IHB OpenIR  > 淡水生态学研究中心  > 期刊论文
Predicting fish species richness and assemblages with climatic, geographic and morphometric factors: A broad-scale study in Chinese lakes
Guo, Chuanbo1,2; Lek, Sovan1,2; Ye, Shaowen1; Li, Wei1; Liu, Jiashou1; Chen, Yushun1,3; Li, Zhongjie1
2015-09-01
Source PublicationLIMNOLOGICA
ISSN0075-9511
Volume54Pages:66-74
AbstractThe 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.
SubtypeArticle
KeywordChina Environmental Factors Fish Assemblages Lakes Macroecological Patterns Prediction Species Richness
DOI10.1016/j.limno.2015.08.002
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
Funding Organization"Special Fund for Agro-scientific Research in the Public Interest" of China(200903048 ; "Special Fund for Agro-scientific Research in the Public Interest" of China(200903048 ; National Natural Science Foundation of China(30830025 ; National Natural Science Foundation of China(30830025 ; 20130305) ; 20130305) ; 30900182) ; 30900182) ; "Special Fund for Agro-scientific Research in the Public Interest" of China(200903048 ; "Special Fund for Agro-scientific Research in the Public Interest" of China(200903048 ; National Natural Science Foundation of China(30830025 ; National Natural Science Foundation of China(30830025 ; 20130305) ; 20130305) ; 30900182) ; 30900182)
Indexed BySCI
Language英语
WOS Research AreaMarine & Freshwater Biology
WOS SubjectLimnology
WOS IDWOS:000366078300008
WOS KeywordMULTIVARIATE REGRESSION TREES ; YANGTZE-RIVER BASIN ; FRESH-WATER FISH ; DISTRIBUTION MODELS ; ENVIRONMENTAL REQUIREMENTS ; SHALLOW LAKES ; SALMONID FISH ; SAMPLE-SIZE ; PATTERNS ; TEMPERATURE
Funding Organization"Special Fund for Agro-scientific Research in the Public Interest" of China(200903048 ; "Special Fund for Agro-scientific Research in the Public Interest" of China(200903048 ; National Natural Science Foundation of China(30830025 ; National Natural Science Foundation of China(30830025 ; 20130305) ; 20130305) ; 30900182) ; 30900182) ; "Special Fund for Agro-scientific Research in the Public Interest" of China(200903048 ; "Special Fund for Agro-scientific Research in the Public Interest" of China(200903048 ; National Natural Science Foundation of China(30830025 ; National Natural Science Foundation of China(30830025 ; 20130305) ; 20130305) ; 30900182) ; 30900182)
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ihb.ac.cn/handle/342005/27452
Collection淡水生态学研究中心_期刊论文
Affiliation1.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
Recommended Citation
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.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Guo, Chuanbo]'s Articles
[Lek, Sovan]'s Articles
[Ye, Shaowen]'s Articles
Baidu academic
Similar articles in Baidu academic
[Guo, Chuanbo]'s Articles
[Lek, Sovan]'s Articles
[Ye, Shaowen]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Guo, Chuanbo]'s Articles
[Lek, Sovan]'s Articles
[Ye, Shaowen]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.