Seasonal and spatial characteristics of the macrobenthic community in the South Yellow Sea were studied based on data from three voyages carried out in spring, summer and autumn, 2012. Twenty six stations were sampled and divided into three regions (west, middle and east region of South Yellow Sea). A total of 218 species were obtained with Polychaeta and Crustacea being the predominant groups. Mean abundance varied from 151.4 ind. m−2 in spring to 188 ind. m−2 in autumn showing an increasing trend with season, and mean biomass ranged from 12.1 g m−2 in spring to 33.4 g m−2 in summer. Mean secondary productivity varied from 0.21 g (AFDW)/(m2·month) in spring to 0.48 g (AFDW)/(m2·month) in summer. Biomass was significantly different among seasons, and number of species, secondary productivity and Shannon-Weiner index had significant differences among regions. Abundance, Pielou's evenness index and average taxonomic distinctness were not significantly different among seasons nor regions. Overall significant differences of community structure among both seasons and regions were detected. Depth and the distance from shore were important factors influencing the distribution of macrobenthos in South Yellow Sea.

Introduction

Macrobenthos play an important role in coastal marine systems. Most marine macrobenthic species are slow-moving and produce considerable changes to the sediment both physically and chemically, especially in the water-sediment interface (Shou et al., 2009). Macrobenthos promote organic matter decomposition, nutrient recycling and transferring within marine foodwebs (Carvalho et al., 2007). They are important food for the higher trophic animals in a marine ecosystem (Seitz et al., 2009) and can act as indicators of the deterioration of a marine environment (Wildsmith et al., 2011). Thus, numerous studies on the temporal and spatial distribution and community structure of marine macrobenthos have been conducted worldwide (Thatje and Mutschke, 1999; Mutlu et al., 2010; Kodama et al., 2012).

Biodiversity and ecological studies of macrobenthos in Yellow Sea started in 1950s (Li et al., 2014). Since then, the Yellow Sea has been investigated intensively. Previous studies carried out in Yellow Sea mainly focused on the species composition, numerical abundance, biomass, secondary productivity, dominant species, diversity and community structure of macrobenthos (Liu and Hsu, 1963; Liu and Li, 2003; Li et al., 2005a; Wang et al., 2007; Xu et al., 2009; Zhang et al., 2012; Peng et al., 2014). However, the seasonal and spatial changes of macrobenthic community and diversity in South Yellow Sea were rarely studied simultaneously.

This study aims to analyze the macrobenthic community parameters (number of species, numerical abundance, biomass and secondary productivity) and diversity (Margalef richness index, Shannon-Wiener index, Pielou's evenness and average taxonomic distinctness) both seasonally and spatially in South Yellow Sea.

Materials and methods

Study area and sampling design

South Yellow Sea is located between the mainland of China and the Korean Peninsula (Figure 1) and it has an area of about 3.0 × 105 km2 with a depth of 44 m on average (Zhang et al., 2012). The hydrological regime of South Yellow Sea is mainly influenced by the Yellow Sea Cold Water Mass (YSCWM), the Yellow Sea mixed water and the Yellow Sea Coastal Water from offshore to inshore (Peng et al., 2014). The southwest margin of the study area is adjacent to the estuaries of Yangtze River and Huaihe River, so freshwater inputs also influence the study area. Based on the depth of water (40 m and 70 m), the study area was divided into three regions, which were labeled west (WR), middle (MR) and east region (ER) of South Yellow Sea, respectively.

Figure 1.

Sampling stations of macrobenthos in South Yellow Sea (WR: west region; MR: middle region; ER: east region of South Yellow Sea).

Figure 1.

Sampling stations of macrobenthos in South Yellow Sea (WR: west region; MR: middle region; ER: east region of South Yellow Sea).

Duplicate benthic samples were collected at each station with a modified 0.1 m2 Gray-O' Hara box-corer during June, August and October, 2012. Samples were processed through a 0.5 mm mesh sieve in the field and the retained fractions were preserved in 75% ethanol. In the laboratory, samples were sorted after being stained with Rose Bengal, then identified to the lowest taxonomic level, counted for numerical abundance and weighed for biomass (wet blotted weight; shells included for Mollusca).

Data analysis

For each sample, number of species, numerical abundance (hereforth called abundance), biomass, secondary productivity, Margalef richness index (D), Shannon-Wiener index (H′, base = 2), Pielou's evenness (J′) and average taxonomic distinctness (Δ+) were calculated.

The secondary productivity (g(AFDW)/(m2·a)) was calculated based on the empirical formula from Brey (1990):
formula

B = biomass in “g(AFDW)/m2”; W = mean “g(AFDW)/ind” of total individuals at a station.

Recognizing that W = B/A (A = abundance (ind m−2)), the equation above can be transformed into:
formula

converted to g(AFDW)/(m2·month) in this study (Li et al., 2005a,b).

Average taxonomic distinctness (Δ+) was calculated using the formula from von Euler and Svensson (2001):
formula

s = number of species at a station; dij = taxonomic distance between species i and species j. We determined dij using 6 taxonomic levels: 16.67 (between congeneric species), 33.33 (between species in different genera), 50 (families), 66.67 (orders), 83.33 (classes), 100 (phyla).

Seasonal and spatial variations in these benthic parameters were analyzed through two-way ANOVA (Analysis of variance) via general linear models (GLM) techniques using SPSS (version 16). To approach normality (Kolmogorov-Smirnov test) and homogeneity of variances (Levene's test), abundance and biomass were transformed using ln(x+1). Tukeys HSD for unequal number of samples was used to perform post hoc comparison of means if no significant interaction existed in ANOVA (Catalan et al., 2006). Secondary productivity was analyzed using the Kruskal-Wallis test for the failure in the test of homogeneity of variances. The Mann-Whitney U test was then performed for pairwise test if significant differences were detected in Kruskal-Wallis test.

To explore the differences of macrobenthic communities among seasons and regions in South Yellow Sea, two-way crossed ANOSIM (analysis of similarity) were conducted. Before conducting this analysis, Bray-Curtis similarity matrices were constructed based on square-root transformed pooled abundance data (Clarke and Warwick, 1994). Species in each voyage with a frequency of occurrence less than 5% (Almeida et al., 2008) or collected only from one station were excluded from analysis to minimize effects of rare species. Species contributions to the Bray-Curtis similarity in each season or region were analyzed by SIMPER (similarity percentages). The multivariate analysis mentioned above was performed using PRIMER (version 5).

Results

Composition and number of species

In total, 218 macrobenthic taxa were recorded during three voyages in South Yellow Sea. Polychaeta and Crustacea were the predominant groups, followed by Mollusca, with 80 species of Polychaeta, 75 Crustacea, 35 Mollusca, 15 Echinodermata and 13 species in other groups (Cnidaria, Sipuncula, Nemertea, etc.).

Total species number of each voyage showed an increasing trend, with 83 species in spring, 113 species in summer and 129 species in autumn. The percentage of species in each major group in each voyage was nearly constant (Figure 2). Two-way ANOVA (i.e. the factors of seasons and regions) showed that average species number (species/station) has no significant differences in seasons (F2, 53 = 3.03, P = 0.06) but regions were different (F2,53 = 19.58, P < 0.01) (Figure 3). Multiple post hoc Tukey tests for unequal numbers indicated that average species number in WR was significantly higher than others (unequal HSD, P < 0.05).

Figure 2.

The seasonal percentage of species in each major group in South Yellow Sea.

Figure 2.

The seasonal percentage of species in each major group in South Yellow Sea.

Figure 3.

Seasonal and regional distribution of macrobenthos species, richness (D), diversity (H′), evenness (J′), abundance, biomass, secondary productivity and average taxonomic distinctness (Δ+) in South Yellow Sea (WR: west region; MR: middle region; ER: east region of South Yellow Sea).

Figure 3.

Seasonal and regional distribution of macrobenthos species, richness (D), diversity (H′), evenness (J′), abundance, biomass, secondary productivity and average taxonomic distinctness (Δ+) in South Yellow Sea (WR: west region; MR: middle region; ER: east region of South Yellow Sea).

Abundance, biomass and secondary productivity

Specific abundance of each station ranged from 20 to 550 ind. m−2 in the spring voyage (mean abundance = 151.4 ind. m−2), from 50 to 1140 ind. m−2 in summer (184.0 ind. m−2), and from 45 to 785 in autumn (188.0 ind. m−2), with mean abundance showing an increasing trend with season. Polychaeta accounted for the highest percentage of total abundance in each season (52.3%, 39.6% and 53.8% from spring to autumn). For abundance, no significant differences in seasons (F2, 53 = 1.04, P = 0.36) or in regions (F2, 53 = 1.90, P = 0.16) were observed in two-way ANOVA test (Figure 3).

Biomass varied from 0.3 to 57.3 g m−2 in the spring voyage (mean biomass = 12.1 g m−2), from 0.2 to 234.6 g m−2 in summer (33.4 g m−2), and from 0.5 to 73.9 g m−2 in autumn (21.0 g m−2). Mollusca exhibited the highest percentage in spring (45.2% of total biomass), and Echinodermata in summer and autumn (62.1% and 32.8%, respectively). For biomass, significant differences among seasons (F2, 53 = 3.37, P = 0.04) were found but not among regions (F2, 53 = 0.03, P = 0.97) in two-way ANOVA test (Figure 3). However, in multiple post hoc Tukey tests no significant seasonal differences were detected for biomass.

Secondary productivity ranged from 8.3×10−3 to 0.9 g(AFDW)/(m2·month) in spring (mean secondary productivity = 0.21 g(AFDW)/(m2·month)), from 8.3×10−3 to 3.5 g(AFDW)/(m2·month) in summer (0.48 g(AFDW)/(m2·month)), and from 1.67×10−2 to 1 g(AFDW)/(m2·month) in autumn (0.34 g(AFDW)/(m2·month)). No significant differences in seasons (x2 = 4.77, df = 2, P = 0.09) were detected but in regions (x2 = 12.04, df = 2, P < 0.01) in non-parametric Kruskal-Wallis test for secondary productivity. In Mann-Whitney U test we found that secondary productivity in MR was significantly higher than WR (P = 0.02) and ER (P < 0.01).

Diversity

Margalef richness index (D) of macrobenthos was not significantly different among seasons (F2, 53 = 1.95, P = 0.15) but among regions (F2, 53 = 22.34, P < 0.01) (Figure 3). Multiple post hoc Tukey tests showed that D in WR was significantly higher than others (unequal HSD, P < 0.01). The result of the Shannon-Weiner index (H′) was similar with D, and was not significantly different among seasons (F2, 53 = 1.89, P = 0.16) but among regions (F2, 53 = 12.64, P < 0.01). Multiple post hoc Tukey tests indicated that H′ in WR was significantly higher than others (unequal HSD, P < 0.01). Pielou's evenness index (J′) was not significantly different among either seasons (F2, 53 = 0.03, P = 0.97) or regions (F2, 53 = 1.67, P = 0.20). Average taxonomic distinctness (Δ+) had no significant difference among either seasons (F2,53 = 0.63, P = 0.54) or regions (F2,53 = 2.27, P = 0.11). All of these diversity indexes showed a decrease and then increase trend from inshore to the offshore at the depth range between 24 and 81 m (Figure 3), which indicated that depth and the distance from shore were important factors influencing the macrobenthos in South Yellow Sea.

Macrobenthic community structure

Performed on the pooled abundance matrix, two-way crossed ANOSIM (i.e. the factors of seasons and regions) indicated overall significant differences among seasons (Global R = 0.12, P < 0.01) and regions (Global R = 0.39, P < 0.01). Pairwise tests showed that summer group was significantly different from autumn group (R = 0.19, P < 0.01), and groups of three regions were significantly different from each other (WR-MR, R = 0.20, P < 0.01; MR-ER, R = 0.20, P < 0.01; WR-ER, R = 0.63, P < 0.01).

Dominant species (contribution ≥ 10%) of each seasonal and spatial group were identified using the SIMPER analysis. Ophiura sarsii vadicola and Ninoe palmata dominated in spring (24.77% and 16.36% of contribution, respectively); O. sarsii vadicola, N. palmata and Ophelina acuminate in summer (25.41%, 20.61% and 14.53%, respectively); Thyasira tokunagai and O. sarsii vadicola in autumn (23.67% and 20.40%, respectively). In WR, N. palmata and Notomastus latericeus were identified as the dominated species (21.24% and 10.84%, respectively); in MR, O. sarsii vadicola, O. acuminate and N. palmata dominated (37.90%, 14.03% and 13.68%, respectively); in ER, O. sarsii vadicola and T. tokunagai were the dominant species (34.53% and 17.22%, respectively).

Discussion

Species composition

In this study, a total of 218 taxa were recorded when pooled the data from three voyages together. Total species number of each voyage showed an increasing trend with season in South Yellow Sea. This trend could also be seen in the year 2011 (Li et al., 2014), but not during 1998–2000 (Tang, 2006). Species number showed high variance from 1950s to 2012 (Table 1), with the highest (414 species) in the combined surveys of 1998–2000 and the lowest (83 species) in June 2012 in this study. Beside the complex physical and chemical conditions in South Yellow Sea, the sample methods may also influence the investigation result. It was found that the number of species collected using the 0.5 mm mesh was higher than that when using a 1 mm mesh (Li et al., 2005c). But the composition of main species using the 0.5 mm mesh varied little from that when using a 1 mm mesh. Other reports showed that spatial patterns of species collected using the 0.5 mm mesh varied little from that using a 1 mm mesh (James et al., 1995), while many of the additional individuals between 0.5 mm mesh and 1 mm mesh may be just the juvenile forms of macrobenthos (Zhang et al., 2012).

Table 1.

Number of macrobenthos species in Yellow Sea from 1950s to 2012.

Number of species
RegionSampling dateSitesMesh (mm)Pol.Cru.Mol.Ech.Oth.Tol.Reference
YS 1950s   112 118 37   Liu and Hsu, 1963  
SYS 1992.9 28 58 38 30 142 Zhang et al., 2012  
YS 1998.5   125 52 47 13 10 247 Tang, 2006  
 1999.9   88 54 19 11 181  
 1999.12   92 34 30 13 178  
 2000.8   103 41 46 206  
YS 1998–2000   194 90 86 21 23 414 Li, 2003  
SYSA 2000.10, 2001.3 17 0.5 84 83 76 29 272 Liu and Li, 2003  
SYS 2001.3 18 0.5 46 36 23 10 120 Li et al., 2014  
SYS 2001.8, 2002.8,9,10 10 0.5 54 66 29 17 16 182 Wang et al., 2007  
SYS 2006.7–8 130 0.5 122 22 33 192 Xu et al., 2009  
SYSB 2007.10 24 0.5 68 30 31 120 Fan et al., 2010  
SYS 2008.9–10 40 0.5 46 13 19 12 95 Jia et al., 2010  
SYS 2011.4 28 0.5 61 26 24 10 10 131 Li et al., 2014  
 2011.8 28 0.5 58 33 26 13 136  
SYS 2012.6 18 0.5 39 20 14 83 Present study 
 2012.8 21 0.5 49 29 19 11 113  
 2012.10 23 0.5 55 39 23 129  
 2012.6,8,10 23 0.5 80 75 35 15 15 218  
Number of species
RegionSampling dateSitesMesh (mm)Pol.Cru.Mol.Ech.Oth.Tol.Reference
YS 1950s   112 118 37   Liu and Hsu, 1963  
SYS 1992.9 28 58 38 30 142 Zhang et al., 2012  
YS 1998.5   125 52 47 13 10 247 Tang, 2006  
 1999.9   88 54 19 11 181  
 1999.12   92 34 30 13 178  
 2000.8   103 41 46 206  
YS 1998–2000   194 90 86 21 23 414 Li, 2003  
SYSA 2000.10, 2001.3 17 0.5 84 83 76 29 272 Liu and Li, 2003  
SYS 2001.3 18 0.5 46 36 23 10 120 Li et al., 2014  
SYS 2001.8, 2002.8,9,10 10 0.5 54 66 29 17 16 182 Wang et al., 2007  
SYS 2006.7–8 130 0.5 122 22 33 192 Xu et al., 2009  
SYSB 2007.10 24 0.5 68 30 31 120 Fan et al., 2010  
SYS 2008.9–10 40 0.5 46 13 19 12 95 Jia et al., 2010  
SYS 2011.4 28 0.5 61 26 24 10 10 131 Li et al., 2014  
 2011.8 28 0.5 58 33 26 13 136  
SYS 2012.6 18 0.5 39 20 14 83 Present study 
 2012.8 21 0.5 49 29 19 11 113  
 2012.10 23 0.5 55 39 23 129  
 2012.6,8,10 23 0.5 80 75 35 15 15 218  

YS: the Yellow Sea; SYS: the South Yellow Sea; Pol.: Polychaeta; Cru.: Crustacea; Mol.: Mollusca; Ech.: Echinodermata; Oth.: Other species; Tol.: Total number of species.

A

Pooled with data from Agassiz trawl.

B

Sampling in the sea adjacent to Subei Shoal.

In most studies listed in Table 1, the number of Polychaeta was the highest and followed by Crustacea. This phenomenon has also been detected in the East China Sea (Li et al., 2014), Andaman Sea (Ansari et al., 2012), the India coast (Jayaraj et al., 2008), the southern Gulf of Mexico (Hernandez-Arana et al., 2003), the south Patagonian Ice-Field (Thatje and Mutschke, 1999) and many other places. In our study, when data of three voyages were pooled over the whole year, the percentage of Crustacea increased and was only 5 species less than the number of Polychaeta. Pooled the macrobenthos data from four voyages together, Wang et al. (2007) found that the percentage of Crustacea was even higher than Polychaeta. These results indicated the high variance of Crustacea in different voyages, perhaps because the more mobile Crustacea migrate into the survey area at different times of the year in respose to changing temperatures and they have the high ability to escape (Faulkes, 2008).

Abundance, biomass and diversity

Abundance of macrobenthos in this study showed an increasing trend with season and this trend was also detected in 2001 and 2011 (Li et al., 2014) in South Yellow Sea. The abundance changes could be explained by the recruitment and mortality patterns of macrobenthos (Holland et al., 1987), and recruitment success could lead to the increase of the number of polychaete and crustacean larvae (Li et al., 2002). Compared with the result in August 2001 and 2011, mean abundance in August 2012 declined seriously, with 172.25 and 49.83 ind. m−2 less than during the year 2001 and 2011, respectively (Li et al., 2014). The temporal variation of macrobenthic abundance had also been reported in Jiaozhou Bay (Wang et al., 2011) and Yangtze River estuary (Chao et al., 2012; Liu et al., 2012; Shou et al., 2013), which were adjacent to South Yellow Sea. Biomass showed significant differences in seasons in two-way ANOVA test (P = 0.04), but not in multiple post hoc Tukey tests. Compared with the result in August 2001 and 2011, mean biomass in August 2012 increased, with 5.76 and 10.05 g m−2 more than during the year 2001 and 2011, respectively (Li et al., 2014). This was because at station E2, a lot of Ophiopholis mirabilis were collected and its biomass accounted for 32.44% of total biomass in August 2012. Ignoring O. mirabilis at station E2, mean biomass would be 22.56 g m−2, and would be 5.08 and 0.79 g m−2 less than during the year 2001 and 2011, respectively (Li et al., 2014). Diversity of macrobenthic community showed a decrease and then increase trend from inshore to offshore, and this trend in the same depth range had also been found in the northwest Indian shelf (Jayaraj et al., 2007). This indicated that depth (Peng et al., 2014) and the distance from shore were important factors influencing the macrobenthos in South Yellow Sea.

Macrobenthic community structure

Liu et al. (1986) classified the macrobenthic community in South Yellow Sea into the following categories: coastal, transitional and cold water using the 1950s grab data which used a 1 mm mesh sieve. Zhang et al. (2012) classified the macrobenthic community as: eurythermal, mixed and Yellow Sea Cold Water Mass (YSCWM) using grab data from September 1992 which also used a 1 mm mesh sieve. In this study, we also classified the macrobenthic community into three groups (WR group, MR group and ER group, which were equivalent to Liu's and Zhang's three communities with their locations from inshore to offshore) using 2012 grab data which used a 0.5 mm mesh sieve.

The dominant species in WR changed from Scapharca, Nassarius and sea urchin (Mollusca and Echinodermata) in 1950s (Liu et al., 1986), and Praxillella praetermissa, Sternaspis scutata, Praxillella pacifica, and Glycera chirori (Polychaeta with big body size) in 1992 (Zhang et al., 2012), to N. palmata and N. latericeus (Polychaeta with small body size) in 2012. Small species with short life cycles (small Polychaeta) had replaced big species with long life cycles (Mollusca, Echinodermata and large Polychaeta) in WR between 1950 and 2012. In the inshore area of Yangtze River estuary, which is adjacent to WR in South Yellow Sea, Shou et al. (2013) also found that small Polychaeta replaced larger sea urchins as the dominant species. It had been predicted that dominant species like S. scutata and Nassarius in Yangtze River estuary will gradually be replaced by smaller Polychaeta with the natural environment deteriorating and the human activities increasing (Liu et al., 2008). The inshore WR area of South Yellow Sea is also experiencing environmental disturbance and short-life species with high competitiveness and adaptability can adapt to the increasingly unstable environment. Thus we predict that macrobenthos living in WR area of South Yellow Sea will become smaller and have short life cycles as predicted in Yangtze River estuary (Liu et al., 2008). In MR, dominant species in 2012 (e.g. O. sarsii vadicola, O. acuminate and N. palmata) were also different from those in 1950s (e.g. Ditrupa arientina, Travisia pupa and Eunephythya sp.) (Liu et al., 1986) and those in 1992 (e.g. Terebellides stroemii and T. tokunagai) (Zhang et al., 2012). However, they were not significantly different in body size between 1950 to 2012. The species dominated in ER (e.g. O. sarsii vadicola and T. tokunagai) remained unchanged between 1950 to 2012 (Liu et al., 1986; Zhang et al., 2012). The YSCWM in ER remained stable all the year round and had a low bottom temperature in areas deeper than 40–50 m (Liu and Hsu, 1963; Weng et al., 1988). Cold water species like O. sarsii vadicola and T. tokunagai were typical species of YSCWM in South Yellow Sea. Further more, ER is the most offshore area of South Yellow Sea, and had the least human influence. As a result, the environment of ER remains stable for a typical macrobenthic community to inhabit. Thus, we predict that the stability of the environment of ER will continue and cold water species like O. sarsii vadicola and T. tokunagai will dominate the macrobenthic community in the next 50 years, unless heavy pollution or other devastating events occur at the bottom of the South Yellow Sea.

Conclusions

Number of macrobenthic species, secondary productivity and Shannon-Weiner index were significantly different among the regions of South Yellow Sea, while biomass varied among seasons. Community structures had significant differences among both seasons and regions. Depth and distance from shore were important factors influencing distribution of macrobenthos in South Yellow Sea. Since 1950, the dominant species have changed in the West Region, to small body polychaetes. Future research is needed to determine if environmental and community changes will extend further offshore to the East Region of the South Yellow Sea.

Acknowledgements

We thank Dong Dong, Gan Zhi-Bin, Kou Qi, Ma Lin, Sui Ji-Xing, Wang Jin-Bao and Wang Yue-Yun for their work in the field and laboratory. We also appreciate the valuable comments made on the manuscript by two anonymous reviewers.

Funding

This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA11020303) and the National Natural Science Foundation of China (No. 41176133).

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