Abstract
Protected areas (PAs) are central to China’s forest conservation strategy, yet their effectiveness for carbon storage across governance and management contexts remains unclear. A clearer understanding of their current and future carbon benefits is essential for informing conservation and climate policy. Here, using 1-km GEDI satellite data, we show that forests within China’s PAs store on average 68.29 ± 0.17 Mg C ha⁻¹ – about 13% more than matched unprotected forests. Carbon gains are highest in national parks (18.19 ± 0.69 Mg C ha⁻¹) and in managed naturally regenerating forests (9.85 ± 0.36 Mg C ha⁻¹), although some PA categories underperform. To assess future potential, we integrate GEDI observations with CMIP6 climate projections and find that under the high-emission SSP5-8.5 climate scenario, strongly protected areas could retain an additional ~600 ± 36.39 Tg C by 2100. These results show that strong protection and optimized management substantially enhance China’s carbon sink, offering major opportunities for climate mitigation and biodiversity conservation.
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Enhancing carbon sinks in China using a spatially-optimized forestation strategy
The effectiveness of global protected areas for climate change mitigation
Carbon storage through China’s planted forest expansion
Data availability
Vector layers for national boundaries are available from National Catalogue Service for Geographic Information, National Geomatics Center of China at http://www.webmap.cn/. The PAs spatial data is available from the National Earth System Science Data Center, National Science & Technology Infrastructure of China at http://www.geodata.cn/. The national park maps are available at https://www.forestry.gov.cn/ghjh.jhtml. GEDI L4B data is freely available from Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC) at GEDI L4B Gridded Aboveground Biomass Density, Version 2.1 at https://doi.org/10.3334/ORNLDAAC/2299. The annual land cover dataset in China for 2000 and 2019 are available from https://zenodo.org/records/4417810. The WWF ecoregions and biomes can be downloaded at https://www.worldwildlife.org/publications/terrestrial-ecoregions-of-the-world. The forest management map is available at https://zenodo.org/records/5879022. The intact forest landscape map is available at https://intactforests.org/world.map.html. The gridded population count dataset is available from https://www.resdc.cn/DOI/DOI.aspx?DOIid=32. The mean precipitation and temperature datasets in China are processed from https://zenodo.org/records/3114194 and https://zenodo.org/records/3185722. Elevation and slope are processed using CGIAR SRTM downloaded from https://developers.google.com/earth-engine/datasets/catalog/CGIAR_SRTM90_V4. Distance to cities and roads are obtained using global urban boundaries downloaded from https://data-starcloud.pcl.ac.cn/zh/resource/14 and global roads open assess dataset downloaded from https://sedac.ciesin.columbia.edu/data/set/groads-global-roads-open-access-v1/data-download. Travel time to cities dataset can be downloaded from https://forobs.jrc.ec.europa.eu/products/gam/download.php. The climate data in 1901–2020 and 2021–2100 used for the LPJ-GUESS simulation are available at the Climatic Research Unit https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.08/ and CMIP6 https://aims2.llnl.gov/search. The atmospheric CO2 concentration data for 1901–1958, 1959–2020, and 2021–2100 are available at https://doi.org/10.1073/pnas.0406982101, https://gml.noaa.gov/ccgg/trends/, and https://iiasa.ac.at/models-tools-data/ssp. The data generated in this study are available at: https://zenodo.org/records/17900200.
Code availability
The codes supporting the main findings of this study are available at Zenodo repository: https://zenodo.org/records/17900200.
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Acknowledgements
This study was financed by Intergovernmental International Science and Technology Innovation Cooperation Program Under National Key Research and Development Plan (grant 2024YFE0198600, to W.L.), National Natural Science Foundation of China (grant 42522106 and 42171369, to W.L.; grant 42425103, to F.C.), Humboldt Research Fellowship for Experienced Researchers (grant to W.L.), the Youth Innovation Promotion Association Chinese Academy of Sciences (grant Y2022051, to W.L.), and the Key Deployment Program funded by the Aerospace Information Research Institute Chinese Academy of Sciences (E4Z202021F, to W.L.). We further consider this study a contribution to Center for Ecological Dynamics in a Novel Biosphere (ECONOVO), funded by Danish National Research Foundation (grant DNRF173, to J.-C.S.).
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W.L. and J.-C.S. designed the study. Y.W.F conducted the data analysis with help from Z.N., H.L.Q., and L.W. F.C helped with the attribution and consistency analysis. B.Z. helped with the Monte Carlo uncertainty evaluation and the downscaling analysis. W.L. and Y.W.F. wrote the first draft of the manuscript with input from J.-C.S., and all authors contributed subsequent versions of the paper.
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Fu, Y., Li, W., Niu, Z. et al. Enhanced forest carbon gains from stronger protection in China’s protected areas.
Nat Commun (2026). https://doi.org/10.1038/s41467-026-69505-x
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DOI: https://doi.org/10.1038/s41467-026-69505-x
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