未来气候变化下栎树猝死病菌在中国的适生性分析

基于中国国家有害生物检疫信息平台的有关记录和文献以及WoldClim网站，获取栎树猝死病菌的地理分布数据及气候数据，并用SPSS软件和刀切法筛选主导环境变量。利用MaxEnt生态位模型和ArcGIS软件，对栎树猝死病菌现代和未来情景下在我国的潜在适生区进行预测，并计算和绘制栎树猝死病菌高风险区质心转移轨迹。通过不同年份和不同气候情况下的受试者工作特征曲线(ROC)的训练集和测试集受试者工作特征曲线下面积(AUC)值均大于0.91,说明MaxEnt模型准确并适用于预测栎树猝死病菌在我国的潜在分布，同时结合其主要寄主植物的地理分布进一步增强预测模型的可信度。预测结果表明，最冷季度降水量、最冷季度平均温度、最干季度平均温度和年均降水量是影响栎树猝死病菌分布的主要环境变量。而2030s(2021—2040年)、2050s(2041—2060年)和2070s(2061—2080年)在3种气候情景下(SSP1-2.6、SSP2-4.5、SSP5-8.5),栎树猝死病菌的潜在适生区相较于现代情景下都有所增加。此外，高风险区面积在3个年代3种情景下的面积增长率均高于45%。高风险区质心变化的预测结果表...

Prediction of the potential ecological distribution of Phytophthora ramorum in China under future climate change

Phytophthora ramorum has widely spread in North America and Europe, which exerts a significant impact on the local forest ecosystem and economy. The main host plants of P. ramorum are widely distributed in China, and the climatic conditions are also suitable for the occurrence and spread of this pathogen. It is predicted to cause irreversible damage in China if this pathogen invades. Thus, it is necessary to conduct risk prediction and analysis of the possible occurrence areas of P. ramorum in China. In this study, we analyzed the geographic distribution and related climate data of P. ramorum based on the records and documents of the China National Pest Quarantine Information Platform and the WoldClim website. The dominant environmental variables were screened by SPSS software and the jackknife test. The distribution of potentially suitable areas of P. ramorum in China in different spans of modern (1970-2000), the 2030s, 2050s, and 2070s scenarios was predicted using MaxEnt niche model and ArcGIS software. The centroid transfer trajectory of high-risk areas of P. ramorum was calculated and drawn. The results show that the area under the receiver operating characteristic curve(AUC) values in different years and climates are all greater than 0.96, while the AUC values of the Test data are greater than 0.91. Those are significantly higher than the AUC values of the random model (0.500), indicating that the MaxEnt model is accurate and suitable for predicting the potential distribution of P. ramorum in China. Meanwhile, the coldest season precipitation, the mean temperature of the coldest quarter, the mean temperature of the driest season, and the averagely annual precipitation are the main environmental variables that affect the distribution of P. ramorum in China. According to the forecast, the total areas of the potential suitable area of P. ramorum in China has increased under the three climatic scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) of the 2030s, 2050s, and 2070s. In addition, the area growth rate of high-risk areas in the three future scenarios is greater than 45%. The prediction results of the centroid change in the high-risk area of P. ramorum show that the centroid movement track of the high-risk area of P. ramorum is within the scope of Jiangxi Province, and there is a trend of moving to the north. Most areas in South China, Central China, East China, and Southwest China belong to the pathogen''s middle and high suitable areas. These results show the pathogen has the risk of invasion and spread in China, and its suitable area will be further expanded in the next 2030s, 2050s, and 2070s, which will bring irreversible ecological disaster. Therefore, the quarantine measures should be strengthened to prevent the introduction of the diseased trees and other bacteria-carrying materials and to eliminate the possibility of invasion from the origin.