Protect young secondary forests for optimum carbon removal

Abstract Avoiding severe global warming requires large-scale removals of atmospheric carbon dioxide. Forest regeneration offers cost-effective carbon removals, but annual rates vary substantially by location and forest age. Here we generate grid-level (~1-km 2 ) growth curves for aboveground live carbon in naturally regrowing forests by combining 109,708 field estimates with 66 environmental covariates. Across the globe and the first 100 years of growth, maximum carbon removal rates varied 200-fold, with the greatest rates estimated in ~20- to 40-year-old forests. Despite a focus on new forests for natural climate solutions, protecting existing young secondary forests can provide up to 8-fold more carbon removal per hectare than new regrowth. These maps could help to target the optimal ages and locations where a key carbon removal strategy could be applied, and improve estimates of how secondary forests contribute to global carbon cycling.

Authors

Institutions

Publication Details

Journal
Nature Climate Change
Published
2025-06-24
DOI
https://doi.org/10.1038/s41558-025-02355-5
Citations
19
Primary Topic
Forest Management and Policy
Type
article
Field-Weighted Citation Impact
21.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Protect young secondary forests for optimum carbon removal

Kristine Lister, Adriane Esquivel‐Muelbert, C. Ronnie Drever, Viola Heinrich et al.
19 citations
Nature Climate Change
Forest Management and Policy
21.00
article

Protect young secondary forests for optimum carbon removal

Kristine Lister, Adriane Esquivel‐Muelbert, C. Ronnie Drever, Viola Heinrich, Nathaniel Robinson, Sassan Saatchi, Yidi Xu, Thomas A. M. Pugh, Philippe Ciais, Celso H. L. Silva, Susan C. Cook‐Patton, David A. Gibbs, Zhihua Liu
article en
19 citations

Abstract

Abstract Avoiding severe global warming requires large-scale removals of atmospheric carbon dioxide. Forest regeneration offers cost-effective carbon removals, but annual rates vary substantially by location and forest age. Here we generate grid-level (~1-km 2 ) growth curves for aboveground live carbon in naturally regrowing forests by combining 109,708 field estimates with 66 environmental covariates. Across the globe and the first 100 years of growth, maximum carbon removal rates varied 200-fold, with the greatest rates estimated in ~20- to 40-year-old forests. Despite a focus on new forests for natural climate solutions, protecting existing young secondary forests can provide up to 8-fold more carbon removal per hectare than new regrowth. These maps could help to target the optimal ages and locations where a key carbon removal strategy could be applied, and improve estimates of how secondary forests contribute to global carbon cycling.

Nature Climate ChangeVol. 15(7)
California Institute of Technology (US), The Nature Conservancy (US), World Resources Institute (US), Jet Propulsion Laboratory (US), Duke University (US), Lund University (SE), Université Paris-Saclay (FR), University of Bristol (GB), Instituto de Pesquisa Ambiental da Amazônia (BR), Laboratoire des Sciences du Climat et de l'Environnement (FR), Forest Research (GB), GFZ Helmholtz Centre for Geosciences (DE), Universidade Federal do Maranhão (BR), Smithsonian Environmental Research Center (US), World Agroforestry Centre (KE), Nature Conservancy of Canada (CA), University of Birmingham (GB)
European Commission, Lunds Universitet, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Vetenskapsrådet, Consortium of International Agricultural Research Centers
Openalex Percentile: Top 0%
Forest Management and Policy
21.00
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.