文献类型：期刊文献

中文题名：基于GIS空间技术和MaxEnt模型预测川西松材线虫病入侵风险

英文题名：Prediction of invasion risk of pine wilt disease based on GIS spatial technology and MaxEnt model in western Sichuan Province of southwestern China

作者：许格希[1,2] 余荣兵[3] 杨昌旭[3] 刘怀君[3] 周珠丽[4] 沈延京[5]

第一作者：许格希

机构：[1]中国林业科学研究院森林生态环境与自然保护研究所,国家林业和草原局森林生态环境重点实验室,北京100091;[2]四川米亚罗森林生态系统定位观测研究站,四川理县623100;[3]理县林业和草原局,四川理县623100;[4]阿坝州川西国有林保护局,四川理县623100;[5]北京松山国家级自然保护区管理处,北京102115

年份：2023

卷号：45

期号：9

起止页码：104-115

中文期刊名：北京林业大学学报

外文期刊名：Journal of Beijing Forestry University

收录：CSTPCD;;北大核心:【北大核心2020】；CSCD:【CSCD2023_2024】；

基金：国家自然科学基金项目(32201321);中国林业科学研究院基本科研业务专项(CAFYBB2022QC002)。

语种：中文

中文关键词：松材线虫;MaxEnt模型;ArcGIS;入侵风险;理县;川西林区

外文关键词：pine wilt disease;MaxEnt model;ArcGIS;invasion risk;Lixian County;forest area in western Sichuan Province

分类号：S763.3;S812.2

摘要：【目的】松材线虫在我国主要以松墨天牛和云杉花墨天牛为传播媒介,感染林木后常导致森林毁灭性破坏。预测松材线虫病入侵风险不仅对森林保护与质量提升具有重要参考价值,还关乎我国生态安全与碳中和目标的实现。【方法】本文基于川西理县24个云杉花墨天牛和55个枯死松树(云杉花墨天牛羽化前载体)地理分布点以及20个生物与非生物因子数据,利用GIS分析工具和最大熵模型(MaxEnt)对该县云杉花墨天牛适生区和枯死松树潜在分布区进行预测,并通过MaxEnt软件内建的刀切法剖析影响云杉花墨天牛适生区与松树分布区的主要因子。考虑到松材线虫病发生至少需同时具备传播媒介(云杉花墨天牛)和载体(松树)二要素,将云杉花墨天牛适生区和枯死松树分布区数据进行加权求和,预测松材线虫病发生的潜在分布区,评估其入侵风险。【结果】研究发现MaxEnt模型对云杉花墨天牛适生区和枯死松树分布区的预测工作特征曲线的下面积值分别为0.993和0.969,表明模型的预测结果为优,可用于松材线虫病潜在入侵风险预测。松材线虫病潜在入侵风险评估发现距居民点1.5 km内、年均气温为7.8~10.1℃、最湿季降水量为345~358 mm时松材线虫病潜在发生风险最高。模型预估理县松材线虫病潜在发生高风险区面积为10616 hm^(2),沿道路呈带状分布于各乡镇,占县域针叶林总面积7.1%。【结论】基于GIS空间技术和MaxEnt模型有助于预测川西林区松材线虫病入侵风险。但是,随着经济建设与气候变化,川西松材线虫传播与发生存在较大不确定性,应加强居民点、公路沿线松材线虫及其传播媒介的监测,完善防控应急预案,保障川西林区生态安全。
[Objective] In China,the pine wood nematode(Bursaphelenchus xylophilus) takes Monochamus alternatus and M.saltuarius as propagative materials,leading to catastrophic damage to forests since they infect the forest trees.Predicting the invasion risk of pine wilt disease has critical referred values for forest protection and quality improvement,and as a result,it is related to national ecological security and carbon neutralization.[Method] Based on the data of 24 distribution points for M.saltuarius and another 55 points for dead pine trees(hosts of M.saltuarius before eclosion) as well as 20 abiotic and biotic variables in Lixian County,Sichuan Province of southwestern China,we predicted the potentially suitable distribution areas for M.saltuarius and dead pine trees using GIS analytical tool and the MaxEnt model.Furthermore,the MaxEnt jack-knife of variable importance was applied to analyze the influence of main factors on the areas of M.saltuarius and dead pine trees,respectively.Considering that the occurrence of pine wilt disease at least requires both elements(i.e.,M.saltuarius and pine trees),we evaluated the invasion risk of pine wilt disease by predicting the potential occurred regions of B.xylophilus based on weighting and integrating data of the occurrence of M.saltuarius and dead pine trees generated by MaxEnt models.[Result] Mean area values under curves of the suitable distribution areas of M.saltuarius and dead pines were 0.993 and0.969,respectively from the MaxEnt models,which indicated that the model predictions were ideal and can be used to forecast the potential invasion risk of pine wilt disease.Assessing the invasion risk of pine wilt disease demonstrated that the risk was the highest when mean annual temperature ranged from 7.8 ℃ to10.1 ℃ and the precipitation in the wettest season was 348 mm to 358 mm as well as within 1.5 km from the nearest residential point.The model estimated that the high-risk area of pine wilt disease was 10 616 hm^(2),accounting for 7.1% of the total area of coniferous forests in the county,which was distributed zonally along the roads across villages and towns.[Conclusion] Using GIS spatial technology and MaxEnt modelling can benefit the prediction of the invasion risk of pine wilt disease for the forest zones in western Sichuan Province.However,there still exists great uncertainty in the transmission and occurrence of pine wilt disease due to economic construction and climate change.Therefore,it is necessary to strengthen the monitoring of pine wood nematodes(B.xylophilus) and their propagative materials along the residential areas and roads,promoting the preventive and controlled emergency response to ensure the ecological security of forest zones in western Sichuan Province.