Predicting fish species richness and assemblages with climatic,geographic and morphometric factors: A broad-scale study in Chinese lakes |
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| Institution: | 1. State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China;2. Université de Toulouse, UMR 5174 EDB, CNRS – Université de Paul Sabatier, 118 Route de Narbonne, 31062 Toulouse Cedex 09, France;3. Aquaculture and Fisheries Center, University of Arkansas at Pine Bluff, Pine Bluff, AR 71602, USA |
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| Abstract: | The present study was designed to investigate the relative importance of climatic (temperature and precipitation), geographic (altitude) and morphometric (lake area) factors in predicting fish species richness and assemblages in Chinese lakes at a large spatial scale. Two recursive partitioning tree-based approaches: Classification and Regression Trees (CARTs) and Multivariate Regression Trees (MRTs) were employed to generate predictive models respectively. Six fish assemblages were thus defined from the MRT model. The results indicated that lake altitude was the main determinant for predicting fish assemblages in Chinese lakes (30.43%), followed by precipitation of the driest month (10.47%), temperature annual range (3.62%) and annual mean temperature (3.15%). Validated CART model implied that precipitation of driest month, maximum temperature of warmest month and lake area were the main predictors in determining fish species richness patterns. Overall, our results indicated that the altitudinal extent and range of climatic variation was sufficient to overshadow the area effect in predicting fish species richness and assemblages in Chinese lakes. At the macroecological scale, the effect of temperature and precipitation on fish richness and assemblages also suggests future changes in fish diversity as a consequence of climate change. |
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| Keywords: | China Environmental factors Fish assemblages Lakes Macroecological patterns Prediction Species richness |
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