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Global potential distribution of Oryctes rhinoceros, as predicted by Boosted Regression Tree model

文献类型：期刊论文

作者Hao, Mengmeng1,3; Aidoo, Owusu Fordjour2; Qian, Yushu1,3; Wang, Di1,3; Ding, Fangyu1,3; Ma, Tian1,3; Tettey, Elizabeth4; Ninsin, Kodwo Dadzie2; Osabutey, Angelina Fathia5; Borgemeister, Christian6
刊名GLOBAL ECOLOGY AND CONSERVATION
出版日期2022-09-01
卷号37页码:11
关键词Biological invasion Invasive species Management strategies Modeling Pest
DOI10.1016/j.gecco.2022.e02175
通讯作者Aidoo, Owusu Fordjour(ofaidoo@uesd.edu.gh) ; Wang, Di(wangd.19b@igsnrr.ac.cn) ; Ding, Fangyu(dingfy@igsnrr.ac.cn)
英文摘要Climate change is expected to have a significant influence on species range expansion, habitat shifts, and risk of biological invasion due to changes in survival rates, and rapid reproduction. This will tend to affect their geographical distribution and dispersal patterns, thereby threatening agriculture production and food security. Therefore, it is essential to understand the impact of climate change on the range shifts of an invasive species like the Asiatic rhinoceros beetle, Oryctes rhinoceros Linnaeus (Coleoptera: Dynastinae: Scarabaeidae), to inform policy formulation and preventive measures. To achieve this, we used environmental variables and occurrence records of O. rhinoceros to predict the current and future potential distribution of the pest under two representative concentration pathways (RCPs 4.5 and 8.5) for three time periods (2030, 2050, and 2080). We employed Boosted Regression Tree (BRT) and ArcGIS to create risk maps for the pest. The BRT model predicts an expansion of O. rhinoceros outside the current known distribution. The environmental variables which contributed the most to the geographical distribution of the pest were minimum temperature of coldest month (26.81 %), followed by precipitation of wettest month (20.61 %), temperature annual range (11.34 %), mean diurnal range (11.33 %), and elevation (4.49 %). Under the different climate change scenarios, O. rhinoceros will continue to threaten the economically important host plants until 2080. As a result, there will be a need for effective strategies to prevent its spread. Our predictions are reliable and have the potential to estimate the global distribution of the pest, as well as provide suggestions for prompt of O. rhinoceros prevention and management.
WOS关键词SPECIES DISTRIBUTION MODELS ; COCONUT RHINOCEROS ; CLIMATE-CHANGE ; POPULATION-DYNAMICS ; BIOLOGICAL-CONTROL ; INSECT PEST ; BEETLE ; EFFICACY ; RESOLUTION ; PACIFIC
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences[XDA20010203] ; National Natural Science Foundation of China[42001238]
WOS研究方向Biodiversity & Conservation ; Environmental Sciences & Ecology
语种英语
出版者ELSEVIER
WOS记录号WOS:000818412700001
资助机构Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/180726]  
专题中国科学院地理科学与资源研究所
通讯作者Aidoo, Owusu Fordjour; Wang, Di; Ding, Fangyu
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
2.Univ Environm & Sustainable Dev, Sch Nat & Environm Sci, Dept Biol Phys & Math Sci, Somanya, Ghana
3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
4.Oil Palm Res Inst, Council Sci & Ind Res CSIR, Coconut Res Programme, POB 245, Sekondi, Ghana
5.Hallym Univ, Dept Biomed Gerontol, Grad Sch, Chunchon, Gangwon, South Korea
6.Univ Bonn, Ctr Dev Res ZEF, Genscherallee 3, D-53113 Bonn, Germany
推荐引用方式
GB/T 7714		 Hao, Mengmeng,Aidoo, Owusu Fordjour,Qian, Yushu,et al. Global potential distribution of Oryctes rhinoceros, as predicted by Boosted Regression Tree model[J]. GLOBAL ECOLOGY AND CONSERVATION,2022,37:11.
APA Hao, Mengmeng.,Aidoo, Owusu Fordjour.,Qian, Yushu.,Wang, Di.,Ding, Fangyu.,...&Borgemeister, Christian.(2022).Global potential distribution of Oryctes rhinoceros, as predicted by Boosted Regression Tree model.GLOBAL ECOLOGY AND CONSERVATION,37,11.
MLA Hao, Mengmeng,et al."Global potential distribution of Oryctes rhinoceros, as predicted by Boosted Regression Tree model".GLOBAL ECOLOGY AND CONSERVATION 37(2022):11.

入库方式： OAI收割

来源：地理科学与资源研究所

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