美国白蛾入侵江西省及其各市的综合风险分析

为实现对入侵江西省的美国白蛾Hyphantria cunea进行差异化风险等级管理与分类施策，基于原指标体系确定美国白蛾入侵江西省及各市的综合风险值，通过在原指标体系的准则层、指标层新增传入途径、扩散路径和寄主植物资源3要素，用加权系数对原指标体系的相关指标值进行校正，得到美国白蛾入侵江西省及各市的校正综合风险值，并对比校正前后美国白蛾入侵江西省及各市的综合风险值及风险等级变化。结果显示，新增传入途径、扩散路径和寄主植物资源3要素明显影响美国白蛾入侵江西省及各市的风险评估结果。利用寄主植物资源加权校正后，美国白蛾入侵江西省的综合风险从特别危险级降为高度危险级。而同时利用以上3个要素加权校正后，美国白蛾对江西省上饶、九江、宜春和南昌市的入侵风险从原有的特别危险级降为高度危险级，对抚州、鹰潭和新余市的入侵风险从原有的特别危险级降为中度危险级，对萍乡市的入侵风险从原来的高度危险级降为低度危险级，上饶市仍是江西省风险最高的市，表明改进后的方法更符合江西省的实际情况。

Comprehensive risk analysis of fall webworm Hyphantria cunea invasion in Jiangxi Province and its cities

To develop risk-level management and classification strategies for the invasion of the fall webworm Hyphantria cunea, comprehensive risk values for its invasion into Jiangxi Province and its cities were initially determined using an original index system. Subsequently, three additional elements (invasive pathway, diffusion path, and host plant resources) were incorporated into both the criteria and indicator layers of the original system. Some relevant indices were then corrected by using a weighting method. A comparison was made between the comprehensive risk values before and after adjustments, along with changes in risk evaluation rankings. The results showed that including the elements of invasive way, diffusion path, and host plant resources significantly affected the outcome of the pest risk assessment for the fall webworm in Jiangxi Province. Following the weighting and adjustment based on host plant resources, the overall risk of fall webworm invasion into Jiangxi decreased from the highest risk level to the sub-high risk level. Utilizing the above three elements together for weighted correction, the invasion risk of the fall webworm decreased from the original highest risk level to the sub-high risk level in Shangrao, Jiujiang, Yichun, and Nanchang cities. Similarly, in Fuzhou, Yingtan, and Xinyu cities, the risk level decreased from the highest to the middle, while in Pingxiang City, it decreased from the highest to the low risk level. However, Shangrao remained at the highest risk level, and it was the city with the highest risk in Jiangxi Province. This indicates that the improved method better reflects the actual situation in Jiangxi Province.