Maximizing carbon sequestration potential in Chinese forests through optimal management

Zhen Yu; Shirong Liu; Haikui Li; Jingjing Liang; Weiguo Liu; Shilong Piao; Hanqin Tian; Guoyi Zhou; Chaoqun Lu; Weibin You; Pengsen Sun; Yanli Dong; Stephen Sitch; Evgenios Agathokleous

doi:10.1038/s41467-024-47143-5

Maximizing carbon sequestration potential in Chinese forests through optimal management

Nat Commun. 2024 Apr 11;15(1):3154. doi: 10.1038/s41467-024-47143-5.

Authors

Zhen Yu^{1

2}, Shirong Liu³, Haikui Li⁴, Jingjing Liang⁵, Weiguo Liu⁶, Shilong Piao⁷, Hanqin Tian⁸, Guoyi Zhou⁹, Chaoqun Lu¹⁰, Weibin You¹¹, Pengsen Sun¹², Yanli Dong⁹, Stephen Sitch¹³, Evgenios Agathokleous⁹

Affiliations

¹ Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, China. zyu@nuist.edu.cn.
² Key Laboratory of Forest Ecology and Environment, China's National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, 100091, Beijing, China. zyu@nuist.edu.cn.
³ Key Laboratory of Forest Ecology and Environment, China's National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, 100091, Beijing, China. liusr@caf.ac.cn.
⁴ Key Laboratory of Forest Management and Growth Modelling, China's National Forestry and Grassland Administration, Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, 100091, Beijing, China.
⁵ Forest Advanced Computing and Artificial Intelligence Laboratory (FACAI), Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN, 47907, USA.
⁶ College of Forestry, Northwest agriculture and Forestry University, Yangling, 712100, China.
⁷ Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, 100871, Beijing, China.
⁸ Schiller Institute for Integrated Science and Society, Department of Earth and Environmental Sciences, Boston College, Chestnut Hill, Massachusetts, MA, 02467, USA.
⁹ Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
¹⁰ Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, 50011, USA.
¹¹ College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
¹² Key Laboratory of Forest Ecology and Environment, China's National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, 100091, Beijing, China.
¹³ College of Life and Environmental Sciences, University of Exeter, Exeter, UK.

Abstract

Forest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model to make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion in biomass carbon stock by 13.6 ± 1.5 Pg C from 2020 to 2100, with additional sink through augmentation of wood product pool (0.6-2.0 Pg C) and spatiotemporal optimization of forest management (2.3 ± 0.03 Pg C). We find that statistical model might cause large bias in long-term projection due to underrepresentation or neglect of wood harvest and forest demographic changes. Remarkably, disregarding the repercussions of harvesting on forest age can result in a premature shift in the timing of the carbon sink peak by 1-3 decades. Our findings emphasize the pressing necessity for the swift implementation of optimal forest management strategies for carbon sequestration enhancement.

MeSH terms

Biomass
Carbon / analysis
Carbon Sequestration*
China
Forests*
Trees

Substances

Carbon

Abstract

MeSH terms

Substances

Grants and funding