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Forest expansion dominates China's land carbon sink since 1980.

Authors :
Yu, Zhen
Ciais, Philippe
Piao, Shilong
Houghton, Richard A.
Lu, Chaoqun
Tian, Hanqin
Agathokleous, Evgenios
Kattel, Giri Raj
Sitch, Stephen
Goll, Daniel
Yue, Xu
Walker, Anthony
Friedlingstein, Pierre
Jain, Atul K.
Liu, Shirong
Zhou, Guoyi
Source :
Nature Communications; 9/13/2022, Vol. 13 Issue 1, p1-12, 12p
Publication Year :
2022

Abstract

Carbon budget accounting relies heavily on Food and Agriculture Organization land-use data reported by governments. Here we develop a new land-use and cover-change database for China, finding that differing historical survey methods biased China's reported data causing large errors in Food and Agriculture Organization databases. Land ecosystem model simulations driven with the new data reveal a strong carbon sink of 8.9 ± 0.8 Pg carbon from 1980 to 2019 in China, which was not captured in Food and Agriculture Organization data-based estimations due to biased land-use and cover-change signals. The land-use and cover-change in China, characterized by a rapid forest expansion from 1980 to 2019, contributed to nearly 44% of the national terrestrial carbon sink. In contrast, climate changes (22.3%), increasing nitrogen deposition (12.9%), and rising carbon dioxide (8.1%) are less important contributors. This indicates that previous studies have greatly underestimated the impact of land-use and cover-change on the terrestrial carbon balance of China. This study underlines the importance of reliable land-use and cover-change databases in global carbon budget accounting. The impact of land-use and cover-change (LUCC) on ecosystem carbon stock in China is poorly known due to large biases in existing databases. Here the authors develop a new LUCC database with corrected false signals and reveal that forest expansion is the dominant driver of China's recent carbon sink. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20411723
Volume :
13
Issue :
1
Database :
Complementary Index
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
159086667
Full Text :
https://doi.org/10.1038/s41467-022-32961-2