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Spatiotemporal patterns and environmental drivers of total and active bacterial abundances in Lake Taihu, China

机译:太湖湖中总和活性细菌丰富的时空模式和环境驱动因素

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摘要

Bacteria are a key component in lake ecosystems, playing a crucial role in driving biogeochemical and energy fluxes. In lake biomonitoring, false alarms have often been triggered due to the presence of abundant dead or dormant bacterial cells. Thus, quantification of the metabolically active and dormant cells is required for effective biomonitoring. In this study, 120 sites were seasonally sampled in a large, shallow, eutrophic lake (Taihu, China) to quantify the total bacterial (TB) and active bacterial (AB) abundances and explore their spatiotemporal distribution. Generalized additive models (GAMS) were used to identify the major environmental drivers of TB and AB dynamics. TB ranged from 7.57 x 10(4) to 1.84 x 10(8) cells mL(-1), while AB ranged from 4.42 x 10(3) to 5.56 x 10(6) cells mL(-1). The proportion of AB was significantly higher in May (mean: 18.7%; cyanobacterial bloom thriving season) than in January or September (6.8% and 4.7%, respectively). GAMS indicated that dissolved oxygen, total dissolved nitrogen (TDN), total dissolved phosphorus and turbidity explained 47.8% of the TB variation, while TDN, dissolved organic carbon, water temperature and total phosphorus explained 72.7% of the AB variation. Our study showed that nutrients and physical factors are the major drivers of the TB and AB abundance variations in Lake Taihu. Bacterial responses to environmental variation were mostly nonlinear. The high proportion of AB variation (72.7%) explained by environmental parameters indicates that active bacteria are more sensitive to environmental changes and could be more effective bioindicators for long-term monitoring in shallow eutrophic lakes.
机译:细菌是湖泊生态系统中的关键组成部分,在驾驶生物地球化学和能量通量中发挥着至关重要的作用。在湖泊生物监测中,由于存在丰富的死亡或休眠细菌细胞,通常会触发误报。因此,需要进行代谢活性和休眠细胞的定量来进行有效生物监测。在这项研究中,120个位点在大型浅的养殖湖(中国太湖)中季节性上取样,以量化总细菌(TB)和活性细菌(AB)丰富,并探索其时尚分布。广义添加剂模型(Gam)用于识别TB和AB动态的主要环境驱动因素。 Tb从7.57×10(4)至1.84×10(8)个细胞m1(-1),而AB范围为4.42×10(3)至5.56×10(6)个细胞m1(-1)。 5月(平均值:18.7%;蓝藻盛开季节)的比例显着高于1月或9月(分别为6.8%和4.7%)。表明,溶解氧,总溶解的氮气(TDN),总溶解的磷和浊度解释了TB变异的47.8%,而TDN,溶解有机碳,水温和总磷,则解释了AB变异的72.7%。我们的研究表明,营养素和物理因素是太湖湖的TB和AB丰富变化的主要驱动因素。对环境变异的细菌反应主要是非线性的。通过环境参数解释的高比例的AB变异(72.7%)表明活性细菌对环境变化更敏感,并且可以更有效的生物indicer在浅兴奋湖泊中长期监测。

著录项

  • 来源
    《Ecological indicators》 |2020年第7期|106335.1-106335.11|共11页
  • 作者单位

    Chinese Acad Sci Nanjing Inst Geog & Limnol State Key Lab Lake Sci & Environm Taihu Lab Lake Ecosyst Res Nanjing 210008 Peoples R China|Univ Chinese Acad Sci Beijing 100049 Peoples R China;

    Chinese Acad Sci Nanjing Inst Geog & Limnol State Key Lab Lake Sci & Environm Taihu Lab Lake Ecosyst Res Nanjing 210008 Peoples R China|Univ Chinese Acad Sci Beijing 100049 Peoples R China;

    Chinese Acad Sci Nanjing Inst Geog & Limnol State Key Lab Lake Sci & Environm Taihu Lab Lake Ecosyst Res Nanjing 210008 Peoples R China|Univ Chinese Acad Sci Beijing 100049 Peoples R China;

    Chinese Acad Sci Nanjing Inst Geog & Limnol State Key Lab Lake Sci & Environm Taihu Lab Lake Ecosyst Res Nanjing 210008 Peoples R China|Univ Chinese Acad Sci Beijing 100049 Peoples R China;

    Chinese Acad Sci Nanjing Inst Geog & Limnol State Key Lab Lake Sci & Environm Taihu Lab Lake Ecosyst Res Nanjing 210008 Peoples R China;

    Univ Tennessee Dept Microbiol Knoxville TN 37996 USA;

    Chinese Acad Sci Nanjing Inst Geog & Limnol State Key Lab Lake Sci & Environm Taihu Lab Lake Ecosyst Res Nanjing 210008 Peoples R China|Univ Chinese Acad Sci Beijing 100049 Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Total bacteria; Active bacteria; Generalized additive models; CTC; Lake Taihu; Eutrophic;

    机译:总细菌;活性细菌;广义添加剂模型;CTC;太湖湖;富营养;

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