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Modelling analysis embodies drastic transition among global potential natural vegetations in face of changing climate

Zhengchao Ren Lei Liu Fang Yin Xiaoni Liu

Forest Ecosystems2024,Vol.11Issue(2):P.184-192,9.
Forest Ecosystems2024,Vol.11Issue(2):P.184-192,9.DOI:10.1016/j.fecs.2024.100180

Modelling analysis embodies drastic transition among global potential natural vegetations in face of changing climate

Zhengchao Ren 1Lei Liu 2Fang Yin 3Xiaoni Liu4

作者信息

  • 1. School of Earth Science and Resources,Chang’an University,Xi’an,710054,China Research Center of Ecological Construction and Environmental Conservation in Gansu Province,Gansu Agricultural University,Lanzhou,730070,China
  • 2. School of Earth Science and Resources,Chang’an University,Xi’an,710054,China State Key Laboratory of Tibetan Plateau Earth System,Environment and Resources(TPESER),Institute of Tibetan Plateau Research,Chinese Academy of Sciences,Beijing,100101,China
  • 3. School of Land Engineering,Chang’an University,Xi’an,710054,China
  • 4. College of Pratacultural Science,Gansu Agricultural University,Lanzhou,730070,China
  • 折叠

摘要

关键词

Potential natural vegetation/Global warming/Vegetation classification/Predicted model/CSCS

分类

农业科技

引用本文复制引用

Zhengchao Ren,Lei Liu,Fang Yin,Xiaoni Liu..Modelling analysis embodies drastic transition among global potential natural vegetations in face of changing climate[J].Forest Ecosystems,2024,11(2):P.184-192,9.

基金项目

funded by the National Natural Science Foundation of China(grants No.30960264,31160475 and 42071258) (grants No.30960264,31160475 and 42071258)

Open Research Fund of TPESER(grant No.TPESER202208) (grant No.TPESER202208)

Special Fund for Basic Scientific Research of Central Colleges,Chang’an University,China(grant No.300102353501) (grant No.300102353501)

Natural Science Foundation of Gansu Province,China(grant No.22JR5RA857) (grant No.22JR5RA857)

Higher Education Novel Foundation of Gansu Province,China(grant No.2021B-130)。 (grant No.2021B-130)

Forest Ecosystems

OACSTPCD

2095-6355

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