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题名: Uncertainty in ensemble modelling of large-scale species distribution: Effects from species characteristics and model techniques
作者: Guo, Chuanbo1, 2; Lek, Sovan1, 2; Ye, Shaowen1; Li, Wei1; Liu, Jiashou1; Li, Zhongjie1
关键词: Species distribution model ; Ensemble models ; Uncertainties ; Species characteristic ; China ; Fish species
刊名: ECOLOGICAL MODELLING
发表日期: 2015-06-24
DOI: 10.1016/j.ecolmodel.2014.08.002
卷: 306, 页:67-75
收录类别: SCI ; ISTP
文章类型: Article
WOS标题词: Science & Technology ; Life Sciences & Biomedicine
类目[WOS]: Ecology
研究领域[WOS]: Environmental Sciences & Ecology
英文摘要: Species 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.
关键词[WOS]: STREAM FISH ASSEMBLAGES ; CLIMATE-CHANGE ; GEOGRAPHICAL-DISTRIBUTION ; REGRESSION TREES ; PRESENCE-ABSENCE ; ENVELOPE MODELS ; YANGTZE-RIVER ; SAMPLE-SIZE ; PERFORMANCE ; DIVERSITY
语种: 英语
WOS记录号: WOS:000355708000008
ISSN号: 0304-3800
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.ihb.ac.cn/handle/342005/27112
Appears in Collections:淡水生态学研究中心_期刊论文

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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, ENFA,UMR EDB 5174, F-31062 Toulouse 09, France
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