State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China.
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China.
Sci Total Environ. 2021 Jan 20;753:142158. doi: 10.1016/j.scitotenv.2020.142158. Epub 2020 Sep 6.
Increasing threats to freshwater biodiversity from environmental changes and human activities highlight the need to understand the linkages between biological communities and their environment. Species richness has dominated our view of biodiversity patterns for over a century, but it is increasingly recognized that a trait-based, causal view of biodiversity may be more meaningful than species richness or taxonomic composition. This rationale has led to the exploration of functional diversity (FD) indices to quantify variation in traits that mediate species' contributions to ecosystem processes. In the present study, we quantified FD of fish communities in two large shallow lakes in China with different disturbances level using long-term monitoring data sets. Random-Forests regression was applied to examine how changes in FD were related to natural and human-related environmental variables. Fish stocking, water quality, climate, and hydrological changes were identified as the most important predictors of FD long-term trends. However, the major drivers of FD differed between two lakes, i.e., human activities explaining a greater proportion of FD variance in Lake Taihu, whereas physicochemical environmental factors prominently explained FD variance in Lake Hulun. Moreover, FD indices appeared more sensitive than species richness to multiple disturbances, suggesting that functional traits can be used to detect ecosystem alterations. This study offers insight into how FD can improve our understanding of the associations between fish communities and environmental changes of relevance also for lake and fisheries management.
由于环境变化和人类活动对淡水生物多样性造成的威胁日益增加，我们需要了解生物群落与其环境之间的联系。一个多世纪以来，物种丰富度一直主导着我们对生物多样性模式的看法，但人们越来越认识到，基于特征的、因果关系的生物多样性观点可能比物种丰富度或分类组成更有意义。这一理念促使人们探索功能多样性 (FD) 指数，以量化介导物种对生态系统过程贡献的特征变化。在本研究中，我们使用长期监测数据集，量化了中国两个具有不同干扰水平的大型浅水湖泊鱼类群落的 FD。随机森林回归被应用于检验 FD 的变化如何与自然和人为相关的环境变量相关。鱼类放养、水质、气候和水文变化被确定为 FD 长期趋势的最重要预测因子。然而，FD 的主要驱动因素在两个湖泊之间存在差异，即人类活动在太湖中解释了 FD 方差的更大比例，而理化环境因素在呼伦湖中显著解释了 FD 方差。此外，FD 指数比物种丰富度对多种干扰更敏感，这表明功能特征可用于检测生态系统的变化。本研究深入了解了 FD 如何能够提高我们对鱼类群落与相关环境变化之间关系的理解，这对于湖泊和渔业管理也具有重要意义。
