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Article

Studying the Metazoan Zooplankton Community Characteristics and Evaluating the Water Quality Based on the Ecological and Functional Zones in Gaoyou Lake

by
Liuchao Guo
1,2,*,
Liwu Mo
2,
Yuyan Su
3,
Xiaodong Hu
1 and
Dandan Xu
1
1
Jiangsu Hydraulic Research Institute, Nanjing 210017, China
2
College of Materials Science and Engineering, Nanjing Tech University, Nanjing 211800, China
3
Hydraulic Engineering Science and Technology Consultation Limited Company of Jiangsu Province, Nanjing 210036, China
*
Author to whom correspondence should be addressed.
Water 2023, 15(19), 3357; https://doi.org/10.3390/w15193357
Submission received: 8 August 2023 / Revised: 16 September 2023 / Accepted: 18 September 2023 / Published: 25 September 2023
Browse Figures
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Abstract

:
To study the metazoan zooplankton community structure and water quality, we investigated the amount of metazoan zooplankton and the water quality in Gaoyou Lake from January to December 2022. Furthermore, we also evaluated the multi-index and nutritional status of Gaoyou Lake using the comprehensive nutritional status index of water quality, dominant population composition of the metazoan zooplankton, B/T index, and Shannon–Weaver diversity index based on the situation of each ecological and functional zone. The results indicated that the metazoan zooplankton of Gaoyou Lake included 21 families, 31 genera, and 63 species. The rotifers had 8 families, 16 genera, and 34 species, accounting for 53.9% of all species. The cladocerans had 6 families, 7 genera, and 16 species, which accounted for 25.4% of all species. The copepods had 7 families, 8 genera, and 13 species, that accounted for 20.7% of all species. The density and species of small metazoan zooplankton (rotifers) had a higher proportion than large metazoan zooplankton (crustaceans). The average annual metazoan zooplankton density was 1595.7 ind./L, the average annual biomass was 4.31 mg/L, the average annual total nitrogen (TN) was 1.101 mg/L, and the average annual total phosphorus (TP) was 0.082 mg/L. The TN and TP of the Gaoyou Lake were over the standard. The comprehensive nutritional status indices of the water quality in the entire lake and the ecological and functional areas were consistent with the metazoan zooplankton evaluation results, which determined that Gaoyou Lake showed mild eutrophication.

1. Introduction

Rivers and lakes are important water resources and crucial components of ecosystems and national spaces [1,2,3]. Rivers and lakes with beautiful ecological environments are sources of livelihood and public resources. Since the 18th CPC National Congress, General Secretary Xi Jinping has proposed to prioritize water conservation, the equalization of space, systematic governance, and the “two hands” approach. The idea of “empowering” water control includes making a series of important speeches, issuing instructions, and establishing the “River Strategy”, which provide fundamental guidelines and action guidelines for strengthening the protection of rivers and lakes [4].
Jiangsu Province is located at the lower reaches of the Yangtze River, Huaihe River, and Yishu River basins, with numerous rivers and lakes [5]. Gaoyou Lake spans Gaoyou City, Jinhu County, Baoying County of Jiangsu Province, and Tianchang City of Anhui Province. The water area of the whole lake is ~760 square kilometers and is connected to the Hongze Lake system and Yangtze River system in the north and south, respectively [6]. It is a provincial lake in Jiangsu Province. In 2005, according to the ecological and functional positioning and protection objectives for the Gaoyou Lake, the Water Resources Department of Jiangsu Province uniformly organized and demarcated three types of ecological and functional zones: the core zone, the buffer zone, and the developed and utilized zone. The core zone is a highly significant zone for maintaining lake biodiversity and the fishery population. The buffer zone promotes the restoration of the lake ecosystem and helps improve the lake environment, and it is a zone with a low level of development reserved for future generations. The developed and utilized zone is a zone that can be moderately developed and utilized under relevant regulations. The ecological and functional zones were approved by the People’s Government of Jiangsu Province in 2006 (SZF [2006] No. 99).
Metazoan zooplankton is a collective term for all phyla of multicellular animals except for the protozoa phylum [7,8]. They are very important in the lake ecosystem. They not only provide food for economically important filter-feeding fish like silver carp and bighead carp, but also regulate the occurrence and development of planktonic algae and bacteria [9,10,11]. They are an important link in the energy flow and logistics between the producers in the lake’s biological chain [12,13]. The environmental adaptability of different metazooplankton species is different. The changes in density, biomass, and pollution indicator species can reflect the nutritional status of the lake [14]. Therefore, the community structure characteristics of metazoan zooplankton are highly significant in the study of lake aquaculture, the structure and function of the water ecosystem, and the prevention and control of eutrophication [15,16,17]. Currently, multiple studies have investigated the water quality [18] and sediments [19] in Gaoyou Lake. However, very few have studied the metazoan zooplankton at Gaoyou Lake. In 2022, we investigated the metazoan zooplankton along with the physical and chemical indicators of the water in Gaoyou Lake. We used the water quality indexes and metazoan zooplankton to comprehensively evaluate the nutritional status of Gaoyou Lake. The purpose was to provide basic data and a theoretical basis for the development and utilization of Gaoyou Lake, water environment treatment, and ecological restoration.

2. Research Area and Method

2.1. Sample Point Settings

According to the topographic profile of Gaoyou Lake, the main rivers entering and leaving the lake, the ecological and functional zone, and hydrologic conditions, 13 sampling points (gyh-1–gyh-13, Figure 1) are set in accordance with the principles of full lake coverage, prominent emphasis, and economy.

2.2. Sampling and Processing

2.2.1. Water Quality Sampling, Treatment, and Experimentation

Water quality samples were taken from January to December 2022 with a sampling frequency of once per month. The physical and chemical indexes of water, such as water temperature, pH, dissolved oxygen, and Chl a were measured on-site with a water quality multi-parameter analyzer (exo type) (YSI Inc., 1725 Brannum Lane, Yellow Springs, OH, USA). The water transparency was measured with a Secchi disc. For the water quality permanganate index (CODMn), ammonia nitrogen, TP, and TN, 500 mL of the water sample was collected at ~0.5 m below the water surface of the lake using a 5 L water sampler. Then, 1 mL of sulfuric acid (concentration: 1.84 g/mL) was added to fix it [20,21,22,23], followed by storage at low temperatures, and the sample was finally taken back to the laboratory for further determination.
The water quality permanganate index (CODMn) was determined according to the requirements of GB/T11892-1989 [24].
Ammonia nitrogen was determined by Nessler’s reagent spectrophotometry according to standard HJ535-2009 [25].
TP was determined by ammonium molybdate spectrophotometry according to standard GB11893-1989 [26].
TN was determined by alkaline potassium persulfate ultraviolet spectrophotometry according to standard HJ636-2012 [27].

2.2.2. Sampling, Treatment, and Counting of Metazoan Zooplankton

Metazoan zooplankton was sampled from January to December 2022, with the quantitative samples being taken once in the middle of each month.
The rotifer samples were bottled with 1 L surface water of the lake on board ship, and Lugol’s solution (5%) was immediately added to the samples for fixation to kill the phytoplankton and other organisms. The dosage of Lugol’s solution was 10 mL, so that the sample was brownish-yellow. We took it back to the laboratory to precipitate and concentrate with a separatory funnel. After standing for 48 h, the supernatant was sucked out. When 20~30 mL remained, the sediment was transferred into a 50 mL reagent bottle. Before counting, the quantitative sample was shaken well, and we quickly absorbed a 0.1 mL sample with a pipette and moved it into the counting box. Before moving it in, the cover glass was placed in the counting box to avoid bubbles during injection. After filling, we straightened the cover glass. After the counting specimen was made, we waited for a few minutes for the rotifers to float to the bottom of the frame and counted under the microscope to obtain the density of rotifers in the unit volume (1 L) [28,29]. In the counting process, if the number of rare species was too small to temporarily determine the genus and species, the number could be counted first and the photos could be kept for the specific identification of the species when necessary.
For the cladocerans and copepods, we used a water sampler to take 10 L of water samples on board the ship, filtered them with a No. 25 plankton net, and placed the filtered material into a sample bottle. For water bodies with a depth of less than 3 m and well mixed water masses, only surface water samples could be taken. For areas with deeper water depths, the surface, middle, and bottom mixed water samples were taken separately. After the collected water sample was put into a 50 mL plastic bottle, it was immediately fixed with formaldehyde (40%) to kill the metazoan zooplankton and other organisms [30]. The samples were taken back for microscopic examination to identify the zooplankton to the species level. When counting, all the cladocerans and copepods were counted according to the number of points in the sample [31].

2.2.3. Biomass Conversion of Metazoan Zooplankton

The number of metazoan zooplankton was obtained by counting under a microscope. The length, width, and thickness were measured according to the approximate geometric figure, and the biological volume was calculated by the quadrature formula to convert the biomass [32,33,34].

2.2.4. Quality Control of Metazoan Zooplankton Counting

We counted each sample twice and took the average value, with each result equal to 10% of the average value [35]. Otherwise, we counted a third time.

2.3. Results Analysis and Evaluation Methods

2.3.1. Evaluation of the Comprehensive Nutritional Status of Lake Water Quality

The water quality eutrophication evaluation items included chlorophyll a (Chl a, μg/L), permanganate index (CODMn), TN, TP, and transparency (SD). The comprehensive trophic state index method was adopted [36,37]. The formula for calculation is as follows:
T L I ( ∑ ) = ∑ j = 1 m W j • T L I ( j )
where TLI(∑)—comprehensive nutritional status index; Wj—correlation weight of nutritional status index of jth parameter; TLI(j)—nutritional status index of the jth parameter.
Calculation formulae of the nutritional status index of participating indicators are as follows:
TLI(SD) = 10 × (5.118 − 1.94 × ln SD)
TLI(Chl a) = 10 × (2.500 + 1.086 × lnChla)
TLI(TP) = 10 × (9.436 + 1.624 × lnTP)
TLI(TN) = 10 × (5.453 + 1.694 × lnTN)
TLI(CODMn) = 10 ×(0.109 + 2.661 × lnCODMn)
Taking Chl a as the reference parameter, the normalized correlation weight calculation formula of the jth parameter is as follows:
W j = r i j 2 ∑ j = 1 m r i j 2
where rij—correlation coefficient between the jth parameter and the reference parameter Chl a; m—number of evaluation parameters.
The classification criteria are as follows [38]: poor trophic state—TLI(∑) < 30; mesotrophic status—30 ≤ TLI(∑) ≤ 50; rich nutrition—TLI(∑) > 50; mild eutrophication—50 < TLI(∑) ≤ 60; medium eutrophication—60 < TLI(∑) ≤ 70; severe eutrophication—TLI(∑) > 70.

2.3.2. Calculation Method of the Dominance of Metazoan Zooplankton

The calculation formula of the zooplankton dominance index is as follows:
Y = (ni/N) × fi
where ni is the abundance of the ith species (ind./L); fi is the frequency (%) of the occurrence of the ith species; N is the total abundance of species (ind./L); and the species with dominance Y ≥ 0.02 is taken as the dominant species.

2.3.3. Evaluation of the Trophic Status of Metazoan Zooplankton

In 1983, Sladeck [39] put forward the B/T index that is commonly used to evaluate the water quality trophic state, according to the fact that Brachionus (B) is mostly a eutrophic species and Trichocerca (T) is mostly a poor trophic species [40].
B/T = B (Species of Brachionus)/T (species of Trichocerca). B/T < 1 indicates an oligotrophic lake and 2 > B/T > 1 indicates a mesotrophic lake; B/T > 2 indicates a eutrophic lake.

2.3.4. Diversity Evaluation of Metazoan Zooplankton Communities

The Shannon–Weaver diversity index represents the degree of imbalance and disorder among individual species in a community, indicating the level of diversity of the entire community [41,42,43]. The calculation formula is as follows:
H = − ∑ i = 1 n n i N ln ⁡ n i N
where H is the Shannon–Weaver diversity index of communities; n i is the number of individuals of the ith species in the community; N is the total number of individuals of all species in the community; and n is the number of species in the community.
Diversification level classification [44,45]: H > 3 indicates no polluting or lightly polluted water quality; 1 ≤ H ≤ 3 indicates moderately polluted water quality; H < 1 indicates severely polluted water quality.

3. Results and Analysis

3.1. Condition of Water

3.1.1. Analysis of Physical and Chemical Indexes of Water Quality

The monthly water temperature variation range in Gaoyou Lake was 6.8–33.2 °C, which was mainly related to the external environmental changes of the lake. Although the pH change range was small, the average pH value was 8.4, which favored the growth of aquatic animals and plants [46,47,48]. The range of dissolved oxygen was 5.8–11.5 mg/L, with the average value being 9.2 mg/L, which favored the development of fishery culture in Gaoyou Lake [49,50,51,52]. The change range of transparency was small, with the average value being 0.23 m. The change range of the permanganate index was 4.21–5.95 mg/L, with an average value of 4.75 mg/L, which met the requirements of the class III water quality of the surface water. The variation range of TN was 0.72–1.478 mg/L, with the average value being 1.101 mg/L, and according to thestandard GB3838-2002 [53], it was considered class IV water. The TP variation range was 0.052–0.098 mg/L, with the average value being 0.082 mg/L, thereby categorizing it as class IV water (Table 1). Therefore, we could see that the TN and TP levels in the water quality of Gaoyou Lake were the main parameters that exceeded their standards.

3.1.2. Eutrophication Evaluation of Water Quality Index

According to Table 1 and the data of each station during the monitoring month, we evaluated the water quality of Gaoyou Lake based on the abovementioned lake eutrophication evaluation methods and classification standards. The comprehensive nutritional status of the entire lake and each ecological function zone was basically stable, with the nutritional index ranging from 51.1 to 54.8, thereby indicating that all were mildly eutrophic. The change in the comprehensive nutritional status index of the entire lake is seen in Figure 2, with the comprehensive nutritional status index changes of each zone as follows: the core zone (gyh-3, gyh-9), the buffer zone (gyh-5, gyh-6, gyh-7, gyh-8, gyh-10, gyh-11, gyh-12, and gyh-13 points), and the developed and utilized zone (gyh-1, gyh-2, gyh-4), as shown in Figure 3, Figure 4 and Figure 5.

3.2. Temporal and Spatial Changes in Metazoan Zooplankton in Gaoyou Lake and Evaluation of Their Nutritional Status

3.2.1. Species Composition of Metazoan Zooplankton in Gaoyou Lake

According to the quantitative water sample analysis of metazoan zooplankton in Gaoyou Lake from January to December 2022, the microscopic examination of the species showed 21 families, 31 genera, and 63 species. The rotifers had 8 families, 16 genera, and 34 species, which accounted for 53.9% of all species. The cladocerans had 6 families, 7 genera, and 16 species, accounting for 25.4% of all species. The copepods had 7 families, 8 genera, and 13 species, that accounted for 20.7% of all species.
The dominant species of rotifers in Gaoyou Lake included Keratella cochlearis, Keratella valga, Brachionus angularis, Brachionus calyciflorus, and Polyarthra sp. The dominant species of cladocerans in Gaoyou Lake included Diaphanosoma brachyurum, Bosmina coregoni, and Ceriodaphnia cornuta. The dominant species of copepods were Mesocyclops leuckarti, Cyclops vicinus, and Sinocalanus dorrii (Table 2).

3.2.2. Standing Stock and Seasonal Variation in Metazoan Zooplankton in Gaoyou Lake

In 2022, the annual average number of metazooplankton in Gaoyou Lake was 1595.7 ind./L. Among them, rotifers constituted 1500.4 ind./L (96.0%); cladocerans constituted 47.8 ind./L, (1.9%); and copepods constituted 47.5 ind./L (2.1%). The density demonstrated that the total metazoan zooplankton number in Gaoyou Lake was determined by the number of rotifers, as cladocerans and copepods accounted for only 4.0% of the total number. The error of the two counting results of metazooplankton was 4.6%, which met the requirement of less than 10%.
Among the annual number of rotifers, the highest was 2523.1 ind./L in June, while the lowest occurred at 546.2 ind./L in March, with the highest concentrations in summer and autumn. The cladocerans number was the highest at 120.2 ind./L in August and the lowest at 5.4 ind./L in January, with the highest concentrations in late spring and summer. The largest number of copepods was 131.9 ind./L in July, with the lowest being 11.9 ind./L in February with the highest concentrations in summer. The monthly variation in the density of metazoan zooplankton can be seen in Figure 6.
The annual average total biomass of metazoan zooplankton in Gaoyou Lake was 4.31 mg/L. Among them, the biomass of rotifers, cladocerans, and copepods was 1.66 mg/L (38.5%), 1.44 mg/L (33.4%), and 1.21 mg/L (28.1%). The monthly variation in the biomass of metazoan zooplankton is shown in Figure 7.

3.2.3. Spatial Variation of Metazoan Zooplankton in Gaoyou Lake

The average annual biological density of metazoan zooplankton in Gaoyou Lake was 1171.1–2304.1 ind/L. The top five sites were gyh-1, gyh-2, gyh-4, gyh-8, and gyh-12, with gyh-5 showing the lowest density (Figure 8). The annual average biomass of metazoan zooplankton in each sampling point of Gaoyou Lake varied from 3.47 to 5.77 mg/L. The top five biomass sites were gyh-1, gyh-2, gyh-8, gyh-4, and gyh-3, with average annual biomasses of 5.77, 4.78, 4.74, 4.72, and 4.66 mg/L, respectively, and gyh-9 had the lowest annual average biomass (3.47 mg/L) (Figure 9).
According to the ecological division of Gaoyou Lake, the variation range in the buffer zone was 0–5650 ind./L (rotifers), 0–195 ind./L (cladocerans), and 0–155 ind./L (copepods). For the core zone, it was 300–5000 ind./L, 0–150 ind./L, and 0–125 ind./L for rotifers, cladocerans, and copepods, respectively. However, these variation ranges in the developed and utilized zone were 500–6200 ind./L, 0–200 ind./L, and 0–185 ind./L, respectively. The annual average densities of metazooplankton in the buffer and core zones were close (1289.3 and 1383.0 ind./L), with its biomass density in the developed and utilized zone being the highest (2050.7 ind./L) (Figure 10). We can see from Figure 11 that the annual average biomass of metazoan zooplankton in the different ecological functional zones indicated the following trend: the developed and utilized zone > the buffer zone > the core zone.

3.2.4. Evaluation of the Water Body Using Dominant Species Composition of Metazoan Zooplankton

Considering the different sensitivities of metazoan zooplankton to the water environment, we can use the ecological structure characteristics of the dominant species community for lake water quality assessment [54,55,56].
The dominant species of metazoan zooplankton in Gaoyou Lake were Keratella cochlearis, Brachionus angularis, Brachionus calyciflorus, Bosmina coregoni, and Mesocyclops leuckarti. These were indicator species of eutrophic lakes. According to the dominant species composition of metazoan zooplankton, Gaoyou Lake was classified as a eutrophic lake.

3.2.5. Evaluation of the Water Body of Gaoyou Lake by B/T Index of Metazoan Zooplankton

According to the above B/T index calculation method, we calculated the annual average QB/T value of each station in Gaoyou Lake (Figure 12). The QB/T value of each station in Gaoyou Lake varied from 1.7 to 3.2, with the average value being 2.2. According to the classification of nutritional status levels in Section 2.3.3, Gaoyou Lake was considered overall as a eutrophic lake.

3.2.6. Evaluation of the Water Body of Gaoyou Lake by the Shannon–Weaver Diversity Index

In 2022, the Shannon–Weaver diversity index of zooplankton communities in Gaoyou Lake ranged from 0.65 to 2.66 (Figure 13), with an average of 1.61. According to the diversification level classification in Section 2.3.4, Gaoyou Lake was considered overall as a moderately polluted lake.

4. Discussion

4.1. Community Structure Characteristics of Metazoan Zooplankton in Gaoyou Lake

The community structure characteristics of metazooplankton in Gaoyou Lake are as follows: the density and species of small metazooplankton (rotifers) had a higher proportion than large metazooplankton (crustaceans); this was related to the increasing miniaturization of plankton caused by the eutrophication of water bodies. The significant fluctuations in the biomass of planktonic crustaceans composed of cladocerans and copepods are also characteristic of the changes in the biomass of planktonic animals in Gaoyou Lake.
The number and biomass of cladocerans in zooplankton are greatly affected by water temperature, especially their reproduction. Water temperature not only affects their quantity but also affects their reproductive mode [57,58,59]. The number of cladocerans is the highest in late summer and early autumn, as their life cycle is short. Therefore, as long as external conditions are suitable, they can reproduce in large quantities over a short period of time, and their number increases sharply. In late autumn and winter, the temperature and water temperatures rapidly decreased, resulting in a significant decline in their numbers.
Previous studies have shown that the entire Gaoyou Lake had mild eutrophication [60]. Our results reached similar conclusions, where we found the entire Gaoyou Lake and its ecological and functional zones showed mild eutrophication. The annual average of the eutrophication index in the developed and utilized zone was the highest, while those in the buffer and the core zones were relatively small. The average annual biological density, the QB/T value, and the comprehensive trophic state index of metazooplankton in the developed and utilized zone were the highest, as this zone was mainly in the north of Gaoyou Lake. Furthermore, there was a large zone of purse seine culture, which increases the organic matter production intensity and the accumulation of metazooplankton in this zone. The core and buffer zones were mainly located in the south-central part of Gaoyou Lake, where the water environment is relatively good. Therefore, the average annual biological density, the QB/T value, and the comprehensive trophic state index of the metazooplankton were relatively small.

4.2. Comprehensive Evaluation of the Multi-Index Water Body of Gaoyou Lake

According to the water quality assessment results, the main parameters exceeding the standards in the entire Gaoyou Lake and all its ecological and functional zones are TN and TP. The variation range of the comprehensive nutritional status index was 50.9–54.8, which indicates that Gaoyou Lake was in a slightly eutrophic state.
According to the evaluation results of the metazoan zooplankton, the QB/T value of Gaoyou Lake was 2.2, which indicated that it was a eutrophic lake. This was consistent with the results of evaluating the nutrient type of the water body of Gaoyou Lake by using the composition of the dominant species of metazoan zooplankton.
According to the evaluation results of the metazoan zooplankton, the average diversity of the Shannon–Weaver diversity index was 1.61. According to the diversification level classification in Section 2.3.4, the Gaoyou Lake was considered overall as a moderately polluted lake.
Combined with the multi-index evaluation results of the effects of water quality factors and metazoan zooplankton on the nutrient level of the water body, the water body of Gaoyou Lake was at a mild eutrophication level.

4.3. Countermeasures to Eutrophication Control in Gaoyou Lake

As the sixth largest freshwater lake in China, Gaoyou Lake is vital due to its water resource supply and ecology. Therefore, it is imperative to improve the eutrophication treatment of Gaoyou Lake and protect its water quality. We must bring the treatment of Gaoyou Lake into the scope of the basin to not only prevent and control pollution but also to reduce the pollution of water bodies caused by industry and agriculture in the Huaihe River Basin. Furthermore, we must scientifically plan the fishery culture structure, gradually implement the reclamation (polder) of the lake, and carefully develop the lake’s resources. The establishment of Gaoyou Lake’s lakeside Wetland Nature Reserve and the use of wetland interception and water purification measures can reduce the degree of the eutrophication of Gaoyou Lake.

Author Contributions

Conceptualization, L.G.; Methodology, L.G. and L.M.; Validation, X.H.; Formal analysis, Y.S. and D.X.; Investigation, L.M. and Y.S.; Resources, X.H.; Writing-original draft, L.G.; Writing-review & editing, L.M., Y.S., X.H. and D.X.; Project administration, L.G. and X.H.; Visualization, D.X.; Supervision, L.G. All authors have read and agreed to the published version of the manuscript.

Funding

This paper was funded by the Natural Science Foundation of Jiangsu Province (Grant No. BK20220705).

Data Availability Statement

https://www.mdpi.com/ethics.

Acknowledgments

The author (Liuchao Guo) is greatly indebted to my supervisor, Moliwu, for his valuable instructions and suggestions on my thesis as well as his careful reading of the manuscript. I feel grateful to all leaders of Jiangsu Hydraulic Research Institute who once offered me valuable advice. Last but not least, I owe much to my friends and classmates for their valuable suggestions and critiques which are of help and importance in making the thesis a reality.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Schneider, S.C.; Moe, T.F.; Hessen, D.O.; Kaste, Ø. Juncus bulbosus nuisance growth in oligotrophic freshwater ecosystems: Different triggers for the same phenomenon in rivers and lakes? Aquat. Bot. 2013, 104, 15–24. [Google Scholar] [CrossRef]
  2. Bartell, S.M.; Kaminski, G.; Carreau, M.; Campbell, K.R.; Lefebvre, G. An ecosystem model for assessing ecological risks in Quebec rivers, lakes, and reservoirs. Ecol. Model. 1999, 124, 43–67. [Google Scholar] [CrossRef]
  3. Chekryzheva, T.A.; Komulainen, S.F. Algal flora of lakes and rivers in the Republic of Karelia (Russia). Int. J. Algae 2010, 12, 321–334. [Google Scholar] [CrossRef]
  4. Tang, Z.; Han, X.; Li, G.; Tian, S.; Yang, Y.; Zhong, F.; Han, Y.; Yang, J. Occurrence, distribution and ecological risk of ultraviolet absorbents in water and sediment from Lake Chaohu and its inflowing rivers, China. Ecotoxicol. Environ. Saf. 2018, 164, 540–547. [Google Scholar] [CrossRef]
  5. Liu, Y.; Zhou, Y.; Ju, W.; Chen, J.; Wang, S.; He, H.; Wang, H.; Guan, D.; Zhao, F.; Li, Y.; et al. Evapotranspiration and water yield over China’s landmass from 2000 to 2010. Hydrol. Earth Syst. Sci. 2013, 17, 4957–4980. [Google Scholar] [CrossRef]
  6. Wang, Q.; Liu, J.; Zhang, S.; Lian, Y.; Ding, H.; Du, X.; Li, Z.; De, S. Sustainable farming practices of the Chinese mitten crab (Eriocheir sinensis) around Hongze Lake, lower Yangtze River Basin, China. Ambio A J. Hum. Environ. 2015, 45, 361–373. [Google Scholar] [CrossRef] [PubMed]
  7. Bucklin, A.; Ortman, B.D.; Jennings, R.M.; Nigro, L.M.; Wiebe, P. A ‘Rosetta Stone’ for metazoan zooplankton: DNA barcode analysis of species diversity of the Sargasso Sea (Northwest Atlantic Ocean). Deep-Sea Res. Part II Top. Stud. Oceanogr. 2010, 57, 2234–2247. [Google Scholar] [CrossRef]
  8. Nakajima, R.; Yoshida, T.; Othman, B.H.R.; Toda, T. Biomass and estimated production rates of metazoan zooplankton community in a tropical coral reef of Malaysia. Mar. Ecol. 2014, 35, 112–131. [Google Scholar] [CrossRef]
  9. Hirai, J.; Yasuike, M.; Fujiwara, A.; Nakamura, Y.; Hamaoka, S.; Katakura, S.; Takano, Y.; Nagai, S. Effects of plankton net characteristics on metagenetic community analysis of metazoan zooplankton in a coastal marine ecosystem. J. Exp. Mar. Biol. Ecol. 2015, 469, 36–43. [Google Scholar] [CrossRef]
  10. Teubner, K.; Crosbie, N.D.; Donabaum, K.; Kabas, W.; Kirschner, A.K.T.; Pfister, G.; Salbrechter, M.; Dokulil, M.T. Enhanced phosphorus accumulation efficiency by the pelagic community at reduced phosphorus supply: A lake experiment from bacteria to metazoan zooplankton. Limnol. Oceanogr. 2003, 48, 1141–1149. [Google Scholar] [CrossRef]
  11. Olsen, Y.; Andersen, T.; Gismervik, I.; Vadstin, O. Protozoan and metazoan zooplankton-mediated carbon flows in nutrient-enriched coastal planktonic communities. Mar. Ecol. Prog. Ser. 2007, 331, 67–83. [Google Scholar] [CrossRef]
  12. Leakey, R.J.G.; Burkill, P.H.; Sleigh, M.A. Planktonic ciliates in Southampton Water: Abundance, biomass, production, and role in pelagic carbon flow. Mar. Biol. 1992, 114, 67–83. [Google Scholar] [CrossRef]
  13. Chen, H.; Li, H.; Zhao, J.; Li, D.; Wan, J.; Yang, G. Physical-chemical and biological control of the zooplankton community in the Amundsen Sea, Antarctica. Adv. Polar Sci. 2023, 24, 17–27. [Google Scholar] [CrossRef]
  14. Troedsson, C.; Bouquet, J.-M.; Aksnes, D.L.; Thompson, E.M. Resource allocation between somatic growth and reproductive output in the pelagic chordate Oikopleura dioica allows opportunistic response to nutritional variation. Mar. Ecol. Prog. Ser. 2002, 243, 83–91. [Google Scholar] [CrossRef]
  15. Arndt, H.; Krocker, M.; Nixdorf, B.; Köhler, A. Long-term Annual and Seasonal Changes of Meta- and Protozooplankton in Lake Müggelsee (Berlin): Effects of Eutrophication, Grazing Activities, and the Impact of Predation. Int. Rev. Gesamten Hydrobiol. Hydrogr. 1993, 78, 379–402. [Google Scholar] [CrossRef]
  16. Kong, R.; Yang, C.; Huang, K.; Han, G.; Sun, Q.; Zhang, Y.; Zhang, H.; Letcher, R.J.; Liu, C. Application of agricultural pesticides in a peak period induces an abundance decline of metazoan zooplankton in a lake ecosystem. Water Res. 2022, 224, 119040. [Google Scholar] [CrossRef]
  17. Tomasz, M.; Malgorzata, A.; Monika, T.-K.; Dorota, N. Effect of water chemistry on zooplanktonic and microbial communities across freshwater ecotones in different macrophyte-dominated shallow lakes. J. Limnol. 2016, 75, 262–274. [Google Scholar] [CrossRef]
  18. Li, S.; Guo, W.; BrucE, M. Evaluation of water quality and management of Hongze Lake and Gaoyou Lake along the Grand Canal in Eastern China. Environ. Monit. Assess. 2011, 176, 373–384. [Google Scholar] [CrossRef]
  19. Li, S.; Fu, G.; Guo, W.; He, H.; Zhang, Z. Environmental changes during modern period from the record of Gaoyou Lake sediments, Jiangsu. J. Geogr. Sci. 2007, 17, 62–72. [Google Scholar] [CrossRef]
  20. Geng, M.; Wang, K.; Yang, N.; Li, F.; Zou, Y.; Chen, X.; Deng, Z.; Xie, Y. Evaluation and variation trends analysis of water quality in response to water regime changes in a typical river-connected lake (Dongting Lake), China. Environ. Pollut. 2021, 268 Pt A, 115761. [Google Scholar] [CrossRef]
  21. Xie, F.; Liu, Z.; Luo, K.; Li, H.; Li, G. Long Term Comprehensive Evaluation of Temporal and Spatial Variation of Water Quality in Chaohu Lake, China. Pol. J. Environ. Stud. 2022, 31 Pt 1, 4383–4397. [Google Scholar] [CrossRef]
  22. Al-Omari, A.; Al-Houri, Z.; Al-Weshah, R. Impact of the as samra wastewater treatment plant upgrade on thewater quality (COD, electrical conductivity, TP, TN) of the zarqa river. Water Sci. Technol. 2013, 67, 1455–1464. [Google Scholar] [CrossRef] [PubMed]
  23. Liu, P.; Bai, J.; Ding, Q. Effects of Water Level and Salinity on TN and TP Contents in Marsh Soils of the Yellow River Delta, China. Clean-Soil Air Water A J. Sustain. Environ. Saf. 2012, 40, 1118–1124. [Google Scholar] [CrossRef]
  24. GB/T 11892-1989; Water Quality-Determination of Permanganate Index. State Administration for Market Regulation: Beijing, China, 1989.
  25. HJ 535-2009; Water Quality-Determination of Ammonia Nitrogen-Nessler’s Reagent Spectrophotometry. Ministry of Environmental Protection Ministry of Environmental Protection of the PRC: Beijing, China, 2009.
  26. GB/T 11893-1989; Water Quality-Determination of Total Phosphorus-Ammonium Molybdate Spectrophotometric Method. State Administration for Market Regulation: Beijing, China, 1989.
  27. HJ 636-2012; Water Quality—Determination of Total Nitrogen—Alkaline Potassium Persulfate Digestion UV Spectrophotometric Method. Ministry of Environmental Protection Ministry of Environmental Protection of the PRC: Beijing, China, 2012.
  28. Ejsmont-Karabin, J. Does the world need faunists? Based on rotifer (Rotifera) occurrence reflections on the role of faunistic research in ecology. Int. Rev. Hydrobiol. 2019, 104, 49–56. [Google Scholar] [CrossRef]
  29. Verschoor, A.M.; Boonstra, H.; Meijer, T. Application of Stable Isotope Tracers to Studies of Zooplankton Feeding, using the Rotifer Brachionus calyciflorus as an Example. Hydrobiologia 2005, 546, 535–549. [Google Scholar] [CrossRef]
  30. Sokolova, Y.Y.; Senderskiy, I.V.; Tokarev, Y.S. Microsporidia Alfvenia sibirica sp. n. and Agglomerata cladocera (Pfeiffer) 1895, from Siberian microcrustaceans and phylogenetic relationships within the “Aquatic outgroup” lineage of fresh water microsporidia. J. Invertebr. Pathol. 2016, 136, 81–91. [Google Scholar] [CrossRef]
  31. Aksenova, M.D.; Chertoprud, E.S.; Novichkova, A.A.; Tsyganov, A.N.; Pechenkin, D.S.; Mazei, Y.A. Cladocera and Copepoda of Montane Peatlands of the North Caucasus, Russia: Composition and Formation Patterns of Species Complexes. Biol. Bull. 2021, 48, 926–933. [Google Scholar] [CrossRef]
  32. Minutoli, R.; Brugnano, C.; Granata, A.; Zagami, G.; Guglielmo, L. Zooplankton electron transport system activity and biomass in the western Ross Sea (Antarctica) during austral summer 2014. Polar Biol. 2017, 40, 1197–1209. [Google Scholar] [CrossRef]
  33. Mayor, D.J.; Sanders, R.; Giering, S.L.C.; Anderson, T.R. Microbial gardening in the ocean’s twilight zone: Detritivorous metazoans benefit from fragmenting, rather than ingesting, sinking detritus Fragmentation of refractory detritus by zooplankton beneath the euphotic zone stimulates the harvestable production of labile and nutritious microbial biomass. BioEssays News Rev. Mol. Cell. Dev. Biol. 2014, 36, 1132–1137. [Google Scholar] [CrossRef]
  34. Ershova, E.A.; Wangensteen, O.S.; Descoteaux, R.; Barth-Jensen, C.; Præbel, K. Metabarcoding as a quantitative tool for estimating biodiversity and relative biomass of marine zooplankton. ICES J. Mar. Sci. 2021, 78, 3342–3355. [Google Scholar] [CrossRef]
  35. Bucklin, A.; Peijnenburg, K.T.; Kosobokova, K.N.; O’Brien, T.D.; Blanco-Bercial, L.; Cornils, A.; Falkenhaug, T.; Hopcroft, R.R.; Hosia, A.; Laakmann, S.; et al. Toward a global reference database of COI barcodes for marine zooplankton. Mar. Biol. Int. J. Life Ocean. Coast. Waters 2021, 168, 78. [Google Scholar] [CrossRef]
  36. Wei, B.; Sugiura, N.; Maekawa, T. Evaluation of Trophic State of Eutrophicated Lake and Biotic Response from Algal Community Level. Environ. Technol. 2000, 21, 1047–1053. [Google Scholar] [CrossRef]
  37. Beyhan, M.; Meltem, K. Evaluation of Water Quality from the Perspective of Eutrophication in Lake Egirdir, Turkey. Water Air Soil Pollut. 2014, 225, 1994. [Google Scholar] [CrossRef]
  38. Che, L.; Wan, L. Water Quality Analysis and Evaluation of Eutrophication in a Swamp Wetland in the Permafrost Region of the Lesser Khingan Mountains, China. Bull. Environ. Contam. Toxicol. 2022, 108, 234–242. [Google Scholar] [CrossRef] [PubMed]
  39. Sladack, V. Rotifers as indicators of water quality. Hydrobiology 1983, 100, 169–202. [Google Scholar] [CrossRef]
  40. Chen, L.; Liu, Q.; Peng, Z.; Hu, Z.; Xue, J.; Wang, W. Rotifer community structure and assessment of water quality in Yangcheng Lake. Chin. J. Oceanol. Limnol. 2012, 30, 47–58. [Google Scholar] [CrossRef]
  41. Zhang, H.; Jiang, Z.; Liu, L.; Zheng, X.; Li, S.; Zhang, J.; Wang, J.; He, Y.; Lv, W. Effects of Intercropping on Microbial Community Function and Diversity in Continuous Watermelon Cropping Soil. Fresenius Environ. Bull. FEB 2015, 24, 3288–3294. [Google Scholar]
  42. Vajravelu, M.; Martin, Y.; Ayyappan, S.; Mayakrishnan, M. Seasonal influence of physico-chemical parameters on phytoplankton diversity, community structure and abundance at Parangipettai coastal waters, Bay of Bengal, South East Coast of India. Oceanologia 2018, 60, 114–127. [Google Scholar] [CrossRef]
  43. Das, S.C.S.; Khan, A.; Alam, A.; Dubey, V.; Kripal, D. Piscine diversity, Community structure and Distribution patterns of the West Ramganga River: A mid-Himalayan tributary of River Ganga. Indian J. Anim. Sci. 2020, 90, 109–115. [Google Scholar] [CrossRef]
  44. Lehegaratmascle, S.; Taconet, O.; Zribi, M.; Vidalmadjar, D. Application of Shannon Information Theory to A Comparison between L- and C-Band Sir-C Polarimetric Data versus Incidence Angle. Remote Sens. Environ. Interdiscip. J. 1997, 60, 121–130. [Google Scholar] [CrossRef]
  45. Mavrič, B.; Urbanič, G.; Lipej, L.; Simboura, N. Influence of sample size on ecological status assessment using marine benthic invertebrate-based indices. Mar. Ecol. 2013, 34, 72–79. [Google Scholar] [CrossRef]
  46. Magdalena, S.; Monika, K.; Katarzyna, C. Emergent (branched bur-reed-Sparganium erectum L.) and submergent (river water-crowfoot-Ranunculus fluitans Wimm., 1841) aquatic plants as metal biosorbents under varying water pH conditions in laboratory conditions. Environ. Sci. Pollut. Res. Int. 2023, 30, 92053–92067. [Google Scholar]
  47. Camberato, M.D.; Camberato, J.J.; Lopez, G.R. Determining the Effect of Carrier Water pH and Bicarbonate Concentration on Final pH of Plant Growth Regulator Solutions. HortScience 2014, 49, 1176–1182. [Google Scholar] [CrossRef]
  48. Fonseca-Gonzaléz, G.; Avendaño, E.; Araque, L.A. Monitoring of ph, redox and turbidity in a water treatment plant using WSN with ZIGBEE technology. Ing. Investig. Desarro. 2014, 14, 17–21. [Google Scholar]
  49. Zaini, A.; Wulandari, D.P.; Wulandari, R. Data Visualization on Shrimp Pond Monitoring System Based on Temperature, pH, and DO (Dissolved Oxygen) with IoT. In Proceedings of the 2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM 2020), Surabaya, Indonesia, 17–18 November 2020; Virtual Conference. Institute of Electrical and Electronics Engineers: Piscataway, NJ, USA, 2020; pp. 1–6. [Google Scholar]
  50. Misra, A.K.; Tiwari, P.K.; Goyal, A.; Shukla, J.B. Modeling and Analysis of the Depletion of Organic Pollutants by Bacteria with Explicit Dependence on Dissolved Oxygen. Nat. Resour. Model. 2014, 27, 258–273. [Google Scholar] [CrossRef]
  51. Maruya, Y.; Nakayama, K.; Sasaki, M.; Komai, K. Effect of dissolved oxygen on methane production from bottom sediment in a eutrophic stratified lake. J. Environ. Sci. 2023, 125, 61–72. [Google Scholar] [CrossRef]
  52. Missaghi, S.; Hondzo, M.; Herb, W. Prediction of lake water temperature, dissolved oxygen, and fish habitat under changing climate. Clim. Chang. 2017, 141, 747–757. [Google Scholar] [CrossRef]
  53. GB 3838-2002; Environmental Quality Standards for Surface Water. Ministry of Environmental Protection Ministry of Environmental Protection of the PRC: Beijing, China, 2002.
  54. Scott, R.; Zhan, A.; Brown, E.A.; Chain, F.; Cristescu, M.; Gras, R.; MacIsaac, H. Optimization and performance testing of a sequence processing pipeline applied to detection of nonindigenous species. Evol. Appl. 2018, 11, 891–905. [Google Scholar] [CrossRef]
  55. Gerasimova, T.N.; Pogozhev, P.I. The role of zooplankton in phytoplankton biomass decline and water transparency regulation in a water body subject to high organic and mineral load. Water Resour. 2011, 37, 796–806. [Google Scholar] [CrossRef]
  56. Ger, K.A.; Derlet, R.W.; Carlson, J.R.; Goldman, C.R. Variation in bacterial biomass in a subalpine recreational lake: Evidence for pelagic photoinhibition. Int. Assoc. Theor. Appl. Limnoloy 2006, 29 Pt 5, 2324–2329. [Google Scholar] [CrossRef]
  57. Jeppesen, E.; Jensen, J.P.; Lauridsen, T.L.; Amsinck, S.L.; Christoffersen, K.; Sondergaard, M.; Mitchell, S.F. Sub-fossils of cladocerans in the surface sediment of 135 lakes as proxies for community structure of zooplankton, fish abundance and lake temperature. Hydrobiologia 2003, 491, 321–330. [Google Scholar] [CrossRef]
  58. Nevalainen, L.; Luoto, T.P. Temperature sensitivity of gamogenesis in littoral cladocerans and its ecological implications. J. Limnol. 2010, 69, 120–125. [Google Scholar] [CrossRef]
  59. Luoto, T.P.; Nevalainen, L.; Kultti, S.; Sarmaja-Korjonen, K. An evaluation of the influence of water depth and river inflow on quantitative Cladocera-based temperature and lake level inferences in a shallow boreal lake. Hydrobiologia 2011, 676, 143–154. [Google Scholar] [CrossRef]
  60. Su, H.; Xie, Q.; Du, D.; Chen, J.; Han, X. Water quality assessment of Gaoyou Lake. In Advances in Energy Science and Equipment Engineering; CRC Press: Boca Raton, FL, USA, 2015; Volume 2, pp. 953–956. [Google Scholar]
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Figure 1. The sampling points of Gaoyou Lake.
Figure 1. The sampling points of Gaoyou Lake.
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Figure 2. Change in the nutrient index in the entire lake zone.
Figure 2. Change in the nutrient index in the entire lake zone.
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Figure 3. Change in nutrient index in the core zone.
Figure 3. Change in nutrient index in the core zone.
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Figure 4. Change in nutrient index in the buffer zone.
Figure 4. Change in nutrient index in the buffer zone.
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Figure 5. Change in nutrient index in the developed and utilized zone.
Figure 5. Change in nutrient index in the developed and utilized zone.
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Figure 6. Monthly variation in the density of metazoan zooplankton.
Figure 6. Monthly variation in the density of metazoan zooplankton.
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Figure 7. Monthly variation in the biomass of metazoan zooplankton.
Figure 7. Monthly variation in the biomass of metazoan zooplankton.
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Figure 8. Gaoyou Lake’s spatial cloud map of the density of metazoan zooplankton in 2022.
Figure 8. Gaoyou Lake’s spatial cloud map of the density of metazoan zooplankton in 2022.
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Figure 9. Gaoyou Lake’s spatial cloud map of the biomass of metazoan zooplankton in 2022.
Figure 9. Gaoyou Lake’s spatial cloud map of the biomass of metazoan zooplankton in 2022.
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Figure 10. Density of metazoan zooplankton in the ecological and functional zones of Gaoyou Lake.
Figure 10. Density of metazoan zooplankton in the ecological and functional zones of Gaoyou Lake.
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Figure 11. Biomass of metazoan zooplankton in the ecological and functional zones of Gaoyou Lake.
Figure 11. Biomass of metazoan zooplankton in the ecological and functional zones of Gaoyou Lake.
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Figure 12. Annual average QB/T values of the stations in Gaoyou Lake.
Figure 12. Annual average QB/T values of the stations in Gaoyou Lake.
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Figure 13. Shannon–Weaver diversity index of Gaoyou Lake.
Figure 13. Shannon–Weaver diversity index of Gaoyou Lake.
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Table 1. Water quality monitoring index of Gaoyou Lake (2022).
Table 1. Water quality monitoring index of Gaoyou Lake (2022).
MonthsWater Temperature (°C)pHChla
(μg/L)		DO
(mg/L)		TN
(mg/L)		TP
(mg/L)		CODMn
(mg/L)		SD
(m)
January7.08.610.5911.21.3010.0864.410.28
February6.88.29.2611.11.2350.0824.210.31
March10.58.76.3511.31.1240.0784.860.39
April18.19.13.3311.40.9240.0765.160.41
May26.48.64.717.60.7980.0744.210.35
June26.37.75.586.01.1120.0835.950.12
July33.28.56.045.91.1490.0814.620.19
August31.67.96.505.81.2780.0984.260.18
September26.48.58.768.80.8950.0945.250.16
October22.27.911.038.91.1980.0925.140.15
November9.58.511.5311.21.4780.0524.180.10
December8.48.19.1611.50.7250.0824.760.13
Average value18.88.47.739.21.1010.0824.750.23
Table 2. Dominant metazoan zooplankton species and their dominance in Gaoyou Lake.
Table 2. Dominant metazoan zooplankton species and their dominance in Gaoyou Lake.
Dominant SpeciesDominance
Rotifers
Keratella cochlearis0.08
Keratella valga0.06
Brachionus angularis0.10
Brachionus calyciflorus0.04
Polyarthra trigla0.11
Cladocerans
Diaphanosoma brachyurum0.02
Bosmina coregoni0.28
Ceriodaphnia cornuta0.02
Copepods
Mesocyclops leuckarti0.08
Cyclops vicinus0.03
Sinocalanus dorrii0.02
Copepodid0.08
Nauplii0.22
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Guo, L.; Mo, L.; Su, Y.; Hu, X.; Xu, D. Studying the Metazoan Zooplankton Community Characteristics and Evaluating the Water Quality Based on the Ecological and Functional Zones in Gaoyou Lake. Water 2023, 15, 3357. https://doi.org/10.3390/w15193357

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Guo L, Mo L, Su Y, Hu X, Xu D. Studying the Metazoan Zooplankton Community Characteristics and Evaluating the Water Quality Based on the Ecological and Functional Zones in Gaoyou Lake. Water. 2023; 15(19):3357. https://doi.org/10.3390/w15193357

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Guo, Liuchao, Liwu Mo, Yuyan Su, Xiaodong Hu, and Dandan Xu. 2023. "Studying the Metazoan Zooplankton Community Characteristics and Evaluating the Water Quality Based on the Ecological and Functional Zones in Gaoyou Lake" Water 15, no. 19: 3357. https://doi.org/10.3390/w15193357

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