Spatial pattern and determinants of global invasion risk of an invasive species, sharpbelly Hemiculter leucisculus (Basilesky, 1855)
文献类型： 外文期刊
作者： Dong, Xianghong 1 ; Ju, Tao 6 ; Grenouillet, Gael 3 ; Laffaille, Pascal 4 ; Lek, Sovan 3 ; Liu, Jiashou 1 ;
作者机构： 1.Chinese Acad Sci, Inst Hydrobiol, State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
3.CNRS, Lab Evolut & Diversite Biol EDB, UMR5174, IRD,UPS, 118 Route Narbonne, F-31062 Toulouse 9, France
4.Univ Toulouse, Ecolab, CNRS, INPT,UPS, F-31062 Toulouse, France
5.Inst Univ France, Paris, France
6.Chinese Acad Fishery Sci, Yangtze River Fisheries Res Inst, Minist Agr & Rural Affairs China, Key Lab Freshwater Biodivers Conservat, Wuhan 430223, Peoples R China
关键词： Aquatic invasive species; Species distribution models; Ensemble predicting; Habitat-suitability; Invasion risk; Management strategies
期刊名称：SCIENCE OF THE TOTAL ENVIRONMENT （ 影响因子：7.963； 五年影响因子：7.842 ）
ISSN： 0048-9697
年卷期： 2020 年 711 卷
页码：
收录情况： SCI
摘要： Invasive species have imposed huge negative impacts on worldwide aquatic ecosystems and are generally difficult or impossible to be eradicated once established. Consequently, it becomes particularly important to ascertain their invasion risk and its determinants since such information can help us formulate more effective preventive or management actions and direct these measures to those areas where they are truly needed so as to ease regulatory burdens. Here, we examined the global invasion risk and its determinants of sharpbelly (Hemiculter leucisculus), one freshwater fish which has a high invasive potential, by using species distribution models (SDMs) and a layer overlay method. Specifically, first an ensemble species distribution model and its basal models (developed from seven machine learning algorithms) were explored to forecast the global habitat-suitability and variables importance for this species, and then a global invasion risk map was created by combining habitat-suitability with a proxy for introduction likelihood (entailing propagule pressure and dispersal constraints) of exotic sharpbelly. The results revealed that (1) the ensemble model had the highest predictive power in forecasting sharpbelly's global habitat-suitability; (2) areas with high invasion risk by sharpbelly patchily spread over the world except Antarctica; and (3) the Human Influence Index (HII), rather than any of the bioclimatic variables, was the most important factor influencing sharpbelly' future invasion. Based on these results, the present study also attempted to propose a series of prevention and management strategies to eliminate or alleviate the adverse effects caused by this species' further expansion. (C) 2019 Elsevier B.V. All rights reserved.
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