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Spatio-temporal change of soil organic carbon, progress and prospects |
Received:January 08, 2020 |
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KeyWord:SOC;spatio-temporal change;prediction model;driving data;uncertainty evaluation |
Author Name | Affiliation | E-mail | ZHANG Xiu | State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China University of Chinese Academy of Sciences, Beijing 100049, China | | ZHAO Yong-cun | State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China University of Chinese Academy of Sciences, Beijing 100049, China | yczhao@issas.ac.cn | XIE En-ze | State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China University of Chinese Academy of Sciences, Beijing 100049, China | | PENG Yu-xuan | State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China University of Chinese Academy of Sciences, Beijing 100049, China | | LU Fang-yi | State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China University of Chinese Academy of Sciences, Beijing 100049, China | |
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Abstract: |
Soil organic carbon(SOC)forms the basis of soil fertility, food production, and soil health, and plays a key role in global carbon balance. Consequently, accurate characterization of SOC spatio-temporal changes is extremely important for ensuring the soil health and food security, long-term stability of the ecosystem, and the mitigation and adaptation to climate change. In this study, we first reviewed maindriving factors of spatio-temporal SOC change and the approaches in estimating SOC spatio-temporal changes, and then summarized the existing large-scale studies(global/national)on SOC spatio-temporal changes. Finally, we proposed the possible challenges from the aspects of SOC model structure improvement, driving data quality,uncertainty quantification. This review may provide some guidances for large-scale spatio-temporal change research of SOC. |
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