Chinese Journal of Oceanology and Limnology Vol. 32 No. 5, P. 1083-1091, 2014 http://dx.doi.org/10.1007/s00343-014-3354-5
Response of rotifer community to environmental changes in five shallow lakes in the middle reach of Changjiang River, China* DU Xue (都雪)1, 2, FENG Weisong (冯伟松)1, LI Wei (李为)1, YE Shaowen (叶少文)1, LIU Jiashou (刘家寿)1, ZHANG Tanglin (张堂林)1, LI Zhongjie (李钟杰)1, ** 1
State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
Received Dec. 26, 2013; accepted in principle Feb. 20, 2014; accepted for publication Mar. 4, 2014 © Chinese Society for Oceanology and Limnology, Science Press, and Springer-Verlag Berlin Heidelberg 2014
Abstract We evaluated the response of a rotifer community to environmental changes in five shallow lakes in the middle reach of the Changjiang (Yangtze) River in summer and autumn 2010. These five lakes differed in trophic status and rotifer community structure. Twenty-nine rotifer species were collected, of which Keratella cochlearis, Polyarthra dolichoptera, and Trichocerca elongate were dominant. The mean density, Shannon-Wiener diversity, and equitability among the five lakes differed significantly (P<0.05). The mean rotifer density was positively correlated with trophic state. The diversity was higher in lakes with high macrophyte coverage. The composition of rotifer species was closely associated with the trophic gradient. Five environmental variables, Secchi depth, conductivity, TN, NH4-N, and TP, significantly affected the composition of rotifer species. Keratella quadrata, Brachionus calyciflorus, and B. forficula were more common in eutrophic conditions. Our results suggest that eutrophication has a significant influence on the rotifer community structure and highlight the potential for using rotifer community structure as an indicator of trophic status in subtropical lakes. Keyword: rotifer; environmental variables; shallow lakes; eutrophication
1 INTRODUCTION Eutrophication is one of the most significant problems affecting freshwater ecosystems worldwide (Carpenter et al., 1998). Eutrophication is characterized by an increase in nutrient loading, a decrease of water transparency, the loss of submerged macrophytes, and a change in ecosystem structure and function (Jeppesen et al., 1997; Duggan et al., 2002). The Changjiang (Yangtze) River, the longest river in Asia and the third longest in the world, flows more than 6 300 km from the glaciers on the QinghaiTibet Plateau across southwestern, central, and eastern China before entering the East China Sea (Liu et al., 2007). The river is a key water resource for drinking, irrigation, industry, transportation, fishery, recreation, and the support of biodiversity (Carpenter et al., 1998; Wu et al., 2012). The Changjiang River basin also
contains a number of lakes, totaling more than 20 000 km2 in area, and accounting for one third of the total lake area in China (Cui and Li, 2005). However, most lakes in the middle and lower reaches of the river have become mesotrophic or eutrophic due to anthropogenic activity during recent decades (Chai et al., 2006; Wu et al., 2012). Unfortunately, eutrophication is often associated with undesirable and harmful effects on the structure and function of biota in the aquatic ecosystem. The structure of zooplankton communities varies between lakes and is dependent on physical, chemical,
* Supported by the Special Fund for Agro-Scientific Research in the Public Interest (No. 20130356), the National Key Technology Research and Development Program of China (No. 2012BAD25B08), and the National Natural Science Foundation of China (Nos. 30830025, 31201994) ** Corresponding author:
[email protected]
CHIN. J. OCEANOL. LIMNOL., 32(5), 2014
30.85°
1084
WHL
30.45°
30.65°
N
TXH
BDT
30.25°
NSH
30.05°
LZH
0 114.10°
114.30°
114.50°
10
20 km
114.70°
E 114.90°
Fig.1 Location of the lakes sampled in this study BDT: Biandan Tang; NSH: Niushan Hu; LZH: Liangzi Hu; TXH: Tangxun Hu; WHL: Wuhu Lake
and biological factors (Jeppesen et al., 1997; Duggan et al., 2002). Thus, zooplankton are an indicator of ecological status, and in particular, the trophic status of lakes (Sládeček, 1983; Bērziņš and Pejler, 1989; Duggan et al., 2001). However, the majority of studies to date have focused on cladocerans. In contrast, little is known about the relationship between tropic status and rotifers, the principal component of freshwater zooplankton communities (Castro et al., 2005; Wen et al., 2011). Rotifers play a major role in transferring energy from phytoplankton to fish, a factor that should be taken into account given their higher rate of growth, reproduction, and metabolism which makes a substantial contribution to zooplankton production (Sládeček, 1983; Castro et al., 2005). The intermediate trophic position of rotifers within aquatic food-webs makes them sensitive to both biotic and abiotic factors (McQueen et al., 1986). In general, the food resources available to rotifers are much more abundant in nutrient-rich lakes so rotifer density tends to increase with an increase in trophic status (Arnott and Vanni, 1993; Castro et al., 2005). Macrophytes, which are scarce in eutrophic lakes, are also known to affect the distribution of rotifers (Duggan et al., 2001; van Donk and van de Bund, 2002). Thus, the process of eutrophication in freshwater lakes directly or indirectly causes changes in the rotifer community. Although the freshwater shallow lakes distributed along the Changjiang River have significant social
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and biological functions in China, relatively little research has been conducted to describe the relationship between rotifer communities and environmental variables in these lakes. Most previous reports have focused on the composition and seasonal changes of rotifer communities in a single lake or a few lakes along the lower reach of the Changjiang River basin (Yang et al., 2009; Wen et al., 2011), or have focused on the composition and density, but not diversity of the rotifer community (Wang et al., 2010). Given this, our objectives were to: (1) evaluate whether the rotifer community structure can be use as an index of the trophic status of the shallow lakes in the Changjiang River basin; and (2) evaluate the relationship between environmental variables related to trophic status and the rotifer community structure. In particular, we evaluated whether the density of rotifers was positively correlated with trophic level. We documented the community structure of rotifers and measured environmental variables in five lakes with different trophic status in the Changjiang River basin. Our results provide insight into the potential use of rotifers as an indicator of aquatic ecosystem health during a more intensive monitoring program.
2 MATERIAL AND METHOD 2.1 Description of study area We collected samples from five lakes, including Tangxun Hu (TXH, hu means lake in Chinese), Wuhu Lake (WHL), Biandan Tang (BDT, tang means pool), Niushan Hu (NSH), and Liangzi Hu (LZH), are all located in the middle reach of the Changjiang River in the central region of China (Fig.1). These lakes were chosen because they differ in the extent of macrophyte coverage and trophic status. The characteristics of these lakes are summarized in Table 1. 2.2 Sampling methods Sampling was carried out in summer and autumn 2010. Water temperature (WT), dissolved oxygen (DO), pH, and conductivity were measured in situ using an YSI 85 and YSI pH100. Water depth (WD) and Secchi depth (SD) were determined using a Secchi disk. Sampling sites were selected based on the area of the lake, with 5 to 8 sites chosen for each lake. Water samples from each site were also collected and transported to our laboratory for further analysis. Chemical oxygen demand (COD), chlorophyll a and the concentrations of ammonia nitrogen (NH4-N),
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Table 1 Environmental variables measured in five lakes in the middle reach of the Changjiang River* Environmental variables
Abbreviation
BDT
NSH
LZH
TXH
WHL
Water depth (cm)
WD
271±33
430±66
345±84
333±13
334±16
Secchi depth (cm)
SD
54±11
187±71
133±79
64±20
90±32
Conductivity (μS/cm)
Conductivity
374±57
166±29
137±37
305±66
220±63
pH
pH
8.20±0.12
8.34±0.74
8.76±0.51
8.65±0.40
7.89±0.26
Water temperature (°C)
WT
23.21±2.40
23.23±2.81
22.09±6.12
22.38±2.12
21.54±1.47
Dissolved oxygen (mg/L)
DO
7.24±0.54
8.01±0.61
8.81±2.74
6.21±1.32
8.14±0.61
Total nitrogen (mg/L)
TN
0.31±0.15
0.46±0.12
0.74±0.13
2.02±.72
0.65±0.58
Total phosphorus (mg/L)
TP
0.05±0.02
0.02±0.01
0.05±0.04
0.07±0.03
0.05±0.03
Ammonia (mg/L)
NH4-N
0.50±0.15
0.07±0.08
0.23±0.16
0.93±0.51
0.33±0.20
COD (mg/L)
COD
4.74±0.47
4.55±0.41
5.26±0.92
6.16±0.71
6.09±0.58
Chlorophyll a (μg/L)
Chl a
20.31±12.41
9.53±7.04
28.31±19.91
46.6±24.2
16.13±8.03
Macrophyte coverage
Macrophyte
0%
60%
80%
0%
30%
Note: Data are expressed as the mean±S.D. Same abbreviations are also used in Figs.2 and 5. BDT: Biandan Tang; NSH: Niushan Hu; LZH: Liangzi Hu; TXH: Tangxun Hu; WHL: Wuhu Lake.
total phosphorus (TP) and total nitrogen (TN) were determined according to the description by APHA (1992). Rotifer samples were taken at each site concurrent with collection of water samples. On each occasion, 20–30 L depth-integrated water was collected using a 5-L modified Van-Dorn sampler and filtered through a 64-μm mesh net for rotifer species identification. Additionally, water samples were collected with the 5 L modified Van-Dorn sampler at 1 m vertical depth intervals and pooled for the collection of 1 L subsamples from each site. Samples were preserved in 5% Lugol’s solution and concentrated by sedimentation. To obtain abundance estimates, 1 mL subsamples were transferred to a Sedgwick-Rafter chamber and the number of rotifers was enumerated under an inverted microscope until the coefficient of variation of the most abundant species was <20%. Species were identified according to the descriptions of Koste (1978) and Zong and Huang (1991). 2.3 Data analysis A principal component analysis (PCA) was performed on the environmental variables to reduce the dimensionality of these data and to identify the relationships between these variables among the lakes. The PCA was performed on a correlation matrix of standardized and transformed data. Rankabundance curves were used to compute and then identify the dominant rotifer species, with a relative abundance of >10% being defined as the dominant species. PCA and rank-abundance curve analysis
were performed using the “ade4” and “BiodiversityR” packages, respectively, in R (R Development Core Team, 2010). Species diversity and equitability were determined using Shannon-Wiener diversity (H′) and Pielou evenness (J) index, respectively, with the following formulas: s
H p i log 2 pi ; i 1
J=H′/lnS, where Pi represents the relative abundance of each rotifer species and S represents total species richness. We tested for differences in mean density, ShannonWiener diversity, and Pielou evenness among the rotifer communities using Kruskal-Wallis and multiple comparison tests in the “agricolae” package in R. Redundancy analyses (RDA) were used to evaluate the relationships between the composition of rotifer species and environmental variables because the gradient length of the first DCA (detrended correspondence analysis) axis performed using species data was less than 3 standard deviation (SD) units (ter Braak and Smilauer, 2002). Species data were transformed by the Hellinger distance (Legendre and Gallagher, 2001) and environmental variables were standardized. Collinearity among the environmental variables was identified by inspection of variance inflation factors (VIF). VIF scores >20 indicate strong collinearity and indicate the variable should be eliminated from further analysis (er Braak
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a
WHL TXH
BDT
NSH LZH
WD 4
c
b
Chl a COD
3
NH4-N TN
Macrophyte 2
Conductivity
DO
1
SD
0
pH
TP
WT
Fig.2 Results of PCA performed on environmental variables a. ellipsoid represents samples for each lake ordinated in the PCA plane; b. barplot of eigenvalues of each PCA axis (the eigenvalues of the first two PCA axes are color-code differently); c. the correlation circle of environmental variables (Abbreviations for environmental variables see Table 1) in the first two axes.
and Smilauer, 2002). Forward selection of environmental variables was used to explain the composition of the rotifer community to obtain a small set of environmental variables maximally related to the rotifer species composition. RDA was performed using the “vegan” package in R.
3 RESULT 3.1 Difference of environmental variables in five lakes The results of PCA analysis described 36.66% and 19.63% of the variance in the environmental variables in the first two axes, respectively. The ordination of environmental variables on the first PCA axes is illustrated in Fig.2. TN (0.743), NH4-N (0.837), conductivity (0.724), chlorophyll a (0.666), and COD (0.559) had the highest positive correlation with the first PCA axis, whereas macrophytes (-0.787), Secchi
depth (-0.605), and dissolved oxygen (-0.542) exhibited a negative correlation with this axis. Clearly, the first component axis was related to the eutrophic status of the lakes. Water depth (0.455) was positive correlated with the second PCA axis, while water temperature (-0.909) was negative correlated with this axis. The location of Tangxun Hu (TXH) in the ordination diagraph was separated from the other lakes (Fig.2). This lake was strongly associated with the concentrations of nutrients, such as TN, TP, NH4-N, and chlorophyll a. Niushan Hu (NSH) and Liangzi Hu (LZH), which were close to each other and distant from TXH, had the highest values for macrophyte coverage, dissolved oxygen, and Secchi depth. The remaining two lakes, Wuhu Lake (WHL) and Biandan Tang (BDT), were located in the middle position between TXH Lake and NSH and LZH Lakes.
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Table 2 List of rotifer species found in the five lakes* Species
Family
Abbr.
BDT
NSH
LZH
TXH
WH
Keratella cochlearis
Brachionidae
K. coch
+
+
+
+
+
Polyarthra dolichoptera
Synchaetidae
P. doli
+
+
+
+
+
Trichocerca elongata
Trichocercidae
T. elon
+
+
+
+
+
Trichocerca pusilla
Trichocercidae
T. pusi
+
+
+
+
+
Trichocerca rousseleti
Trichocercidae
T. rous
+
+
+
-
-
Trichocerca similis
Trichocercidae
T. simi
-
+
+
-
+
Brachionus angularis
Brachionidae
B. angu
+
+
+
+
+
Keratella valga
Brachionidae
K. valg
+
+
+
-
-
Trichocerca cylindrica
Trichocercidae
T. cyli
-
+
+
-
-
Filinia longiseta
Testudinellidae
F. long
+
-
+
+
+
Polyarthra vulgaris
Synchaetidae
P. vulg
+
-
+
+
-
Harringia eupoda
Asplanchnidae
H. eupo
-
-
+
+
-
Trichocerca longiseta
Trichocercidae
T. long
-
+
+
+
-
Brachionus diversicornis
Brachionidae
B. dive
-
-
+
+
+
Brachionus forficula
Brachionidae
B. forf
-
-
+
+
+
Asplanchna priodonta
Asplanchnidae
A. prio
-
-
+
+
+
Hexarthra mira
Testudinellidae
H. mira
+
+
+
+
-
Brachionus calyciflorus
Brachionidae
B. caly
-
+
+
+
+
Monostyla unguitata
Lecanidae
M. ungu
-
-
-
-
+
Trichocerca bicristata
Trichocercidae
T. bicr
-
-
-
+
-
Polyarthra minor
Synchaetidae
P. mino
-
-
-
+
-
Monostyla lunaris
Lecanidae
M. luna
-
-
+
+
-
Trichocerca gracilis
Trichocercidae
T. grac
-
-
+
-
-
Keratella quadrata
Brachionidae
K. quad
-
-
-
+
-
Trichocerca capucina
Trichocercidae
T. capu
-
-
+
-
-
Monostyla closterocerca
Lecanidae
M. clos
-
-
+
-
-
Trichocerca rattus
Trichocercidae
T. ratt
-
-
+
-
-
Filinia minuta
Testudinellidae
F. minu
-
-
+
-
-
Lecane luna
Lecanidae
L. luna
-
-
+
-
-
Note: + and - indicate the presence and absence of rotifer species in each lake. BDT: Biandan Tang; NSH: Niushan Hu; LZH: Liangzi Hu; TXH: Tangxun Hu; WHL: Wuhu Lake. Column Abbr. shows the abbreviations for the species names of rotifers.
3.2 Composition, dominance, and biological index of the rotifer community A total of 29 rotifer species were identified in the five lakes with in the highest and lowest number of species in LZH and BDT, respectively (Table 2). The rank-abundance curve for rotifer species in the five lakes is illustrated in Fig.3. Keratella cochlearis was the most dominant species in the five lakes followed by Polyarthra dolichoptera and Trichocerca elongata. The genera Keratella, Polyarthra, and Trichocerca were the only dominant species, and their distribution was similar in all five lakes. Some rare species ranked lowly in the rank-abundance curve, including
Monostyla closterocerca, Trichocerca rattus, and Lecane luna, which were only found in LZH. The rotifer densities differed significantly among the lakes (P<0.001). The density of the rotifer communities ranged from 302 to 1 773 ind./L. The density was significantly higher in TXH, LZH, and BDT than in NSH. The Shannon diversity index ranged from 0.82 to 1.78 and equitability ranged from 0.46 to 0.87. Both the Shannon diversity and equitability indexes differed significantly among lakes (P=0.02 and P=0.008, respectively). The Shannon diversity index was higher in LZH and WHL. The Pielou evenness index was highest in NSH and lowest in BDT (Fig.4).
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3.3 Community analysis The RDA revealed the relationship between the composition of rotifer species and environmental variables (Fig.5). The adjusted R2 value was 0.46. The adjusted constrained eigen values for the first two RDA axes were 0.166 and 0.033, accounting for 34.24% and 6.93% of variation in the rotifer species data, respectively. Only five environmental variables were significant after forward selection. Conductivity, TP, and TN were positively related with axis 1, L
N
50 0
5
10
15 20 Species rank
25
30
Fig.3 Rank-abundance curve of rotifer species in the five lakes
ac
a
The five lakes differed primarily along gradients of Secchi depth, dissolved oxygen, nutrients, and biotic factors (chlorophyll a and macrophyte coverage), indicating that the environmental heterogeneity of these lakes was primarily due to the difference in trophic status. An increase in nutrient concentrations can lead to an increase in phytoplankton productivity, contributing to the process of eutrophication of freshwater lakes (Jeppesen et al., 1997, 2000; Carpenter et al., 1998). Urban lakes are particularly susceptible to eutrophication as a result of anthropogenic nutrient inputs from fertilizers and municipal and industrial wastewater (Carpenter et al., 1998; Smith et al., 1999). In recent years, with the
b
a
c
5000 2000 0
Pielou evenness index
Shannon index
Density (ind./L)
B: Biandan Tang; L: Liangzi Hu; N: Niushan Hu; T: Tangxun Hu; W: Wuhu Lake
i
whereas SD was positively associated with axis 2. The ordination diagram (Fig.5) clearly illustrates the separation among the five lakes based on the composition of rotifer species, in which NSH and LZH are close to each other, BDT and WHL are close to each other, and TXH is distant from the others. The rotifer species, T. elongata, K. quadrata, K. valga, B. angularis, and B. calyciflorus that were encountered in phosphorus- and nitrogen-rich habitats are displayed on the right of the triplot, whereas the species, L. luna and M. closterocerca, that prefer a relatively oligotrophic state are represented on the top of the triplot (Fig.5). The most dominant species, K. cochlearis and P. dolichoptera, were less influenced by the selected environmental variables.
4 DISCUSSION
B L N T W
W
100
Abundance (ind./L) 200 500 1000 2000
5000
B T
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ii
a
2
ab
b
b
ab
1 0 iii
a
ab
c
LZH
NSH
abc
b c
TXH
WHL
1
0 BDT
Fig.4 Differences in density (i), Shannon index (ii) and Pielou evenness index (iii) among the five lakes The median values for each of the five lakes that share the same letter are not significantly different (P<0.05).
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1 BDT NSH LZH
SD
TXH WHL 0.5 TN
RDA2
L. luna
0
K. coch
P. mino M. clos T. grac T. long T. simi NH4-N T. rous T. capu T. bicr B. forf M. luna H. eupo T. cyli T. ratt F. minu H. mira T. pusi B. angu K. quad P. doli A. prio B.caly P. vulg T. elon B. dive K. valg M. ungu F. long TP
-0.5
Conductivity
-1 -1
-0.5
0 RDA1
0.5
1.0
Fig.5 Ordination diagram by RDA of the rotifer species and the environmental variables Abbreviations for environmental variables see Table 1 and abbreviations for rotifer species see Table 2.
rapid development of industry and agriculture, the lakes in the middle and lower reaches of the Changjiang River have begun to face problems associated with degradation of water quality by eutrophication (Chai et al., 2006; Wu et al., 2012). Our results suggest that the level of eutrophication was higher in TXH, likely because it is a shorter distance from the downtown area of Wuhan city than the remaining four lakes. Rotifer species whose presence or abundance reflect the characteristics of the habitat within which they are found are often considered as indicator species (Anas et al., 2013). For instance, some rotifer species can be used to evaluate the acid-stress status of lakes (Anas et al., 2013) and, likewise, the presence or relative abundance of some species is a good indicator of the trophic status of lakes (Bērziņš and Pejler, 1989; Duggan et al., 2001). The abundance of the genera Keratella and Trichocerca is indicative of a higher eutrophic status (Sládeček, 1983). Among the 29 rotifer species we observed, K. cochlearis, P.
dolichoptera, and T. elongata were the three most dominant species. Our results suggest that the process of eutrophication in these five lakes has significantly increased the prevalence of K. cochlearis and the genus Trichocerca. We speculate that this may be due to a shift in the fish assemblage. Planktivorous fish are often more abundant in the eutrophic lakes (Arnott and Vanni, 1993; Jeppesen et al., 1997), resulting in increased predation pressure on zooplankton. However, species in the genera Keratella, Polyarthra, and Trichocerca often have morphological defenses and adaptations that protect them from predators so they are able to successfully dominate in lakes, even under higher predation pressure (Yoshida et al., 2003). The density of rotifer communities differed significantly (P<0.05) among the five lakes and was significantly higher in TXH and BDT. The density of rotifers, in general, reflects the availability of food resources. Rotifers can feed on phytoplankton, bacteria, and detritus (Sládeček, 1983; Bērziņš and Pejler, 1989), the abundance of which is generally
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positively correlated with nutrient concentrations (especially N and P), and tends to be high in eutrophic lakes (Arora and Mehra, 2003). Moreover, eutrophication is often associated with a shift in the phytoplankton community assemblage, with cyanobacteria becoming more dominant and replacing the food source of large-bodied cladoceran zooplankton. However, cyanobacteria are more difficult to ingest, have lower nutritional value, and are sometimes toxic (Jeppesen et al., 1997). Thus, small-bodied zooplankton, such as rotifers are favored over the large bodied zooplankton. The density of rotifers was particularly high in LZH, possibly due to the extensive coverage of macrophytes. Macrophytes alter the microhabitat (van Donk and van de Bund, 2002), often resulting in conditions that are favorable to rotifers. For example, epiphytic algae, which are abundant on submerged macrophytes, are a preferred food source for macrophyte-associated rotifers. The Shannon diversity index varied among lakes in our study. However, it is difficult to explain this variability because of differences in the lake areas, sampling frequency, and the small numbers of samples collected from each lake (Duggan et al., 2002). Interestingly though, a number of studies have demonstrated a relationship between trophic status (Jeppesen et al., 2000), lake size or area (Dodson, 1992), or phytoplankton spatial heterogeneity (Barnett and Beisner, 2007) and species richness or diversity. Our data suggest a trend towards higher diversity associated with increased macrophyte coverage in LZH, WHL, and NSH than in TXH and BDT. Thus, we speculate that the presence of macrophytes in shallow lakes provides microhabitat for more diverse rotifer fauna, thereby explaining the increase in diversity. The relationship between the composition of rotifer species and environmental variables was demonstrated by RDA (Fig.5). Environmental variables were important for some rotifer species in structuring their community. Five of 12 environmental variables, including Secchi depth, conductivity, TN, NH4-N, and TP explained almost 41.17% of the variance in rotifer species composition. Lecane luna and M. closterocerca were found in LZH only that was characterized by high macrophyte coverage and high transparency (Fig.5). The genera Lecane is known to inhabit macrophyte-dominated water bodies (Wen et al., 2011). Submerged macrophytes can increase the transparency of shallow lakes (van Donk and van de Bund, 2002), so Secchi depth can be used as an index
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of macrophyte biomass. However, Secchi depth is lower in eutrophic lakes because of the increase in primary production, as measured by a rise in chlorophyll a concentrations (Yoshida et al., 2003). Eutrophication and the disappearance of submerged macrophytes explains the variation in the composition of rotifer communities. Indeed, our results suggest that the abundance of K. quadrata, B. calyciflorus, and B. forficula was related to the level of eutrophication, which is consistent with previous reports (Bērziņš and Pejler, 1989; Duggan et al., 2002; Wang et al., 2010). Conductivity, TP, TN, and NH4-N were all key determinants of rotifer community structure. Eutrophication is generally a result of nutrient enrichment (particularly N and P), and results in excessive algae growth and decay, simplification of the phytoplankton community structure, and a severe reduction in water quality (Carpenter et al., 1998; Smith et al., 1999). Conductivity is a very complex environmental variable. It reflects the concentrations of inorganic compound, so can be also used as an indicator of the concentration of mineral salts and eutrophic status (Radwan, 1984). Although our results suggest that the most dominant species, K. cochlearis and P. dolichoptera, were less influenced by the environmental variables we tested, the presence and prevalence of these two species were indicative of the eutrophic status, which is consistent with prior studies (Sládeček, 1983; Wen et al., 2011). The RDA triplot of rotifer species, environmental variables, and lakes revealed that the composition of rotifer species among lakes followed a nutrient gradient, indicating that eutrophication was the most important factor in determining rotifer community structure.
5 CONCLUSION We observed significant differences in trophic status and rotifer community structure among the five lakes. All five lakes are undergoing eutrophication. It appears that the rotifer community structure is significantly influenced by environmental variables related to the trophic status. Thus, the rotifer community structure could be used to indicate the level of eutrophication. The density of rotifers was positively correlated with trophic status and there was a trend towards higher diversity in lakes with relatively high macrophyte coverage. K. cochlearis and P. dolichoptera were abundant in eutrophic lakes, and the density of T. elongate, K. quadrata, B. calyciflorus, and B. forficula can be used as an indicator to eutrophic status.
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