Global potential distribution of Oryctes rhinoceros, as predicted by Boosted Regression Tree model
文献类型:期刊论文
作者 | Hao, Mengmeng3,5; Aidoo, Owusu Fordjour4; Qian, Yushu3,5; Wang, Di3,5; Ding, Fangyu3,5; Ma, Tian3,5; Tettey, Elizabeth1; Ninsin, Kodwo Dadzie4; Osabutey, Angelina Fathia6; Borgemeister, Christian2 |
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 |
DOI | 10.1016/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.Oil Palm Res Inst, Council Sci & Ind Res CSIR, Coconut Res Programme, POB 245, Sekondi, Ghana 2.Univ Bonn, Ctr Dev Res ZEF, Genscherallee 3, D-53113 Bonn, Germany 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 4.Univ Environm & Sustainable Dev, Sch Nat & Environm Sci, Dept Biol Phys & Math Sci, Somanya, Ghana 5.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 6.Hallym Univ, Dept Biomed Gerontol, Grad Sch, Chunchon, Gangwon, South Korea |
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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