Seasonal variation of microbial eukaryotic community composition in the large,shallow, subtropical Taihu Lake,China |
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Authors: | Meijun Chen Feizhou Chen Biying Zhao Qinglong L. Wu Fanxiang Kong |
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Affiliation: | (1) State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography & Limnology, Chinese Academy of Science, 210008 Nanjing, People’s Republic of China;(2) Graduate School of Chinese Academy of Science, 100049 Beijing, People’s Republic of China;(3) Nanjing Normal University, 210046 Nanjing, People’s Republic of China |
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Abstract: | Microbial eukaryotic community (0.8–20 μm) composition and its seasonal variation were investigated in large, shallow, subtropical Lake Taihu located in Southeast China. The water samples were collected monthly from August 2006 to July 2007 at two sites distantly located in Meiliang Bay and Lake Center, which differed strongly in their trophic status and sediment resuspension. The microbial eukaryotic community compositions (MECC) were measured using denaturing gradient gel electrophoresis (DGGE) of PCR-amplified eukaryotic 18S rRNA gene fragments. Seasonal variations were related to environmental factors by means of redundancy analysis (RDA) in order to reveal the most important regulating factors. At both sites, the structures and Shannon–Wiener indices of the microbial eukaryotic communities displayed apparent seasonal variations, which were significantly related to environmental variables. There were significant intrahabitat differences in environmental factors regulating MECC, as well as in the seasonal dynamics of the two sites during the study period. At Meiliang Bay, the variations of total phosphorus concentration and cladocera abundance had the most profound impacts on the microbial eukaryotic community composition, while at Lake Center, the total nitrogen concentration and conductivity were most influential. Our results suggest that the DGGE method is a cost-effective way to analyze the seasonal dynamics of MECC and their interaction with environmental variables, which will provide new insights into the diversity and dynamics of MECC. |
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