基于MAXENT的番茄潜叶蛾在贵州省的适生区分布预测  

The Prediction of Potential Geographic Distributions for Tuta absoluta Meyrick in Guizhou Province Based on MAXENT Model

作　　者：金剑雪[1] 张晓明[2] 叶照春[1] 王宇 邵昌余 张桂芬[4] JIN Jianxue;ZHANG Xiaoming;YE Zhaochun;WANG Yu;SHAO Changyu;ZHANG Guifen(The Institute of Plant Protection,Guizhou Academy of Agricultural Sciences,Guiyang 550006,China;College of Plant Protection,Yunnan Agricultural University/National Key Laboratory for Conservation and Utilization of Biological Resources in Yunnan,Kunming 650201,China;Guizhou Plant Protection Station,Guiyang 550001,China;State Key Laboratory for Biology of Plant Diseases and Insect Pests/Key Laboratory of Invasive Alien Species Control of MARA/Key Laboratory of Integrated Pest Management of Crop of MARA/Center for Management of Invasive Alien Species of MARA/Institute of Plant Protection,Chinese Academy of Agricultural Sciences,Beijing 100193,China)

机构地区：[1]贵州省农业科学院植物保护研究所,贵阳550006 [2]云南农业大学植物保护学院/云南生物资源保护与利用国家重点实验室,昆明650201 [3]贵州省植保植检站,贵阳550001 [4]中国农业科学院植物保护研究所/植物病虫害综合治理全国重点实验室/农业农村部入侵生物防控重点实验室/农业农村部作物有害生物综合治理重点实验室/农业农村部外来入侵生物预防与控制研究中心,北京100193

出　　处：《中国生物防治学报》2024年第4期750-759,共10页Chinese Journal of Biological Control

基　　金：国家重点研发计划(2021YFD1400200);贵州省科研机构创新能力建设专项资金(黔科合服企-2023-011)。

摘　　要：为研究番茄潜叶蛾在贵州省的适生区分布及未来扩张/收缩趋势,明确其在我省的潜在危害及威胁,利用MaxEnt生态位模型结合ArcGIS软件,基于331个分布点地理信息、23组生物气候变量及未来4种共享社会经济途径下2021—2100年的生物环境变量对番茄潜叶蛾在我省的适生区分布及未来模式下发生趋势进行预测分析。结果表明,MaxEnt预测模型AUC值为0.958,说明模型对番茄潜叶蛾的适生区预测结果较为精准。通过刀切法筛选出11月的降水量(p11)、最冷月最低温(bio6)、年平均温(bio1)、海拔(elev)、年温变化范围(bio7)等5个因子是影响番茄潜叶蛾潜在分布的主要限制环境变量。经预测,在我省的适生区面积约为15.967万km^(2),占全省面积的99.99%,高适生区主要集中在贵阳市、安顺市、黔西南州和六盘水市大部分地区、毕节市东部地区、遵义市西北部与黔南州大部地区,面积约为8.94万km^(2),占全省面积的55.96%;中适生区主要集中在黔东南州、铜仁市、毕节西部、遵义市东南部、黔南州南部等,面积为6.47万km^(2),占比为40.54%,贵州省近99.99%的区域均为番茄潜叶蛾的适生区。从未来模式的发展趋势可知,番茄潜叶蛾在我国的适生区范围总体呈现先缩减后扩张的趋势。至2081—2100年,适生区面积变化范围在-32.74万km^(2)~8.54万km^(2)间浮动;在我省的适生区总面积没有变化,其中高适生区整体往我省西部移动;我省东部、南部、北部等部分区域将由高适生区转变为中适生区或低适生区。因此,我省将成为番茄潜叶蛾在我国扩张蔓延最重要的中转站,其西部地区也将成为高风险地区,应进一步提升对该虫的监测预警意识,积极开展该虫的预测预报及防控力度,采取积极措施防止该虫进一步扩张蔓延。In order to study the suitable distribution and the future expansion/contraction trend of Tuta absoluta and clarify the potential hazards and threats in Guizhou province,in this article,MaxEnt model combined with ArcGIS 10.8 software were used to predict the occurrence distribution of T.absoluta from now to the future based on the geographical information of 331 distribution points,23 groups of bioclimatic variables and the biological environment variables from 2021 to 2100 under four SSP pathways.The results showed that the AUC value of the MaxEnt model was 0.958 and indicated that the model was more accurate in predicting the suitable area of T.absoluta.Through doing jackknife,november precipitation(p11),the minimum temperature of the coldest month(bio6),annual mean temperature(bio1),elevation(elev)and temperature annual range(bio7)were selected as the main limiting environmental variables affecting the potential distribution of T.absoluta.As predicted,the suitable area was about 159,670 km^(2) in Guizhou province,accounting for 99.99%of the provincial area.The high risk area mainly included Guiyang,Anshun,Qianxinan prefecture and most areas of Liupanshui,Eastern Bijie,Northwestern Zunyi and most areas of Qiannan prefecture,and the area was approximately 89,400 km^(2),accounting for 55.96%of the provincial area.The moderate risk areas were mainly concentrated in Qiandongnan prefecture,Tongren,Western Bijie,Southeastern Zunyi,Southern Qiannan Prefecture,with an area of 64,700 km^(2) and accounting for 40.54%.In general,nearly 99.99%regions in Guizhou province were suitable for T.absoluta.The overall distribution range of T.absoluta shows a trend of first reduction and then expansion in the future development trend in China.From 2081 to 2100,the chang value of the suitable area would vary from-327,400 km^(2) to 85,400 km^(2).The total suitable area in our province would not change.The high risk area would tend to move westward,and the parts regions of Eastern,Southern and Northern parts of our province would be t

关 键 词：番茄潜叶蛾 适生区预测 最大熵模型 

分 类 号：S476[农业科学—农业昆虫与害虫防治]