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基于MaxEnt 模型的毛红椿全球潜在适生区分布及其特征预测研究

黄红兰 张露 贾黎明 梁跃龙 温婷 程子珊 刘远生 甘文峰

江西农业大学学报2018,Vol.40Issue(2):241-247,7.
江西农业大学学报2018,Vol.40Issue(2):241-247,7.DOI:10.13836/j.jjau.2018032

基于MaxEnt 模型的毛红椿全球潜在适生区分布及其特征预测研究

Prediction of Global Potential Suitable Distribution Areas and Attributes of Toona ciliata var. pubescens with MaxEnt

黄红兰 1张露 2贾黎明 2梁跃龙 3温婷 4程子珊 2刘远生 2甘文峰5

作者信息

  • 1. 江西环境工程职业学院,江西 赣州341000
  • 2. 江西农业大学 江西特色林木资源培育与利用2011协同创新中心,江西 南昌330045
  • 3. 北京林业大学,北京100083
  • 4. 江西九连山国家级自然保护区,江西 龙南341701
  • 5. 安福县明月山林场,江西 安福343200
  • 折叠

摘要

Abstract

A maximum entropy model(MaxEnt)was used to investigate the prediction of the global poten-tial distribution areas of T.ciliata var.pubescens and the key factors in its distribution.As a result,its pattern of the global geographical distribution was continuous,while the high distribution areas followed a patchy pattern. The climatic factors that were found to affect the distribution of T.ciliata var.pubescens were mainly precipitation of the warmest quarter,SD of temperature seasonality and min temperature of the coldest months,with the suit-able value ranges being 494.79-1 504 mm,2 362.88-9 986.69,-10.35-10.44 ℃,respectively.The continu-ous distribution in China is better than abroad,and there were two patches of most suitable distribution,one of which is located in the southeast of Anhui Province and Zhejiang Province,and the other in Fujian Province, Guangdong Province,and in the south of Jiangxi Province.The regions of the two patches are basically coinci-dent with the existing research areas with higher genetic characters.fherefore they should be included in the ar-eas under prior protection in further study.

关键词

毛红椿/MaxEnt/潜在适生区/分布格局/优先保护

Key words

Toona ciliata var. pubescens/MaxEnt/potential suitable distribution area/distribution pattern/prior protection

分类

农业科技

引用本文复制引用

黄红兰,张露,贾黎明,梁跃龙,温婷,程子珊,刘远生,甘文峰..基于MaxEnt 模型的毛红椿全球潜在适生区分布及其特征预测研究[J].江西农业大学学报,2018,40(2):241-247,7.

基金项目

国家自然科学基金项目(31360171)、江西省科技厅科技支撑项目(20151BBF60019)和国家重点研发专项子课题(2016YFD060060605).Project supported by the National Natural Science Foundation of China(31360171),Jiangxi Provincial Science&fech-nology Support Project(20151BBF60019)and National Key Research&Development Project(2016YFD060060605) (31360171)

江西农业大学学报

OA北大核心CSCDCSTPCD

1000-2286

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