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Predicting the responses of subalpine forest landscape dynamics to climate change on the eastern Tibetan Plateau.

Authors :
Liu, Junyan
Zou, Heng‐Xing
Bachelot, Benedicte
Dong, Tingfa
Zhu, Zhongfu
Liao, Yuchen
Plenković‐Moraj, Anđelka
Wu, Yan
Source :
Global Change Biology. Sep2021, Vol. 27 Issue 18, p4352-4366. 15p.
Publication Year :
2021

Abstract

Subalpine vegetation across the Tibetan Plateau is globally one of the most sensitive to climate change. However, the potential landscape‐scale effects of climate change on subalpine forest dynamics remain largely unexplored. Here, we used a forest landscape model (LANDIS‐II) coupled with a forest ecosystem process model (PnET‐II) to simulate forest dynamics under future climate change in Jiuzhaigou National Nature Reserve in the eastern subalpine region of the Tibetan Plateau. We examined changes in the composition, distribution and aboveground biomass of cold temperate coniferous forests, temperate coniferous forests, deciduous broad‐leaved forests and redwood forest under four climate change scenarios (RCP2.6, RCP4.5, RCP8.5 and the current climate) from 2016 to 2096. Our model predicts that by 2096, (i) cold temperate coniferous forests will expand and increase by 7.92%, 8.18%, 8.65% and 7.02% under current climate, RCP2.6, RCP4.5 and RCP8.5 scenarios, respectively; (ii) distribution of forests as a whole shows upward elevational range shift, especially under RCP8.5 scenario and (iii) total aboveground biomass slowly increases at first and then decreases to 12%–16% of current distribution under RCPs. These results show that climate change can be expected to significantly influence forest composition, distribution and aboveground biomass in the subalpine forests of eastern Tibetan Plateau. This study is the first to simulate forest dynamics at the landscape scale in subalpine areas of the Tibetan Plateau, which provides an important step in developing more effective strategies of forest management for expected climate change, not only in China but also around the world. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13541013
Volume :
27
Issue :
18
Database :
Academic Search Index
Journal :
Global Change Biology
Publication Type :
Academic Journal
Accession number :
151911714
Full Text :
https://doi.org/10.1111/gcb.15727