Migration of vegetation boundary between alpine steppe and meadow on a century-scale across the Tibetan Plateau

Ecological Indicators

Chongchong Ye¹  Youchao Chen²  Shaoxiu Ma³  Jian Sun⁴  Huakun Zhou⁵  Atsushi Tsunekawa⁶  Chiyuan Miao⁷  Yi Wang⁸  Xiaoyu Gan⁸  Tao Zeng⁹  Biying Liu⁹  Wen He⁹ 

[1] Corresponding author.;School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China;State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China;State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China;College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China;International Platform for Dryland Research and Education, Tottori University, 6800001, Japan;Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China;School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China;State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China;

关键词: Vegetation distribution;    Alpine grassland;    Vegetation biomass;    Random Forest;    Migration;    Machine Learning;   

DOI  :  

来源: DOAJ

【 摘 要 】

The distribution of alpine vegetation is highly sensitive to climate change, which attracted the attention of climate scientists as well as ecologists. However, the dominant factors of vegetation distribution showed greatly spatiotemporal variation, especially the alpine grasslands on the Tibetan Plateau, which is known as an amplifier of climate warming. In this study, to identify the dominant factors of vegetation distribution, we verified the reliability and accuracy of the classification of alpine steppe and alpine meadow by Random Forest and tried to provide a new reference for the classification schemes. Dataset collected from the field investigations (200 sites) and previous publications(200 sites) were used in this study for model calibration and validation. Then climate models of CMIP6 were used to forecast the underlying transfers and changes of vegetation boundary in the future. Our results revealed that precipitation may be the dominant driver in the alpine grassland distribution, with the highest relative importance of 41.26%. Through different climate scenarios from 2000 to 2100, the vegetation boundary showed a shift from northeast to southwest. Within the SSP5-8.5 scenario it moves from 94.50° to 93.49° and shifted from north to south by 0.34°. Our results demonstrated the significant role of precipitation in the alpine grassland distribution and revealed the migration of the alpine grassland ecosystem under different climate change scenarios. Our work may be useful to deal with global climate change, early warning, and grassland protection, as well as adaptive management of grassland.

【 授权许可】

Unknown