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4. Satellite-based monitoring of China's above-ground biomass carbon sink from 2015 to 2021

Author

Fang, Hongqian, Fan, Lei, Ciais, Philippe, Xiao, Jingfeng, Fensholt, Rasmus, Chen, Jingming, Frappart, Frédéric, Ju, Weimin, Niu, Shuli, Xiao, Xiangming, Yuan, Wenping, Xia, Jiangzhou, Li, Xin, Liu, Liangyun, Qin, Yuanwei, Chang, Zhongbing, Yu, Ling, Dong, Guanyu, Cui, Tianxiang, Li, Xiaojun, Wigneron, Jean Pierre, Fang, Hongqian, Fan, Lei, Ciais, Philippe, Xiao, Jingfeng, Fensholt, Rasmus, Chen, Jingming, Frappart, Frédéric, Ju, Weimin, Niu, Shuli, Xiao, Xiangming, Yuan, Wenping, Xia, Jiangzhou, Li, Xin, Liu, Liangyun, Qin, Yuanwei, Chang, Zhongbing, Yu, Ling, Dong, Guanyu, Cui, Tianxiang, Li, Xiaojun, and Wigneron, Jean Pierre

Abstract

China's terrestrial ecosystems are pivotal in upholding the global carbon balance, with their recognized capacity for carbon sequestration holding significant importance on a global scale, but there are still challenges in accurately monitoring its spatial-temporal patterns. SMOSMAP-IB L-VOD, a recently developed low-frequency L-band Vegetation Optical Depth (L-VOD) product, was employed to monitor the fluctuations in aboveground vegetation carbon stock over China between 2015 and 2021, and to investigate the influence of forest age and ecological restoration projects on China's carbon sink capacity. The carbon sink of above-ground vegetation in China was Tg C yr-1 during 2015–2021. Southwest and northeast China's forests exhibit higher carbon sink capacity, contrasting with lower values per unit area are mainly found in northwestern China. The forest served as the foremost contributor to the carbon sink of above-ground vegetation in China, although their carbon density peaked in the middle-aged forests and then gradually decreased as the age of the forest grew. Furthermore, carbon sink areas were observed in most regions where ecological restoration projects were implemented, indicating that the execution of afforestation and ecological restoration initiatives has proven effective in carbon sequestration, creating a sink in these areas. Our results provide an improved foundation for formulating new afforestation policies in the future., China's terrestrial ecosystems are pivotal in upholding the global carbon balance, with their recognized capacity for carbon sequestration holding significant importance on a global scale, but there are still challenges in accurately monitoring its spatial-temporal patterns. SMOSMAP-IB L-VOD, a recently developed low-frequency L-band Vegetation Optical Depth (L-VOD) product, was employed to monitor the fluctuations in aboveground vegetation carbon stock over China between 2015 and 2021, and to investigate the influence of forest age and ecological restoration projects on China's carbon sink capacity. The carbon sink of above-ground vegetation in China was +169.98+135.59+179.44 Tg C yr-1 during 2015–2021. Southwest and northeast China's forests exhibit higher carbon sink capacity, contrasting with lower values per unit area are mainly found in northwestern China. The forest served as the foremost contributor to the carbon sink of above-ground vegetation in China, although their carbon density peaked in the middle-aged forests and then gradually decreased as the age of the forest grew. Furthermore, carbon sink areas were observed in most regions where ecological restoration projects were implemented, indicating that the execution of afforestation and ecological restoration initiatives has proven effective in carbon sequestration, creating a sink in these areas. Our results provide an improved foundation for formulating new afforestation policies in the future.

Published
2024

6. Soil Organic Carbon Lateral Movement Processes Integrated Into a Terrestrial Ecosystem Model.

Author

Lu, Haibo, Wang, Xiaoyuan, Zhang, Haicheng, Xie, Xianhong, Nakhavali, Mahdi, Quine, Timothy A., Xu, Wenfang, Xia, Jiangzhou, He, Bin, Hao, Zhixin, Geng, Xiu, and Yuan, Wenping

Subjects
CARBON cycle, DISSOLVED organic matter, CARBON in soils, ECOSYSTEMS, SOIL erosion, COLLOIDAL carbon, WATERSHEDS
Abstract

Lateral movement of soil organic carbon (SOC) induced by soil erosion and runoff changes spatial distributions of SOC, and further changes the land‐atmosphere CO2 exchange and terrestrial carbon budget. However, current ecosystem models do not or only poorly integrate the process of SOC lateral movement and cannot simulate the impacts of soil erosion on the carbon cycle. This study integrated SOC erosion and deposition processes into a process‐based ecosystem model (i.e., Integrated BIosphere Simulator (IBIS)), and separately simulated the lateral movements of dissolved organic carbon (DOC) and particulate organic carbon (POC). The model was evaluated in three river basins in Northeast China that are dominated by cropland, forest, and grassland. The results showed that the model reproduced well the production, erosion, and deposition of DOC and POC. The annual SOC lateral movement (1.34–7.22 g C m−2 yr−1) induced by erosion in the three tested basins was 0.27%–1.45% of the annual net primary production. The model developed in this study has great implications for simulating the lateral movements of SOC in terrestrial ecosystems, which can improve model performance in projecting the terrestrial carbon budget. Plain Language Summary: Lateral movement of soil organic carbon (SOC) with soil erosion and runoff is an important process in estimating land carbon budget. However, the current ecosystem models are not or poorly integrated this process, and cannot simulate the impacts of lateral movement of SOC on carbon cycle. This study integrates SOC erosion and deposition processes into a process‐based ecosystem model (Integrated BIosphere Simulator (IBIS)), and separately simulates the lateral movements of dissolved organic carbon (DOC) and particulate organic carbon (POC). The model was evaluated at three river basins in Northeast China dominated by cropland, forest and grassland, respectively. The results showed the model can reproduce well the production, erosion, deposition of DOC and POC. The model developed in this study has great implications for simulating the lateral movements of SOC in terrestrial ecosystem, which can improve model performance on projecting terrestrial carbon budget. Key Points: Current ecosystem models inadequately depict the lateral movement of SOC, causing uncertainties in terrestrial carbon cycle modelingWe integrated SOC erosion and deposition into a process‐based ecosystem model and evaluated it in three Chinese river basinsModel simulations well represented observed data for the production, erosion, and deposition of organic carbon [ABSTRACT FROM AUTHOR]

Published
2024
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8. Vegetation-specific model parameters are not required for estimating gross primary production

Author

Yuan, Wenping, Cai, Wenwen, Liu, Shuguang, Dong, Wenjie, Chen, Jiquan, Arain, M. Altaf, Blanken, Peter D., Cescatti, Alessandro, Wohlfahrt, Georg, Georgiadis, Teodoro, Genesio, Lorenzo, Gianelle, Damiano, Grelle, Achim, Kiely, Gerard, Knohl, Alexander, Liu, Dan, Marek, Michal V., Merbold, Lutz, Montagnani, Leonardo, Panferov, Oleg, Peltoniemi, Mikko, Rambal, Serge, Raschi, Antonio, Varlagin, Andrej, and Xia, Jiangzhou

Published
2014
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9. Estimation of gross primary production over the terrestrial ecosystems in China

Author

Li, Xianglan, Liang, Shunlin, Yu, Guirui, Yuan, Wenping, Cheng, Xiao, Xia, Jiangzhou, Zhao, Tianbao, Feng, Jinming, Ma, Zhuguo, Ma, Mingguo, Liu, Shaomin, Chen, Jiquan, Shao, Changliang, Li, Shenggong, Zhang, Xudong, Zhang, Zhiqiang, Chen, Shiping, Ohta, Takeshi, Varlagin, Andrej, Miyata, Akira, Takagi, Kentaro, Saiqusa, Nobuko, and Kato, Tomomichi

Published
2013
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18. Satellite-Based Analysis of Evapotranspiration and Water Balance in the Grassland Ecosystems of Dryland East Asia

Author

Xia, Jiangzhou, primary, Liang, Shunlin, additional, Chen, Jiquan, additional, Yuan, Wenping, additional, Liu, Shuguang, additional, Li, Linghao, additional, Cai, Wenwen, additional, Zhang, Li, additional, Fu, Yang, additional, Zhao, Tianbao, additional, Feng, Jinming, additional, Ma, Zhuguo, additional, Ma, Mingguo, additional, Liu, Shaomin, additional, Zhou, Guangsheng, additional, Asanuma, Jun, additional, Chen, Shiping, additional, Du, Mingyuan, additional, Davaa, Gombo, additional, Kato, Tomomichi, additional, Liu, Qiang, additional, Liu, Suhong, additional, Li, Shenggong, additional, Shao, Changliang, additional, Tang, Yanhong, additional, and Zhao, Xiang, additional

Published
2014
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