Contrasting zooplankton communities of two bays of the large, shallow, eutrophic Lake Taihu, China: Their relationship to environmental factors

Contrasting zooplankton communities of two bays of the large, shallow, eutrophic Lake Taihu, China: Their relationship to environmental factors

Journal of Great Lakes Research 38 (2012) 299–308 Contents lists available at SciVerse ScienceDirect Journal of Great Lakes Research journal homepag...

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Journal of Great Lakes Research 38 (2012) 299–308

Contents lists available at SciVerse ScienceDirect

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Contrasting zooplankton communities of two bays of the large, shallow, eutrophic Lake Taihu, China: Their relationship to environmental factors Yang Guijun a, b, Qin Boqiang a,⁎, Tang Xiangming a, Gong Zhijun a, Zhong Chunni c, Zou Hua b, Wang Xiaodong a a b c

State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 East Beijing Road, Nanjing 210008, China Environment and Civil Engineering School, Jiangnan University, 1800 Lihu Road, Wuxi 214122, China Wuxi Taihu Lake Management Co., Ltd., Wuxi 214023, China

a r t i c l e

i n f o

Article history: Received 9 August 2011 Accepted 14 December 2011 Available online 16 April 2012 Communicated by Joseph Makarewicz Index words: Lake Taihu Seasonal variations Size-selective predation Zooplankton

a b s t r a c t Zooplankton are an important link in aquatic food webs of lakes serving as consumers of algae, bacteria, and other microorganisms and as prey for fish and invertebrates. Despite their importance, little is known about the structure of the zooplankton communities of subtropic, large, shallow, eutrophic freshwater lakes. Our investigation of zooplankton communities in Lake Taihu, a subtropic, shallow, eutrophic lake and the third largest lake in China provides new information on this subject. Zooplankton, phytoplankton, and water chemistry samples were collected monthly from July 2006 to June 2007 in Meiliang and Gonghu Bays of Lake Taihu. Thirty zooplankton species were identified in Meiliang Bay with small-bodied cladocerans Bosmina coregoni and Ceriodaphnia cornuta contributing 21% and 11%, respectively to total zooplankton abundance which averaged 459 ind/L. Thirty-five species were identified in Gonghu Bay with the rotifers Polyarthra trigla and Brachionus calyciflorus the dominant species, contributing 21% and 11% respectively to total zooplankton abundance which averaged 467 ind/L. Predation by lake anchovy (Coilia ectenes taihuensis) and ice fish (Neosalanx tangkahkeii taihuensis) likely accounted for the dominance of both bays by small-bodied species. Community structure and community patterns were correlated with differences in Microcystis blooms and organic matter levels (chemical oxygen demand) in the two bays. Based on canonical correspondence analyses dissolved total nitrogen, orthophosphate, Cyclotella and Pinnularia also contributed to variability in zooplankton community composition. Crown Copyright © 2012 Published by Elsevier B.V. on behalf of International Association for Great Lakes Research. All rights reserved.

Introduction As anthropogenic eutrophication becomes widespread worldwide, the characterization of the trophic status of aquatic ecosystems becomes increasing important (Qin, 2008). Eutrophication is commonly accompanied by structural changes in the food webs of lakes with substantial changes in phytoplankton, macrophyte, zooplankton and fish assemblages (Bosselmann and Riemann, 1986; Persson et al., 1991; Sas and Ahlgren, 1989). Thus zooplankton community structure provides insight into the trophic status of a water body. The role of zooplankton in efficient energy transfer from the microbial food web to higher trophic levels has been demonstrated in mesotrophic and eutrophic lakes (Pace et al., 1990; Wylie and Currie,

⁎ Corresponding author. E-mail addresses: [email protected] (Y. Guijun), [email protected] (Q. Boqiang).

1991). Nutrient enrichment generally leads to increased abundance and biomass of zooplankton through changes at lower trophic levels (Auer et al., 2004; Pace, 1986). Bacteria, phytoplankton, and protists are suitable food for many metazooplankton species and microbial food webs are coupled to metazoan food webs (Adrian and Schneider-Olt, 1999; Burns and Schallenberg, 1996; Modenutti et al., 2003). Zooplankton abundance also is influenced by physicochemical (e.g. temperature, light, nutrients, etc.) and biological (e.g. phytoplankton, fish) factors in aquatic ecosystems. Large, shallow lakes display a number of features that set them apart from the more often-studied deeper, dimictic systems: (1) a lack of stable long-term thermal stratification (Beaver et al., 1981); (2) frequent mixing of the entire water column and resuspension of unconsolidated sediments (Ishikawa and Tanaka, 1993); and (3) substantial internal loading of nutrients from the sediments to water column (Sondergaard et al., 1992). However, few studies (Yang et al., 2009) have investigated zooplankton communities in the large shallow lakes of China including their interactions with the phytoplankton, and physicochemical features of their environment.

0380-1330/$ – see front matter. Crown Copyright © 2012 Published by Elsevier B.V. on behalf of International Association for Great Lakes Research. All rights reserved. doi:10.1016/j.jglr.2012.03.011


Y. Guijun et al. / Journal of Great Lakes Research 38 (2012) 299–308

the water column. This water was filtered through a 48-μm mesh plankton net and the filtered material preserved with 4% formalin. Cladocera and Copepoda were enumerated and identified (Einsle, 1993; Smirnov and Timms, 1983) at 40× magnification using a Nikon E200 compound microscope. All individuals were identified, where possible, to species or to genus. For each species of Crustacea, the length of 30 individuals was measured from each sample to convert abundances to biomass using length-weight regressions (Zhang and Huang, 1991). For quantification of Rotifera, all individuals were identified to species level, where possible, or to genus level, according to the identification guide of Koste (1978). As with crustaceans, abundances of rotifers were converted to biomass (wet weight) following Zhang and Huang (1991). Biomass of zooplankton was wet weight in the research.

Phytoplankton sampling

Fig. 1. Map of the sampling stations in Meiliang Bay and Gonghu Bay of Lake Taihu, China.

Lake Taihu (Fig. 1) is a large (2338 km 2), shallow (average depth = 1.9 m), eutrophic lake and China's third largest lake. It lies in Changjiang River delta (30°05′N to 32°08′N and 119°08′E to 121°55′E), the most industrialized and urbanized area in China (Qin, 2008). Meiliang Bay (mean depth = 2.4 m) in the north is highly eutrophic with extensive Microcystis cyanobacteria blooms from May to October each year (Chen et al., 2003). Gonghu Bay (mean depth= 1.8 m) in the northeast was dominated by submerged macrophytes until 2005 (Qin, 2008) which have since generally disappeared (Zhu, 2008); macrophytes are now sparse and phytoplankton dominated by Microcystis and Bacillariophyta. In shallow lakes, spatial heterogeneity and macrophyte provide refuges for invertebrates against fish predation (Jeppesen et al., 1998). Therefore, the loss of the macrophytes in Gonghu Bay may increase the strength of top-down impact of planktivorous and omnivorous fish on zooplankton communities and ultimately phytoplankton communities. In Lake Taihu, two species of fish feed extensively on zooplankton, namely the dominant lake anchovy (Coilia ectenes taihuensis Yuen et Lin) which accounted for 64% of the total fish production in 2002 (Liu et al., 2005a) and the ice fish (Neosalanx tangkahkeii taihuensis) which represented 1.2% of the total fish production in 2006 (He et al., 2009). Previous studies on Lake Taihu focused on zooplankton composition and the eutrophication of the lake (Bai, 1962; Bao and Chen, 1983; Chen and Qin, 1998). Here we investigate and compare the zooplankton communities in the Microcystis-dominated Meiliang Bay to the zooplankton community of the shallower, Microcystis and Bacillariophyta dominated Gonghu Bay. Our study has two objectives: (1) investigate seasonality in the zooplankton communities in the two bays; and (2) investigate the role of the physicochemical features and phytoplankton communities in influencing zooplankton community structure in the two bays. We also investigate long-term trends in zooplankton abundance in the two bays in relation to trends in nitrogen and phosphorus concentrations.

Materials and methods Zooplankton sampling Once a month from July 2006 to June 2007, replicate (n = 3) zooplankton were collected in Meiliang and Gonghu Bays (Fig. 1); a tube-sampler was used to obtain a vertically integrated 5-L sample of

From July 2006 to June 2007, phytoplankton samples were collected once a month; a tube sampler was used to collect a 1-L vertically integrated water sample which was preserved with Lugol's iodine solution. After the phytoplankton settled for 48 h, they were counted (400× magnification) with an Olympus CKX31 inverted microscope. Identification was to species level followed Hu and Wei (2006). Algal biovolumes were calculated from cell numbers and cell size measurements, assuming that 1 mm 3 of volume was equivalent to 1 mg of fresh-weight algal biomass (Hu and Wei, 2006).

Water sampling Water transparency was measured with a Secchi disk, while temperature, dissolved oxygen, and pH were measured using a Yellow Springs YSI 556 probe. As with phytoplankton and zooplankton, vertically integrated water samples were collected with a tube-sampler. Chemical analysis included total nitrogen, dissolved total nitrogen, ammonium, nitrite, nitrate, total phosphorus, dissolved total phosphorus, orthophosphate, chemical oxygen demand (CODMn), suspended solids, and cations (K, Na, Ca, Mg) following the Chinese Standard Methods for the Surveys of Lake Eutrophication (Jin and Tu, 1990). After a 90% hot ethanol extraction, chlorophyll-a (Chl-a) was measured spectrophotometrically (UV spectrophotometer) (Lorenzen, 1967).

Statistical analyses Canonical correspondence analysis (CCA) was used to elucidate the relationships between zooplankton and related environments (ter Braak and Verdonschot, 1995; Waite, 2000). Monthly species abundance values and corresponding variables were log10(x +1) transformed to ensure normal distribution. For CCA, we considered 36 zooplankton taxa along with 66 environmental factors (19 physicochemical and 47 phytoplankton taxa including Bacillariophyta, Cryptophyta, Cyanobacteria, Chlorophyta, Xanthophyta, Euglenophyta, and Chrysophyta). The forward selection of CCA, which is analogous to step-wise multiple regression, was used to determine the minimum number of explanatory factors that could explain statistically significant (Pb 0.05) proportions of variation in the species data. The significance of these variables was assessed using Monte Carlo permutation tests (with 499 unrestricted permutations). All the ordinations were performed using CANOCO Version 4.5 (ter Braak, 2002). Pearson's Correlation Analysis was used to determine the relationships between the physicochemical parameter and zooplankton abundance. Univariate data analysis was performed using SPSS15.0 for Windows. A t-test was performed to detect overall significant differences in the mean values of physical, chemical, and biological parameters between the two bays.

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Bay (5.5%). The average individual wet weight of zooplankton was 9.23 μg in Meiliang Bay but only 3.70 μg in Gonghu Bay.

Results Zooplankton species composition, abundance, and biomass Thirty zooplankton species were identified in Meiliang Bay and 35 in Gonghu Bay (Table 1). Although the mean monthly abundance of total zooplankton was similar in both bays (Meiliang Bay= 459 ind/L; Gonghu Bay= 467 ind/L), there were significant compositional differences. Rotifers were a significantly (Pb 0.01, t = −3.186, df = 22, ) smaller component of the zooplankton abundance in Meiliang Bay (35.7%) than in Gonghu Bay (72.4%) while the converse was observed for Cladocera (P b 0.01, t = 3.529, df = 22); Cladocera represented 38.8% of the Meiliang Bay zooplankton community but only 9.5% in Gonghu Bay (Fig. 2). Mean monthly biomass of zooplankton (Fig. 2) was markedly higher in Meiliang Bay (4.23 mg/L, wet weight) than in Gonghu Bay (1.73 mg/L). Cladocera accounted for significantly (P b 0.01, t = 5.169, df = 22) more of zooplankton biomass in Meiliang Bay (70.9%) than in Gonghu Bay (27.3%) while rotifers contributed more (P b 0.01, t = −3.304, df = 22) to biomass in Gonghu Bay (39.9%) than in Meiliang

Dominant zooplankton species In Meiliang Bay, the dominant species were the small-bodied cladocerans Bosmina coregoni (average = 98 ind/L) and Ceriodaphnia cornuta (50 ind/L) accounting for 21% and 11%, respectively, of the zooplankton community abundance (Table 1; Figs. 3, 4). The highest abundance of B. coregoni in Meiliang Bay was 379 ind/L in September 2006 (Fig. 3); the highest abundance of C. cornuta was also in September 2006 (247 ind/L, Fig. 3). In Gonghu Bay, the zooplankton dominant species were the rotifers Polyarthra trigla (average = 99 ind/L) and Brachionus calyciflorus (49 ind/L) representing 21% and 11%, respectively, of the zooplankton abundance (Figs. 3, 4). The highest abundance of P. trigla (697 ind/L) in Gonghu Bay was observed in February 2007 (Fig. 3) while the highest abundance of B. calyciflorus (200 ind/L) was observed in May 2007 (Fig. 3).

Table 1 Mean and range of abundance and biomass of zooplankton in Meiliang Bay and Gonghu Bay in Lake Taihu, July 2006 to June 2007. Species

Meiliang Bay

Gonghu Bay

Mean abundance (ind/L)

Range (ind/L)

Mean biomass (mg/L)

Mean abundance (ind/L)

Range (ind/L)

Mean biomass (mg/L)

Copepoda Cyclopoids Cyclops strennus Cyclops vicinus Microcyclops varicans Mesocyclops leuckarti Limnoithona sinensis

0.3 0.1 22.9 3.1 19.2

0.0–2.0 0.0–0.7 0.0–107.0 0.0–26.7 0.0–134.7

0.0272 0.0065 0.0347 0.0846 0.0693

0.1 0.0 14.6 0.6 14.9

0.0–0.7 0.0–88.0 0.0–2.7 0.0–99.3

0.0054 0.0000 0.0220 0.0151 0.0540

Calanaoids Schmackeria inopinus Sinocalanus dorrii Nauplius

3.3 7.4 60.4

0.0–27.3 0.0–17.3 4.0–182.0

0.1437 0.4533 0.1813

1.1 4.5 48.6

0.0–3.3 0.0–26.0 5.3–206.7

0.0479 0.2761 0.1458

Cladocera Daphnia hyalina Daphnia cucullata Daphnia longispina Daphnia carinata Bosmina coregoni Diaphanosoma brachyurum Ceriodaphnia cornuta Moina macrocopa Alona rectangula

9.6 0.0 2.7 0.4 97.9 6.9 50.1 10.3 0.0


0.4751 0.0000 0.5755 0.0254 0.7908 0.2914 0.4258 0.3226 0.0000

0.9 0.3 0.1 0.0 32.2 0.4 8.3 1.7 0.4

0.0–7.3 0.0–3.3 0.0–0.7

0.0442 0.0123 0.0117 0.0000 0.2599 0.0188 0.0709 0.0523 0.0017

Rotifera Brachionus caudatus Brachionus angularis Brachionus calyciflorus Brachionus diversicornis Brachionus farficula Brachionus falcatus Brachionus budapestiensis Brachionus urceus Asplanchna brightwelli Keratella cochlearis Keratella quadrata Keratella valga Filinia longiseta Synchaeta pectinata Trichocerca gracilis Polyarthra trigla Conochilus dossuarius Euehlalns dilatata Hexarthra mira Harringia cupoda Ascomorpha ecaudis Ploesoma hudsoni

0.1 46.8 45.0 0.0 0.0 0.0 12.7 0.1 0.6 11.6 3.2 1.9 1.6 0.4 1.1 36.2 2.2 0.2 0.2 0.0 0.0 0.0

0.0–0.7 0.0–464.7 0.0–531.3

0.0001 0.0237 0.1580 0.0000 0.0000 0.0000 0.0030 0.0001 0.0134 0.0001 0.0015 0.0008 0.0006 0.0069 0.0065 0.0113 0.0041 0.0005 0.0005 0.0000 0.0000 0.0000

16.4 32.5 49.2 3.6 8.7 0.6 5.3 8.2 16.6 3.6 10.3 8.1 11.4 1.1 0.3 98.5 18.8 0.2 0.0 3.3 41.2 0.2

0.0–14.7 0.0–2.7 0.0–378.7 0.0–37.3 0.0–247.3 0.0–52.7

0.0–122.7 0.0–0.7 0.0–2.0 0.0–62.7 0.0–16.7 0.0–16.7 0.0–6.0 0.0–5.3 0.0–9.3 0.0–391.3 0.0–17.3 0.0–1.3 0.0–2.0

0.0–192.0 0.0–4.0 0.0–61.3 0.0–12.7 0.0–5.3

0.0–117.3 0.0–114.0 0.0–200.0 0.0–32.0 0.0–100.0 0.0–6.0 0.0–24.7 0.0–93.3 0.0–99.3 0.0–13.3 0.0–68.7 0.0–28.7 0.0–50.0 0.0–6.0 0.0–1.3 0.0–697.3 0.0–100.0 0.0–2.0 0.0–40.0 0.0–418.7 0.0–1.3

0.0083 0.0165 0.1728 0.0019 0.0010 0.0001 0.0013 0.0110 0.3633 0.0000 0.0049 0.0033 0.0042 0.0172 0.0017 0.0308 0.0357 0.0004 0.0000 0.0081 0.0051 0.0004


Y. Guijun et al. / Journal of Great Lakes Research 38 (2012) 299–308

Fig. 2. Comparison of temporal changes in abundance and biomass of Rotifera, Cladocera, and Copepoda in Meiliang Bay and Gonghu Bay, July 2006 to June 2007.

Fig. 3. Comparison of temporal changes in abundance of six dominant species of Rotifera, Cladocera, and Copepoda in Meiliang Bay and Gonghu Bay, July 2006 to June 2007. Data presented is mean and standard deviation.

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Fig. 4. Comparison of percentage contributions in abundance and biomass of the dominant species of zooplankton in Meiliang Bay and Gonghu Bay, July 2006 to June 2007.

Abundance and Biomass of phytoplankton

Physicochemical variables

The average monthly abundance of phytoplankton was 9,960,529 ind/L in Meiliang Bay but only 563,265 ind/L in Gonghu Bay. Microcystis abundance was significantly (P b 0.05, t = 2.714, df = 22) greater in Meiliang Bay (9,742,735 ind/L) than Gonghu Bay (105,537 ind/L) (Table 2, Fig. 5). However, average monthly biomass of phytoplankton was similar in both bays averaging 0.84 mg/L in Meiliang Bay and 0.75 mg/L in Gonghu Bay. On a biomass basis Cyanophyta was the dominant group of phytoplankton in Meiliang Bay, whereas in Gonghu Bay Bacillariophyta was the dominant followed by Cyanophyta (Fig. 6). Diatom biomass was significantly (P b 0.01, t = 3.714, df = 22) greater in Gonghu Bay (0.428 mg/L) than Meiliang Bay (0.096 mg/L).

The seasonal range (approximately 5 °C to 30 °C) in water temperature was similar for both bays (Table 3; Fig. 7). Secchi disc transparency in Meiliang Bay ranged from 0.18 m and 0.50 m with a mean of 0.32 m; in Gonghu Bay the range was 0.15 m to 0.75 m with a mean of 0.45 m. Average TN concentration in Meiliang Bay (4.57 mg/L) was significantly (P b 0.01, t = 3.035, df = 22) greater than in Gonghu Bay (3.00 mg/L). TDN, TP, and chlorophyll-a concentrations averaged 3.1 mg/L, 0.165 mg/L, and 17.78 μg/L, respectively in Meiliang Bay while in Gonghu Bay, the corresponding averages were lower at 2.3 mg/L, 0.108 mg/L, and 13.02 μg/L, respectively indicating a slightly lower trophic status. Statistical analyses

Table 2 Mean of abundance and biomass of phytoplankton in Meiliang Bay and Gonghu Bay in Lake Taihu, July 2006 to June 2007. Meiliang Bay

Cyanophyta Cryptophyta Bacillariophyta Xanthophyta Chrysophyta Euglenophyta Chlorophyta

Gonghu Bay

Abundance (ind/L)

Biomass (μg/L)

Abundance (ind/L)

Biomass (μg/L)

9807812 566 44280 20938 0 566 86368

702.9 1.4 95.7 2.9 0.0 5.8 28.1

197139 778 169977 28153 5942 3325 157952

229.5 1.3 427.9 3.9 2.3 26.9 55.5

Rotifera abundance was positively correlated with transparency and negatively correlated with TP, suspended solids and CODMn (Table 4). Cladocera abundance was positively correlated with TP, CODMn, suspended solids, and water temperature and negatively correlated with transparency. Copepoda abundance was positively correlated with DTP, TP, CODMn, suspended solids, Chl-a, and water temperature and negatively correlated with DTN, ammonium, and nitrate. The CCA analyses indicated that the variability in zooplankton composition between Meiliang and Gonghu Bays was related to four environmental factors: dissolved total nitrogen, phosphate, and the diatoms Cyclotella and Pinnularia, (P b 0.05, Fig. 8). The eigenvalues of the first and second axis were 0.274 and 0.212, respectively, and explained 24.7% of the observed variation zooplankton.


Y. Guijun et al. / Journal of Great Lakes Research 38 (2012) 299–308

Fig. 5. Comparison of temporal changes in abundance of Microcystis, chlorophyll-a, Cyclotella spp. and Pinnularia sp. in Meiliang Bay and Gonghu Bay, July 2006 to June 2007.

Temporal trends In Meiliang Bay, there was a trend for TN and TP concentrations to decline from 1996 to 2001 and then increase from 2002 to 2006 suggesting increased productivity and/or nutrient enrichment; this

was followed by a slight decline in 2007 and 2008 (Fig. 9). Nutrient enrichment of a lake generally leads to an increased abundance and biomass of zooplankton (Auer et al., 2004; Pace, 1986). However, total zooplankton abundance did not follow TN and TP trends. Unfortunately biomass was not estimated. In Gonghu Bay, TN and TP

Fig. 6. Comparison of temporal changes in abundance and biomass of seven groups of phytoplankton in Meiliang Bay and Gonghu Bay, July 2006 to June 2007.

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Table 3 Mean, minimum (min) and maximum (max) values of 19 physicochemical parameters in Meiliang Bay and Gonghu Bay, July 2006 to June 2007. The P-values associated with the t-tests are also given (df = 22) for differences between the two bays. Meiliang Bay

Gonghu Bay







Physical–chemical variables Water temperature (°C) Transparency (m) Suspended solids (mg l− 1) pH Chemical oxygen demand (mg l− 1) Dissolved oxygen (mg l− 1) K (mg l− 1) Na (mg l− 1) Ca (mg l− 1) Mg (mg l− 1)

18.5 0.32 58.16 8.30 6.27 9.15 6.22 68.0 29.2 8.81

5.2 0.18 19.92 8.04 4.76 6.96 4.74 46.5 14.8 5.69

29.9 0.50 124.7 8.92 7.72 11.11 8.13 101.6 47.1 12.53

18.6 0.45 47.48 8.22 4.31 8.7 4.7 49.5 30.3 8.54

5.1 0.15 12.68 7.93 2.99 5.49 2.76 22.4 17.5 5.68

29.6 0.75 141 8.50 5.71 11.72 6.01 75.5 45.8 12.8

Nutrient variables Ammonium (mg l− 1) Nitrite (mg l− 1) Nitrate (mg l− 1) Dissolved total nitrogen (mg l− 1) Total nitrogen (mg l− 1) Orthophosphate (mg l− 1) Dissolved total phosphorus (mg l− 1) Total phosphorus (mg l− 1) Chlorophyll-a (μg l− 1)

0.74 0.048 1.28 3.10 4.57 0.012 0.041 0.165 17.78

0.06 0.006 0.09 0.57 2.17 0.001 0.021 0.078 1.79

2.49 0.116 3.2 6.10 6.46 0.047 0.098 0.324 31.81

0.51 0.041 1.02 2.28 3.00 0.008 0.027 0.108 13.02

0.04 0.003 0.1 0.85 1.58 0.000 0.01 0.04 3.91

1.43 0.107 2.69 3.49 4.72 0.026 0.06 0.323 26.78

t-test P-value

− 0.024 − 1.882 0.712 0.883 4.576⁎⁎ 0.627 3.430⁎⁎ 2.950⁎⁎ − 0.270 0.301

0.891 0.491 0.774 1.344 3.035⁎⁎ 0.969 1.635 1.734 1.198

⁎⁎ P b 0.01.

Fig. 7. Comparison of temporal changes in temperature, transparency, total nitrogen, total phosphorus, orthophosphate, dissolved total nitrogen in Meiliang Bay and Gonghu Bay, July 2006 to June 2007.


Y. Guijun et al. / Journal of Great Lakes Research 38 (2012) 299–308

Table 4 Values for Pearson's correlation coefficients between zooplankton abundance and 15 physicochemical parameters in Meiliang Bay and Gonghu Bay in Lake Taihu.

Water temperature Transparency Suspended solids pH Chemical oxygen demand Dissolved oxygen Ammonium Nitrite Nitrate Dissolved total nitrogen Total nitrogen Orthophosphate Dissolved total phosphorus Total phosphorus Chlorophyll-a




Total abundance

− 0.209 0.532⁎⁎ − 0.599⁎⁎ − 0.085 − 0.641⁎⁎ 0.042 0.134 − 0.244 − 0.143 − 0.130 − 0.403 0.023 − 0.113 − 0.413⁎

0.453⁎ − 0.491⁎ 0.524⁎⁎ 0.176 0.634⁎⁎ − 0.201 − 0.370 − 0.150 − 0.283 − 0.312 0.130 0.081 0.395 0.572⁎⁎

0.627⁎⁎ − 0.392 0.421⁎ 0.239 0.484⁎ − 0.371 − 0.430⁎

0.153 0.219 − 0.253 0.062 − 0.041 − 0.041 − 0.138 − 0.305 − 0.389 − 0.473⁎ − 0.403 − 0.014 0.051 0.106 0.242

− 0.318


− 0.218 − 0.516⁎⁎ − 0.543⁎⁎ − 0.103 0.270 0.435⁎ 0.655⁎⁎ 0.534⁎⁎

⁎ P b 0.05. ⁎⁎ P b 0.01.

showed a steady increase from 1998 to 2007 and a weak trend of increasing zooplankton abundances (Fig. 9); rotifers were the dominant group of zooplankton. Cladocera in particular showed evidence of increasing abundance despite the loss of macrophytes in 2005. However, zooplankton abundances were substantially lower in Gonghu Bay than Meiliang Bay as were TN and TP concentrations.

Fig. 8. Canonical correspondence analysis biplots showing the differences in zooplankton communities in relation to the main environmental factors in Meiliang Bay and Gonghu Bay in Lake Taihu. The points on the graph represent assemblages of zooplankton species abundance of the monthly samples (M= Meiliang Bay; G = Gonghu Bay; the number behind M or G represents each month). The abbreviations PO4-P and DTN represent phosphates and dissolved total nitrogen, respectively.

Discussion Comparison with other large freshwater lakes in China When compared to other large freshwater lakes in China, the average monthly abundance of zooplankton in Lake Taihu (1508 ind/L) (Yang et al., 2009) was similar with that of Lake Chaohu (1809 ind/L) (Wang et al., 2006) and Lake Hongzehu (1458 ind/L) (Yang, 2003) and considerably higher than that of Lake Poyanghu (75 ind/L) (Wang et al., 2003). Lake Taihu and Lake Chaohu have been eutrophic since the late 1970s and early 1980s (Qin, 2002; Yin and Zhang, 2003), and Lake Hongzehu has recently become eutrophic (Wang et al., 2010); in contrast, Lake Poyanghu is mesotrophic (Li, 1996). Trophic status is often suggested as the main factor leading to differences in zooplankton abundance among freshwater lakes. Effects of predation by fish on zooplankton composition Predation by fish is one of the main factors that may strongly affect zooplankton community structure in freshwater ecosystems (Brooks and Dodson, 1965). In lakes, predation pressure on large crustaceans by fish may lead to a shift towards smaller crustaceans and rotifers (Brooks and Dodson, 1965; Korponai et al., 1997; Makarewicz, 2001; Xie and Yang, 2000; Yang et al., 2005). In Lake Taihu, lake anchovy and the ice fish feed extensively on the zooplankton. Cladocera are the dominant prey of the lake anchovy, constituting almost 80% of their diet, while Copepoda are the dominant prey of the ice fish, constituting more than 70% of their diet (Chen and Zhu, 2008; Liu et al., 2005b). Size-selective predation may explain why smaller crustaceans, such as B. coregoni and C. cornuta were the dominant groups in Meiliang Bay and rotifers in the more shallow Gonghu Bay. The influence of physicochemical factors and phytoplankton on zooplankton composition Zooplankton community structure differed between Meiliang Bay and Gonghu Bay. In Meiliang Bay the cladocerans B. coregoni and

C. cornuta were dominant while in Gonghu Bay the rotifers P. trigla and B. calyciflorus were dominant. The results of CCA suggest that the two physicochemical and two phytoplankton features influenced differences in zooplankton communities between the two bays: these were concentrations of DTN and PO4-P, which are important factors influencing the abundance and structure of phytoplankton, and abundances of the diatoms Cyclotella and Pinnularia. Cyclotella is generally considered as a suitable food for zooplankton (Cisneros et al., 1991; Edmondson, 1965; Infante, 1978) but Pinnularia may not be edible because with a mean length of 56.5 μm (range = 38 to 75 μm) Pinnularia are larger than the preferred particulate size range (5 to 50 μm) of zooplankton (Dodoson and Frey, 1991). Some studies have shown inhibitory effects of some diatoms on crustacean abundance (Juttner, 2005; Miralto et al., 1999). When TP and chemical oxygen demand (CODMn), an indicator of organic matter including algae, bacteria, detrital particles, etc., was high, cladoceran and copepod abundances also tended to be high while the converse was observed for rotifers. Cladoceran abundances were greater at higher temperatures and suspended solid concentrations and low water clarity; copepods also were more abundant at warmer temperatures. The greater biomass of zooplankton in Meiliang Bay than Gonghu Bay may be associated with the slightly higher trophic status of the bay in addition to lower fish predation pressures because its deeper waters combined with lower water clarity provided more protection from visual feeding planktivores. Cyanobacteria blooms, particularly Microcystis, occur in Lake Taihu from May to October and were particularly intense in the northern region of the lake, especially Meiliang Bay (Chen et al., 2003). The low nutrient content and toxicity of Cyanophyta blooms may adversely influence the growth and reproduction of larger Cladocera (DeMott, 1999; Hietala et al., 1995; Rohrlack et al., 1999). Cyanobacterial blooms can also restructure the zooplankton community by favoring smaller species (Geng et al., 2005). Both Bosmina and Ceriodaphnia may coexist with Cyanobacteria during blooms (Chen and Xie, 2003; DeMott and Kerfoot, 1982; Nandini, 2000; Yang et al., 2009), as they use their fifth pair of limbs to screen out and avoid feeding on Cyanobacteria. Similarly in Meiliang Bay where Microcystis blooms

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Fig. 9. Comparison of temporal changes in abundance of zooplankton and concentration of TN and TP in Meiliang Bay, 1981 to 2008 and in Gonghu Bay, 1998 to 2007.

are present, the dominance of B. coregoni and C. cornuta over copepods may simply be due to their tolerance to Cyanobacteria. In addition several studies have shown that a higher proportion of Microcystis aeruginosa in the diet resulted in decreased population growth rate of rotifer Brachionus havanaensis and B. calyciflorus (Alejandro et al., 2009; Nandini, 2000). This might explain why rotifers are not dominant in Meiliang Bay although predation by predaceous zooplankton may also be a factor. In Gonghu Bay, the rotifers Polyartra trigla and B. calyciflorus were the dominant species. Kirk and Gilbert (1990) found that high, naturally occurring, concentrations of coarse, suspended clay (50–100 mg/L) (b2 μm particle size) caused large reductions in the population growth rates of four cladoceran species (Bosmina longirostris, Ceriodaphnia dubia, Daphnia ambigua, and D. pulex). However, high concentrations of coarse or fine clay (b1 μm) did not affect the population growth rates of four rotifer species (B. calyciflorus, Keratella cochlearis, Polyarthra vulgaris, and Synchaeta pectinata), even at very low food levels (Kirk and Gilbert, 1990) and cladoceran and copepod abundances were positively correlated with suspended sediment concentrations. Furthermore, since suspended solid concentrations were generally similar in both bays (Table 1) they do not provide an explanation of the difference in the zooplankton communities observed in the two bays.

Acknowledgments We thank Zhu Guangwei, Chao Jianying, Chen Feizhou, Deng Jianming, Li Kuangyi, Qian Kuimei, Wang Hongyan, and Wang Yuanyuan for their help and support during the field sampling. We also thank the Taihu Laboratory for Lake Ecosystem Research, Chinese Academy of Sciences, for supplying physicochemical data. This study was funded by the State Key Laboratory of Lake Science and Environment of China (Grant #2008SKL012), the Natural Scientific Foundation of China (Grant #40825004, 41101053, 40730529, 20707007), and by Water Pollution Control and Management Project (Grant #2009ZX07101-013).

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