基于MaxEnt模型的大豆蚜全球潜在地理分布分析

【目的】为预测和分析大豆蚜Aphis glycines的全球潜在地理分布，研究大豆蚜分布与环境变量之间的联系。【方法】利用最大熵法生态位模型(maximum entropy niche-based modeling, MaxEnt)和地理信息系统软件ArcGIS，根据收集的大豆蚜已知分布点和环境变量，预测大豆蚜的全球潜在地理分布区，推测环境变量对大豆蚜分布的影响。【结果】结果表明，大豆蚜适生区主要分布在低海拔地区，高 度适生区集中在25°~50°N的中国、日本、韩国、朝鲜、加拿大、美国、意大利和格鲁吉亚。决定大豆蚜分布地点的关键环境变量为最暖季度降水量、最暖季度平均温度、最湿季度平均温度、最干月降水量、月平均昼夜温差和温度季节性变化标准差。【结论】大豆蚜潜在地理分布区域广泛，应在各国大豆农产品贸易时做好检验检疫工作，以防止大豆蚜的扩散。

Potential geographical distribution of the soybean aphid,Aphis glycines(Hemiptera:Aphididae), in the world based on MaxEnt model

【Aim】 The objective of this study is to predict and analyze the potentialgeographical distribution of the soybean aphid, Aphis glycines, in the world, and to studythe relationship between its potential geographical distribution and environmentalvariables. 【Methods】 Maximum entropy niche-based modeling (MaxEnt) was combined with thegeographic information system ArcGIS to predict the potential geographical distribution ofA. glycines in the world and to infer the influence of environmental variables on its distribution based on the distribution records of A. glycines and a set of environmentalvariables. 【Results】 The results showed that the suitable distribution areas of A.glycines are mainly in the low altitude areas, and the high suitable distribution areas areChina, Japan, South Korea, North Korea, Canada, the United States, Italy, and Georgia at 25°-50°N. The dominant environmental variables affecting the potential geographicaldistribution of A. glycines are the precipitation of warmest quarter, mean temperature ofwarmest quarter, mean temperature of wettest quarter, precipitation of driest month, meandiurnal range ［mean of monthly (max temp-min temp)］, and temperature seasonality(stardard deviation×100). 【Conclusion】 The potential geographical distribution of A.glycines is wide. To prevent A. glycines from further spreading, inspection and quarantineshould be done properly in the global trade of soybean agricultural products.