生态与农村环境学报 ›› 2015, Vol. 31 ›› Issue (1): 69-76.doi: 10.11934/j.issn.1673-4831.2015.01.010

• 自然保护与生态 • 上一篇    下一篇

基于IPCC AR5的我国常绿阔叶林潜在适宜生境变化分析

雷军成,徐海根,吴军,关庆伟   

  1. 南京林业大学生物与环境学院
  • 收稿日期:2014-03-31 修回日期:2014-12-03 出版日期:2015-01-25 发布日期:2015-04-15
  • 通讯作者: 关庆伟 南京林业大学生物与环境学院 E-mail:guanjapan999@163.com
  • 作者简介:雷军成(1984—),男,江苏连云港人,博士生,主要研究方向为生物多样性保护。E-mail:ljctnt@126.com
  • 基金资助:

    中国清洁发展机制基金赠款项目(1213114)

IPCC AR5-Based Analysis of Variation of Potential Suitable Habitats for Evergreen Broadleaf Forest in China

 LEI  Jun-Cheng, XU  Hai-Gen, WU  Jun, GUAN  Qing-Wei   

  1. College of Biology and Environment,Nanjing Forestry University
  • Received:2014-03-31 Revised:2014-12-03 Online:2015-01-25 Published:2015-04-15
  • Contact: GUAN Qing-Wei College of Biology and Environment,Nanjing Forestry University E-mail:guanjapan999@163.com

摘要: 了解气候变化情景下我国常绿阔叶林潜在适宜生境的空间变化特征,对于未来的生物多样性保护、植被修复及区域规划等方面都具有极其重要的作用。利用联合国政府间气候变化专门委员会(IPCC)第5 次评估报告(AR5)发布的最新气候情景数据,结合物种分布多模型集合预测平台ModEco,预测气候变化情景下到21 世纪50年代我国常绿阔叶林潜在适宜生境的变化。结果表明,气候变化将导致我国常绿阔叶林潜在适宜生境面积增加,增加的潜在适宜生境主要位于青藏高原南部和东南部地区;大气中排放的温室气体浓度越高,我国常绿阔叶林潜在适宜生境的面积增幅越大。

关键词: 气候变化, 情景, 温室气体, 物种分布模型, 集合预测

Abstract: A better understanding of spatial variation of potential suitable habitats for evergreen broadleaf forest in China will play an extremely significant role in biodiversity conservation, vegetation restoration, and regional planning in the future. Based on the latest climate scenario data published in the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) , changes in potential suitable habitat for evergreen broadleaf forest under predicted changing climate till 2050s were predicted with the aid of ModEco, a multi-model ensemble forecasting platform for prediction of species distribution. Results show that climate change will lead to expansion of the area of potential suitable habitat for evergreen broadleaf forest, mainly in the southeast and south parts of the Qinghai-Tibetan Plateau. The higher the concentration of greenhouse gases in the atmosphere, the more significant the expansion.

Key words: climate change, scenario, greenhouse gas, species distribution model, ensemble forecasting

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