TY - JOUR
T1 - Impacts of land use change and elevated CO2 on the interannual variations and seasonal cycles of gross primary productivity in China
AU - Jia, Binghao
AU - Luo, Xin
AU - Cai, Ximing
AU - Jain, Atul
AU - Huntzinger, Deborah N.
AU - Xie, Zhenghui
AU - Zeng, Ning
AU - Mao, Jiafu
AU - Shi, Xiaoying
AU - Ito, Akihiko
AU - Wei, Yaxing
AU - Tian, Hanqin
AU - Poulter, Benjamin
AU - Hayes, Dan
AU - Schaefer, Kevin
N1 - Funding Information:
Financial support. This research has been supported by the National Key R&D Program of China (grant no. 2016YFA0600203), the Key Research Program of Frontier Sciences, CAS (grant no. QYZDY-SSW-DQC012), the National Natural Science Foundation of China (grant nos. 41575096, 41830967), and the Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou Institute of Geography (grant no. 2017B030314138).
Funding Information:
This research has been supported by the National Key R&D Program of China (grant no. 2016YFA0600203), the Key Research Program of Frontier Sciences, CAS (grant no. QYZDY-SSW-DQC012), the National Natural Science Foundation of China (grant nos. 41575096, 41830967), and the Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou Institute of Geography (grant no. 2017B030314138).
Funding Information:
Acknowledgements. This research was supported by the National Key R&D Program of China (2016YFA0600203), the Key Research Program of Frontier Sciences, CAS (QYZDY-SSW-DQC012), the National Natural Science Foundation of China (41575096, 41830967), and the Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou Institute of Geography (2017B030314138). We acknowledge the MsTMIP modelers, including Maoyi Huang from the Pacific Northwest National Laboratory, Shushi Peng from Peking University, Joshus B. Fisher from the California Institute of Technology and Daniel M. Ricciuto from the Oak Ridge National Laboratory, for contributing model output used in this work. We also thank Wenhui Kuang for providing us with the China Land Use/Cover Dataset (CLUD). Finalized MsTMIP data products are archived at the ORNL DAAC (https://daac.ornl.gov/ NACP/guides/NACP_MsTMIP_TBMO.html, last access: 24 January 2016). The MTE data were downloaded freely from the Max Planck Institute for Biogeochemistry (https://www.bgc-jena.mpg. de/geodb/projects/Data.php, last access: 20 November 2017). We thank Somnath Baidya Roy and two anonymous reviewers for the helpful comments that improved the paper.
Publisher Copyright:
© Author(s) 2020.
PY - 2020/3/9
Y1 - 2020/3/9
N2 - Climate change, rising CO2 concentration, and land use and land cover change (LULCC) are primary driving forces for terrestrial gross primary productivity (GPP), but their impacts on the temporal changes in GPP are uncertain. In this study, the effects of the three main factors on the interannual variation (IAV) and seasonal cycle amplitude (SCA) of GPP in China were investigated using 12 terrestrial biosphere models from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project. The simulated ensemble mean value of China's GPP between 1981 and 2010, driven by common climate forcing, LULCC and CO2 data, was found to be 7.4±1.8 Pg C yr-1. In general, climate was the dominant control factor of the annual trends, IAV and seasonality of China's GPP. The overall rising CO2 led to enhanced plant photosynthesis, thus increasing annual mean and IAV of China's total GPP, especially in northeastern and southern China, where vegetation is dense. LULCC decreased the IAV of China's total GPP by ∼7 %, whereas rising CO2 induced an increase of 8 %. Compared to climate change and elevated CO2, LULCC showed less contributions to GPP's temporal variation, and its impact acted locally, mainly in southwestern China. Furthermore, this study also examined subregional contributions to the temporal changes in China's total GPP. Southern and southeastern China showed higher contributions to China's annual GPP, whereas southwestern and central parts of China explained larger fractions of the IAV in China's GPP.
AB - Climate change, rising CO2 concentration, and land use and land cover change (LULCC) are primary driving forces for terrestrial gross primary productivity (GPP), but their impacts on the temporal changes in GPP are uncertain. In this study, the effects of the three main factors on the interannual variation (IAV) and seasonal cycle amplitude (SCA) of GPP in China were investigated using 12 terrestrial biosphere models from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project. The simulated ensemble mean value of China's GPP between 1981 and 2010, driven by common climate forcing, LULCC and CO2 data, was found to be 7.4±1.8 Pg C yr-1. In general, climate was the dominant control factor of the annual trends, IAV and seasonality of China's GPP. The overall rising CO2 led to enhanced plant photosynthesis, thus increasing annual mean and IAV of China's total GPP, especially in northeastern and southern China, where vegetation is dense. LULCC decreased the IAV of China's total GPP by ∼7 %, whereas rising CO2 induced an increase of 8 %. Compared to climate change and elevated CO2, LULCC showed less contributions to GPP's temporal variation, and its impact acted locally, mainly in southwestern China. Furthermore, this study also examined subregional contributions to the temporal changes in China's total GPP. Southern and southeastern China showed higher contributions to China's annual GPP, whereas southwestern and central parts of China explained larger fractions of the IAV in China's GPP.
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U2 - 10.5194/esd-11-235-2020
DO - 10.5194/esd-11-235-2020
M3 - Article
AN - SCOPUS:85081630150
SN - 2190-4979
VL - 11
SP - 235
EP - 249
JO - Earth System Dynamics
JF - Earth System Dynamics
IS - 1
ER -