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Vegetation structural shift tells environmental changes on the Tibetan Plateau over 40 years.

Authors :
Wang, Yanfen
Xue, Kai
Hu, Ronghai
Ding, Boyang
Zeng, Hong
Li, Ruijin
Xu, Bin
Pang, Zhe
Song, Xiaoning
Li, Congjia
Du, Jianqing
Yang, Xiuchun
Zhang, Zelin
Hao, Yanbin
Cui, Xiaoyong
Guo, Ke
Gao, Qingzhu
Zhang, Yangjian
Zhu, Juntao
Sun, Jian
Source :
Science Bulletin. Sep2023, Vol. 68 Issue 17, p1928-1937. 10p.
Publication Year :
2023

Abstract

[Display omitted] Structural information of grassland changes on the Tibetan Plateau is essential for understanding alterations in critical ecosystem functioning and their underlying drivers that may reflect environmental changes. However, such information at the regional scale is still lacking due to methodological limitations. Beyond remote sensing indicators only recognizing vegetation productivity, we utilized multivariate data fusion and deep learning to characterize formation-based plant community structure in alpine grasslands at the regional scale of the Tibetan Plateau for the first time and compared it with the earlier version of Vegetation Map of China for historical changes. Over the past 40 years, we revealed that (1) the proportion of alpine meadows in alpine grasslands increased from 50% to 69%, well-reflecting the warming and wetting trend; (2) dominances of Kobresia pygmaea and Stipa purpurea formations in alpine meadows and steppes were strengthened to 76% and 92%, respectively; (3) the climate factor mainly drove the distribution of Stipa purpurea formation, but not the recent distribution of Kobresia pygmaea formation that was likely shaped by human activities. Therefore, the underlying mechanisms of grassland changes over the past 40 years were considered to be formation dependent. Overall, the first exploration for structural information of plant community changes in this study not only provides a new perspective to understand drivers of grassland changes and their spatial heterogeneity at the regional scale of the Tibetan Plateau, but also innovates large-scale vegetation study paradigm. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20959273
Volume :
68
Issue :
17
Database :
Academic Search Index
Journal :
Science Bulletin
Publication Type :
Academic Journal
Accession number :
171342652
Full Text :
https://doi.org/10.1016/j.scib.2023.07.035