Taihu Laboratory for Lake Ecosystem Research, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
Taihu Laboratory for Lake Ecosystem Research, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; College of Biology and Pharmaceutical Engineering, West Anhui University, Lu'an 237012, China.
J Environ Manage. 2024 Feb 14;352:120119. doi: 10.1016/j.jenvman.2024.120119. Epub 2024 Jan 19.
Eutrophication is a growing environmental concern in lake ecosystems globally, significantly impacting the structures and ecological functions of bacterioplankton communities and posing a substantial threat to the stability of lake ecosystems. However, the patterns of functional dissimilarity, network complexity, and stability within bacterioplankton communities across different trophic states, along with the underlying mechanisms through which eutrophication influences these aspects, are not well-understood. To bridge this knowledge gap, we collected 88 samples from 34 lakes spanning trophic gradients and investigated bacterioplankton communities using network analysis and multiple statistical methods. Our results reveal that eutrophication, progressing from mesotrophic to hyper-eutrophic states, reduces the putative functional dissimilarity of bacterioplankton, particularly affecting the relative proportions of functional groups such as oxygenic photoautotrophy, phototrophy, and photoautotrophy. Network complexity exhibited a unimodal pattern across increasing trophic states, peaking at mesotrophic states and then decreasing towards hyper-eutrophic conditions, while stability exhibited the opposite pattern (U-shaped), indicating a variation in response to trophic state changes. In essence, eutrophication diminishes network complexity but enhances network stability. Collectively, these findings shed light on the ecological impact of eutrophication on bacterioplankton communities and elucidate the potential mechanisms by which eutrophication drives functional dissimilarity, network complexity and stability within bacterioplankton communities. These insights carry significant implications for the ecological management of eutrophic lakes.
富营养化是全球湖泊生态系统中日益严重的环境问题,对细菌浮游生物群落的结构和生态功能产生重大影响,对湖泊生态系统的稳定性构成重大威胁。然而,不同营养状态下细菌浮游生物群落的功能差异模式、网络复杂性和稳定性,以及富营养化影响这些方面的潜在机制,尚不清楚。为了弥补这一知识空白,我们从营养梯度的 34 个湖泊中收集了 88 个样本,并使用网络分析和多种统计方法研究了细菌浮游生物群落。我们的结果表明,富营养化从中营养状态发展到超营养状态,降低了细菌浮游生物的假定功能差异,特别是影响了好氧光合作用、光合作用和自养等功能组的相对比例。网络复杂性在营养状态增加的过程中呈现出单峰模式,在中营养状态达到峰值,然后在超营养状态下降低,而稳定性则呈现相反的模式(U 形),表明对营养状态变化的反应有所不同。从本质上讲,富营养化降低了网络复杂性但增强了网络稳定性。总的来说,这些发现揭示了富营养化对细菌浮游生物群落的生态影响,并阐明了富营养化驱动细菌浮游生物群落功能差异、网络复杂性和稳定性的潜在机制。这些见解对富营养湖泊的生态管理具有重要意义。