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基于MaxEnt模型的森林天幕毛虫适生区预测OA

Suitable region prediction of Malacosoma disstria based on MaxEnt model

中文摘要英文摘要

为筛选影响森林天幕毛虫Malacosoma disstria适生区的主导环境因子,预测其在全球及我国潜在适生区分布格局,评估未来气候变化对其在我国适生区范围的影响,基于其全球分布数据,结合当前在不同胁迫情景下的未来环境因子数据,利用R软件的Kuenm包优化MaxEnt模型参数,分析模型运行结果.结果表明:调控倍频设置为0.5,特征组合为线性特征、二次型特征、阈值特征和片段化特征是模型最优参数组合;模型评价指标显示,受试者工作特征曲线下面积为0.947,真实技能统计值为0.834,预测结果具有较高的可靠性;影响适生区的主导环境因子为最干月的降水量(bio14)、最湿季度降水量(bio16)和最暖月的最高温度(bio5);在当前气候条件下,该害虫在我国的适生区主要分布在东北、华中、华东、华南和西南地区,其中吉林、辽宁、河南、山东、安徽、江西、福建和云南等省份的中、高适生区面积占我国森林总面积的35.06%;未来气候情景下,该害虫在我国的适生区范围呈现相对稳定态势.

To predict the distribution pattern of Malacosoma disstria suitable region and evaluate the impact of future climate change on its suitable region range in China,global distribution data combined with current and future environmental factors under different climate scenarios were utilized.The parameters of the MaxEnt model were optimized using the Kuenm package in R software,followed by analysis of the optimized model outputs.The results indicated that the optimal model parameters were determined as regularization multiplier(Rm)of 0.5,with feature combinations(Fc)including linear(L),quadratic(Q),threshold(T),and hinge(H)features.Model evaluation metrics revealed that the area under the curve(AUC)of receiver operating characteristic curve(ROC)was 0.947 and the true skill statistic(TSS)was 0.834,indicating that the model predictions were highly reliable.The primary environmental factors influencing the suitable habitat were identified as precipitation in the driest month(bio14),precipitation in the wettest quarter(bio16),and maximum temperature in the warmest month(bio5).Under current climatic conditions,the pest's suitable regions in China were concentrated in the northeastern,central,eastern,southern,and southwestern regions.Moderately suitable region and high suitability region in provinces including Jilin,Liaoning,Henan,Shandong,Anhui,Jiangxi,Fujian,and Yunnan accounted for 35.06%of Chinese total forest coverage.Under future climate scenarios,the distribution range of M.disstria suitable region in China is expected to remain relatively stable.

何旭诺;颜素娟;林莉;李盼畔;武目涛;赵菊鹏

广州海关技术中心,广东 广州 510623从化海关综合技术服务中心,广东 广州 510999广州海关技术中心,广东 广州 510623广州海关技术中心,广东 广州 510623广州海关技术中心,广东 广州 510623广州海关技术中心,广东 广州 510623

农业科技

森林天幕毛虫最大熵模型适生区有害生物风险分析定殖风险

Malacosoma disstriaMaxEnt modelsuitable regionpest risk analysiscolonization risk

《中国森林病虫》 2026 (2)

15-24,10

广州市重点研发计划项目"口岸危险性有害物快速鉴定及入侵机制研究"(2023B04J0154)广州海关科研计划项目"甲虫类'异虫'风险评估及重要的多虫态精准识别综合应用研究"(2023GZCK02)

10.19688/j.cnki.issn1671-0886.20260008

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