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Mapping carbon accumulation potential from global natural forest regrowth


To constrain global warming, we must strongly curtail greenhouse gas emissions and capture excess atmospheric carbon dioxide1,2. Regrowing natural forests is a prominent strategy for capturing additional carbon3, but accurate assessments of its potential are limited by uncertainty and variability in carbon accumulation rates2,3. To assess why and where rates differ, here we compile 13,112 georeferenced measurements of carbon accumulation. Climatic factors explain variation in rates better than land-use history, so we combine the field measurements with 66 environmental covariate layers to create a global, one-kilometre-resolution map of potential aboveground carbon accumulation rates for the first 30 years of natural forest regrowth. This map shows over 100-fold variation in rates across the globe, and indicates that default rates from the Intergovernmental Panel on Climate Change (IPCC)4,5 may underestimate aboveground carbon accumulation rates by 32 per cent on average and do not capture eight-fold variation within ecozones. Conversely, we conclude that maximum climate mitigation potential from natural forest regrowth is 11 per cent lower than previously reported3 owing to the use of overly high rates for the location of potential new forest. Although our data compilation includes more studies and sites than previous efforts, our results depend on data availability, which is concentrated in ten countries, and data quality, which varies across studies. However, the plots cover most of the environmental conditions across the areas for which we predicted carbon accumulation rates (except for northern Africa and northeast Asia). We therefore provide a robust and globally consistent tool for assessing natural forest regrowth as a climate mitigation strategy.

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Fig. 1: Variation in carbon accumulation among biomes and previous land use/disturbance.
Fig. 2: Mapping carbon accumulation potential.
Fig. 3: Predicted rates compared to IPCC defaults.

Data availability

The literature-based dataset (both raw and filtered) and detailed descriptions of the environmental covariates are all available at, where GROA stands for Global Restoration Opportunity Assessment. Data are also archived on Zenodo at The Supplementary Information includes metadata for the literature-derived dataset (Supplementary Table S3, Supplementary sections 4 and 5). We also include data on country-level estimates (see Supplementary Data 1). Spatial data for both aboveground carbon accumulation rates and uncertainty (scaled and unscaled by mean pixel value), as well as belowground carbon accumulation rates can be downloaded from Global Forest Watch ( S.C.C.-P. and N.H. welcome discussions around potential collaborations, and the data are freely available. Source data are provided with this paper.

Code availability

We include code for constructing the global maps and assessing uncertainty at


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We thank the Children’s Investment Fund Foundation, COmON Foundation, the Craig and Susan McCaw Foundation, the Doris Duke Charitable Foundation, the Good Energies Foundation, and Microsoft’s AI for Earth program for financial support. This paper was also developed with funding from the Government of Norway, although it does not necessarily reflect their views or opinions. We thank J. Adams, E. Brolis, A. Hector, J. Ghazoul, M. Hamsik, S. Lewis, B. Luraschi, R. Thadani, B. Tsang and A. Yang for the initial idea development at an Oxford University workshop in 2017. We thank G. Domke and B. Walters (USDA Forest Service) for providing fuzzed FIA plot data, J. Fridman (Swedish National Forest Inventory) for providing Swedish data, and H. Xu for providing raw biomass data from Jainfengling Nature Reserve (Hainan Island, China).

Author information




S.C.C.-P., B.W.G., N.L.H., D.G., K.L., S.S. and L.X. designed the study with input from all authors. S.C.C.-P. contributed to and led all other facets of the study. S.M.L., K.J.A.-T., R.D.B., P.W.E., H.P.G., K.D.H., C.L., R.L., K.P., S.R., S.A.W., C.E.W., W.S.W. and B.W.G. contributed to database compilation, analyses and manuscript preparation. N.L.H., K.L., D.G., T.W.C., D.R., S.S., L.X. and J.v.d.H. constructed the global maps and contributed to manuscript preparation. G.L., R.L., V.H., K.P. and S.R. contributed to database compilation and manuscript preparation. R.L.C., R.A.H., Y.M., P.M., A.P. and J.D.P. contributed to manuscript preparation. S.C.C.-P. is the corresponding author, handling requests for reprints and materials not included in the data repository.

Corresponding author

Correspondence to Susan C. Cook-Patton.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Michael Ryan, Edzo Veldkamp and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Variation in carbon accumulation among biomes.

Observed variation in total plant carbon accumulation rates and soil carbon accumulation rates (mean ± 95% confidence intervals) from the literature-derived dataset. We did not have plant biomass data for subtropical and tropical conifer forests.

Source data

Extended Data Fig. 2 Accumulation of coarse woody debris and litter carbon through time.

We did not find studies describing litter (black) or coarse woody debris (grey) pools in temperate savannas, or coarse woody debris in tropical savannas.

Source data

Extended Data Fig. 3 Variation in carbon stocks among biomes.

Carbon pools (mean ± standard error) in coarse woody debris (grey) and litter (black).

Source data

Extended Data Fig. 4 Effect of disturbance intensity on carbon accumulation.

Carbon accumulation in plots with high intensity disturbance (black circles, black line) versus low intensity disturbance (grey circles, grey line). The most disturbed categories had lower residual biomass at the initiation of regrowth (for example, 0 Mg C ha−1 versus 28 Mg C ha−1 in the least disturbed category; Welch’s t-value = 5.9, P < 0.0001), suggesting that the higher rate in the most disturbed category is due to standard sigmoidal growth rates in forests.

Source data

Extended Data Fig. 5 Map of extent of extrapolation per pixel across all covariate layers.

A value of 1 indicates that 100% of pixels fall within the sample range (that is, there is no extrapolation).

Extended Data Fig. 6 Fine-scale variation in rates.

a, Map of predicted carbon accumulation rates in Colombia, as an example. b, Map of predicted rates filtered to the area of opportunity in Griscom et al.3 to demonstrate where these rates might apply.

Extended Data Fig. 7 Coverage of field data.

Distribution of sites after final filtering of the literature-based dataset (blue) and inclusion of the field inventory data (green). We compiled data from forest (dark grey) and savanna biomes (light grey). We restricted savanna data to portions of these grassland-forest matrices with forest cover >25%.

Extended Data Table 1 General approaches for restoring forest or tree cover
Extended Data Table 2 Effect of disturbance intensity on carbon accumulation

Supplementary information

Supplementary Information

This supplementary information file includes additional methodological details (Table S1 and S2), metadata for the literature-derived dataset (Tables S3, S4 and S5), and a list of all publications included in the literature-derived dataset.

Supplementary Data

This supplementary dataset includes country-level summaries of carbon accumulation rates (Mg C ha−1 yr−1) and mitigation potential from natural forest regrowth (Tg C yr−1) under two scenarios for natural forest regrowth. The first scenario represents a biophysical maximum3 and the second is based on national commitments12. Mitigation estimates are illustrative only, based on assumptions of new forest area. Note that the national commitments scenario includes commitments around “forest restoration”, which may or may not describe areas of new forest. The rate column includes rates from pixels that overlap with area of opportunity pixels in Griscom et al3. We only list countries that are a million hectares or larger.

Source data

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Cook-Patton, S.C., Leavitt, S.M., Gibbs, D. et al. Mapping carbon accumulation potential from global natural forest regrowth. Nature 585, 545–550 (2020).

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