文献类型：期刊文献

中文题名：云南省松墨天牛适生性空间模拟

英文题名：Spatial Simulation of the Adaptability of Monochamus alternatus Hope in Yunnan Province

作者：叶江霞[1,2] 周汝良[1] 吴明山[1] 刘智军[1] 石雷[2]

第一作者：叶江霞

机构：[1]西南林业大学;[2]中国林业科学研究院资源昆虫研究所

年份：2013

卷号：26

期号：4

起止页码：420-425

中文期刊名：林业科学研究

外文期刊名：Forest Research

收录：CSTPCD;;Scopus;北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

基金：国家林业局林业公益性行业科研专项(201004062);云南省科技计划项目(2005YX27);国家自然基金项目(D0106)

语种：中文

中文关键词：松墨天牛;松材线虫;适生性;空间模拟

外文关键词：Monochamus alternatus; Bursaphelenchus xylophilus; adaptability; spatial simulation

分类号：S763

摘要：根据影响松墨天牛生长发育的主要生态因子年均气温及≥10.8℃积温,建立松墨天牛适生性空间分布模型;利用云南省常规气象站点历史数据以及其它环境变量因子,建立云南省年均气温空间模拟模型;借助GIS空间分析及建模功能,完成云南全境的年均气温≥10.8℃积温的空间连续化模拟与表达。最后以90 m×90 m空间尺度,实现了云南省松墨天牛空间适生性计算、空间分布模拟与可视化表达。结果表明:松墨天牛适生性较广,云南北部雪线附近及雪线以上的高山地区为不适宜区,滇西北及滇东北的高山区域为低适宜区之外,云南大部分为松墨天牛的高适生区或较高适生区,适生性明显与生态区位相关。以定量化、精细化及可视化方式进行松墨天牛适生性研究,能获取山头地块的适生级别,从而为森防部门的预警及风险评估发布、基层单位开展有针对性防治提供决策依据。
Monochamus alternatus Hope is the main intermediary insect of Bursaphelenchus xylophilus.According to the main ecological factors of average temperature and above 10.8 ℃ accumulated temperature,the spatial distribution of M.alternatus was modeled in order to prevent the occurrence of B.xylophilus.A method was proposed to simulate annual average temperature and above 10.8 ℃ accumulated temperature by using statistical data from conventional weather stations in Yunnan province and environment variable factors based on GIS spatial analysis and modeling.The result was presented in 90 m × 90 m spatial resolution to realize the computation,spatial pattern simulation and visualization of the adaptability of M.alternatus.The results shows that there are wide region suitable for M.alternatus besides the snow mountain in north Yunnan with no suitability,and high mountains in northwest and northeast Yunnan with low suitability.Moreover,the results are definitely related to ecological location.Since the results are presented in a quantitative,refine and visual way,so it is easy to obtain the adaptability of M.alternatus in grid cell,which can provide data for warning,risking assessment,and decision-making in disease prevention.