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当前位置: 首页 > 文章 > 基于Maxent生态位模型预测球果角胫象在云南的潜在地理分布 环境昆虫学报 2013,35 (1) 28-32
Position: Home > Articles > Maximum entropy niche-based modeling (Maxent) of potential geograp-hical distributions of weevil Shirahoshizo conifera Chao in Yunnan Province Journal of Environmental Entomology 2013,35 (1) 28-32

基于Maxent生态位模型预测球果角胫象在云南的潜在地理分布

作  者：
张晓峰;佟友贵;杨建东;黄忠;熊忠平
单  位：
楚雄市林业局;昆明市东川区森防站;西南林业大学林学院
关键词：
云南油杉;球果角胫象;Maxent模型;潜在分布
摘  要：
掌握球果角胫象Shirahoshizo conifera Chao在云南潜在分布区,对了解其危害和防控具有重要的意义。本文利用球果角胫象的分布点数据和环境因子数据,通过Maxent生态位模型预测其在云南的潜在分布区。结果表明:球果角胫象的潜在分布区主要集中滇中地区;在ArcGIS中进行显示与风险等级划分,按栅格数值的大小将球果角胫象的适生范围分为4级,分级标准为:高适生区、中适生区、低适生区、非适生区,经ROC曲线分析法验证,Maxent生态位模型的AUC值为0.998,表明预测获得了较好的效果。
译  名：
Maximum entropy niche-based modeling (Maxent) of potential geograp-hical distributions of weevil Shirahoshizo conifera Chao in Yunnan Province
作  者：
ZHANG Xiao-Feng1, TONG You-Gui2,YANG Jian-Dong3,HUANG Zhong3, XIONG Zhong-Ping3*(1.Foresty Bureau of Chuxiong Municipality, Chuxiong 675000, Yunnan Province,China ; 2.Forest Disease and Insect Pest Control and Quarantine Protection Station of Dongchuan,Kunming 654100, China;3.Key Laboratory of Forest Disaster Warning and Control, Faculty of Forestry, Southwest Forestry University, Kunming 650224, China)
关键词：
Keteleeria evelyniana; Shirahoshizo conifera Chao; maxent;potential distribution
摘  要：
To estimate the risk of this species and take effective measures,it's necessary to investigate the infected region and potential distribution of the weevil Shirahoshizo conifera Chao in Yunnan Province.Maxent was used to predict potential distribution of weevil Shirahoshizo conifera in Yunnan based on the S.conifera distribution points datas and environmental factors datas.The results showed that the suitable areas for S.conifera infestations were central areas of Yunnan.With the revelation in ArcGIS,the grades were made and the areas for S.conifera infestations were divided into four grades:the highly suitable areas;the moderate suitable areas;the low suitable areas and the unsuitable areas.The results were proved by ROC analytical method and the AUC value of Maxent was 0.998 which close to 1 and it meaned that the prediction was highly dependable.

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