Abstract
Background
Forest is the largest biomass carbon (C) pool in China, taking up a substantial amount of atmospheric carbon dioxide. Although it is well understood that planted forests (PFs) act as a large C sink, the contribution of human management to C storage enhancement remains obscure. Moreover, existing projections of forest C dynamics suffer from spatially inconsistent age and type information or neglected human management impacts. In this study, using developed PF age and type maps and data collected from 1371 forest plantation sites in China, we simulated biomass C stock change and quantified management impacts for the time period 2010–2050.
Results
Results show that future forest biomass C increment might have been overestimated by 32.5%–107.5% in former studies. We also found that age-related growth will be by far the largest contributor to PF biomass C increment from 2010 to 2050 (1.23 ± 0.002 Pg C, 1 Pg = 1015 g = 1 billion metric tons), followed by the impact of human management (0.57 ± 0.02 Pg C), while the contribution of climate is slight (0.087 ± 0.04 Pg C). Besides, an additional 0.24 ± 0.07 Pg C can be stored if current PFs are all managed by 2050, resulting in a total increase of 2.13 ± 0.05 Pg C.
Conclusions
Forest management and age-related growth dominate the biomass C change in PFs, while the effect of climatic factors on the accumulation is minor. To achieve the ambitious goal of forest C stock enhancement by 3.5 Pg from 2020 to 2050, we advocate to improve the management of existing forests and reduce the requests for more lands for forest expansion, which helps mitigate potential conflicts with agricultural sectors. Our results highlight that appropriate planning and management are required for sustaining and enhancing biomass C sequestration in China’s PF.
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; You Weibin 2 ; Agathokleous Evgenios 3 ; Zhou Guoyi 3 ; Liu Shirong 4 1 Nanjing University of Information Science & Technology, Institute of Ecology, Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing, China (GRID:grid.260478.f); Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Key Laboratory of Forest Ecology and Environment, China’s National Forestry and Grassland Administration, Beijing, China (GRID:grid.216566.0) (ISNI:0000 0001 2104 9346)
2 Fujian Agriculture and Forestry University, College of Forestry, Fuzhou, China (GRID:grid.256111.0) (ISNI:0000 0004 1760 2876)
3 Nanjing University of Information Science & Technology, Institute of Ecology, Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing, China (GRID:grid.260478.f)
4 Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Key Laboratory of Forest Ecology and Environment, China’s National Forestry and Grassland Administration, Beijing, China (GRID:grid.216566.0) (ISNI:0000 0001 2104 9346)





