How does fish functional diversity respond to environmental changes in two large shallow lakes?


Mao Z., Gu X., Cao Y., Luo J., Zeng Q., Chen H., ...Daha Fazla

SCIENCE OF THE TOTAL ENVIRONMENT, cilt.753, 2021 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 753
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.scitotenv.2020.142158
  • Dergi Adı: SCIENCE OF THE TOTAL ENVIRONMENT
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Analytical Abstracts, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Chemical Abstracts Core, Chimica, Communication Abstracts, Compendex, EMBASE, Environment Index, Food Science & Technology Abstracts, Geobase, Greenfile, MEDLINE, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Water quality, Fish stocking, Human activities, Functional dispersion, Random Forests regression, FRESH-WATER, SPECIES RICHNESS, INNER-MONGOLIA, BODY-SIZE, COMMUNITY, CONSERVATION, BIODIVERSITY, FRAMEWORK, ENHANCEMENT, PREDICTIONS
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

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 traitbased, 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. (C) 2020 Elsevier B.V. All rights reserved.