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.
| Original language | English |
|---|---|
| Article number | 5374 |
| Journal | Nature Communications |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2022 |
Funding
This work was supported by the National Key Research and Development Program of China (No. 2021YFD2200405), the National Science Foundation of China (No. 32001166, No. 42130506, and No. 42071031), the Startup Foundation for Introducing Talent of NUIST (No. 2019r059 and 003080), and the Natural Science Foundation of Jiangsu Higher Education Institution of China (20KJB170013). We thank TRENDY and MsTMIP modeling groups for providing model simulation data. Funding for the Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP; https://nacp.ornl.gov/MsTMIP.shtml) activity was provided through NASA ROSES Grant #NNX10AG01A. Data management support for preparing, documenting, and distributing model driver and output data was performed by the Modeling and Synthesis Thematic Data Center at Oak Ridge National Laboratory (ORNL; https://nacp.ornl.gov), with funding through NASA ROSES Grant #NNH10AN681. Finalized MsTMIP data products are archived at the ORNL DAAC (https://daac.ornl.gov). G.R.K. would like to acknowledge Longshan Professorship in NUIST. ORNL is managed by UT-Battelle, LLC, for the DOE under contract DE-AC05-1008 00OR22725. This manuscript has been co-authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). This work was supported by the National Key Research and Development Program of China (No. 2021YFD2200405), the National Science Foundation of China (No. 32001166, No. 42130506, and No. 42071031), the Startup Foundation for Introducing Talent of NUIST (No. 2019r059 and 003080), and the Natural Science Foundation of Jiangsu Higher Education Institution of China (20KJB170013). We thank TRENDY and MsTMIP modeling groups for providing model simulation data. Funding for the Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP; https://nacp.ornl.gov/MsTMIP.shtml ) activity was provided through NASA ROSES Grant #NNX10AG01A. Data management support for preparing, documenting, and distributing model driver and output data was performed by the Modeling and Synthesis Thematic Data Center at Oak Ridge National Laboratory (ORNL; https://nacp.ornl.gov ), with funding through NASA ROSES Grant #NNH10AN681. Finalized MsTMIP data products are archived at the ORNL DAAC ( https://daac.ornl.gov ). G.R.K. would like to acknowledge Longshan Professorship in NUIST. ORNL is managed by UT-Battelle, LLC, for the DOE under contract DE-AC05-1008 00OR22725. This manuscript has been co-authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).
| Funders | Funder number |
|---|---|
| DOE Public Access Plan | |
| Natural Science Foundation of Jiangsu Higher Education Institution of China | 20KJB170013 |
| ORNL DAAC | |
| United States Government | |
| U.S. Department of Energy | DE-AC05-1008 00OR22725 |
| National Aeronautics and Space Administration | 10AG01A |
| Oak Ridge National Laboratory | 10AN681 |
| UT-Battelle | DE-AC05-00OR22725 |
| National Natural Science Foundation of China | 32001166, 42071031, 42130506 |
| Nanjing University of Information Science and Technology | 003080, 2019r059 |
| National Key Research and Development Program of China | 2021YFD2200405 |
