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林业科学 ›› 2019, Vol. 55 ›› Issue (4): 160-170.doi: 10.11707/j.1001-7488.20190417

• 问题与讨论 • 上一篇    下一篇

基于MaxEnt模型的松针红斑病在中国的潜在分布区及适生性预测分析

王晓玮, 任雪燕, 梁英梅   

  1. 北京林业大学林学院 北京林业大学博物馆 北京 100083
  • 收稿日期:2018-06-07 修回日期:2018-12-26 出版日期:2019-04-25 发布日期:2019-04-30
  • 基金资助:
    国家重点研发计划“森林生态系统入侵生物本底普查与动态分布”(2016YFC1202102)。

MaxEnt-Based Prediction of Potential Geographic Distribution and Habitat Suitability Analysis for Dothistroma pini in China

Wang Xiaowei, Ren Xueyan, Liang Yingmei   

  1. College of Forestry, Beijing Forestry University Museum of Beijing Forestry University Beijing 100083
  • Received:2018-06-07 Revised:2018-12-26 Online:2019-04-25 Published:2019-04-30

摘要: [目的]依据气候变化,探究气候变化对松针红斑病分布的影响,预测中国松针红斑病的潜在分布区。[方法]根据松针红斑病已知分布区域和相关气候数据,结合政府间气候变化专门委员会(IPCC)针对未来气候变化情景发布的CCSM4气候模式数据,采用最大熵模型(MaxEnt)预测松针红斑病的潜在分布区。[结果]松针红斑病最适宜分布区为黑龙江、吉林、辽宁、内蒙古东北部和云南省。经刀切法分析(Jackknife)表明,6月降水量、11月平均最高温度和最冷季度降水量等主要影响松针红斑病的潜在分布区。在未来不同气候变化情景下,总适宜区面积呈上升趋势,增加幅度为15.66%~18.29%。山东北部、河北、山西的大部分地区、陕西中部和南部、甘肃东南部、四川北部和南部、辽宁西部和内蒙古东部的各等级适宜区面积增加,适宜等级上升。[结论] MaxEnt模型预测结果与实际调查结果具有很高的一致性,能够反映松针红斑病在中国的分布情况。随着未来气候变化,云南、四川交界地区,东北三省和内蒙古东北部最适宜分布区呈现破碎化的趋势。松针红斑病适生区质心有由东北向华北、西北扩散的趋势。

关键词: 松针红斑病, 地理分布, MaxEnt模型, 气候变化, 适生性分析

Abstract: [Objective]The objective of the research is to predict the potential geographical distributions of Dothistroma pini under the climate change, and to study the effects of climatic factors on the geographical distribution.[Method] Based on the known distribution areas of D. pini and related climate data, combined with the CCSM4 climate model data released by the Intergovernmental Panel on Climate Change (IPCC) for future climate change scenarios, the maximum entropy model (MaxEnt) was used to predict the potential suitable geographical distributions of D. pini.[Result]The results showed that the principal geographical distribution areas of D. pini were Heilongjiang, Jilin, Liaoning, northeastern Inner Mongolia and Yunnan. The analysis of Jackknife showed that factors such as precipitation in June, average highest temperature in November and precipitation in the coldest quarter had important influences on the geographical distribution areas of D. pini. Under different scenarios of climate change in the future, the total area of suitable geographical distributions is on the rise, with an increase range of 15.66% to 18.29%. The suitable distribution areas of each grade in northern Shandong, Hebei and Shanxi, central and southern Shaanxi, southeastern Gansu, northern and southern Sichuan, western liaoning and eastern Inner Mongolia increased, and the appropriate grade increased.[Conclusion] The MaxEnt model is proved high reliability to determine the geographic distribution range of D. pini. Under different scenarios of climate change in the future, the principal geographical distribution areas in border area of Yunnan and Sichuan, northeast three provinces and northeast Inner Mongolia show a trend of fragmented. The centroid suitable for the D. pini distribution tends to spread from northeast to north and northwest in China.

Key words: Dothistroma pini, geographic distribution, MaxEnt model, climate change, potential geographical distribution

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