引用本文: | 万凌琳,陈芷凡,郭佳,佟立辉,任丽娟,韩博平,吴庆龙.生物共现网络原理及其在淡水生态系统评估中的应用.湖泊科学,2022,34(6):1765-1787. DOI:10.18307/2022.0601 |
| Wan Linglin,Chen Zhifan,Guo Jia,Tong Lihui,Ren Lijuan,Han Boping,Wu Qinglong.Principle and application of co-occurrence networks for freshwater ecosystem assessment. J. Lake Sci.2022,34(6):1765-1787. DOI:10.18307/2022.0601 |
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生物共现网络原理及其在淡水生态系统评估中的应用 |
万凌琳1, 陈芷凡1, 郭佳1, 佟立辉2, 任丽娟1, 韩博平1, 吴庆龙3,4
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1.暨南大学生命科学技术学院生态学系, 广州 510632;2.广东粤港供水有限公司, 深圳 518021;3.中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室, 南京 210008;4.中国科学院大学中丹学院, 北京 101408
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摘要: |
快速有效的生物监测指标对于评估、保护、管理和恢复淡水生态系统至关重要.传统评估方法主要利用指示生物或类群的出现率和多度信息,但是忽略了水体环境中“生物”与“生物”,以及“生物”与“环境”间相互作用的复杂关系,而这些相互作用对淡水生态系统的生物多样性、生态系统服务功能以及生态系统对环境变化的响应有着深刻影响.生物共现网络是群落水平物种互作的结构模型,通过物种在群落出现及丰度数据,描述了物种间潜在的相互作用、群落的基本结构,反映群落在生态系统的功能和结构特性.生物共现网络展示了淡水生态系统中所有生物体之间潜在的相互作用关系,其拓扑结构特性可与特定的生态系统状态相关联,能够揭示生态系统的组织规律及其功能,可作为早期的、灵敏的生物指标,是一种很有应用前景的评估淡水生态系统状态和稳定性的工具. |
关键词: 共现性网络 生物群落 淡水生态系统 生态监测与评估 |
DOI:10.18307/2022.0601 |
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基金项目:国家自然科学基金项目(31870445,U2040201,32171517)、湖泊与环境国家重点实验室开放基金项目(2018SKL007)和东深供水水生态评价咨询服务项目(40116086001)联合资助. |
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Principle and application of co-occurrence networks for freshwater ecosystem assessment |
Wan Linglin1, Chen Zhifan1, Guo Jia1, Tong Lihui2, Ren Lijuan1, Han Boping1, Wu Qinglong3,4
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1.Department of Ecology and Institute of Hydrobiology, Jinan University, Guangzhou 510632, P. R. China;2.Guangdong Water Supply Company for Hongkong and Macao, Shenzhen 518021, P. R. China;3.State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China;4.Sino Danish Center for Science and Education, University of Chinese Academy of Sciences, Beijing 101408, P. R. China
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Abstract: |
Rapid, robust and cost-effective biological monitoring indicators are crucial for the assessment, protection, management, and restoration of freshwater ecosystems. Traditional biomonitoring has focused on the presence/absence or abundance of taxa of biological indicators, ignoring the complex relationships between organisms, and interactions between organisms and environmental factors in aquatic ecosystems. These complex interactions profoundly influence biodiversity and ecosystem functioning, as well as the system's sensitivity to environmental changes. A biological co-occurrence network is a structure model of species interaction at the community level. Based on the occurrence and abundance data of species in the community, the biological co-occurrence network demonstrates the complex biological interactions between species, the basic structure of the community, as well as the function and stability of the ecosystem. Biological co-occurrence networks provide an integrated vision of all the potential relationships occurring between organisms in freshwater ecosystems. Topological metrics of biological co-occurrence networks may be associated with specific ecosystem states, reveal underlying organizational rules of an ecosystem, and can be used as an early indicator of the functional response of the ecosystem. Thus, biological co-occurrence networks provide promising tools for evaluating the state and stability of a freshwater ecosystem. |
Key words: Co-occurrence networks biological community freshwater ecosystem monitoring and assessment of ecosystem state |
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