基于最大熵模型分析小麦黄花叶病在黄淮海地区的适生性

Habitat Suitability for Wheat Yellow Mosaic Disease in Huang-Huai-Hai Region Based on the Maximum Entropy Model

科学预测小麦黄花叶病在黄淮海地区的适生区,对控制该地区小麦黄花叶病扩展蔓延、保障小麦生产具有重要意义。采用最大熵(MaxEnt)模型,基于小麦黄花叶病的分布和环境因子数据,对该病害适生区进行预测,并分析生态因子的贡献率与ROC曲线,探索影响小麦黄花叶病的主要生态因子。结果表明:ROC曲线下面积的AUC为0.955,模型可靠,其中最干月降水量、最暖月最高温、海拔、黏土、最湿月降水量对该病害的分布具有重要影响;适生区主要分布在已发生地区(威海、烟台、青岛、潍坊、淄博、济南、泰安、日照、临沂、济宁、枣庄、平顶山、驻马店、周口、开封和阜阳)和预测地区(莱芜、菏泽、信阳、商丘、淮南、淮北、宿州、徐州、宿迁连云港以及蚌埠)。预测适生面积较广,建议增补小麦黄花叶病为全国农业植物检疫性有害生物,在高适生区设立疫情监测点,根据主要环境因子,加强田间管理。

The scientific prediction of the suitable growing area of wheat yellow mosaic disease in Huang-Huai-Hai area is of great significance to control the spread of the disease and ensure wheat production. Based on the data of the distribution of wheat yellow mosaic disease and the environmental factors, the MaxEnt model was used to predict the suitable area of this disease, and the contribution rate and ROC curve of ecological factors were analyzed to explore the main ecological factors affecting wheat yellow mosaic disease. The results showed that AUC of the area under the ROC curve was 0.955, and the model was reliable. The precipitation of the driest month and the warmest month, the highest temperature, altitude, clay and the wettest month had important effects on the distribution of this disease. The suitable growing areas mainly distributed in existing areas(Weihai, Yantai, Qingdao, Weifang, Zibo, Jinan, Tai’an, Rizhao, Linyi, Jining, Zaozhuang, Pingdingshan, Zhumadian, Zhoukou, Kaifeng and Fuyang) and the predicted area(Laiwu, Heze, Xinyang, Shangqiu, Huainan, Huaibei, Suzhou, Xuzhou, Suqian Lianyungang and Bengbu). The predicted proper area was wide, so it was suggested to add yellow mosaic disease of wheat as a national agricultural phytosanitary pest, and set up epidemic detection points in high-fitness areas, and strengthen field management according to main environmental factors.