Incorporating site suitability and carbon sequestration of tree species into China’s climate-adaptive forestation
Strategic selection and precise matching of climate-resilient tree species are crucial for maximizing the mitigation and adaptation potential of Climate-Smart Forestry. However, current forestation plans often overlook species-specific environmental shifts, leading to suboptimal long-term carbon sequestration. Here we developed a climate-adaptive optimization framework to guide tree species selection and planting in China, based on projected habitat suitability and range shifts under future climate scenarios. Utilizing over 200,000 tree records from China's National Forest Inventory (1999-2018), we quantified habitat suitability declines of 12.1%-42.9% for currently dominant plantation species by 2060 due to climate change. By optimizing species-site matching and strategically harvesting timber at peak carbon uptake, we identified 43.2 million hectares suitable for climate-resilient forestation between 2025 and 2060, enabling the planting of approximately 46 billion climate-adapted trees with a total sequestration potential of 3822.6 Tg of carbon-a 28.7% increase compared to unmanaged scenarios. Our study highlights the importance of optimizing adaptive forestation strategies to enhance carbon sequestration under future climate conditions, providing technical guidance for climate-resilient forest management in support of China's net-zero commitment.
Authors
- Xiangzhong Luo
- Trevor F. Keenan (ORCID: https://orcid.org/0000-0002-3347-0258)
- Chiwei Xiao
- Peng Gong (ORCID: https://orcid.org/0000-0003-1513-3765)
- Meinan Zhang
- Liyong Fu (ORCID: https://orcid.org/0000-0002-5794-9458)
- Yao Zhang (ORCID: https://orcid.org/0000-0002-7468-2409)
- Shirong Liu (ORCID: https://orcid.org/0000-0002-1103-9803)
Institutions
- Hong Kong Baptist University (HK)
- Lawrence Berkeley National Laboratory (US)
- National University of Singapore (SG)
- Chinese Academy of Sciences (CN)
- Peking University (CN)
- Institute of Forest Resource Information Techniques (CN)
- Chinese Academy of Forestry (CN)
- Institute of Forest Ecology, Environment and Protection (CN)
- Institute of Geographic Sciences and Natural Resources Research (CN)
- University of Hong Kong (HK)
Publication Details
- Journal
- Science Bulletin
- Published
- 2025-03-17
- DOI
- https://doi.org/10.1016/j.scib.2025.03.035
- Citations
- 17
- Primary Topic
- Forest ecology and management
- Type
- article
- Field-Weighted Citation Impact
- 39.32
Funders
- National Aeronautics and Space Administration
- Ministry of Science and Technology of the People's Republic of China
- National Key Research and Development Program of China