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 conifer
作者
许格希
余荣兵
杨昌旭
刘怀君
周珠丽
沈延京
Xu Gexi;Yu Rongbing;Yang Changxu;Liu Huaijun;Zhou Zhuli;Shen Yanjing(Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration,Ecology and Nature Conservation Institute,Chinese Academy of Forestry,Beijing 100091,China;Miyaluo Research Station of Alpine Forest Ecosystem,Lixian 623100,Sichuan,China;Lixian Forestry and Grassland Bureau,Lixian 623100,Sichuan,China;State-Owned Forest Protection Bureau of West Sichuan in Aba Prefecture,Lixian 623100,Sichuan,China;Beijing Songshan National Nature Reserve Administration,Beijing 102115,China)
出处
《北京林业大学学报》
CAS
CSCD
北大核心
2023年第9期104-115,共12页
Journal of Beijing Forestry University
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)。
关键词
松材线虫
MaxEnt模型
ARCGIS
入侵风险
理县
川西林区
pine wilt disease
MaxEnt model
ArcGIS
invasion risk
Lixian County
forest area in western Sichuan Province
