Assessment of the benthic ecological status in the adjacent waters of Yangtze River Estuary using marine biotic indices

Marine Pollution Bulletin 137 (2018) 104–112

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Assessment of the benthic ecological status in the adjacent waters of Yangtze River Estuary using marine biotic indices Baochao Qiua, Xin Zhonga, Xiaoshou Liua,b, a b

T

⁎

College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China Institute of Evolution and Marine Biodiversity, Ocean University of China, Qingdao 266003, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Benthic ecological status Macrofauna Waters adjacent to Yangtze River Estuary Shannon–Wiener diversity index AMBI M-AMBI

The adjacent waters of the Yangtze River Estuary are influenced by heavy anthropogenic activities. The benthic ecological status was assessed using the Shannon–Wiener diversity index, the AZTI Marine Biotic Index (AMBI), and the multivariate AMBI (M-AMBI) based on macrofaunal data collected in this area at 51 sites in June 2013 and June 2014. In total, 321 species of macrofauna were identified. Polychaetes were the most dominant, followed by mollusks and crustaceans. The AMBI results showed that 72.55% of the sites were under slight disturbance with a decreasing disturbance trend from inshore to offshore. M-AMBI showed that most of the sites were under lower disturbance level than those shown by AMBI. The Shannon–Wiener diversity index showed that only two sites, near the Yangtze River Estuary and the Zhoushan Islands, respectively, were under moderate status. Other sites were under good or high status, which is consistent with the M-AMBI results.

As the largest river on the west coast of the Pacific Ocean, the Yangtze River plays an important role in fishery, transportation, conservation, and depuration of pollutants. Owing to its large input of freshwater, the Yangtze River brings a great amount of fresh water, sand, nutrients, and pollutants into the East China Sea (Hua et al., 2014). In addition, the water is brackish in the Estuary and in its adjacent waters. Because of the strong influence of freshwater runoff, the Yangtze River Estuary and its adjacent waters have become the most intense zones for the exchange of materials and energy between the land and the sea, and complex physical, chemical, biological, and geological processes have taken place (Lane et al., 2007). The Yangtze River Estuary is the region with the most active economic development in China. Frequent human activities have caused the nitrogen and phosphorus contents in the water to be significantly higher than those in other sea areas. The area encompassing the Estuary and its adjacent waters has become a zone in which frequent harmful algal blooms (HAB) occur in China owing to the abundant nutrients, sufficient light, and suitable temperature (Zhou et al., 2001; Wang, 2002; Huang et al., 2003). HAB organisms in toxic HAB contain or secrete toxic substances, which may damage the ecosystems, fishery resources, mariculture, and human health. Moreover, the large proliferation of non-toxic HAB organisms can also lead to excessive oxygen consumption in the sea area, which affects the living environment of marine organisms and thus destroys the ecosystem structure of the sea area (Liu et al., 2011).

Macrofauna are important components of marine ecosystems, and they respond predictably to changes in water and sediments caused by natural and anthropogenic activities. For most benthic organisms, macrofauna have high biodiversity owing to the high diversity of their habitats (Liu et al., 2014a). The living environment of benthos is relatively stable. Most species of adults live in fixed places for a lifetime or only within a limited range of the substrate surface. The avoidance of benthic animals against adversity is relatively slow. They are sensitive and show profound reaction to disturbances in the benthic environment, which make them good indicators for reflecting local environmental conditions (Stull, 1995; Thrush and Dayton, 2002; Luo and Yang, 2009; Zhang, 2011). Because the activity of benthic animals is relatively weak, the species composition and density may change according to the direct influence of human activities. The changes in local environmental factors can be inferred on the basis of changes in the abundance and biomass of macrofauna (Cai, 2003; Liu et al., 2014a). Therefore, the environmental conditions indicated by biological characteristics have been widely studied (Wilding and Nickell, 2012; Lacoste et al., 2018). Because the industrial and agricultural development in this region were rapid, the pollution caused to the marine environment gradually exceeded the self-purification ability of the ocean. The role of macrofauna in the benthic environment enables benthic organisms to be used for assessment of the environmental conditions (Tenore, 1970; Cai,

⁎ Corresponding author at: College of Marine Life Sciences and Institute of Evolution and Marine Biodiversity, Ocean University of China, 5 Yushan Road, Qingdao 266003, China. E-mail address: [email protected] (X. Liu).

https://doi.org/10.1016/j.marpolbul.2018.10.006 Received 20 August 2018; Received in revised form 19 September 2018; Accepted 2 October 2018 0025-326X/ © 2018 Elsevier Ltd. All rights reserved.

Marine Pollution Bulletin 137 (2018) 104–112

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laboratory. Samples for sediment characteristics were collected from surface sediments and were stored at −20 °C until analysis (Wang et al., 2017). The biological samples were stained with 1‰ Rose Bengal sodium salt dye 24 h prior to analysis. The macrofaunal biomass is expressed as wet weight gram per square meter; group specimens were not counted (Eleftheriou and McIntyre, 2005). The sediment organic matter content was measured by using the potassium dichromate‑sulfuric acid (K2Cr2O7-H2SO4) oxidization method (Walkley and Black, 1934). The sediment grain size was measured by using a laser particle size analyzer (Master Sizer 3000; Liu et al., 2007). The seawater characteristics including temperature, salinity, and pH were measured by using a YSI 600XLM Multi-Parameter Water Quality Sonde (YSI Inc., Yellow Springs, Ohio, USA) in situ (Wang, 2001; Zhang, 2001). The chlorophyll a (Chl-a) and phaeophorbide (Pha) were measured by using a fluorophotometer. The ship's Global Positioning System (GPS) was used to determine the location of the sampling sites. The sampling site distribution map, data statistical histogram, and pie chart were drawn by using Surfer 8.0 and Excel 2010. Pearson correlation analysis was conducted using SPSS22.0 statistics software to analyze the abundance, biomass, and environmental factors of macrofauna in the adjacent waters of the Yangtze River Estuary. The community structure was analyzed by using the clustering and BIOENV functions of the Primer 6.0 program. Data related to AMBI and M-AMBI were processed by AMBI software obtained from the AZTI Center website (http://www.azti.es). The Shannon–Wiener diversity index can effectively reflect the temporal and spatial changes of benthic communities. The formula (Sun, 2001) is

2003; Moreno et al., 2008; Bonzini et al., 2008; Liu et al., 2014b). On the basis of species composition, temporal and spatial changes of the community, and the surrounding habitat disturbances of benthic organisms, a variety of benthic organism indices has been established such as the Shannon–Wiener diversity index, AZTI Marine Biotic Index (AMBI; Borja et al., 2000), multivariate AMBI (M-AMBI), Bentix Index (Simboura and Zenetos, 2002), Benthic Quality Index (BQI; Rosenberg et al., 2004), and Marine Pollution Index (MPI) (Cai, 2003) among others. Shannon–Wiener diversity index has been used to evaluate environmental pollution status for long time (Cai et al., 2002). The AMBI method was proposed by Borja et al. (2000) at the Spanish Institute of Fisheries and Food Technology (AZTI-Tecnalia) on the basis of the biotic indices (BI) ecological model established by Glémarec and Hily (1981). It also led to the establishment of M-AMBI (Muxika et al., 2007). AMBI and M-AMBI are widely used in assessing the quality of benthic environment all over the world and they were also reported as good approaches to assess the benthic ecological quality in China seas (e.g., Cai et al., 2013; Li et al., 2017). Cai et al. (2013) assessed the benthic ecological status in Yangtze River Estuary using AMBI and MAMBI. Lu et al. (2013) also assessed the benthic ecological status in coastal area near Yangtze River Estuary using AMBI and M-AMBI. However, these studies only focused on the areas located at the coastal or inshore waters of the Yangtze River Estuary. In this study, AMBI and M-AMBI methods combined with the Shannon–Wiener diversity index were used to assess the benthic ecological status of the adjacent waters of the Yangtze River Estuary, both including the inshore and offshore waters. Samples for macrofauna and environmental factors were collected in the adjacent waters of the Yangtze River Estuary in June 2013 and June 2014 by the vessel Runjiang I. The collection range for the former year was 30.25°–32.6° N, 122°–124.5° E at 19 sites, and that for the latter was 27°–33° N, 121°–125° E. In total, 32 sites were sampled, 17 of which were sampled in both years (Fig. 1). Two replicate samples were collected by a 0.1 m2 box corer and were sieved with a 0.5 mm mesh sieve at each site. All animals were fixed in 5% buffered formalin solution and were identified in the 34° N

33°

Yellow Sea Ya

32°

ng

A1 t ze

r iv er

e st

31°

ua

ry B1

A3 A5

B2 B3

A7

C3

C9 C11 C5

C7

D5

D7

East China Sea

D2 D3

30°

29°

F1

where Pi is the proportion of the individuals of the i species in the sample. For example, if the total number of individuals in the sample is N, the number of i individuals is ni; therefore, Pi = ni/N. In addition, s is the number of benthic species collected. The H' value is equal to 0, where the absence of benthic organisms indicates serious pollution, 0–1 represents heavy pollution, 1–2 represents moderate pollution, 2–3 represents mild pollution, and values > 3 represent clean conditions (Cai et al., 2002). Glémarec and Hily (1981) established the BI ecological model, which divides the health of benthic communities into eight levels representing eight environmental quality conditions of BI = 0, where the benthic community is normal, to BI = 7, where the benthic community is inanimate; this range represents no contamination to extreme pollution, respectively (Grall and Glemarec, 1997). On the basis of this index, AMBI was built by Borja et al. (2000). The grading and the corresponding benthic ecological quality status of AMBI are shown in Table 1 (Borja et al., 2000). This index is calculated as

B9

B7

B5

D9 D11

AMBI = [(0 × EGI%) + (1.5 × EGII%) + (3 × EGIII%) + (4.5 × EGIV%)

F5

F7

28°

where EGn corresponds to the following groups: EG I is sensitive to Table 1 Classification threshold levels for benthic ecological status based on the Shannon–Wiener diversity index, AMBI, and M-AMBI (adapted from Wang et al., 2017).

F9

2013 sites

27°

2014 sites sites in 2013 and 2014

26° 120°

121°

122°

123°

124°

(2)

+ (6 × EGV%)]/100,

E1 E3 E5 E7 E9 F3

(1)

i=1

A9

C2

C1

s

H ′ = − ∑ (Pi )(log2 Pi ),

125°

126°

127° E

Fig. 1. Map of adjacent waters of the Yangtze River Estuary, indicating the sites of macrofauna sampling in June 2013 and June 2014. 105

AMBI

M-AMBI

Shannon–Wiener diversity index

Ecological quality status

< 1.2 1.2–3.3 3.3–5.0 5.0–6.0 > 6.0

> 0.77 0.53–0.77 0.38–0.53 0.20–0.38 < 0.20

>3 2–3 1–2 0–1 0

High Good Moderate Poor Bad

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Table 2 Results of correlation analysis among macrofaunal abundance, biomass, biodiversity indices, and environmental factors in June 2013 and 2014. Year

Biotic characteristics

2013

Abundance biomass

2014

S H′ AMBI M-AMBI Abundance biomass S H′ AMBI M-AMBI

Water depth 0.364 −0.094 0.604b 0.567a −0.084 0.732 0.236 −0.184 0.272 0.104 0.66 0.722

Sediment median diameter a

0.492 −0.177 0.096 −0.364 −0.320 0.182 0.304 0.132 −0.100 −0.196 0.109 0.522

Organic matter content

Sediment water content

Chlorophyll a

Pheophorbide

−0.572 0.21 −0.567a −0.176 0.124 0.614 −0.277 −0.100 −0.014 −0.050 −0.073 0.689

−0.433 0.020 −0.456a −0.158 0.142 0.563 0.149 0.240 0.155 0.187 0.099 0.590

−0.32 0.041 −0.166 −0.189 −0.205 0.400 0.026 −0.158 0.195 0.217 −0.017 0.925

−0.516a 0.138 0.671b 0.390 −0.336 0.160 −0.001 −0.034 0.333 0.277 −0.174 0.340

a

Note: S: species number; H′: Shannon–Wiener diversity index. a Correlation is significant at the 0.05 level (two-tailed). b Correlation is significant at the 0.01 level (two-tailed).

E4, D4, E5, C4, and D6. In 2014, the moderate disturbed sites were A7, C2, and F7; the light disturbed sites were A1, A3, A5, A9, B2, B3, B5, B9, C3, C5, C9, D2, D3, D7, D9, E1, E9, E7, F1, F3, F5, and F9; and the clean sites were B7, C7, C11, D5, D11, E5, and E9. The dominant species included Sternaspis scutata, Neanthes japonica, Glycera alba, Capitella capitata, Notomastus latericeus, Cossurella dimorpha, Paralacydonia paradoxa, Apionsoma trichocephala, Amphioplus japonicus, Macoma candida, Lutraria maxima, Podocerus tuberculosis, and Alpheus japonicus. In 2013, 255 species were identified, and the average abundance of macrofauna was 1077.89 ind./m2. The total average biomass of each site was 3.5 g/m2, and the dominant species were polychaetes, at 1.6 g/m2 and 45.7%. In 2014, 183 species were identified, and the average abundance of macrofauna was 153.34 ind./m2. The total average biomass of each site was 1.87 g/m2, and the dominant species were polychaetes, at 0.36 g/m2 and 19.33%. The results of BIOENV showed three important factors affecting the macrofaunal assemblages in 2013: water depth, organic matter content, and Chl-a (Coefficient = 0.697). In 2014, the important factors were water depth, sediment median diameter, silt clay content, and organic matter content (Coefficient = 0.257). Results of the benthic ecological status assessed by Shannon–Wiener diversity index (H′), AMBI and M-AMBI were shown in Appendix B. In 2013, site D2, including one species, had an H′ value of 0–1, which was under serious pollution, accounting for 2.0%. The H′ value of site B3 in 2013 and site F7 in 2014 was between 1 and 2, which was under moderate pollution level, accounting for 3.9%. At site B3, near the Yangtze River Estuary, results of both AMBI and H′ showed that it was under disturbance, and M-AMBI showed that it was under slight disturbance. Eight sites had an H′ value between 2 and 3 indicating light pollution. These sites include A1, A3, A5, A7, D9, and F5 in 2014 and C1 and C2 in 2013, accounting for 15.7%. Forty sites had H′ values > 3, indicating clean conditions. These included B2, C2, D5, and E1 in 2013 and B4, D3, and D7 in 2014, accounting for 78.4%. No sites showed AMBI = 0 (0.0 < BC ≤ 0.2). Eleven sites showed AMBI = 1 (0.2 < BC ≤ 1.2), such as Sites B9, C2, C7, C11, D9, and F5 in 2014 and B2, B3, D3, E3, and E4 in 2013, accounting for 21.57%. Of these sites, the EGI ratio of sites B9 and C2 in 2014 was higher than 60%, indicating that the environmental quality was very good. In addition, 37 sites had AMBI = 2 (1.2 < BC ≤ 3.3), accounting for 72.55%. One of the 51 sites had AMBI = 4 (3.3 < BC ≤ 4.3), accounting for about 2.0%. In 2013, site E5 had the worst environmental quality, and its environment was severely disturbed. D2 displayed inanimate behavior in 2013. The EGI–EGV values in this sample were all < 41%. In 2014, the F9 had the AMBI value of 4, accounting for about 2.2%. The other sites were under slight disturbance. The environmental quality was good at site C4 and poor at site C1 in 2013. Among the sites in 2014, the environment at site C7 was good,

disturbances; EG II is insensitive to disturbances; EG III is tolerant to disturbances; EG IV is a second-order species; and EG V is a first-order species (Borja et al., 2000; Borja et al., 2003; Muxika et al., 2005). The reference value of diversity and species number in the M-AMBI reference state, based on AMBI, is 0 (Muxika et al., 2007). The present study used M-AMBI-15% to indicate the reference state for obtaining the M-AMBI value (Cai et al., 2013). The sediment characteristics of the sampling sites in the adjacent waters of the Yangtze River Estuary in June 2013 and 2014 were shown in Appendix A. In 2013 and 2014, the percentage of sand content in the study area was 3.51–93.00% and 1.71–100%, respectively (Table 2). The lowest percentages occurred at sites D6 and F1, and the highest occurred at B3 and C9. The percentage of silt content was 5.75–68.64% and 0–70.32%, respectively. The lowest percentages occurred at B3 and C9, and the highest occurred at D6 and C3, respectively. The percentage of clay content was 1.25–27.85% and 0–32.55%, respectively. The lowest percentages occurred at B3 and C9, and the highest occurred at D6 and C9. The sediment median diameter (Md) was 0.009–0.247 mm and 0.007–0.284 mm, respectively. The lowest Md occurred at D6 and F3, respectively, and the highest occurred at B3 and C9. The types of sediments included sandy silt, silty sand, sand, clay silt, and sand–silt–clay. The Chl-a content of the sediment showed a distinct peak at the north side of the Yangtze River Estuary; that for Pha was similar (Fig. 2). The Chl-a content in 2013 and 2014 was 0.11–4.44 μg/g and 0.099–0.745 μg/g, respectively. The Pha content was 1.88–6.86 μg/g and 0.099–0.745 μg/g, respectively, which showed a significant difference between the sites. The changing trends of Chl-a and Pha were same. The overall content of Chl-a was low, and the content of Pha was slightly higher than that of Chl-a. The concentration of organic matter at the inshore sites was significantly higher than that at the offshore sites (Fig. 2). The percentage of organic matter in 2013 and 2014 was 1.16–8.46% and 0.241–1.265%, respectively (Fig. 2). The highest percentage of organic matter occurred at B2 in 2013 and C2 in 2014, and the lowest percentage occurred at E1 in 2013 and C9 in 2014. The overall distribution of organic matter showed a downward trend from the inshore to the offshore areas, with two troughs occurring at the junction of the Yangtze River fresh water and the Pacific Ocean. In 2013 and 2014, 255 species and 183 species of macrofauna were identified, respectively. According to the richness index, Site E5 in 2013 had a maximum of 8.7, and Site C1 had a minimum of 1.6. In 2014, Site E9 had a maximum of 7.5, and Site F7 had a minimum of 1. In 2013 and 2014, the Shannon–Wiener diversity index was 1.3–3.6 with a mean of 2.89 and 1.3–3.4 with a mean of about 2.53, respectively. In 2013, the moderate disturbed sites were C1, E1, and D2; the light disturbed sites were B5, B2, C2, E3, D3, B1, and B4; and the clean sites were C3, E2, 106

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34°N

34°N

a

32°

32°

30°

30°

28°

28°

120°

122°

124°

34°N

120°

E

32°

30°

30°

28°

28°

122°

124°

34°N

120°

E

30°

30°

28°

28°

124°

E

e

122°

124°

E

f

32°

122°

124°

34°N

c

32°

120°

122°

34°N

b

32°

120°

d

120°

E

122°

124°

E (caption on next page)

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Fig. 2. Distribution of sediment organic matter in June (a) 2013 and (d) 2014, chlorophyll a content in (b) 2013 and (e) 2014, and phaeophorbide content in (c) 2013 and (f) 2014 at the sampling sites in the adjacent waters of the Yangtze River Estuary.

34°N

34°N AMBI in 2013

33°

AMBI in 2014

33°

7

7 6

6

32°

5.5

32°

5.5

5

5

31°

4.3

31°

4.3

3.3 2.5

3.3 1.691

30°

1.8

30°

1.635

1.6 1.4

1.468

29°

East China Sea

1.2

29°

1.2

1

0.2

28°

27° 120° 121° 122° 123° 124° 125° 126°

34°N

0.2

28°

0

0

East China Sea

27° 120° 121° 122° 123° 124° 125° 126°

E

34°N

M-AMBI in 2013

33°

M-AMBI in 2014

33°

1

1 0.9

32°

32°

0.9

0.8

31°

E

0.77

31°

0.77

0.6 0.6

30° 29°

30°

0.53

East China Sea

0.38

0.53 0.38

29°

0.2

28°

28°

27° 120° 121° 122° 123° 124° 125° 126° 34°N

0.2

0

East China Sea

27° 120° 121° 122° 123° 124° 125° 126°

E

34°N

H' in 2013

33°

33°

5.5 4.5

32°

5

4

4.5

31°

E

H' in 2014

5.5

32°

0

31°

4

3.7 3

30°

30°

3.5

2.5

2

29°

East China Sea

2

29°

1

1

28°

0

27° 120° 121° 122° 123° 124° 125° 126°

28°

East China Sea

0

27° 120° 121° 122° 123° 124° 125° 126°

E

E

Fig. 3. Distribution of AMBI, M-AMBI, and Shannon–Wiener diversity index (H′) at each sampling site in the adjacent waters of Yangtze River Estuary in June 2013 and 2014.

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was the primary productivity. The Chl-a in the sediment is an important food source of benthic animals and can be used to evaluate the sedimentary environment, and the content of Pha reflects the amount of dead plants in the sediment. As the percentage of clay in the sediment decreases, the organic matter and water content decrease accordingly. The reason may be that fine substrate results in low ease of ventilation; thus, anoxic conditions can easily form. This process is not conducive to the oxidation of organic matter but is favorable for its preservation (Liu et al., 2014a). The results of Hua et al. (2014) showed that the Chl-a and Pha concentrations were the main influencing factors of those species diversity indices. In addition, the overall distribution of organic matter showed a downward trend from the inshore to offshore areas, indicating that the Yangtze River was rich in organic matter that settled at the Estuary and that pollution of seawater from the side was present. In addition, two troughs were present at the junction of the Yangtze River fresh water and the Pacific Ocean. It is possible that the density of seawater was not conducive for sedimentation of the organic matter, resulting in a lower concentration that affected the environmental assessment by AMBI. The organic matter contour maps in Fig. 2d and Fig. 1 showed that the organic matter content in 2014 was very high and that the sediment type of site B3 was sand–silt–clay. This indicated that the organic matter in the sea area was rich, which strongly affected the use of AMBI at this site. Both Fig. 1 and the Chl-a contour maps in Fig. 2e indicated that the primary productivity at this site was high, which may be the reason why AMBI could not be used to determine the environmental quality status at A3 in 2014. This method could not be used to determine the environmental condition of D9 in 2014 likely because the area had been disturbed by humans or natural stress. Fig. 1 and the Pha contour map in Fig. 2f showed that the Pha was higher at site D9. It is possible that changes in the external environment affected the primary productivity to disturb the benthic organisms in that area. Thus, AMBI cannot be used to indicate the environmental conditions of the sea area. The results of environmental assessment using the Shannon–Wiener diversity index and AMBI were different. The evaluation by Cai (2003) for the quality of marine benthic organisms in the Shenzhen Futian intertidal zone and by Cai et al. (2012) for the environmental quality of the Bohai Sea showed similar results. The Shannon–Wiener diversity index (H′) of the population showed a decline from 2013 to 2014, and the increase in the proportion of polychaetes was a response of the benthic community to eutrophic conditions. This enabled the opportunistic species to multiply. The decline in the diversity index of the community was also caused by an increase in the number of opportunistic species and a decrease in the number of large individuals (Tian et al., 2006). In 2013, the proportion of polychaetes increased, and the AMBI indicated slight disturbance. In 2014, the number of species decreased, indicating pollution by AMBI. By comparison with the analysis of H′, we determined that AMBI is reliable in monitoring the environmental quality of some sea areas in China. This index had the same performance as some traditional methods such as the ABC curve and the Shannon–Wiener diversity index, and in some respects, they complement each other. For example, compared with the H′, AMBI was more sensitive in assessing the quality of benthic communities, whereas the H′ was sensitive to the indication of environmental pollution status (Cai et al., 2012).

and that at site F9 was poor (Fig. 3). Although the AMBI value showed that some sites were not disturbed, the results are needed to be evaluated with caution. The neighboring waters and coastal cities of the Yangtze River Estuary are the important economic zones in China. In the process of rapid economic and population development, large amounts of urban domestic sewage and industrial wastewater were discharged into the offshore waters of the Yangtze River to cause habitat deterioration. Previous studies have also shown that habitats with severe degradation in the Yangtze River Estuary caused significant changes in the benthic ecosystems of the Yangtze River in both time and space (Liu et al., 2012). AMBI was a weak indicator at these sampling sites, likely because the sampling sites were relatively close. Therefore, AMBI can be selectively used only for environmental quality conditions in these areas. In the sampling of the two samplings in 2013 and 2014, 37 sites had AMBI = 2, accounting for 72.55%; this indicates that most of the sea areas were slightly disturbed (Li et al., 2007; Liu et al., 2012; Cai et al., 2013). M-AMBI showed that the environmental conditions of all sites were moderate or above (Fig. 3). The Yangtze River Estuary and the Hangzhou Bay near land were subject to large disturbances, while the offshore waters were less disturbed (Fig. 3). Moreover, the overall southward disturbance was greater than that to the north. These results are consistent with the results of Cai et al. (2013). The distribution of these disturbances is related to frequent human activities in the Yangtze River Estuary, such as large-scale water conservancy projects, ship commercial transportation, land-based sewage discharge, and Estuary pollution. The long-term changes in community structure may include seawater and bottom sediment pollution, seawater eutrophication, overfishing by humans, and the use of large bottom trawls (Gao et al., 2014). In 2013, site D2 had AMBI = 7, with one type of organism. This indicated no life. The reason for this phenomenon may be that the number of species at this site was not more than three. When using AMBI to evaluate the environmental quality, the index sensitivity will decrease if the number of species is one to three or the number of individuals is less than three (Borja and Muxika, 2005). Another reason may be that AMBI originated in Europe, and the benthic organisms in the Chinese seas are very different from those in the European seas. AMBI has strong applicability in various estuaries and coastal waters in Europe and is widely used to detect environmental stress caused by humans in that region (Borja et al., 2012). However, AMBI is used to a lesser extent in China's seas. Understanding of the ecological environment characteristics of major estuaries and coastal waters in China is insufficient. Moreover, the taxonomic and biological knowledge reserves of benthic organisms in the Yangtze River are not sufficiently rich. Further, the related research is relatively lagging, and some species have not been placed in the corresponding groups. For these reasons, AMBI has limited use in China. Results of Shannon–Wiener diversity index showed that two sites, B3 in 2013 and F7 in 2014, had values between 1 and 2, indicating moderate disturbance and they accounted for 3.9%. In addition, eight sites had values between 2 and 3, showing slight pollution. These sites included A1, A3, A5, A7, D9, and F5 in 2014 and C1 and C2 in 2013, accounting for 15.7%. The sites affected by pollution accounted for 19.6%, which differed significantly from the AMBI values. However, both methods showed that same disturbances occurred at sites A1, A5, A7, C2, and F7. This may be related to the following conditions and limitations of AMBI, which were proposed by Borja and Muxika (2005). Firstly, it cannot be used at sites with lower salinity such as estuaries or estuarine and inshore environments that were disturbed by natural processes such as humus development. Secondly, for species that are classified only into higher orders such as Bivalvia and Gastropoda, ecological grouping was not possible (Borja et al., 2005). The four sites not indicated by AMBI—A3, D9, F5 and B3– were near the bank of the Yangtze River (Fig. 1). As shown by the chlorophyll contour maps in Fig. 2b and Fig. 1, the chlorophyll content of B3 in 2013 was high, as

Acknowledgements We appreciate the help of the captain and crew of the R/V ‘Runjiang 1’ during the in situ investigation. We are also sincerely grateful to Profs. Wensheng Jiang, Lei Li, Chunying Liu, Tie Li, Anlong Li, Liangming Zhou and Mr. Tongtong Chen for their assistance and cooperation during the research. Thanks are also given to many undergraduates for their help during the field samplings and laboratory analysis. This study was financially funded by the National Natural Science Foundation of China, China (No. 41576135) and the field teaching base project of the Ministry of Education, China: ‘A 109

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comprehensive practical education base for marine science in the Yangtze River Estuary and its adjacent sea area’.

Appendix A. Sediment characteristics of the sampling sites in the adjacent waters of the Yangtze River Estuary in June 2013 and 2014

Year

Site

Region

2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014

B1 B2 B3 B4 B5 C1 C2 C3 C4 D2 D3 D4 D5 D6 E1 E2 E3 E4 E5 A1 A3 A5 A7 A9 B2 B3 B5 B7 B9 C2 C3 C5 C7 C9 C11 D2 D3 D5 D7 D9 D11 E1 E3 E5 E7 E9 F1 F3 F5 F7 F9

North North North North North South South South South South South South South South South South South South South North North North North North North North North North North South South South South South South South South South South South South South South South South South South South South South South

of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of

the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the

Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary

Sand percentage %

Silt percentage %

Clay percentage %

Median diameter mm

Sediment type

25.82 74.42 93.00 39.15 5.24 13.59 56.11 56.34 8.71 43.18 68.84 63.87 53.50 3.51 38.76 31.28 56.84 52.32 25.82 42.34 21.47 48.94 53.46 43.95 11.87 59.39 95.15 54.49 54.01 7.42 9.88 68.72 68.28 100 57.03 21.74 14.98 40.9 70.33 78.66 65.96 1.77 19.45 44.61 51.5 42.36 1.71 2.21 21.83 75.38 72.32

64.00 20.43 5.75 41.95 68.25 67.32 31.47 31.49 66.19 37.14 18.53 26.26 28.74 68.64 38.98 41.74 25.07 31.62 64.00 50.17 64.6 37.48 32.78 38.69 65.94 30.42 4.14 33.27 32.64 66.31 70.32 21.4 23.03 0 31.17 61.05 65.06 39.91 18.39 14.79 22.86 68.02 52.53 33.73 28.97 38.28 68.6 65.25 51.49 14.64 17.8

10.18 5.14 1.25 18.90 26.51 19.09 12.42 12.17 25.10 19.68 12.63 9.87 17.76 27.85 22.26 26.98 18.10 16.07 10.18 7.49 13.94 13.59 13.76 17.36 22.18 10.19 0.71 12.24 13.34 26.27 19.81 9.89 8.69 0 11.8 17.22 19.69 19.19 11.29 6.55 11.18 30.22 28.03 21.67 19.53 19.37 29.7 32.55 26.68 9.97 9.88

0.035 0.217 0.247 0.020 0.010 0.020 0.123 0.086 0.011 0.024 0.121 0.114 0.089 0.009 0.017 0.010 0.089 0.073 0.035 0.053 0.03 0.054 0.097 0.035 0.013 0.164 0.252 0.1 0.133 0.01 0.015 0.196 0.108 0.284 0.128 0.022 0.019 0.022 0.123 0.147 0.138 0.008 0.009 0.025 0.071 0.027 0.008 0.007 0.011 0.233 0.172

Sandy silt Silty sand Sand Sandy silt Clay silty sand Clay silty sand Silty sand Silty sand Clay silty sand Silty sand Silty sand Silty sand Silty sand Clay silty sand Sand–silt–clay Sand–silt–clay Silty sand Silty sand Sandy silt Sandy silt Sandy silt Silty sand Silty sand Silty sand Clay silty sand Silty sand Sand Silty sand Silty sand Clay silty sand Clay silty sand Silty sand Silty sand Sand Silty sand Sandy silt Clay silty sand Silty sand Silty sand Sand Silty sand Clay silty sand Clay silty sand Sand–silt–clay Silty sand Silty sand Clay silty sand Clay silty sand Sand–silt–clay Sand Silty sand

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Appendix B. Results of the benthic ecological status assessed by Shannon–Wiener diversity index (H′), AMBI and M-AMBI

Year

2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014

Site

B1 B2 B3 B4 B5 C1 C2 C3 C4 D2 D3 D4 D5 D6 E1 E2 E3 E4 E5 A1 A2 A5 A7 A9 B2 B3 B5 B7 B9 C2 C3 C5 C7 C9 C11 D2 D3 D5 D7 D9 D11 E1 E3 E5 E7 E9 F1 F3 F5 F7 F9

Region

North North North North North South South South South South South South South South South South South South South North North North North North North North North North North South South South South South South South South South South South South South South South South South South South South South South

of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of

H′

the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the

Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary Estuary

AMBI

M-AMBI

Value

Status

Value

Status

Value

Status

3.761 4.031 1.992 4.276 4.271 2.922 4.073 4.352 5.297 0.000 3.675 4.307 4.916 5.326 5.116 3.403 4.913 4.102 4.583 2.678 2.971 2.72 2.713 3.783 3.282 3.838 3.455 5.105 3.16 2.902 4.394 3.976 4.942 3.702 4.253 3.19 3.75 4.077 4.015 2.722 4.64 3.189 4.015 4.141 3.397 4.403 4.117 3.576 2.804 1.607 3.366

High High Moderate High High Good High High High Bad High High High High High High High High High Good Good Good Good High High High High High High Good High High High High High High High High High Good High High High High High High High High Good Moderate High

2.054 1.200 1.014 1.963 1.795 2.063 1.632 1.757 1.635 7.000 1.000 1.415 1.691 1.468 1.436 1.630 1.177 1.095 6.880 1.527 2.348 1.370 1.575 2.011 2.020 2.682 1.274 2.333 0.568 1.091 1.441 1.601 1.089 2.184 1.035 1.875 2.032 1.731 1.842 0.717 1.828 1.625 1.496 1.484 1.332 1.680 1.911 1.664 0.843 1.276 4.435

Good Good High Good Good Good Good Good Good Bad High Good Good Good Good Good Good High Bad Good Good Good Good Good Good Good Good Good High High Good Good High Good High Good Good Good Good High Good Good Good Good Good Good Good Good High Good Moderate

0.787 0.687 0.636 0.775 0.675 0.473 0.683 0.864 0.954 −0.047 0.618 0.899 0.916 0.934 0.883 0.559 0.839 0.806 0.555 0.542 0.587 0.548 0.535 0.646 0.599 0.657 0.676 0.885 0.634 0.575 0.743 0.848 0.953 0.658 0.763 0.550 0.626 0.755 0.697 0.574 0.775 0.588 0.718 0.714 0.638 0.919 0.700 0.677 0.625 0.461 0.429

High Good Good High Good Moderate Good High High Bad Good High High High High Good High High Good Good Good Good Good Good Good Good Good High Good Good Good High High Good Good Good Good Good Good Good High Good Good Good Good High Good Good Good Moderate Moderate

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