Globocassidulina subglobosa 90 80 – – 22.6 –––––– Gyroidella planata 175 160 – 22.6 22.6 – – – 11.3 – – Gyroidina orbicularis 160 120 – – – 22.6 90.5 – – – – Hopkinsina atlantica 200 95 79.2 – 113.2 – – 45.3 34.0 56.6 11.3 Murrayinella globosa 125 120 11.3 – 45.3 – – 22.6 45.3 56.6 45.3 Natlandia secasensis 155 130 – – – – – 22.6 – 11.3 – Nonionella stella 200 125 – – – – – 22.6 – – – Protelphidium sp.2 200 180 34.0 158.5 22.6 113.2 633.8 90.5 90.5 79.2 67.9 Pseudoeponides japonicus 180 140––––––34.0 22.6 – Rotalidium annectens 200 180 11.3 – 22.6 22.6 – – – 11.3 – Rotalinoides compressiusculus 125 145 – – – 22.6 – – 11.3 – 11.3

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