Science & Technology
; Life Sciences & Biomedicine
类目[WOS]:
Limnology
研究领域[WOS]:
Marine & Freshwater Biology
英文摘要:
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. (C) 2015 Elsevier GmbH. All rights reserved.
关键词[WOS]:
MULTIVARIATE REGRESSION TREES
; YANGTZE-RIVER BASIN
; FRESH-WATER FISH
; DISTRIBUTION MODELS
; ENVIRONMENTAL REQUIREMENTS
; SHALLOW LAKES
; SALMONID FISH
; SAMPLE-SIZE
; PATTERNS
; TEMPERATURE
语种:
英语
项目资助者:
"Special Fund for Agro-scientific Research in the Public Interest" of China(200903048
; National Natural Science Foundation of China(30830025
; 20130305)
; 30900182)
