Search

Menu
Search
in Ecology

Forest connectivity boosts carbon recovery in regenerating Atlantic Forests

169 Views


Abstract

Understanding the fate of carbon stocks in human-modified tropical landscapes is critical for mitigating climate change. Yet quantifying the impacts of landscape connectivity on the potential of regrowing forests to sequester carbon remains underrepresented. Using remote sensing and a space-for-time substitution approach, we analyzed aboveground carbon accumulation across the Brazilian Atlantic Forest. Forest connectivity emerged as a key determinant of carbon gains, with accumulation rates increasing by 43%–69% from fragmented to highly connected landscapes. In the western and coastline region, highly connected forests accumulated over three times more carbon (3.03 ± 0.81 vs. 0.93 ± 0.34 Mg C ha⁻¹ yr⁻¹) than those in low-connectivity areas. We modeled carbon stocks and found that full protection of secondary forests as of 2020 could increase stocks by 35% (132 Tg C) by 2030. Our results highlight the importance of protecting both old-growth and secondary forests while enhancing connectivity through targeted restoration. Strengthening conservation policies that integrate spatial connectivity is essential to maximizing the climate mitigation potential of tropical forests.

Data availability

All datasets supporting this study are publicly available on Zenodo (https://doi.org/10.5281/zenodo.16838291).

External data sources include the ESA CCI Biomass 2020 dataset (https://catalogue.ceda.ac.uk/uuid/af60720c1e404a9e9d2c145d2b2ead4e/), the MapBiomas dataset (https://brasil.mapbiomas.org/en/colecoes-mapbiomas/), and the TerraClimate evapotranspiration dataset (https://www.climatologylab.org/terraclimate.html).

Code to generate secondary forest age from MapBiomas Collection 7 was written by Viola Heinrich. Code to calculate MCWD is available at https://github.com/celsohlsj/RasterMCWD.

Code availability

All code supporting this study analysis and figures are publicly available on Zenodo (https://doi.org/10.5281/zenodo.16838291).

References

  1. Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).

    Google Scholar 

  2. Chazdon, R. L., Blüthgen, N., Brancalion, P. H. S., Heinrich, V. & Bongers, F. Drivers and benefits of natural regeneration in tropical forests. Nat. Rev. Biodivers. 1–17 https://doi.org/10.1038/s44358-025-00043-y (2025).

  3. Roman-Cuesta, R. M. et al. Land remains a blind spot in tracking progress under the Paris Agreement due to lack of data comparability. Commun. Earth Environ. 6, 598 (2025).

    Google Scholar 

  4. Matos, F. A. R. et al. Secondary forest fragments offer important carbon and biodiversity cobenefits. Glob. Change Biol. 26, 509–522 (2020).

    Google Scholar 

  5. Robinson, N. et al. Protect young secondary forests for optimum carbon removal. Nat. Clim. Chang. 15, 793–800 (2025).

    Google Scholar 

  6. Haneda, L. E. et al. Edge effect impacts on forest structure and carbon stocks in REDD+projects: an assessment in the Amazon using UAV-LiDAR. For. Ecol. Manag. 585, 122646 (2025).

    Google Scholar 

  7. Silva Junior, C. H. L. et al. Persistent collapse of biomass in Amazonian forest edges following deforestation leads to unaccounted carbon losses. Sci. Adv. 6, eaaz8360 (2020).

    Google Scholar 

  8. Myers, N., Mittermeier, R. A., Mittermeier, C. G., da Fonseca, G. A. B. & Kent, J. Biodiversity hotspots for conservation priorities. Nature 403, 853–858 (2000).

    Google Scholar 

  9. Brancalion, P. H. S. et al. Global restoration opportunities in tropical rainforest landscapes. Sci. Adv. 5, eaav3223 (2019).

    Google Scholar 

  10. Griscom, B. W. et al. National mitigation potential from natural climate solutions in the tropics. Philos. Trans. R. Soc. B Biol. Sci. 375, 20190126 (2020).

    Google Scholar 

  11. Ribeiro, M. C., Metzger, J. P., Martensen, A. C., Ponzoni, F. J. & Hirota, M. M. The Brazilian Atlantic Forest: how much is left, and how is the remaining forest distributed? Implications for conservation. Biol. Conserv. 142, 1141–1153 (2009).

    Google Scholar 

  12. Amaral, S. et al. Alarming patterns of mature forest loss in the Brazilian Atlantic Forest. Nat. Sustain. 1–9, https://doi.org/10.1038/s41893-025-01508-w (2025).

  13. de Barros, F. et al. Cost-effective restoration for carbon sequestration across Brazil’s biomes. Sci. Total Environ. 876, 162600 (2023).

    Google Scholar 

  14. Crouzeilles, R. et al. Achieving cost-effective landscape-scale forest restoration through targeted natural regeneration. Conserv. Lett. 13, e12709 (2020).

    Google Scholar 

  15. Crouzeilles, R. et al. There is hope for achieving ambitious Atlantic Forest restoration commitments. Perspect. Ecol. Conserv. 17, 80–83 (2019).

    Google Scholar 

  16. Heinrich, V. H. A. et al. Large carbon sink potential of secondary forests in the Brazilian Amazon to mitigate climate change. Nat. Commun. 12, 1–11 (2021).

    Google Scholar 

  17. MapBiomas Project. Collection 7.1 of the Annual Land Use Land Cover Maps of Brazil. Available at: projects/mapbiomas-public/assets/brazil/lulc/collection7/mapbiomas_collection70_integration_v2. Accessed 17 September 2023.

  18. Santoro, M. & Cartus, O. ESA Biomass climate change initiative (Biomass_cci): global datasets of forest above-ground biomass for the years 2010, 2017, 2018, 2019 and 2020, v4. 5183 Files, 302039459020 B NERC EDS Center for Environmental Data Analysis, https://doi.org/10.5285/AF60720C1E404A9E9D2C145D2B2EAD4E (2023).

  19. Resende, A. F. et al. How to enhance Atlantic Forest protection? Dealing with the shortcomings of successional stages classification. Perspect. Ecol. Conserv. 22, 101–111 (2024).

    Google Scholar 

  20. Piffer, P. R. et al. Ephemeral forest regeneration limits carbon sequestration potential in the Brazilian Atlantic Forest. Glob. Change Biol. 28, 630–643 (2022).

    Google Scholar 

  21. Smith, C. C. et al. Amazonian secondary forests are greatly reducing fragmentation and edge exposure in old-growth forests. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/ad039e (2023).

    Google Scholar 

  22. Chen, N. et al. Revealing the spatial variation in biomass uptake rates of Brazil’s secondary forests. ISPRS J. Photogramm. Remote Sens. 208, 233–244 (2024).

    Google Scholar 

  23. Piotto, D. et al. Nearby mature forest distance and regenerating forest age influence tree species composition in the Atlantic forest of Southern Bahia, Brazil. Biodivers. Conserv 30, 2165–2180 (2021).

    Google Scholar 

  24. Chaves, ÓM., Bicca-Marques, J. C. & Chapman, C. A. Quantity and quality of seed dispersal by a large arboreal frugivore in small and large Atlantic forest fragments. PLoS ONE 13, e0193660 (2018).

    Google Scholar 

  25. Fricke, E. C., Cook-Patton, S. C., Harvey, C. F. & Terrer, C. Seed dispersal disruption limits tropical forest regrowth. Proc. Natl. Acad. Sci. USA 122, e2500951122 (2025).

    Google Scholar 

  26. Poorter, L. et al. Multidimensional tropical forest recovery. Science 374, 1370–1376 (2021).

    Google Scholar 

  27. Magnago, L. F. S., Rocha, M. F., Meyer, L., Martins, S. V. & Meira-Neto, J. A. A. Microclimatic conditions at forest edges have significant impacts on vegetation structure in large Atlantic forest fragments. Biodivers. Conserv. 24, 2305–2318 (2015).

    Google Scholar 

  28. Silva, C. H. L. et al. Deforestation-induced fragmentation increases forest fire occurrence in central Brazilian Amazonia. Forests 9, 305 (2018).

  29. Rosan, T. M. et al. Fragmentation-driven divergent trends in burned area in Amazonia and Cerrado. Front. For. Glob. Change 5, 801408 (2022).

  30. Broggio, I. S., Silva-Junior, C. H. L., Nascimento, M. T., Villela, D. M. & Aragão, L. E. O. C. Quantifying landscape fragmentation and forest carbon dynamics over 35 years in the Brazilian Atlantic Forest. Environ. Res. Lett. 19, 034047 (2024).

    Google Scholar 

  31. Groeneveld, J. et al. Long-term carbon loss in fragmented Neotropical forests. Nat. Commun. 5, 1–8 (2014). uuml rgen.

    Google Scholar 

  32. Lapola, D. M. et al. The drivers and impacts of Amazon forest degradation. Science 379, eabp8622 (2023).

    Google Scholar 

  33. Brancalion, P. H. S., Hua, F., Joyce, F. H., Antonelli, A. & Holl, K. D. Moving biodiversity from an afterthought to a key outcome of forest restoration. Nat. Rev. Biodivers. 1–14 https://doi.org/10.1038/s44358-025-00032-1 (2025).

  34. Crouzeilles, R. et al. Ecological restoration success is higher for natural regeneration than for active restoration in tropical forests. Sci. Adv. 3, e1701345 (2017).

    Google Scholar 

  35. Rosa, M. R. et al. Hidden destruction of older forests threatens Brazil’s Atlantic Forest and challenges restoration programs. Sci. Adv. 7, 1–9 (2021).

    Google Scholar 

  36. Silveira, M. V. F. et al. Observed shifts in regional climate linked to Amazon deforestation. Commun. Earth Environ. 6, 948 (2025).

    Google Scholar 

  37. Safar, N. V. H., Magnago, L. F. S. & Schaefer, C. E. G. R. Resilience of lowland Atlantic forests in a highly fragmented landscape: insights on the temporal scale of landscape restoration. For. Ecol. Manag. 470–471, 118183 (2020).

    Google Scholar 

  38. Rozendaal, D. M. A. et al. Biodiversity recovery of Neotropical secondary forests. Sci. Adv. 5, eaau3114 (2019).

    Google Scholar 

  39. Poorter, L. et al. Biomass resilience of Neotropical secondary forests. Nature 530, 211–214 (2016).

    Google Scholar 

  40. Heinrich, V. H. A. et al. The carbon sink of secondary and degraded humid tropical forests. Nature 615, 436–442 (2023).

    Google Scholar 

  41. Santoro, M. et al. Design and performance of the Climate Change Initiative Biomass global retrieval algorithm. Sci. Remote Sens. 10, 100169 (2024).

    Google Scholar 

  42. Araza, A. et al. A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps. Remote Sens. Environ. 272, 112917 (2022).

    Google Scholar 

  43. Begliomini, F. N. & Brancalion, P. H. S. Are state-of-the-art LULC maps able to track ecological restoration efforts in Brazilian Atlantic Forest? in Proc. IGARSS 2024 IEEE International Geoscience and Remote Sensing Symposium, 4748–4752, https://doi.org/10.1109/IGARSS53475.2024.10641177 (2024).

  44. Málaga, N. et al. GFOI Rapid Response Module: Guidance to Inform the Use of Space-Based Forest Biomass-Related Data in MRV Procedures. Global Forest Observations Initiative. 38 pp. Available at: https://www.reddcompass.org/mgd/resources/GFOI_BiomassMaps_Guidance-20251022.pdf (2025). Accessed 10 November 2025.

  45. Su, Y. et al. Pervasive but biome-dependent relationship between fragmentation and resilience in forests. Nat. Ecol. Evol. 9, 1670–1684 (2025).

    Google Scholar 

  46. Silva Junior, C. H. L. et al. Benchmark maps of 33 years of secondary forest age for Brazil. Sci Data 7, 269 (2020).

  47. Harris, N., Goldman, E. D. & Gibbes, S. Spatial database of planted trees (SDPT Version 1.0). https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-10 (2019).

  48. Dong, H. et al. 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4: Agriculture, Forestry and Other Land Use. Available at: https://www.ipcc-nggip.iges.or.jp/public/2019rf/vol4.html (IPCC, Geneva, Switzerland, 2019) Accessed 24 August 2025.

  49. Ferreira, I. J. M. et al. Potential aboveground biomass increase in Brazilian Atlantic Forest fragments with climate change. Glob. Change Biol. 29, 3098–3113 (2023).

  50. de Paula, M. D., Costa, C. P. A. & Tabarelli, M. Carbon storage in a fragmented landscape of Atlantic Forest: the role played by edge-affected habitats and emergent trees. Trop. Conserv. Sci. 4, 349–358 (2011).

    Google Scholar 

  51. Zanne, A. E. et al. Data from: towards a worldwide wood economics spectrum. https://doi.org/10.5061/DRYAD.234 (2009).

  52. Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).

    Google Scholar 

  53. Silva Junior, C. H. L. & Campanharo, W. A. Maximum Cumulative Water Deficit – MCWD: a R language script (v1.1.0). Zenodo https://doi.org/10.5281/zenodo.5034650 (2019).

  54. Aragão, L. E. O. C. et al. Spatial patterns and fire response of recent Amazonian droughts. Geophys. Res. Lett. 34, https://doi.org/10.1029/2006GL028946 (2007).

  55. Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data 5, 170191 (2018).

    Google Scholar 

  56. Farr, T. G. et al. The shuttle radar topography mission. Rev. Geophys. 45, https://doi.org/10.1029/2005RG000183 (2007).

  57. Silva, J. L. A., Souza, A. F. & Vitória, A. P. Mapping functional tree regions of the Atlantic Forest: how much is left and opportunities for conservation. Environ. Conserv. 49, 164–171 (2022).

    Google Scholar 

  58. Brown, J. L. et al. Seeing the forest through many trees: multi-taxon patterns of phylogenetic diversity in the Atlantic Forest hotspot. Divers. Distrib. 26, 1160–1176 (2020).

    Google Scholar 

  59. Vogt, P. Measuring forest area density to quantify forest fragmentation. European Commission http://ies-ows.jrc.ec.europa.eu/gtb/GTB/psheets/GT (2018).

  60. Richards, F. J. A flexible growth function for empirical use. J. Exp. Bot. 10, 290–301 (1959).

    Google Scholar 

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

    Google Scholar 

  62. MCTI. Relatório do Inventário Nacional 1990–2022. Ministério da Ciência, Tecnologia e Inovação, Brazil. Available at: https://www.gov.br/mcti/pt-br/acompanhe-o-mcti/sirene/publicacoes/relatorios-bienais-de-transparencia-btrs/Relatorio_deInventario_NacionalNIR_2024_PORT.pdf (2024) Acessed March 2025.

  63. Pinheiro, J. C. & Bates, D. M. Mixed-Effects Models in S and S-PLUS. https://doi.org/10.1007/b98882 (Springer, 2000).

  64. Zimbres, B. et al. Improving estimations of GHG emissions and removals from land use change and forests in Brazil. Environ. Res. Lett. 19, 094024 (2024).

    Google Scholar 

Download references

Acknowledgements

S.S. and L.E.O.C.A. acknowledge funding from the UK Natural Environment Research Council (NERC) project, Amazon-SOS (NE/X019055/1). T.M.R. and S.S. acknowledge support through Schmidt Sciences, LLC. V.H. acknowledges support from the Consultative Group on International Agricultural Research (CGIAR) MITIGATE+ project, the Open Earth Monitor Project funded by the European Union (grant agreement number 101059548) and NextGenCarbon (https://www.nextgencarbon-project.eu/) Project. For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) license to any author-accepted manuscript version arising from this submission.

Author information

Authors and Affiliations

  1. Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK

    Thais M. Rosan, Stephen Sitch & Luiz E. O. C. Aragão

  2. Department of Forest Sciences, “Luiz de Queiroz” College of Agriculture, University of São Paulo, Piracicaba, Brazil

    Laura B. Vedovato & Pedro H. S. Brancalion

  3. Global Land Monitoring Group, Section 1.4 Remote Sensing and Geoinformatics, GFZ Helmholtz Centre for Geosciences, Potsdam, Germany

    Viola H. A. Heinrich

  4. Instituto de Pesquisa Ambiental da Amazônia (IPAM), Brasília, Brazil

    Celso H. L. Silva-Junior

  5. Universidade Federal do Maranhão (UFMA), São Luís, Brazil

    Celso H. L. Silva-Junior

  6. National Institute for Space Research (INPE), São José dos Campos, Brazil

    Luiz E. O. C. Aragão

Authors

  1. Thais M. Rosan
    View author publications

    Search author on:PubMed Google Scholar

  2. Laura B. Vedovato
    View author publications

    Search author on:PubMed Google Scholar

  3. Viola H. A. Heinrich
    View author publications

    Search author on:PubMed Google Scholar

  4. Celso H. L. Silva-Junior
    View author publications

    Search author on:PubMed Google Scholar

  5. Pedro H. S. Brancalion
    View author publications

    Search author on:PubMed Google Scholar

  6. Stephen Sitch
    View author publications

    Search author on:PubMed Google Scholar

  7. Luiz E. O. C. Aragão
    View author publications

    Search author on:PubMed Google Scholar

Contributions

T.M.R. led the manuscript writing, designed the study, and compiled, analyzed, and processed the data. L.B.V. and P.H.S.B. provided field data for validation and contributed to writing. L.B.V. also performed field data analysis. V.H. and C.H.L.S.J. assisted with data processing and methodology design and contributed to writing. L.E.O.C.A. and S.S. assisted with study design and contributed to reviewing the manuscript.

Corresponding author

Correspondence to
Thais M. Rosan.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Communications Earth and Environment thanks the anonymous reviewers for their contribution to the peer review of this work. Primary handling editors: Rossella Guerrieri, Mengjie Wang. A peer review file is available.

Additional information

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

Supplementary information

Transparent Peer Review File (download PDF )

Supplementary Material (download PDF )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Cite this article

Rosan, T.M., Vedovato, L.B., Heinrich, V.H.A. et al. Forest connectivity boosts carbon recovery in regenerating Atlantic Forests.
Commun Earth Environ (2026). https://doi.org/10.1038/s43247-026-03480-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s43247-026-03480-5

Source: Ecology - nature.com

HST-former: hierarchical spatio-temporal aggregation for video-based animal re-identification

Author Correction: Trade-offs in the externalities of pig production are not inevitable

This portal is not a newspaper as it is updated without periodicity. It cannot be considered an editorial product pursuant to law n. 62 of 7.03.2001. The author of the portal is not responsible for the content of comments to posts, the content of the linked sites. Some texts or images included in this portal are taken from the internet and, therefore, considered to be in the public domain; if their publication is violated, the copyright will be promptly communicated via e-mail. They will be immediately removed.

Back to Top
Close