IHB OpenIR  > 淡水生态学研究中心  > 期刊论文
Uncertainty in ensemble modelling of large-scale species distribution: Effects from species characteristics and model techniques
Guo, Chuanbo1,2; Lek, Sovan1,2; Ye, Shaowen1; Li, Wei1; Liu, Jiashou1; Li, Zhongjie1
2015-06-24
Source PublicationECOLOGICAL MODELLING
ISSN0304-3800
Volume306Pages:67-75
AbstractSpecies distribution models (SDM) have been routinely used for the purpose of species conservation and biodiversity management, especially in the context of global climate change. However, there is little knowledge about the uncertainty source on the SDM for the predictions in aquatic ecosystems, especially in the large-scale research. Therefore, we contribute to the first perspective on the uncertainties of SDMs in predicting fish species distribution in lake ecosystems. In total, 92 fish species were predicted with climatic and geographical variables, respectively, using nine widely implemented species distribution models. Generally, we focused on the potential impacts from two main kinds of uncertainty sources: species characteristics (containing species prevalence, altitude range, temperature range and precipitation range) and model technique (calibration technique and evaluation technique). Finally, our results highlight that predictions from single SDM were so variable and unreliable for all species while ensemble approaches could yield more accurate predictions; we also found that there was no significant influence on the model outcomes from the evaluation measures; we emphasized that species characteristics as species prevalence, altitude range size and precipitation range size would strongly affect the outcomes of SDMs, but temperature range size didn't show a significant influence; our findings finally verified the hypothesis that species distributed with a smaller range size could be more accurately predicted than species with large range size was plausible in aquatic ecosystems. Our research would provide promising insights into the prediction of fish species in aquatic ecosystems under the impacts of global climate change, especially for the conservation of endemic fish species in China. Moreover, our results improved the understanding of uncertainties from species characteristics and modelling techniques in species distribution model. (C) 2014 Elsevier B.V. All rights reserved.
SubtypeArticle
KeywordSpecies Distribution Model Ensemble Models Uncertainties Species Characteristic China Fish Species
DOI10.1016/j.ecolmodel.2014.08.002
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
Indexed BySCI ; ISTP
Language英语
WOS Research AreaEnvironmental Sciences & Ecology
WOS SubjectEcology
WOS IDWOS:000355708000008
WOS KeywordSTREAM FISH ASSEMBLAGES ; CLIMATE-CHANGE ; GEOGRAPHICAL-DISTRIBUTION ; REGRESSION TREES ; PRESENCE-ABSENCE ; ENVELOPE MODELS ; YANGTZE-RIVER ; SAMPLE-SIZE ; PERFORMANCE ; DIVERSITY
Citation statistics
Cited Times:20[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ihb.ac.cn/handle/342005/27112
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, ENFA,UMR EDB 5174, F-31062 Toulouse 09, France
Recommended Citation
GB/T 7714
Guo, Chuanbo,Lek, Sovan,Ye, Shaowen,et al. Uncertainty in ensemble modelling of large-scale species distribution: Effects from species characteristics and model techniques[J]. ECOLOGICAL MODELLING,2015,306:67-75.
APA Guo, Chuanbo,Lek, Sovan,Ye, Shaowen,Li, Wei,Liu, Jiashou,&Li, Zhongjie.(2015).Uncertainty in ensemble modelling of large-scale species distribution: Effects from species characteristics and model techniques.ECOLOGICAL MODELLING,306,67-75.
MLA Guo, Chuanbo,et al."Uncertainty in ensemble modelling of large-scale species distribution: Effects from species characteristics and model techniques".ECOLOGICAL MODELLING 306(2015):67-75.
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.