中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Predicting fish species richness and assemblages with climatic, geographic and morphometric factors: A broad-scale study in Chinese lakes

文献类型:期刊论文

作者Guo, Chuanbo1,2; Lek, Sovan1,2; Ye, Shaowen1; Li, Wei1; Liu, Jiashou1; Chen, Yushun1,3; Li, Zhongjie1
刊名LIMNOLOGICA
出版日期2015-09-01
卷号54页码:66-74
关键词China Environmental factors Fish assemblages Lakes Macroecological patterns Prediction Species richness
ISSN号0075-9511
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.
WOS标题词Science & Technology ; Life Sciences & Biomedicine
类目[WOS]Limnology
研究领域[WOS]Marine & Freshwater Biology
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
收录类别SCI
语种英语
WOS记录号WOS:000366078300008
源URL[http://ir.ihb.ac.cn/handle/342005/27452]  
专题水生生物研究所_淡水生态学研究中心_期刊论文
作者单位1.Chinese Acad Sci, Inst Hydrobiol, State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Peoples R China
2.Univ Toulouse 3, Univ Toulouse, CNRS, EDB UMR 5174, F-31062 Toulouse 09, France
3.Univ Arkansas, Aquaculture & Fisheries Ctr, Pine Bluff, AR 71602 USA
推荐引用方式
GB/T 7714
Guo, Chuanbo,Lek, Sovan,Ye, Shaowen,et al. Predicting fish species richness and assemblages with climatic, geographic and morphometric factors: A broad-scale study in Chinese lakes[J]. LIMNOLOGICA,2015,54:66-74.
APA Guo, Chuanbo.,Lek, Sovan.,Ye, Shaowen.,Li, Wei.,Liu, Jiashou.,...&Li, Zhongjie.(2015).Predicting fish species richness and assemblages with climatic, geographic and morphometric factors: A broad-scale study in Chinese lakes.LIMNOLOGICA,54,66-74.
MLA Guo, Chuanbo,et al."Predicting fish species richness and assemblages with climatic, geographic and morphometric factors: A broad-scale study in Chinese lakes".LIMNOLOGICA 54(2015):66-74.

入库方式: OAI收割

来源:水生生物研究所

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