亚洲免费av电影一区二区三区,日韩爱爱视频,51精品视频一区二区三区,91视频爱爱,日韩欧美在线播放视频,中文字幕少妇AV,亚洲电影中文字幕,久久久久亚洲av成人网址,久久综合视频网站,国产在线不卡免费播放

        ?

        Effects of Liaoning Hongyanhe Nuclear Power Plant on the Zooplankton Community in Summer of 2017

        2020-09-27 14:53:54WANGJunjianTAOZhenchengWANGYantaoWEIHaoLIUXinandLIChaolun
        Journal of Ocean University of China 2020年5期

        WANG Junjian, TAO Zhencheng, WANG Yantao, WEI Hao,LIU Xin, and LI Chaolun

        Effects of Liaoning Hongyanhe Nuclear Power Plant on the Zooplankton Community in Summer of 2017

        WANG Junjian1), 2), #, TAO Zhencheng1), 3), 4), #, WANG Yantao1), 3), 4), WEI Hao5),LIU Xin6), and LI Chaolun1), 2), 3), 4), *

        1),,,266071,2),100049,3),,266237,4),,266071,5),,300072,6),,361005,

        To evaluate the effects of the Hongyanhe Nuclear Power Plant on the zooplankton community in the surrounding sea- water during summer, multiple environmental factors and zooplankton distribution along the east coast of Liaodong Bay were inves- tigated in the summer of 2017. In particular, the influences of seawater temperature, salinity, and chlorophyll(Chl) on the zoo- plankton community were analyzed. Zooplankton abundances and Chlconcentrations along the east coast of Liaodong Bay showed an initial increase followed by a decrease from July to September. During the three months, the zooplankton abundance was the highest (8116.70indm?3) in August. The Shannon-Wiener index showed a downtrend from July to September, with the average value falling from 1.65 in July to 1.50 in September.,, copepodid, and bivalve larvae were the domi- nant species/groups in the three months. The effects of the nuclear power plant’s outlet on the environment factors were mainly re- flected in the increased seawater temperature. Redundancy analysis showed that the zooplankton community was jointly affected by seawater temperature, salinity and Chlconcentration, and the degree of this impact varied monthly. The impact of seawater tem- perature on the zooplankton community was stronger than that of salinity. The primary impact of the Hongyanhe Nuclear Power Plant on the structure and distribution of the zooplankton community in the surrounding seawater during the summer was increased seawater temperature, which caused a reduction in the abundance of dominant species/groups.

        zooplankton; abundance; community structure; diversity; environmental factor; Hongyanhe Nuclear Power Plant

        1 Introduction

        The Hongyanhe Nuclear Power Plant is currently the only nuclear power plant operating in the northern seas of China. The plant is located along the west coast of the sou- thern central part of the Liaodong Peninsula, where the coast generally runs from northeast to southwest (Larson, 2014). Its surrounding seawater has high productivity and is influenced by seasonal circulation. During operation of the power plant, the discharge of warm seawater inevitably affects the environment, biological communities, and eco- logical characteristics in the nearby sea (Fang, 2000; Zhou, 2009; Liu, 2017). In recent years, the enrichment of gelatinous zooplankton, such as jellyfish, has occasionally blocked the water inlet of the power plant (Li and Wang 2009; Lin and Holbert, 2009). In the 1960s in Japan, jellyfish and other gelatinous zooplankton block- ed the water-intake system of power plants in coastal areas numerous times. Clogging incidents can cause emergency situations at nuclear power plants and may jeopardize the safe operation of the units, resulting in significant power loss and economic damage to affected cities (Purcell, 2007). Wu(2017) have analyzed the oceanic matter that can block the nuclear power plant cold source sys- tems.

        As widely distributed marine creatures, zooplankton is important for the energy flow and biogeochemical cycles of marine ecosystem (Biard, 2016). It plays a key role in the conversion of primary production to higher trophic levels in all pelagic ecosystems (Irigoien, 2004; Sun, 2010). Zooplankton is also one of the main biological groups affected by environmental factors and can be regarded as one important indicator of the marine ecosystem (Roemmich and Mcgowan, 1995; Ri- chardson and Schoeman, 2004). Thus, it is necessary to determine how the environment affects the zooplankton community.

        Many studies have confirmed that seawater temperature, salinity, and chlorophyll(Chl) are important factors in marine ecosystem (H?kanson and Eklund, 2010; Loeb, 2010; Petrou, 2011; Feng, 2017). Most marine organisms can only live within a relatively narrow range of seawater temperatures (Gillooly, 2000; Petrou, 2011). Salinity could directly affect the osmotic balance of marine organisms (H?kanson and Eklund, 2010; Petrou, 2011). In the photosynthetic ecosystem, the Chlconcentration determines the primary productivity of the entire ecosystem and the amount of dissolved oxygen in the seawater (H?kanson and Eklund, 2010). In most cases, the various ecological factors are interrelated and have an integrative impact on marine organisms. Exploring the im- pact of environmental factors changes on zooplankton is important for studying the changes of ecological commu- nity and the interaction between nuclear power plant and marine organisms.

        To date, many studies have focused on the ecosystem of the Bohai Sea. Lin(2001) investigated the salin- ity and temperature of the Bohai Sea and analyzed their influence on the ecosystem. Tang(2003) evaluated theecosystem productivity of the Bohai Sea. Many stud- ies on Bohai Sea zooplankton have also been published. Microzooplankton in Bohai Sea and their grazing pres- sure were studied (Zhang and Wang, 2000). Zhang. (2002) investigated the Bohai Sea zooplankton commu- nity in spring and autumn. Wang. (2014) studied the zooplankton community structure of Bohai Bay in the spring and analyzed its relationship with environmental factors. Gao. (2014) studied the diversity of the zoo- plankton community in Bohai Bay and showed its varia- tions. But the zooplankton in the surrounding seawater of the Hongyanhe plant has rarely been the focus of research. Meanwhile, the effects of environmental factors and the Hongyanhe Nuclear Power Plant on the distribution and structure of zooplankton community have not been assess- ed. Here, we investigated the impact of seawater tempera- ture, salinity, Chlconcentration, and other environmen- tal factors on the structure and distribution of the zoo- plankton community in the sea area surrounding Hong- yanhe Nuclear Power Plant in summer. The aim of thisstudy was to clarify the distribution mechanism of the zooplankton community in the seawater surrounding the Hongyanhe plant and to determine how it was affected by the power plant’s drainage outlet.

        2 Materials and Methods

        2.1 Field Sampling and Measurement of Environmental Factors

        Three surveys were conducted in the seawater surround- ing the Hongyanhe Nuclear Power Plant during 13–20 July, 12–19 August, and 14–18 September of 2017. The effects of extreme seawater temperature resulting from warm drainage during these high-temperature months on zoo- plankton can be studied in the three months. Additionally, the jelly organisms bloom in the area during these months. Samples were collected from 24 stations along seven tran- sects (Fig.1). D4 is the nearest station to the outlet of the nuclear power plant. Because of bad weather and unfore- seen circumstances during the surveys, three stations (F1, G1, G4) and four stations (F1, F3, G1, G3) were not in- vestigated in July and September, respectively. The tem- perature and salinity of seawater column were obtained at all stations using an RBR XR-420 CTD. To determine Chl, 500mL of surface seawater was collected using a water collector (5L) and filtered through a 25-mm Whatman GF/ F filter, which was then stored in a freezer at ?20℃. Con- sidering the shallow depth of the sampling area and the uniform mixing of the seawater column, the seawater for the detection of Chlwas sampled from the surface layer. After extracting Chlwith 90% aqueous acetone solution at ≤4℃ for 24h, the Chlconcentration was measured using a Turner Designs Fluorometer (Parsons, 1984).Zooplankton larger than 500μm were collected with a max- zooplankton net (mesh size: 500μm; diameter: 50cm) and others with a midi-zooplankton net (mesh size: 160μm, dia-meter: 31.6cm) (Sun, 2010; Chen, 2016). Nets were towed vertically from 2m above the bottom (max bottom depth: 33m) up to the surface at a rate of about 0.8ms?1. Zooplankton samples were then immediately preserved in 5% neutral formalin seawater solution. We measured and calibrated the volume of seawater that fil- tered through a calibrated flowmeter (HYDROBIOS, Ger- many), which was equipped at the net mouth.

        Fig.1 The study area and location of the sampling stations in the surrounding seawater of the Hongyanhe Nuclear Power Plant during July, August, and September of 2017. The red star marks the outlet of the nuclear power plant.

        2.2 Zooplankton Processing in Laboratory

        All specimens were identified and counted under a ste- reo zoom microscope (Nikon SMZ-745T, Japan) in the laboratory. Samples from the maxi-zooplankton net wereused to count the species/groups larger than 500μm (.,macrozooplankton and giant zooplankton). The others (.,mesozooplankton and microzooplankton) were countedusing the samples from the midi-zooplankton net. The spe- cific sampling nets for each zooplankton species/groupare shown in Table 2. To calculate zooplankton abundance, the count under the microscope was divided by the volu- me of the filtered seawater. The biological abundance datain this study are presented as indm?3.

        2.3 Data Analysis and Statistical Methods

        The zooplankton community diversity and structure were evaluated in terms of the Shannon-Wiener diversity index () (Shannon and Weaver, 1949), Margalef index (m) (1957), and evenness coefficient () (Pielou, 1969). The do- minance index () was used to identify the dominant spe- cies each month (Odum, 1959). The formulas were as fol- lows:

        ,

        whereis species abundance;is the number of all zoo- plankton species;is the total abundance of all zooplank- ton species; andis the occurrence frequency of species in all stations.>0.02 indicates that the species is dominant (Odum, 1959).

        Correlations between the abundance of zooplankton and environmental factors (temperature, salinity, and Chlcon- centration) were statistically evaluated using the Pearson rank correlation with SPSS V16.0 software. A combina- tion of environmental factors that can best explain the zoo- plankton community changes is identified using the BIO- ENV procedure in PRIMER V6.0 software. To assess the similarity of the zooplankton community between stations, a cluster analysis was conducted with PRIMER V6.0. More- over, CANOCO for Windows V5.0 was also used to per- form principal component analysis and redundancy analy- sis (RDA), which we used to analyze the impact of dif- ferent environmental factors on the zooplankton commu- nity.

        3 Results

        3.1 Environmental Factors in the Seawater Surround- ing the Hongyanhe Nuclear Power Plant

        Changes in seawater temperature (ST), seawater sali- nity (SS), and Chlconcentration over three months are shown in Table 1. The average ST increased from 23.29±1.59℃ in July to the highest in August (24.34±1.50℃), and then decreased to 24.12±0.44℃ in September. The minimum bottom seawater temperature (BST) (19.96℃) in August was lower than that in September (23.41℃). In contrast, SS decreased first and then increased. In Septem- ber, the average Chlconcentration reached its maximumvalue (1.46±0.56mgm?3), and the highest Chlconcen- tration was 5.12mgm?3. The Chlconcentration was low in July, with an average of 1.04±0.56mgm?3and a mini- mum of 0.13mgm?3.

        In July, the average ST in the investigation area was (23.29±1.59)℃. The surface seawater temperature (SST) distribution in July was high in the southwest and low in the northeast. The SST at stations D4 and E5 were higher than those in the surrounding area, and this trend also applied to BST. The ST distribution on the bottom layer was the opposite of that of the surface layer, which was high in the southwest and low in the northeast. The dis- tribution pattern of surface seawater salinity (SSS) was un- clear. The bottom seawater salinity (BSS) was high in the west and low in the east. The three highest Chlconcen- trations were observed at stations A3 (2.16mgm?3), E5 (2.02mgm?3), and F2 (1.89mgm?3). The average Chlcon-centration was (1.04±0.56)mgm?3. The lowest Chlcon- centration was only 0.13mgm?3at station C1 (Fig.2). The average ST of the whole seawater column increased to (24.34±1.50)℃, and the average SST was (26.10±1.10)℃ in August. There was no obvious trend in horizontal dis- tribution. The SST and BST of stations D4 and E5 were still higher than those of the other stations. The BST was high in the southwest and low in the northeast, which was also the case in July. The average Chlconcentration was (1.41±0.77)mgm?3. The distribution of Chlconcentra- tions was similar to the average ST. Except for the twostations (E2 and E5) in transect A, the concentration of Chlwas lower than 2.30mgm?3, and the lowest Chlwas recorded at station F2 (0.56mgm?3). The average ST in September was high in the southwest and low in the northeast, which was consistent with the BST. We observed the highest SST (25.50℃) and BST (24.98℃) at station D4. The average Chlconcentration was (1.46±0.56)mgm?3, and the Chlconcentration at all stations in transect A were higher than in other transects. At four stations the Chlconcentrations were below 0.6mgm?3and the low- est Chlconcentration was 0.53mgm?3at station E2. During the three months, the SST of station D4 was high- er than the average ST of the remaining stations by 0.48– 0.78℃, and the difference of BST was larger (0.79–2.33℃). The Chlconcentration was low at station D4, and it was lower than the average Chlconcentration by 0.09–0.73mgm?3. There was only a slight difference in the salinity distribution.

        Table 1 The temperature, salinity, and Chl a concentration in the seawater surrounding the Hongyanhe Nuclear Power Plant in July, August, and September 2017

        Notes: SST, surface seawater temperature; BST, bottom seawater temperature; SSS, surface seawater salinity; BSS, bottom seawater salinity.

        Fig.2 Horizontal distribution of Chl a concentrations (mgm?3) in the seawater surrounding the Hongyanhe Nuclear Power Plant during July, August, and September of 2017.

        3.2 Zooplankton Community and Diversity in the Seawater Surrounding the Hongyanhe Nuclear Power Plant

        From July to September 2017, we collected and identi- fied 49 species/groups of zooplankton from the seawater surrounding the Hongyanhe Nuclear Power Plant, includ- ing 16 species/groups of larvae and 33 species of adults (Table 2).

        The average abundance of zooplankton first increased and then decreased from July to September. The average abundance across all stations in July was (4653.95±2750.66)indm?3, and the maximum was 10000indm?3at station E3. The average abundance in August was (8116.70±7204.30)indm?3, and the maximum abundance was 32320indm?3at station D3. In September, the average abundance was (3124.59±3231.48)indm?3. The highest abundance was observed at station A3 and it was 40987.5indm?3, of whichcontributed 39500indm?3.

        The total numbers of zooplankton species/groups de- clined, with 38 species/groups in July, 29 in August, and 27 in September. In July, there were 12 species of cope- pods, three species of small jellyfish, and 14 groups of lar- vae. Copepod species richness was stable in July and Au- gust, and then declined to eight groups in September. Groups of larvae declined from 14 to 9 over the course of these months. In September, we observed five species of jellyfish, which was the maximum.

        The cluster analysis of the zooplankton distribution is shown in Fig.3. In July, the zooplankton community at station D4, which was closed to the outlet of the power plant, was similar to those of three adjacent stations D2, D3 and E3, with the similarity exceeding 70%. The simi- larity between station D4 and most of the stations in the C and E sections exceeded 65%. No obvious distribution characteristics were observed from cluster analysis results in August. The similarity between D4 and other stations in the same section (D1 and D2) and the southern section (F2, F1, E1, and G2) was higher than 70%. In September, only station C4 had over 70% similarity with D4. Stations C3 and A1 and stations in section B had more than 65% similarity with station D4.

        Table 2 Zooplankton species/groups in the seawater surrounding the Hongyanhe Nuclear Power Plant in July, August, and September of 2017

        Notes: –, Species/groups not found; +, Species/groups found but not the dominant species/groups; ++, Species/groups found and also the dominant species/groups;, maxi-zooplankton net; *, midi-zooplankton net.

        Fig.3 Cluster analysis of zooplankton community in different sample stations. The red block represents stations with more than 70% similarity with station D4. The blue block represents stations with more than 65% similarity with station D4.

        The trends of the Shannon–Wiener index (), Margalefindex (m), and evenness coefficient () are shown in Fig.4. The Shannon-Wiener index showed a gentle downward trend, and the maximum value for all of the stations in August was 1.16–1.98 lower than in the other two months. The minimum value ofdropped significantly from Au- gust to September. Thevalue was fairly consistent with thevalue, which also showed a downward trend over the three months. The Dm in the seawater surrounding the Hongyanhe Nuclear Power Plant was the lowest in Au- gust, ranging from 0.95 to 1.55. The maximum and aver- age values of Dm were significantly lower in August, and rose sharply in September. The minimum value rebound in September was slight.

        Fig.4 The diversity index of the seawater surrounding the Hongyanhe Nuclear Power Plant during July, August, and Sep- tember of 2017.

        3.3 Distribution of Main Dominant Species/Groups in Seawater Surrounding the Hongyanhe Nuclear Power Plant

        In July 2017,,, cope- podid, and Bivalvia larvae accounted for 49% of the total zooplankton abundance in seawater surrounding the Hong- yanhe Nuclear Power Plant. The maximum zooplankton abundances were 5017.60, 1779.31, 2320.00, and 4057.14indm?3, respectively. This abundance ratio increased to 70% in August, and the maximum abundances for each group reached 1010.00, 7120.00, 8640.00, and 6577.78indm?3, respectively.became the domi- nant species, with a maximum abundance of 2466.67indm?3. In September,alone accounted for 72% of the total zooplankton abundance.,, copepodid, and Bivalvia larvae accounted for 56% of the zooplankton abundance whenwas not in- cluded. Their maximum abundances were 106.67, 250.00, 283.33, and 1590.00indm?3, respectively. The abundance of Chaetognatha larvae was also high, with a maximum of 415.79indm?3.

        The dominance index () ofshowed a down- ward trend with values of 0.495, 0.328, and 0.048 in July, August, and September, respectively.ofwas 0.039, 0.274, and 0.022 in July, August, and September, respectively, with a maximum in August. The copepodid also reached their maximum value in August, with 0.161, 0.265, and 0.037 for each of the respective three months. The index of Bivalvia larvae decreased from 0.259 to 0.042 during the summer (Table 3). In September,comprised a great percentage (72%) of the total zooplank- ton abundance, leading to the low dominance indexes of the four groups.

        Table 3 Dominance index of four dominant species/groups in the Hongyanhe Nuclear Power Plant in July, August,and September of 2017

        The distribution of dominant copepod speciesandis shown in Fig.5. The distribution ofwas uneven in July. It reached 5017.60indm?3at the southernmost station (G4). Without considering the G4 station, the average abundance of the remaining stations was (106.17±50.23)indm?3. The distribution ofwas more even in August than in July, with an average abundance of (183.13±43.34)indm?3. At transects C and D, the abundance ofwas relatively high, with an average of (467.79±139.66)indm?3and (284.03±80.21)indm?3, and the maximum abundance was 1010.00indm?3at station C2. In September, the total abundance decreased rapidly, with an average of (16.62±11.87)indm?3. The high- est abundance was 73.33indm?3, which was found at sta- tion E1. This station was located the farthest from the shore. The overall distribution of the zooplankton community was balanced and was trending away from the shore.

        Fig.5 Horizontal distribution of the dominant species/groups in the seawater surrounding the Hongyanhe Nuclear Power Plant during July, August, and September of 2017.

        In July, the average abundance ofwas 231.60± 183.55indm?3. It was generally distributed in the south- west. The highest abundance was 1779.31indm?3and wasobserved at station F2. The abundance ofin August increased sharply, with an average abundance of 2226.40±1549.35indm?3and a maximum abundance of 7120.00indm?3(station D3). In September, the average and maximum abundances ofwere 69.80±82.73indm?3and 250.00indm?3, respectively (station A3). The over- all abundance at transect E was high in September, with an average abundance of (118.30±39.25)indm?3.

        3.4 Relationship Between Environmental Factors and the Zooplankton Community

        The indicators of community changes were different for each of the three months. We used the BIO-ENV proce- dure to identify the combination of Chl, BST, and aver- age SS as the most reliable indicators (=0.427) in July (Table 4). Chlconcentrations appeared in all the eight combinations with the highestvalue. In August, the cor- relation was weaker than in the other two months (best=0.204), and the most reliable combination of factors in- cluded Chlconcentration and average ST. Chlwas also found to be among the most reliable five combinations. Chl, average ST, and average SS were the most reliableindicators (=0.238) of community changes in Septem- ber.

        Table 4 Results from BIO-ENV analysis, correlation of environmental factors, and zooplankton community in the seawater surrounding the Hongyanhe Nuclear Power Plant in July, August, and September of 2017

        Note:, correlation index between zooplankton community and environmental factors group.

        Fig.6 RDA of zooplankton abundance and environmental factors in the seawater surrounding the Hongyanhe Nuclear Power Plant during July, August, and September of 2017. CS, Calanus sinicus; ML, Macrura larvae; BL, Brachyura larva; PP, Paracalanus parvus; AB, Acartia bifilosa; CA, Corycaeus affinis; OD, Oikopleura dioica; CL, Chaetognatha larvae; BiL, Bivalvia larvae; OL, Ophiopluteus larvae; NS, Noctiluca scintillans; GL, Gastropoda larvae; OS, Oithona similis.

        The results of the RDA are shown in Fig.6. The aver- age ST, BST, and average SSwere the three environmen- tal variables with the greatest influence in July. The inf-luence of BST and average ST was basically the same, showing a significant negative correlation with the abun- dance ofand. Conversely, the BST was positively correlated with the Gastropoda larvae,, copepodid, Macrura larvae, bivalve larvae,, and nauplius.abundance was signifi- cantly affected by SS, and we identified a significant po- sitive correlation between its abundance and average SS.andabundances were also po- sitively correlated with average SS, butwas ne- gatively correlated with average ST.abundance was significantly negatively correlated with salinity.

        In August, average ST still had the greatest impact on zooplankton among all the environmental factors examined. Gastropoda larvae were no longer the dominant group. Zoo-plankton community composition was affected by changes in ST. The abundances of copepodid, bivalve larvae, and Macrura larvae were negatively correlated with BST in August, yet positively correlated with BST in July. The distribution of nauplii was not affected by other environ- mental factors. Onlywas still positively corre- lated with ST and salinity. Bothandwere negatively correlated with SST and Chl. Similarly, the abundance of new dominant species of Chaetognatha larva andwere significantly negatively af- fected by SST and Chlin August (Fig.6).

        In September, SS, BST, and average ST were the most significant variables (Fig.6)., Macrura larvae, andwere no longer the dominant species/group. Ins-tead,andwere the dominant spe- cies.andwere the newly collected jellyfish species in Sep- tember. The abundances of, bivalve larvae,, and copepodid showed a significantly negative correlation with average ST. Onlywas positively correlated with ST. We did not observe a sig- nificant positive relationship between the dominant spe- cies/group with SS, but the abundance of bivalve larvae,,, Chaetognatha larva, andwere negatively correlated with SS.

        The two species of small jellyfishandthat appeared in September were consid- ered to be important influencing factors. The RDA show- ed thatandhad a significant effect on the zooplankton community. The abundances of, bivalve larvae, and copepodid were significantly positively correlated with the total abundance of jellyfish. Conversely,,,, andwere unaffected by the jellyfish.

        4 Discussion

        4.1 Effects of the Liaoning Hongyanhe Nuclear Power Plant on Environment

        In general, the cooling systems of nuclear power plants cause an increase in the surrounding ST (Hung, 2006;Ma, 2014; Cardoso-Mohedano, 2015; Lee,2018), which was consistent with the findings of this study. On the basis of remote-sensing data from NASA, the SST change at station D4 was evident from 2010 to 2017 (Ta- ble 5). The average SST in the summer started to increase in 2013, after the nuclear power plant units were succes- sively put into operation. In June 2016, Wang(2018) found that in the seawater surrounding the Hongyanhe Nuclear Power Plant, the ST at the outlet was about 4℃ higher than that in the area 200m away. The SST values at station D4, which is located near the location of the hot-water exchange port of the power plant, were 1.55℃, 2.26℃, and 1.22℃ higher in July, August, and September, respectively, than the temperatures at the neighboring sta- tion D3. The ST at station D4 was 0.48–2.33℃ higher than the average ST, which was lower than that reported by other researchers (Bamber and Seaby, 2004; Cardoso-Mo- hedano, 2015). Cardoso-Mohedano(2015) found that the mean thermal impact was distributed along the shoreline within approximately 100m of the outlet of power plant. Hot-water exchange was supposed to mostly and directly affect the ST of station D4. The BST in July, how- ever, showed a decreasing trend from the southwest to the northeast. We speculated that the bottom cold-water flow caused the outflow of surface hot-water flow. The BST distribution in September was different from those in July and August, and it was almost the same as the average ST. In September, the ST at station D4 was the highest among all stations. It may be that the seawater convection ex- change for each seawater layer was weakened in Septem- ber.

        Table 5 Average SST in summer months at station D4 based on NASA remote-sensing data

        Note:The data represent the average SST of days 173–264 in the years 2012 and 2016, and days 172–263 in the other years.

        The Chlconcentration ranged from 0.13 to 5.12mgm?3, which is consistent with previous studies in Liao- dong Bay and the Bohai Sea (Song, 2010; Liu, 2014). The average Chlconcentration first increased and then decreased from July to September, which was consistent with the change of ST. In August, the highest Chlconcentration and salinity were found in transect A. It is likely that the ST did not increase to a point that sur- passed the thermal tolerance of the phytoplankton during these three months. The distributions of Chlconcentra- tion and ST in July and September were not consistent. The reasons might be that the phytoplankton populations at different stations were different, and that the population changed with different degrees of temperature adaptation.

        The average SS values for the three months were simi- lar, which is consistent with previous studies in Liaodong Bay (Song, 2010), and slightly higher than the re- sults from the central Bohai Sea (Liu, 2014). Liao- dong Bay is far from the Yellow River estuary, which makes the higher salinity reasonable. The value of SS at station D4 did not differ from those of other stations. Thus SS was not significantly affected by the outlet of the nu- clear power plant.

        4.2 Dominant Species/Groups Affected by Environmental Factors

        Environmental factors greatly affect the zooplankton com-munity (Plourde, 2002; Poornima, 2005; Tachi- bana, 2013; Dessier, 2018)The zooplankton community may also be a reliable indicator for evaluating the state of aquatic ecosystems (Mayer-Pinto, 2012; Vandysh, 2012). Following a 30-year study from 1959 to 1992 in the Bohai Sea, Tang(2003) suggested that a progressive depletion in zooplankton may be a response to the warming trend. In this study, we also found that the proportion of small-sized copepods increased over a re- latively short period, and this was closely related to tem- perature. Our results are consistent with predictions ofthe effects of environmental warming on ectotherms (Daufres- ne, 2009).

        andwere the dominant species of the zooplankton community in the seawater surrounding the Hongyanhe Nuclear Power Plant in July, August, and September of 2017. Recent studies found that, in addition to Bivalvia larvae, the other three groups were common dominant groups in Bohai Bay (Yang, 2018). We re- corded a total of 49 zooplankton species/groups in the seawater surrounding the Hongyanhe Nuclear Power Plant from July to September in 2017. There were 43 species/ groups found in Liaodong Bay from July to September in 2005 (Song, 2010) and 48 species/groups collected from the coastal seawater of Tianjin of the Bohai Sea over three months (May, July, and August) in three years (Gao, 2014). In July, the highest abundances ofwere found mainly at the three stations (E1, F2, and G4) with the lowest average ST (about 22℃). This is likely related to the adaptability of copepod species to low ST (Huntley and Lopez, 1992; Karas, 1992; Pu, 2004b). High abundances ofwere found at transects B and C in August. The distribution ofwas af- fected by the interactive effects of several environmental factors. A negative correlation existed among them, indi- cating that the high ST and Chlconcentration brought survival stress toin August. Sincecannot live in the surface seawater of Yellow Sea in sum- mer (Pu, 2004a), the ST was probably near the up- per temperature limit ofin the Bohai Sea. In September,was significantly negatively corre- lated with all the environmental factors, and its abun- dance was low in the nearshore and high offshore. With regard to environmental factors, ST and salinity tended to be high in the nearshore and low offshore. Additionally, the jellyfish bloom may have also had a negative impact onabundance (Kawahara, 2006; Uye, 2011, 2014; Shi, 2015). According to our field observations, a large number of giant jellyfishandappeared in the seawater surrounding the Hongyanhe Nuclear Power Plant in the summer, and the correlation coefficient also showed that the distribution of large jellyfish was negatively correlated within the summer (=?0.22 and ?0.31, respectively;<0.05) (unpublished data).

        In July,was affected by environmental factors in a similar way to. Theabundance is high in the southwest and low in the northeast seawater, which was negatively correlated with the average ST. In August and September, there was no significant correla- tion between the abundance ofand ST, salinity, or Chlconcentration. RDA results showed thatwas less affected by environmental factors. Addition- ally, the distribution ofin the summer was also affected by, with a correlation coefficient of ?0.41.

        The copepodid were distributed close to the nearshore in July, and we did not detect obvious distribution regu- larity in August. According to the RDA, copepodid were less affected by environmental factors in August. In Sep- tember, there was a low abundance of copepodid in the south and a high abundance in the north seawater, whereas the average ST was also low in the southwest and high in the northeast seawater. The RDA showed that copepodid were negatively correlated with SST over the three months, suggesting that copepodid are relatively sensitive to ST and prefer a lower ST.

        It is relatively difficult to directly judge whether the dis- tribution of bivalve larvae was affected by environmental factors. Different larvae groups had different adaptability to environmental factors. Bivalve larvae uniformly dis- tributed in July may be two different species, which are difficult to identify with the traditional morphological ta- xonomy method. From the RDA, the correlation of bi- valve larvae with ST changed from positive to negative in the three months. Considering that the planktonic larvae of benthic organisms had certain movement limitations, their response to the impact of environmental factors may have been delayed.

        4.3 Impact of Power Plants on Zooplankton

        The similarities between the zooplankton communities at the stations close to the nuclear power plant were rela- tively high, especially in July and September. In August, zooplankton diversity was relatively low, and the abun- dance of the dominant species/groups including, copepodid, and bivalve larvae was significantly higher than those in the other two months. Meanwhile, the three dominant species/groups were less affected than others by environmental factors in August (Fig.6), which may have resulted in the unobvious cluster of the zooplankton com- munity. ST plays an important role in the impact of power plants on the zooplankton community (Dias and Bonecker, 2008; Wang, 2012; Ma, 2014; Lee, 2018). In the seawater surrounding the Hongyanhe Nuclear Power Plant, the zooplankton community was negatively corre- lated with ST in the summer of 2017. When ST peaked in August, zooplankton diversity was the lowest. Song(2010) and Li(2014) found that zooplankton diver- sity was positively correlated with ST in Liaodong Bay and Daya Bay. The highest BST (up to 28.16 in August) could exceed the optimal survival range of some zoo- plankton such as(Karas, 1992; Bi, 2001; Pu, 2004b), which could result in a negative correla- tion between zooplankton diversity and ST. Furthermore, increased ST resulting from nuclear power plants was found to raise the respiratory and metabolism rates and carbon dioxide emissions of zooplankton, affecting their survival (Shiah, 2005). A study on pelagic copepods in the Yangtze River Estuary, which has higher temperature than Hongyanhe sea area, also found a negative correlation between temperature and zooplankton diversity (Li and Qian, 2009). Song(2010) found that in LiaodongBay, the total abundance was positively correlated with Chlconcentration in August when the temperature was the highest. The number of zooplankton species decreased, but species diversity increased in September. Total zoo- plankton abundance was positively correlated with Chlconcentration in September, which was higher than the concentrations in July and August. This could have been caused by the outbreak of small hydromedusae in Sep- tember, which compete with zooplankton for food (Li and Qian, 2009).

        In this study, the primary influence of the nuclear power plant on environmental factors was increasing the ST. High temperature was not conducive to the survival and repro- duction rates of copepods, such as(Karas, 1992; Zhang, 2002; Li and Qian, 2009). The negative im- pact of the Hongyanhe plant on the nearby zooplankton community owing to its influence on ST is consistent with previous studies. Many studies have found that high water temperatures caused by power plants may lead to a de- crease in the abundance of the zooplankton (Karas, 1992; Perissinotto and Wooldridge, 2010; Ma, 2014), and that higher ST in low-temperature months were positively correlated with the abundances of some copepods (Bi, 2001; Pu, 2004b; Lee, 2018). Wang(2009) found that the Daya Bay Power Plant had a greater impact on the phytoplankton community than on the zoo- plankton community. Ye(2018) suggested that the nuclear power plant changed the zooplankton community through its effect on phytoplankton in Daya Bay. Several environmental factors, including ST, dissolved oxygen, and nitrogen, could play important roles in determining zoo- plankton biomass in Daya Bay (Wang, 2012). The precise mechanism how nuclear power plants affect the zooplankton community requires additional research.

        5 Conclusions

        The zooplankton community in the seawater surround- ing the Hongyanhe Nuclear Power Plant was affected by ST, SS, and Chlconcentration, and the degree of influ- ence varied over the three summer months. The influence of temperature was relatively strong while that of salinity was relatively weak. The zooplankton abundance first in- creased and then decreased from July to September in 2017, and the biodiversity of the zooplankton communi- ty declined from July to September. The abundances of three dominant copepod species were significantly nega- tively affected by ST. In addition to the dominant cope- pod, the bivalve larvae had a different distribution mode in relation to the changes of ST. The Hongyanhe Nuclear Power Plant can affect the zooplankton community struc- ture as it can increase the ST near the outlet of the power plant.

        Acknowledgements

        This work was supported by the National Key R&D Program of China (Nos. 2017YFC1404401, 2017YFC140 4402), the Science & Technology Basic Resources Inves- tigation Program of China (No. 2017FY100803), and the National Natural Science Foundation of China (No. 4130 6155). We thank Dr. Natalie Kimfor improving this ma- nuscript.

        Bamber, R. N., and Seaby, R. M. H., 2004. The effects of power station entrainment passage on three species of marine plank- tonic crustacean,(Copepoda),(Decapoda) and(Decapoda).,57: 281-294, https://doi.org/10.1016/j. marenvres.2003.08.002.

        Bi, H. S., Sun, S., Gao, S. W., and Zhang, G. T., 2001. The eco- logical characteristics of zooplankton community in the Bo- hai Sea II. The distribution of copepoda abundance and sea- sonal dynamics., 21 (2): 177-185 (in Chi- nese with English abstract).

        Biard, T., Stemmann, L., Picheral, M., Mayot, N., Vandromme, P., Hauss, H., Gorsky, G., Guidi, L., Kiko, R., and Not, F., 2016.imaging reveals the biomass of giant protists in the global ocean., 532: 504-507, https://doi.org/10.1038/ nature17652.

        Cardoso-Mohedano, J. G., Bernardello, R., Sanchez-Cabeza, J. A., Ruiz-Fernández, A. C., Alonso-Rodriguez, R.,and Cruzado, A., 2015. Thermal impact from a thermoelectric power plant on a tropical coastal lagoon., 226: 1-11, https://doi.org/10.1007/s11270-014-2202-8.

        Chen, H. J., Yu, H., and Liu, G. X., 2016. Comparison of cope- pod collection efficiencies by three commonly used plankton nets: A case study in Bohai Sea, China., 15 (6): 1007-1013, https://doi.org/10.1007/ s11802-016-3122-6.

        Daufresne, M., Lengfellner, K., Sommer, U., and Carpenter, S. R., 2009. Global warming benefits the small in aquatic eco- systems.,106: 12788-12793, https://doi.org/10.1073/pnas.0902080106.

        Dessier, A., Bustamante, P., Chouvelon, T., Huret, M., Pagano, M., Marquis, E., Rousseaux, F., Pignon-Mussaud, C., Mornet, F., and Bréret, M., 2018. The spring mesozooplankton varia- bility and its relationship with hydrobiological structure over year-to-year changes (2003–2013) in the southern Bay of Bis- cay (Northeast Atlantic)., 166: 76-87, https://doi.org/10.1016/j.pocean.2018.04.011.

        Dias, C. D., and Bonecker, S. L. C., 2008. Long-term study of zoo- plankton in the estuarine system of Ribeira Bay, near a power plant (Rio de Janeiro, Brazil).,614: 65-81, https:// doi.org/10.1007/s10750-008-9537-3.

        Fang, Y., Fang, G. H., and Zhang, Q. H., 2000. Numerical simu- lation and dynamic study of the wintertime circulation of the Bohai Sea., 18 (1): 1-9, https://doi.org/10.1007/BF02842535.

        Feng, S., Lin, J. N., Sun, S., Zhang, F., and Li, C. L., 2018. Hy- posalinity and incremental micro-zooplankton supply in early- developedpolyp survival, growth, and podocyst reproduction.,591: 117-128, https://doi.org/10.3354/meps12204.

        Gao, W. S., Liu X. B., Zhang, Q. F., Xu, Y. S., Ma, Y. Y., He, R., and Liu, Y., 2014. Species diversity of zooplankton in thecoastal area of Bohai Bay., 38: 55-60 (in Chi- nese with English abstract).

        Gillooly, F. J., 2000. Effect of body size and temperature on ge- neration time in zooplankton., 22: 241-251.

        H?kanson, L., and Eklund, J. M., 2010. Relationships between chlorophyll, salinity, phosphorus, and nitrogen in lakes and ma- rine areas., 26: 412-423, https:// doi.org/10.2112/08-1121.1.

        Hung, T. C., Huang, C. C., and Shao, K. T., 2006. Ecological sur- vey of coastal water adjacent to nuclear power plants in Tai- wan., 15: 129-142, https://doi.org/10. 1080/02757549808037625.

        Huntley, M. E., and Lopez, M. D., 1992. Temperature-depend- ent production of marine copepods: A global synthesis., 140 (2): 201-242, https://doi.org/10.1086/ 285410.

        Irigoien, X., Huisman, J., and Harris, R. P., 2004. Global biodi- versity patterns of marine phytoplankton and zooplankton.,429 (6994): 863-867, https://doi.org/10.1038/nature02 593.

        Karas, P., 1992. Zooplankton entrainment at Swedish nuclear powerplants., 24: 27-32, https://doi.org/10. 1016/0025-326X(92)90313-U.

        Kawahara, M., 2006. Unusual population explosion of the giant jellyfish(Scyphozoa: Rhizostomeae) in East Asian waters., 307:161- 173, https://doi.org/10.3354/meps307161.

        Larson, A., 2014. Hongyanhe Nuclear Power Plant, Liaoning Pro- vince, China., 158 (11): 24-25.

        Lee, P. W., Tseng, L. C., and Hwang, J. S., 2018. Comparison of mesozooplankton mortality impacted by the cooling systems of two nuclear power plants at the northern Taiwan coast, sou- thern East China Sea., 136: 114-124, https://doi.org/10.1016/j.marpolbul.2018.09.003.

        Li, J. Q., and Wang, L. H., 2009. Numerical simulation of tem- perature field in turbo-generators stator on cooling water blo- ckage., 29 (12): 70-74 (in Chinese with English abstract).

        Li, K. Z., Yin, J. Q., Tan, Y. H., Huang, L. M., and Song, X. Y., 2014. Short-term variation in zooplankton community from Daya Bay with outbreaks of., 56: 583-602, https://doi.org/10.5697/oc.56-3.583.

        Li, X. Z., and Qian, G., 2009.: Its distribu- tion in Yangtze River Estuary and responses to global warming., 20: 1196 (in Chinese with English abstract).

        Lin, C. L., Su, J. L., Xu, B. R., and Tang, Q. S., 2001. Longterm variations of temperature and salinity of the Bohai Sea and their influence on its ecosystem.,49 (1-4): 7-19, https://doi.org/10.1016/S0079-6611(01)00013-1.

        Lin, K., and Holbert, K. E., 2009. Blockage diagnostics for nu- clear power plant pressure transmitter sensing lines.,239 (2): 365-372, https://doi.org/10.1016/ j.nucengdes.2008.10.012.

        Liu, L. X., Wang, Y. J., Di, B. P., and Liu, D. Y., 2014. Spatial distribution of chlorophylland environmental factors in the Bohai Sea in spring of 2012., 38 (12): 8-15 (in Chinese with English abstract).

        Liu, Y. W., Wang, Z. Y., Cao, G. W., Cao, Y., and Huo, Y., 2017. Study on corrosion behavior of zinc exposed in coastal-indus- trial atmospheric environment.,198: 243-249, https://doi.org/10.1016/j.matchemphys.2017. 05.043.

        Loeb, V., Hofmann, E. E., Klinck, J. M., and Holm-Hansen, O., 2010. Hydrographic control of the marine ecosystem in the South Shetland-Elephant Island and Bransfield Strait region.–, 57: 519-542, https://doi.org/10.1016/j.dsr2.2009.10.004.

        Ma, Y. E., Ke, Z. X., Huang, L. M., and Tan, Y. H., 2014. Iden- tification of human-induced perturbations in Daya Bay, China: Evidence from plankton size structure., 72: 10-20, https://doi.org/10.1016/j.csr.2013.10.012.

        Margalef, R., 1957. La teoria de la informacion en ecologia., 32: 373-499.

        Mayer-Pinto, M., Ignacio, B. L., Szechy, M. T. M., Viana, M. S., Curbelo-Fernandez, M. P., Lavrado, H. P., Junqueira, A. O. R., Vilanova, E., and Silva, S. H. G., 2012. How much is too little to detect impacts? A case study of a nuclear power plant., 7: e47871, https://doi.org/10.1371/journal.pone.0047871.

        Odum, E. P., 1959.. W. B. Saunders Co., Philadelphia, 384pp.

        Parsons, T. R., Lebrasseur, R. J., and Fulton, J. D., 1967. Some observations on the dependence of zooplankton grazing on the cell size and concentration of phytoplankton blooms., 23: 10-17, https://doi.org/10.5928/ kaiyou1942.23.10.

        Perissinotto, R., and Wooldridge, T. H., 2010. Short-term ther- mal effects of a power-generating plant on zooplankton in the Swartkops Estuary, South Africa.,10: 205- 219, https://doi.org/10.1111/j.1439-0485.1989.tb00473.x.

        Petrou, K., Doblin, M. A., and Ralph, P. J., 2011. Heterogeneity in the photoprotective capacity of three Antarctic diatoms du- ring short-term changes in salinity and temperature., 158: 1029-1041, https://doi.org/10.1007/s00227-011- 1628-4.

        Pielou, E. C., 1966. The measurement of diversity in different types of biological collections., 13: 131-144,https://doi.org/10.1016/0022-5193(66)90013-0.

        Plourde, S., Dodson, J. J., Runge, J. A., and Therriault, J. C., 2002. Spatial and temporal variations in copepod community struc- ture in the lower St. Lawrence Estuary, Canada.,230: 211-224, https://doi.org/10.3354/ meps230211.

        Poornima, E. H., Rajadurai, M., Rao, T. S., Anupkumar, B., Ra- jamohan, R., Narasimhan, S. V., Rao, V. N. R., and Venugo- palan, V. P., 2005. Impact of thermal discharge from a tropical coastal power plant on phytoplankton., 30: 307-316, https://doi.org/10.1016/j.jtherbio.2005. 01.004.

        Pu, X. M., Sun, S., Yang, B., Ji, P., Zhang, Y., and Zhang, F., 2004. The combined effects of temperature and food supply onin the southern Yellow Sea in summer.,26: 1049-1057, https://doi.org/10. 1093/plankt/fbh097.

        Purcell, J. E., Uye, S. I., and Lo, W. T., 2007. Anthropogenic cause of jellyfish blooms and their direct consequences for humans: A review., 350: 153-174, https:// doi.org/10.3354/meps07093.

        Richardson, A. J., and Schoeman, D. S., 2004. Climate impact on plankton ecosystems in the Northeast Atlantic., 305 (5690): 1609-1612, https://doi.org/10.1126/science.1100958.

        Roemmich, D., and Mcgowan, J., 1995. Climatic warming and the decline of zooplankton in the California Current., 267 (5202): 1324-1326, https://doi.org/10.1126/science.267.5202. 1324.

        Shannon, C., and Weaver, W., 1949.. University of Illinois Press, Urbana, IL, 94pp.

        Shi, Y. Q., Sun, S., Zhang, G. T., Wang, S. W., and Li, C. L., 2015.Distribution pattern of zooplankton functional groups in the Yellow Sea in June: A possible cause for geographical sepa- ration of giant jellyfish species., 754: 43-58, https://doi.org/10.1007/s10750-014-2070-7.

        Shiah, F. K., Tu, Y. Y., Tsai, H. S., Kao, S. J., and Jan, S., 2005. A case study of system and planktonic responses in a subtro- pical warm plume receiving thermal effluents from a power plant., 16: 513- 528, https://doi.org/10.3319/TAO.2005.16.2.513(O).

        Song, L., Zhou, Z. C., Wang, N. B., Ma, Z. Q., Xue, K., Tian, J., Yang, S., Wang, Z. H., and Wu, J. H., 2010. Zooplankton di- versity of Liaodong Bay and relationship with oceanic envi- ronmental factors.,34: 35-39 (in Chinese with English abstract).

        Sun, S., Huo, Y. Z., and Yang, B., 2010. Zooplankton functional groups on the continental shelf of the Yellow Sea.–, 57 (11-12): 1006-1016, https://doi.org/10.1016/j.dsr2.2010.02.002.

        Tachibana, A., Itoh, H., and Yoshida, Y., 2013. Seasonal and an- nual change in community structure of meso-sized copepods in Tokyo Bay, Japan., 69: 545-556, https://doi.org/10.1007/s10872-013-0191-7.

        Tang, Q. S., Jin, X. S., Wang, J., Zhuang, Z. M., Cui, Y., and Meng, T. X., 2003. Decadal-scale variations of ecosystem produc- tivity and control mechanisms in the Bohai Sea., 12 (4-5): 223-233, https://doi.org/10.1046/j.1365- 2419.2003.00251.x.

        Uye, S. I., 2011. Human forcing of the copepod-fish-jellyfish tri-angular trophic relationship., 666: 71-83, https:// doi.org/10.1007/s10750-010-0208-9.

        Uye, S. I., 2014. The giant jellyfishin East Asian marginal seas. In:. Pitt, K. A., and Lucas, C. H., eds., Springer, Dordrecht, 185-205, https://doi.org/10.1007/978-94-007-7015-7_8.

        Vandysh, O. I., 2012. Specific features of zooplankton commu- nity in industrially polluted areas of Subarctic Lake Imandra (Monche, Belaya, and Molochnaya Bays)., 43: 390-397, https://doi.org/10.1134/S10674136120 50153.

        Wang, Y., Fang, E. J., Guo, B., Gao, Y., and Hou, C. Q., 2014. Zoo- plankton community structure and its relationship with envi- ronmental factors in spring of Bohai Bay in Tianjin sea area., 36: 300-305, https://doi:10.13233/j.cnki.mar. fish.2014.04.004 (in Chinese with English abstract).

        Wang, X., Wang, X. X., Su, X., Meng, Q. H., Zou, D. J., Yin, X. D., Wang, L., Wen, S. Y., and Zhao, J. H., 2018. Thermal dis- charge monitoring of nuclear power plant with aerial remote sensing technology using a UAV platform: Take Hongyanhe Nuclear Power Plant, Liaoning Province, as example., 30 (4): 182-186 (in Chinese with English abstract).

        Wang, Y. S., Lou, Z. P., Sun, C. C., Wang, H. L., Mitchell, B. G., Wu, M. L., and Deng, C., 2012. Identification of water quality and zooplankton characteristics in Daya Bay, China, from 2001 to 2004., 66: 655-671, https:// doi.org/10.1007/s12665-011-1274-7.

        Wang, Z. H., Zhao, J. G., Zhang, Y. J., and Yu, C., 2009. Phyto-plankton community structure and environmental parameters in aquaculture areas of Daya Bay, South China Sea., 21: 1268-1275, https://doi.org/10. 1016/S1001-0742(08)62414-6.

        Wu, Y. N., Wang, Y. Q., Hou, Q. M., Jiao, F., and Sun, G. C., 2017. Experience feedbacks on events of nuclear power plants cold source systems blocked by oceanic foreign matter., 16 (1): 26-32 (in Chinese with English abstract).

        Yang, L., Liu, J., Zhang, J., Wang, X. L., Xu, Y., Li, X., and He, L., 2018. Zooplankton community variation and its relation- ship with environmental variables in Bohai Bay.,36 (1): 93-101 (in Chinese with English ab- stract).

        Ye, Y. Y., Chen, K. B., Zhou, Q. Q., Xiang, P., Huo, Y. L., and Lin, M., 2018. Impacts of thermal discharge on phytoplankton in Daya Bay., 83: 135-147, https:// doi.org/10.2112/SI83-022.1.

        Zhang, W. C., and Wang, R., 2000. Microzooplankton and their grazing pressure on phytoplankton in Bohai Sea., 31: 252-258 (in Chinese with English abstract).

        Zhang, W. C., Wang, K., Gao, S. W., and Wang, R., 2002. Zoo- plankton in the Bohai Sea in spring and autumn., 33: 630-639 (in Chinese with English ab- stract).

        Zhou, F., Huang, D. J., and Su, J. L., 2009. Numerical simulation of the dual-core structure of the Bohai Sea cold bottom water in summer., 54 (23): 4520-4528,https:// doi.org/10.1007/s11434-009-0019-4.

        #The two authors contributed equally to this work.

        . E-mail: lcl@qdio.ac.cn

        December 25, 2019;

        April 1, 2020;

        May 26, 2020

        (Edited by Qiu Yantao)

        日本久久大片中文字幕| 欧美午夜精品一区二区三区电影 | 在线观看国产成人av片| 一区二区视频观看在线| 色婷婷精品国产一区二区三区| 日日麻批免费高清视频| 一 级做人爱全视频在线看| 国产午夜精品一区二区三区| 妇女性内射冈站hdwwwooo| AV在线中出| 国产另类人妖在线观看| 欧美午夜理伦三级在线观看| 性大毛片视频| 亚洲日韩精品欧美一区二区三区不卡| 久久精品国产亚洲av成人擦边 | 国产一区二区三区不卡在线观看| 国产精品成人免费视频一区| 久久精品一区二区三区av| 久久久久成人精品免费播放| 少妇一区二区三区精选| 午夜视频在线观看视频在线播放| 欧美老熟妇喷水| 久久久久无码国产精品不卡 | 亚洲香蕉久久一区二区| 亚洲中文字幕精品乱码2021 | 亚洲乱码av中文一区二区| 亚洲天堂av免费在线看| 美利坚亚洲天堂日韩精品| 麻豆文化传媒精品一区观看| 国产精品欧美一区二区三区| 99久久久精品免费香蕉| 一本久道视频无线视频试看| 在线观看视频日本一区二区| 欧美精品黑人粗大免费| 久久亚洲道色宗和久久| 国产一区二区高清不卡在线| 久久精品国产亚洲av四叶草| 青春草在线视频免费观看| 国产精品爆乳在线播放| 亚洲天堂色婷婷一区二区| 丰满少妇在线播放bd|