气候变化情景下细叶云南松的潜在分布预测  

Prediction of potential distribution of Pinus yunnanensis under climate change scenarios

作　　者：凌冬霖 潘玥婧 黄春晖 白天道[1,2,3] 蒋维昕[1,2,3] LING Donglin;PAN Yuejing;HUANG Chunhui;BAI Tiandao;JIANG Weixin(College of Forestry,Guangxi University,Nanning 530004,Guangxi,China;Guangxi Key Laboratory of Forest Ecology and Conservation,Guangxi University,Nanning 530004,Guangxi,China;Key Laboratory of National Forestry and Grassland Administration on Cultivation of Fast-Growing Timber in Central South China,Guangxi University,Nanning 530004,Guangxi,China)

机构地区：[1]广西大学林学院,广西南宁530004 [2]广西大学广西森林生态与保育重点实验室,广西南宁530004 [3]广西大学国家林草局中南速生材繁育重点实验室,广西南宁530004

出　　处：《中南林业科技大学学报》2024年第12期154-165,共12页Journal of Central South University of Forestry & Technology

基　　金：国家自然科学基金项目(32160381);广西自然科学基金项目(2024GXNSFAA010375)。

摘　　要：【目的】分析并预测未来不同气候情景下细叶云南松的潜在分布范围,探讨影响其地理分布的主要环境因子,为细叶云南松潜在分布区和种质资源的有效保护提供理论依据。【方法】以全球生物多样性信息网络(GBIF)、中国国家标本资源平台(NSII)、文献资料、实地采样记录等多渠道获取的细叶云南松分布数据和13个环境因子为基础,应用最大熵模型(MaxEnt)预测细叶云南松在未来6种气候情景下的潜在分布区,使用ArcGIS10.8软件进行可视化表达,利用刀切法、环境因子贡献率、置换重要性等方法分析影响细叶云南松分布的主要环境因子。【结果】受试者工作特征曲线(Receiver operating characteristic curve,ROC)的AUC值为0.989,表示预测准确性极高;细叶云南松主要分布在广西、贵州、云南交界地区,福建、四川、广东等也有潜在分布区;最暖季度降水量(bio18)、最干季度降水量(bio17)是影响细叶云南松地理分布的主要环境因子,降水因子累计贡献率为64.51%;未来气候情景下,细叶云南松的中心分布区不变,边缘潜在分布区逐渐丧失,新增潜在分布区主要在中心分布区广西、云南、贵州的外围。【结论】最暖季度降水量(bio18)是影响细叶云南松分布的首要因子,降水因子对细叶云南松地理分布的影响比温度因子更大;随着未来气候变化,细叶云南松的潜在分布面积呈现缩小趋势,但中心分布区较为稳定,可以在中心分布区扩大细叶云南松种植面积,保护物种资源。【Objective】The potential distribution range of Pinus yunnanensis var.tenuifolia is analyzed and predicted under different future climate scenarios.The main environmental factors affecting geographical distribution of P.yunnanensis var.tenuifolia was discussed to provide a theoretical basis for the effective conservation of potential distribution area and germplasm resources of P.yunnanensis var.tenuifolia.【Method】Based on GBIF,NSII,literature data,field sampling data and 13 environmental factors,the MaxEnt model was used to simulate the potential distribution area in six future climate scenarios.The ArcGIS10.8 software was used to visualize the distribution.The main environmental factors influencing the distribution of P.yunnanensis var.tenuifolia were analyzed by Jackknife method,percent contribution of environmental factors and permutation importance.【Result】The area under the receiver operating characteristic curve(AUC)was 0.989,indicating that the predictive accuracy was very high.At present,P.yunnanensis var.tenuifolia,mainly distributed in the border areas of Guangxi,Guizhou and Yunnan,had potential distribution areas in Fujian,Sichuan and Guangdong.Precipitation of warmest quarter(bio18)and precipitation of driest quarter(bio17)were the main environmental factors affecting the geographical distribution of P.yunnanensis var.tenuifolia.The cumulative contribution rate of precipitation was 64.51%.Under the future climate scenario,the central distribution area of P.yunnanensis var.tenuifolia would not change,the marginal potential distribution area would gradually lose,and the new potential distribution area would mainly be in the periphery of the central distribution area of Guangxi,Yunnan and Guizhou.【Conclusion】The precipitation of warmest quarter(bio18)is the primary factor affecting the distribution of P.yunnanensis var.tenuifolia,and the precipitation factors has a greater effect on the distribution than the temperature factors.With the future climate change,the potential distribution are

关 键 词：松属 MaxEnt模型 潜在分布 适生区 森林资源保育 

分 类 号：S718.48[农业科学—林学]