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The relative importance of environmental factors in predicting phytoplankton shifting and cyanobacteria abundance in regulated shallow lakes

机译:环境因素在预测植物浅湖中预测浮游植物换血和蓝藻丰富的相对重要性

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摘要

The phytoplankton community can be affected by multiple environmental factors such as climate, meteorology, hydrology, nutrients, and grazing. The complex interactive effects of these environmental factors as well as the resilience of phytoplankton communities further make the prediction of phytoplankton communities' dynamics challenging. In this study, we analyzed multiple environmental factors and their relative importance in predicting both phytoplankton shifting and cyanobacteria abundance in two regulated shallow lakes in central China. Our results indicated that the phytoplankton community in the study areas could be mainly classified into 1. Cryptophyta dominated group, 2. Biologically diverse group, and 3. Cyanobacteria dominated group. The Multinomial Logistic Regression model indicated the Cryptophyta dominated group was sensitive to temperature, while other groups were sensitive to both temperature and nutrients. The interactive effects of temperature and nutrients were synergistic in the cyanobacteria dominated group, while they were antagonistic or minor in other groups. The Negative Binomial Regression model suggested high total phosphorus and low total nitrogen but not temperature were responsible for high cyanobacteria abundance. The conditional plot indicated nutrients affected cyanobacteria abundance more significantly under low wind speeds and lake volume fluctuations, and cyanobacteria abundance in the cyanobacteria dominated group maintained high levels with increasing hydrological dynamics. Our results demonstrated that environmental factors played inconsistently significant roles in different phytoplankton groups, and reducing nutrients could decrease adverse effects of warming and water project constructions. Our models can also be applied to forecast phytoplankton shifting and cyanobacteria abundance in the management of regulated shallow lakes.
机译:浮游植物社区可能受到气候,气象,水文,营养和放牧等多种环境因素的影响。这些环境因素的复杂互动效果以及浮游植物社区的复原力进一步使浮游植物社区的动态挑战的预测。在这项研究中,我们分析了多种环境因素及其相对重视预测中国中部两次监管浅湖中的浮游植物转移和蓝细菌丰富。我们的结果表明,研究领域的浮游植物群落主要分为1.Cryptophyta主导组,2.生物多样化的组和3. Cyanobacteria主导组。多项逻辑回归模型表明Cryptophyta主导组对温度敏感,而其他基团对温度和营养素敏感。温度和营养素的互动效果在Cyanobacteria主导基团中是协同的,而在其他组中它们是拮抗的或未杀伤的。负二项式回归模型建议高总磷和低总氮,但不温度负责高肌菌丰度。条件绘制指出的营养物质在低风速和湖泊体积波动下更显着地影响蓝杆菌的丰度,并且Cyanobacteria中的蓝细菌丰度随着水文动力学的增加而保持高水平。我们的研究结果表明,环境因素在不同的植物组织中发挥了不一致的重要作用,减少营养物质可以降低加热和水项目结构的不利影响。我们的模型也可用于预测浮游植物换档和Cyanobacteria丰富在监管浅湖泊中。

著录项

  • 来源
    《Environmental Pollution》 |2021年第10期|117555.1-117555.11|共11页
  • 作者单位

    Wuhan Univ State Key Lab Water Resources & Hydropower Engn S Wuhan 430072 Peoples R China|Wuhan Univ Hubei Key Lab Water Syst Sci Sponge City Construc Wuhan 430072 Peoples R China|Hydrol & Water Resources Survey Bur Wuhan City Wuhan 430074 Peoples R China;

    Wuhan Univ State Key Lab Water Resources & Hydropower Engn S Wuhan 430072 Peoples R China|Wuhan Univ Hubei Key Lab Water Syst Sci Sponge City Construc Wuhan 430072 Peoples R China;

    Hydrol & Water Resources Survey Bur Wuhan City Wuhan 430074 Peoples R China;

    Changjiang Water Resources Commiss Changjiang River Sci Res Inst Wuhan 430010 Peoples R China;

    Hydrol & Water Resources Survey Bur Wuhan City Wuhan 430074 Peoples R China;

    Sophia Univ Grad Sch Global Environm Studies Tokyo 1028554 Japan;

    Wuhan Univ State Key Lab Water Resources & Hydropower Engn S Wuhan 430072 Peoples R China|Wuhan Univ Hubei Key Lab Water Syst Sci Sponge City Construc Wuhan 430072 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Community prediction; Cyanobacteria blooms; Environmental drivers; Multinomial logistic regression; Negative binomial regression;

    机译:社区预测;蓝藻绽放;环境司机;多项式逻辑回归;负二项式回归;

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