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Vegetation biomass change in China in the 20th century: an assessment based on a combination of multi-model simulations and field observations

Authors :
Xiang Song
Fang Li
Sandy P Harrison
Tianxiang Luo
Almut Arneth
Matthew Forrest
Stijn Hantson
Gitta Lasslop
Stephane Mangeon
Jian Ni
Chao Yue
Thomas Hickler
Yiqi Luo
Stephen Sitch
Xin Xu
Zaichun Zhu
Source :
Environmental Research Letters, Vol 15, Iss 9, p 094026 (2020)
Publication Year :
2020
Publisher :
IOP Publishing, 2020.

Abstract

Vegetation biomass is a key and active component of the carbon cycle. Though China’s vegetation biomass in recent decades has been widely investigated, only two studies have quantitatively assessed its century-scale changes so far and reported totally opposite trends. This study provided the first multi-model estimates of China’s vegetation biomass change for the 20th century and its responses to historical changes in environmental and anthropogenic factors, based on simulations evaluated with the field observations from 3757 inventory plots in China and bias-corrected using machine learning (Gaussian process regression). A significant decline in vegetation biomass over the 20th century was shown by bias-corrected simulations from the six Dynamic Global Vegetation models (DGVMs) with trends ranging from −32.48 to −11.10 Tg C yr ^–1 and a mean trend of −17.74 Tg C yr ^–1 . Land use and land cover change (LULCC) was primarily responsible for the simulated downward trend (−50.71 to −24.28 Tg C yr ^–1 ), while increasing atmospheric CO _2 concentration lead to increased vegetation biomass (+9.27 to + 13.37 Tg C yr ^–1 ). Climate change had limited impacts on the long-term trend (−3.75 to + 5.06 Tg C yr ^–1 ). This study highlights the importance of LULCC for historical reconstruction and future projection of vegetation biomass over China. It also suggests that the incorrect change in China’s forest area for 1980–2000 in the LULCC dataset used as model input data of many existing and ongoing model intercomparison projects (MIPs) has likely led to inaccurate estimations of historical vegetation biomass changes in China.

Details

Language :
English
ISSN :
17489326
Volume :
15
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Environmental Research Letters
Publication Type :
Academic Journal
Accession number :
edsdoj.4cd7e88d622c4c30899016045aa450ff
Document Type :
article
Full Text :
https://doi.org/10.1088/1748-9326/ab94e8