基于生态位因子模型的湖北省松材线虫病风险评估

  目的   当前湖北省松材线虫Bursaphelenchus xylophilus疫情形势严峻。通过研究湖北省松材线虫病的入侵风险，分析松材线虫病在湖北省的危害程度，为当前疫情的防治工作提供建议和参考。   方法   结合“3S”技术，应用生态位因子模型(ENFA)，选取影响松材线虫定殖和传播的4类影响因素(气候、植被、地形、人类活动)，对松材线虫病在湖北的入侵风险进行了预测和评价。   结果   湖北省松材线虫病高风险区面积38 884.62 km2，占湖北省总面积的20.92%，高风险区主要集中于海拔较低、人类活动频繁的中部和东部地区，中风险区面积66 501.84 km2，占总面积的35.77%，低风险区面积80 513.54 km2，占总面积的43.31%，中低风险地区主要分布在林地稀少的江汉平原和西部的高海拔山地。松材线虫偏好分布在温度较高，降水丰富，海拔较低，离人类居住点较近且人类活动频繁的针叶林地区。通过交叉验证(cross-validation)对模型的预测进行检验，得到P/E曲线，曲线呈单调递增且Boyce指数很高，说明模型精度很高。   结论   ENFA模型能很好模拟松材线虫病的风险区域，模型结果可为湖北省各县市的松材线虫病防治决策提供参考。图2表3参25

Risk assessment of Bursaphelenchus xylophilus in Hubei Province based on ecological niche factor analysis model

  Objective   The epidemic situation of Bursaphelenchus xylophilus in Hubei Province is severe. The objective of this study is to investigate the invasion risk and the damage degree of B. xylophilus disease in Hubei Province, so as to provide suggestions and reference for current epidemic prevention and control.   Method   Combined with 3S technology, the ecological niche factor analysis (ENFA) model was used, and 4 factors affecting the colonization and spread of B. xylophilus (climate, vegetation, terrain, human disturbance) were selected to predict and evaluate the invasion risk of the disease.   Result   The high risk area of B. xylophilus disease in Hubei Province covered an area of 38 884.62 km2, accounting for 20.92% of the total area of Hubei Province, mainly concentrated in the central and eastern regions with low altitude and frequent human activities. The moderate risk area was 66 501.84 km2, representing 35.77% of the total area. The low risk area was 80 513.54 km2, representing 43.31% of the total area. These areas were mainly distributed in Jianghan Plain and high-altitude mountains in the west. B. xylophilus preferred to be distributed in coniferous forest areas with high temperature, abundant precipitation, low altitude, close to human settlements and frequent human activities. Through cross-validation to test the prediction of the model, the P/E curve was obtained. The curve was monotonically increasing and the Boyce index was very high, indicating that the model had high accuracy.   Conclusion   The ENFA model can simulate the risk areas of B. xylophilus. The results of the model can provide reference for the prevention and control of B. xylophilus in Hubei Province. Ch, 2 fig. 3 tab. 25 ref.]