论文
论文标题: Spatio-temporal patterns of zooplankton in a main-stem dam affected tributary: a case study in the Xiangxi River of the Three Gorges Reservoir, China
作者: Li, Xinghao; Huang, Jie; Filker, Sabine; Stoeck, Thorsten; Bi, Yonghong; Yu, Yuhe; Song, Weibo
出版刊物: SCIENCE CHINA-LIFE SCIENCES
出版日期: AUG
出版年份: 2019
卷/期: 8
DOI: 10.1007/s11427-018-9523-0
论文摘要: As the ecologically important recipient channels for riverine ecosystems, tributaries provide unique microhabitats for microorganisms, among which zooplankton constitutes the most important heterotrophic organisms. In particular, the reduced water velocity caused by dams is more favorable for zooplankton development; therefore, dammed rivers are expected to support extremely diverse and abundant zooplankton communities and notably different spatiotemporal distribution patterns. So far, however, only very few molecular studies support these assumptions. Using high-throughput sequencing, a high number of 350 operational taxonomic units (OTUs; 97% cutoff) were retrieved from 30 samples collected in the Xiangxi River, the nearest large tributary upstream of the Three Gorges Dam. Zooplankton did not show significant spatial distribution in the channel. Instead, the community structures varied significantly over sampling dates, corroborating the seasonal patterns found in lakes and ponds in the subtropical zone. As expected, the community compositions were deterministically governed by environmental filtering processes (phylogenetic clustering), in which water velocity appeared to be much less important than other investigated environmental factors. Moreover, most of the detected phylotypes (OTUs) had a relatively high (>90%) sequence similarity to previously deposited sequences, suggesting a mediocre degree of genetic novelty within the zooplankton communities in the Xiangxi River.
== 实验室与学会 ==
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  • 水产品种创制与高效养殖全国重点实验室
  • 中国科学院藻类生物学重点实验室
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  • 武汉白暨豚保护基金会
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  • 中国动物学会原生动物学分会
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  • 中国水产学会鱼病学专业委员会
  • 中国鱼类学会
== 平台建设 ==
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  • “一带一路”海域赤潮数据库
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  • 国家斑马鱼资源中心
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  • 中国科学院水生生物研究所分析测试中心
  • 中国科学院超级计算武汉分中心
  • 水生生物博物馆
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