Interactive effects of aridity and local environmental factors on the functional trait composition and diversity of macroinvertebrate assemblages in dryland rivers

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作者
Key Laboratory of Freshwater Animal Breeding, Ministry of Agriculture and Rural Affair, Engineering Research Center of Green Development for Conventional Aquatic Biological Industry in the Yangtze River Eco-nomic Belt, Ministry of Education, College of Fisheries, Huazhong Agricultural University, Wuhan [1 ]
430070, China
不详 [2 ]
FI-90014, Finland
不详 [3 ]
510632, China
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基金
中国国家自然科学基金;
关键词
Abiotic; -; Biotic;
D O I
10.1016/j.scitotenv.2024.176671
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学科分类号
摘要
Drought and local habitat alteration are major environmental stressors shaping the aquatic biota in dryland rivers. However, the combined effects of these factors on aquatic biodiversity remain poorly understood. We collected macroinvertebrate data from Central Asian dryland rivers in Xinjiang, China, from 2012 to 2022, to investigate the individual and interactive effects of drought (as indicated by increasing values of Aridity, AI) and local habitat conditions (fine sediments, velocity and pH) on aquatic macroinvertebrate functional trait composition and diversity. We found that interactions of the selected environmental stressors exhibited more frequent additive than synergistic or antagonistic effects, leading to shifts in macroinvertebrate functional trait composition and diversity accordingly. Interaction of AI and fine sediments showed more pronounced synergistic effects (positive or negative) compared to others and had positive influences on traits like small body size, ovoviviparity, etc. Functional diversity metrics responded differently to stressor interactions, with FRic and FDis being negatively affected, whereas FEve was positively correlated to stressor interaction, suggesting the complementary roles of functional diversity metrics to diagnose impacts of stressor interactions. Overall, our study provides new insights into macroinvertebrate assemblage-stressor relationships in dryland rivers and can help better assess, predict and manage aquatic biodiversity in these rivers under ongoing environmental change. © 2024
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