Seasonal Variation of Zooplankton Communities and the Effects of Environmental Factors in the Seawater Near Taishan Nuclear Power Station

In the seawater near Taishan Nuclear Power Station, Zooplankton community composition and abundance, the biomass of major taxa, vertical distribution pattern, together with several environmental factors were investigated to evaluate the variation tendency as the seasons change. The structure characteristics of the zooplankton community were analyzed by Margalef species richness (d), Shannon-wiener species diversity index (H’), Pielou evenness index(J’), zooplankton dominant (Y), and dominant species replacement rate (R). There are 48 species within 11 classes of zooplankton identified, including 32 species of copepods. Zooplankton species richness changed obviously in the four seasons, Spring saw the highest (8010.00 ind.m-3), followed by winter (5100.00 ind.m-3), autumn (1713.75 ind.m-3), and summer (1196.25 ind.m-3). Similar trends were observed for the wet biomass, which was highest in spring (215.90 mg.m-3), followed by winter (181.70 mg.m-3), summer (78.56 mg.m-3), and autumn (24.69 mg.m-3), which gave an annual average of 125.21 mg.m-3. The results indicate that the abundance and biomass in spring were significantly higher than those in other seasons. Altogether 8 dominant species were identified along the whole year: Acrocalanmus gibber, Bestiolina amoyensis, Paracalanus parvus, Acartia danae, Mesocyclops leuckarti, Noctiluca scientillans, Penilla avirostris, and Lucifer penicilliger. The annual average Shannon-Wiener diversity index, Margalef diversity index, Pielou evenness index were 1.75, 1.83, and 0.74, respectively. The effects of environmental factors on the zooplankton community were studied by R and canonical correspondence analysis (CCA). According to Pearson correlation analysis and canonical correspondence analysis, the most important environmental factors influencing the changes of zooplankton species composition, abundance and distribution were water temperature, salinity, and pH in the whole year.


INTRODUCTION
Nuclear power has played an important role in energy development. However, due to warmer waters brought by heatwaves, many nuclear facilities have already reduced their output in the recent decade. More and more people begin to pay close attention to the threat of nuclear power stations on marine life and the coastal environment, particularly after the Fukushima incident. Nuclear reactors are located near a river or the ocean since they are the most water-intensive energy-producing technology. That may bring temperature drainage, residual chlorine, radioactive materials, and other problem (Chen et al. 2017, Jiang & Hou, 2015, Jiang & Wang 2020, Muthulakshmi et al. 2019. Zooplankton communities are the vital secondary producers and main drivers of the biological pump in the Marine food web (Muthulakshmi et al. 2019, Goncalves et al. 2012, Wu et al. 2011, Steinberg & Landry 2017. Since they are highly sensitive to environmental conditions, zooplankton communities are good indicators of the coastal environment change impacts and have been widely used to study such changes and their impacts (Batchelder et al. 2013). Buesseler et al. (2016) had found that when the temperature reached 37.0°C ~ 37.6°C, large zooplankton disappeared and Copepods dropped dramatically in the eastern Indian Ocean due to thermal drainage. Taishan Nuclear Power Station is located about 1.2 km to the northeast of Chixi town, Taishan city in Guangdong province.
There have been relevant studies on the zooplankton community in the coastal waters (Alagan et al. 2020, Asgari & Steiner, 2017, Lin, et al. 2021, Maja et al. 2018, Richardson et al. 2019, Sonia et al. 2019, Thirunavukkarasu et al. 2020, however, few studies on zooplankton community Vol. 20, No. 4, 2021 • Nature Environment and Pollution Technology characteristics in the waters near the nuclear power plant have been reported (Ding et al. 2019).
In this paper, four quarterly background surveys of the zooplankton community in this area from 2015 to 2016 were investigated, focusing on its community structure, abundance distribution, and seasonal changes. The relationship between the zooplankton community and several environmental factors including temperature, salinity, pH, and nutrient salts was also discussed. Our result intended to provide fundamental information for the sustainable utilization of resources in the seawater near Taishan Nuclear Power Station.

Study Site
The zooplankton samples were collected in the seawater near Taishan Nuclear Power Station from Dec. 2015 to Sept. 2016, including 10 points along the coast station (S1-S10) and another 10 offshore (S11-S20) (Fig. 1).
At each station, water temperature, salinity, and pH were measured in situ with a multi-parameter water quality meter along with sample collection. For quantitative investigation, 5 L water samples were collected from different sampling sites by an organic glass water extractor and then filtered by a 25# plankton net (with 200 64-µm apertures); And then 50 mL was collected in plastic bottles and immediately fixed with 5% formalin solution. The identifications were analyzed by Olympus SZ61 stereomicroscope after being settled and concentrated to 5 mL. The phyletic analysis was conducted referring to the Chinese Marine plankton map, and Chinese phytoplankton map, and Chinese zoological freshwater copepods.

Data Analysis
The structure characteristics of the zooplankton community were analyzed by Margalef species richness (d), Shannon-wiener species diversity index (H') (Shannon & Weaver 1949), Pielou evenness index(J') (Pielou 1969), zooplankton dominant(Y) and dominant species replacement rate (R) (Walkusz et al. 2009, Zervoudaki et al. 2009), calculated as below: Species richness index: parameter water quality meter along with sample collection. water samples were collected from different sampling sites by a then filtered by a 25# plankton net (with 200 64-µm apertures) plastic bottles and immediately fixed with 5% formalin solution by Olympus SZ61 stereomicroscope after being settled and c analysis was conducted referring to the Chinese Marine plankto map, and Chinese zoological freshwater copepods.

Data Analysis
The structure characteristics of the zooplankton community richness (d), Shannon-wiener species diversity index (H') (S evenness index(J') (Pielou 1969), zooplankton dominant(Y) and (R) (Walkusz et al. 2009, Zervoudaki et al. 2009 parameter water quality meter along with sample collection. Fo water samples were collected from different sampling sites by an then filtered by a 25# plankton net (with 200 64-µm apertures); plastic bottles and immediately fixed with 5% formalin solution.
by Olympus SZ61 stereomicroscope after being settled and con analysis was conducted referring to the Chinese Marine plankton map, and Chinese zoological freshwater copepods.

Data Analysis
The structure characteristics of the zooplankton community w In this paper, four quarterly background surveys of the zooplankton community in this area from 2015 to 2016 were investigated, focusing on its community structure, abundance distribution, and seasonal changes. The relationship between the zooplankton community and several environmental factors including temperature, salinity, pH, and nutrient salts was also discussed. Our result intended to provide fundamental information for the sustainable utilization of resources in the seawater near Taishan Nuclear Power Station.
Sampling Fig. 1: Map of the different sampling stations. Intake point: Coastwise (S1-S10) and Offshore (S11-S20). The R Programming Language cor and cor test functions were used for correlation analysis.
The biodiversity of the zooplankton community was analyzed by large multivariate statistical software PRIMER6.0. Redundancy analysis (RDA) was performed on zooplankton species and environmental data using Canoco5.0. Canonical-correlation analysis (CCA) was conducted between six water environmental factors (water temperature, salinity, pH, COD, nitrate-nitrogen, and labile phosphate) measured at 20 stations and the abundance of 25 optimal zooplankton species.

Species evenness index:
Replacement rate of dominant species: R= The R Programming Language cor and cor test functions were used for correlation analysis.
The biodiversity of the zooplankton community was analyzed by large multivariate statistical software PRIMER6.0. Redundancy analysis (RDA) was performed on zooplankton species and environmental data using Canoco5.0. Canonical-correlation analysis (CCA) was conducted between six water environmental factors (water temperature, salinity, pH, COD, nitrate-nitrogen, and labile phosphate) measured at 20 stations and the abundance of 25 optimal zooplankton species.

Species evenness index:
Replacement rate of dominant species: R= The R Programming Language cor and cor test functions were used for correlation analysis. The biodiversity of the zooplankton community was analyzed by large multivariate statistical software PRIMER6.0. Redundancy analysis (RDA) was performed on zooplankton species and environmental data using Canoco5.0. Canonical-correlation analysis (CCA) was conducted between six water environmental factors (water temperature, salinity, pH, COD, nitrate-nitrogen, and labile phosphate) measured at 20 stations and the abundance of 25 optimal zooplankton species.

Species Composition
A total of 48 species of zooplankton taxa (excluding 13 planktonic larvae) belonging to 11 taxonomic groups were identified in seawater around Taishan as shown during the seasonal surveys in Table 1. At the taxonomic level, copepods were numerically the most abundant with 32 species recorded (RA 66.67%), followed by Sergestidae (RA 6.25%, 3 species). The taxonomic groups with 2 species were Cladocera, Rotifera, and Hydromedusae, respectively. The rest classes that had only 1 species recorded were Planktonic mollusks, Cumacea, Isopoda, and Amphipoda, respectively.

Zooplankton Abundance and Biomass
In the present study, the zooplankton abundance showed a noticeable change among the study stations and between different seasons (Fig. 2). Zooplankton abundance ranged from 75.00 to 9600.00 ind.m -3 in all the samples investigated with an annual average of 4005.00 ind.m -3 . The highest average abundance was observed in spring (8010.00 ind./m 3 ) and followed by winter (5100.00 ind.m -3 ), autumn (1713.75 ind.m -3 ), and summer (1196.25 ind.m -3 ). It presented seasonal changes as: spring > winter > autumn > summer.
The biomass of zooplankton samples ranged from 2.63 to 815.10 mg.m -3 with an annual average of 125.21 mg.m -3 . The total biomass of zooplankton showed similar trends with the zooplankton abundance. In general, maximum biomass occurred in spring (215.90 mg.m -3 ), and then followed a declining trend in the order of winter (181.70 mg. m -3 ), summer (78.56 mg.m -3 ), and autumn (24.69 mg.m -3 ), showing obvious seasonal changes (Fig. 3).
From the perspective of the horizontal distribution shown in Figs. 2-3, the abundance and biomass of zooplankton in near-shore samples collected in spring were significantly different from those in open-sea samples but similar in the other three seasons. In spring, zooplankton abundance and biomass were dramatically higher in near-shore than in opensea samples with 3.50 times and 3.22 times, respectively. The zooplankton was mainly distributed in the neritic area, while its abundance and biomass were low. This distribution pattern of zooplankton was contributed by the high abundance of Noctiluca scintillans as shown in Table 2. The zooplankton showed different distribution patterns in summer, which was mainly distributed in the estuary region to the north of the sampling station and higher compared to other stations (Fig. 2). This is because the N. scintillans is still dominant in the summer (Table 2). In addition, the zooplankton was mainly distributed in the southern part of the sampling area in autumn, because Penilla acirostris and Tortanus forcipatus largely appeared (Table 2) and planktonic larvae were detected at the same time. However, the abundance distribution of zooplankton was relatively uniform in winter (Fig. 2), mainly dominated by copepods (Table 2).

Dominant Zooplankton Species and Their Seasonal Variations
In the present study, 8 dominant species were found in surface seawater near Taishan during the investigation (not including 2 phytoplankton). Apparently, there were substantial seasonal changes in the zooplankton dominant species, from A. gibber, Bestiolina amoyensis, P. parvus, Acartia danae, and Mesocyclops leuckarti in winter, N. scintillans in spring and summer to P. acirostris and Lucifer penicilliger in autumn. To understand how the dominant species changed in different seasons, the replacement rate of the dominant species and the population turnover rate were calculated. The replacement rate of dominant species in spring-summer, summer-autumn, autumn-winter, and winter-spring was calculated as 0%, 100%, 100%, and 100%, respectively. Successively, the population turnover rate was 53.57%, 77.27%, 76.79%, and 67.44%, respectively. Except for the same dominant species were found in spring and summer, the corresponding replacement rate was above 50%. As a result,   the seasonal replacement rate of zooplankton was relatively high in the whole year.

Species Diversity and Seasonal Variation
As shown in Table 3, the abundance index such as Pielou's index (d), the diversity index (H'), and the Evenness index (J') during investigation time across seasons exhibited a common trend. Pielou's index (d) was in the range of 0.2-3.1, with an annual average of 1.75. The diversity index (H') was in the range of 0.00~3.28, with an annual average of 1.83. The Evenness index(J') was in the range of 0.09~1.00, with an annual average of 0.74. The zooplankton diversity index over the 4 seasons in 2015-2016 was the lowest in spring and followed an increasing trend till winter. While at other times, these values were lower due to the explosive growth of some dominant species.

Effects of Environmental Factors
Environmental factors play important roles in the seasonal succession of the zooplankton community. As showed in Table 4, the results of correlation analysis were performed to evaluate the influence of environmental factors (water temperature, salinity, pH, COD, nitrate-nitrogen, and labile phosphate) on the zooplankton community (species, abundance, biomass, and diversity index). The population and abundance of zooplankton were found to be positively correlated with salinity and pH, while negatively correlated with COD. Zooplankton biomass was positively correlated with nitrate-nitrogen and labile phosphate, while negatively correlated with water temperature. The diversity index of zooplankton was positively correlated with water temperature, salinity, and pH, while negatively correlated with COD and nitrate-nitrogen.   Table 2. The zooplankton showed different distribution patterns in summer, which was mainly distributed in the estuary region to the north of the sampling station and higher compared to other stations (Fig. 2). This is because the N. scintillans is still dominant in the summer (Table 2). In addition, the zooplankton was mainly distributed in the southern part of the sampling area in autumn, because Penilla acirostris and Tortanus forcipatus largely appeared (Table 2) and planktonic larvae were detected at the same time. However, the  Table 2. The zooplankton showed different distribution patterns in summer, which was mainly distributed in the estuary region to the north of the sampling station and higher compared to other stations (Fig. 2). This is because the N. scintillans is still dominant in the summer (Table 2). In addition, the zooplankton was mainly distributed in the southern part of the sampling area in autumn, because Penilla acirostris and Tortanus forcipatus largely appeared (Table 2) and planktonic larvae were detected at the same time. However, the  To further explore the correlations between zooplankton community structure and environmental factors, the canonical correlation analysis (CCA) between the abundance of 25 optimal zooplankton species and six water environmental factors was conducted, as showed in Table 5.
All the characteristic values of CCA sequencing explain 18.7% of the variation degree of zooplankton. The characteristic values of the first two sequencing axes were 0.662 and 0.529, which together explain 15% of the change degree of the zooplankton community. The correlation coefficients between 25 species and 6 water environmental factor sequencing axes (the first axis and the second axis) were 0.956 and 0.886, indicating a close correlation between the zooplankton and the water environmental factors. Thus, the results of CCA were credible. Furthermore, the Monte Carlo test showing that the first axis was significantly different from other axes (P < 0.01) made the ranking results of CCA analysis more convincing.
The distinct clusters in species biplot of CCA analysis clearly revealed that the zooplankton spatio-temporal variation may be caused by different environmental variables. Furthermore, among all the environmental variables, the most important factors affecting the structure of the plankton community were COD, pH, and salinity, which is consistent with Pearson correlation analysis results shown in Table 4. In addition, CCA results divided 25 species of major zooplankton into three groups. The species of group I, including A. gibber, B. amoyensis, etc., were positively correlated with salinity, pH, and labile phosphate, while negatively correlated with COD. On the contrary, group III (P. acirostris, C. larva, etc.) was positively correlated with COD but negatively correlated with salinity, pH, and labile phosphate. Group II (L. penicilliger, C. furcatus, etc.) presented a positive correlation with temperature and a negative correlation with nutrient salts.

Effects of Environmental Factors and Phytoplankton
In the water, environmental conditions are complex and changing, affecting zooplankton species and communities. Temperature, salinity, and phytoplankton were the important factors influencing the distribution of zooplankton. During this study, a significant variation of water temperature exhibited a seasonal pattern: which increased after spring and reached a maximum in summer, decreased in autumn, and dropped to a minimum in winter. While the salinity showed higher values in winter and autumn than in spring and summer.
The concentration and rich nutrient content of phytoplankton were significantly correlated with the water quality characteristics in different seasons (Alagan et al. 2020, He et al. 2018, Lin et al. 2021, Shi et al. 2018. These environmental conditions affected the distribution of zooplankton and thus caused seasonal changes of the zooplankton community (Muthulakshmi et al. 2019, Thirunavukkarasu et al. 2020. Pearson correlation showed that all six environmental factors had affected zooplankton in different aspects, while pH, salinity, and temperature were the most significant factors that influenced the 25 major zooplankton species. The number of phytoplankton peaked in spring because of adequate nutrient salt, which had reached the level of red tide. With abundant food, low temperature, and low salinity, N. scintillans thrived and become the most dominant species (Y = 0.86). S2 stood up with 31125 ind.m -3 among all the sample stations as shown in Fig. 3. Additionally, as a group III species (as discussed in 3.5), N. scintillans displayed a significant negative correlation with water temperature and salinity. A red tide of N. scintillans had occurred several times in the neritic areas of China, resulting in the death of mollusks such as scallops and oysters, and bringing huge economic losses to the fishery (Baliarsingh et al. 2016). In this survey, the massive propagation of N. scintillans was mainly distributed in near-shore and the Pearl River estuary area (with similar environmental conditions of previous N. scintillans-related red tides) (Mikaelyan et al. 2014). It indicates risks of occurrence of red tides caused by N. scintillans. In addition, low salinity zooplankton groups near the shore and estuaries such as Acartia pacifica and Sinocalanus laevidactylus were detected. In summer, the abundance of phytoplankton decreased significantly when water temperature increased and salinity decreased. Although the abundance of N. scintillans decreased, they remained the dominant species (Y=0.76). N. scintillans is mainly distributed in the pearl river estuary sea areas such as Station S3, S11, and S12, among which S11 presented the maximum abundance of 4650 ind.m -3 . As salinity increased while the autumn temperature was still high, the density of phytoplankton as a food source decreased, and thus, replacement of dominant zooplankton species had taken place: P. acirostris and L. penicilliger became the dominant species, while the planktonic larvae began to multiply and became the absolute group. It can be seen from Fig. 4 that Nauplius larvae, belonging to group I, showed a positive correlation with salinity, while Penaenus orientalis and Eriocheir sinensis (in group II) were mainly positively correlated with temperature. The relationship between different species of planktonic larvae and environmental factors is quite different, which is consistent with previous research results (Fanjul et al. 2018). In winter, dominant species became P. parvus, A. gibber, B. amoyensis, and A. danae daphnia with both temperature and phytoplankton abundance decreasing, which were all negatively correlated with temperature.

Other Effects
It is important to note in particular that the direct effect of the nuclear power plants on the environmental changes was due to the increase in the temperature for the temperature drainage, which became a major factor affecting the marine ecological environment (Alibek 2016, Jiang & Wang et al. 2020, Muthulakshmi et al. 2019. In this study, the differ-ity, pH, and labile phosphate. Group II (L. penicilliger, C. furcatus, etc.) presented a orrelation with temperature and a negative correlation with nutrient salts.
nonical correlation analysis between zooplankton species and environmental factors. lankton species number 1-8 is shown in Table 2  ences in the abundance distribution of zooplankton between the four voyage outlets and the neighboring stations were compared. As a result, zooplankton abundance near the outlet was not much different from that at the adjacent stations in spring; What mattered was the distance from shore: zooplankton abundance was higher at near shore stations than that at the stations in the open sea, indicating significant influence from tides. In summer, zooplankton abundance around the outlet and the south sea area is lower than that in the North Sea area, which indicates that the estuary runoff may have a great influence on the distribution of zooplankton. However, zooplankton abundance around the outlet is lower than those found at non-outlet stations in autumn, which is more likely related to temperature drainage from the nuclear power plant. The situation in winter is more complex with zooplankton distributed quite randomly. In conclusion, temperature drainage seems did affect zooplankton distribution in autumn.

CONCLUSION
In the seawater near Taishan Nuclear Power Station, a total of 48 species of zooplankton taxa belonging to 11 taxonomic groups were identified. At the taxonomic level, copepods covered the vast majority of zooplankton and they were mainly composed of low salinity groups near the shore, which is typical of subtropical flora. The differences in zooplankton density, biomass, and diversity indices were significant in different seasons. The results indicate that the abundance and biomass in spring were significantly higher than those in other seasons. However, the zooplankton diversity index was the lowest in spring and showed an upward trend till winter. According to Pearson correlation analysis and canonical correspondence analysis, pH, salinity, and temperature were the principal factors affecting the distribution of zooplankton. By comparing the results among the study stations and between different seasons, it seems that the zooplankton community in the survey area was mainly determined by different seasons, estuary runoff, and tide. This study will be helpful in the further understanding of the threat of the Taishan Nuclear Power Station on the marine life and the coastal environment, and in providing scientific guidance for the protection of the ecological environment of surrounding seas.