Journal article
Region-specific forest structure pathways reveal climate effects on old-growth tropical forest biomass
Scientific Reports, Vol.16, pp.1-19
2026
Abstract
Old-growth tropical forests store vast amounts of carbon in their aboveground biomass (AGB), yet the relative roles of abiotic factors such as climate, soil, and topography in governing its spatial distribution remain poorly understood. In particular, the degree to which climate acts on AGB through forest structure is still poorly quantified at the pantropical scale. Using a pantropical dataset of more than 2,000 old-growth forest plots and a structure-explicit framework, we assess how climate influences AGB through its effects on four structural attributes: basal area, mean diameter, stem density, and basal area-weighted wood density. We find that climate shapes AGB primarily through its effects on forest structure. However, structural attributes respond to climate in opposite directions, so climate’s net effect on AGB largely cancels out, and no clear climate-AGB relationship emerges across tropical regions. Moreover, only wood density responds consistently, decreasing with annual precipitation and increasing with precipitation seasonality, whereas all other attributes respond to climate differently from one region to another. This geographical variation further obscures any global climatic signal on AGB and points to the role of biogeographic history in shaping forest structure. Our findings highlight the central role of the climate-structure nexus in explaining AGB variation, and call for structure-explicit models to improve carbon stock predictions and inform climate adaptation strategies.
Details
- Title
- Region-specific forest structure pathways reveal climate effects on old-growth tropical forest biomass
- Authors
- Pauline Depoortere - University of LiègeDavid Bauman - Centre National de la Recherche ScientifiqueAdeline Fayolle - Centre de Coopération Internationale en Recherche Agronomique pour le DéveloppementOliver Phillips - University of LeedsLalasia Bialic-Murphy - Swiss Federal Institute for Forest, Snow and Landscape ResearchConstantin M. Zohner - The University of TokyoArthur Vander Linden - University of Liege (Belgium)Antoine Plumacker - University of LiègeHugo de Lame - University of LiègeJingjing Liang - Purdue University West LafayetteSee full text for complete author listingAndrew R. Marshall - University of the Sunshine Coast
- Publication details
- Scientific Reports, Vol.16, pp.1-19
- Publisher
- Nature Publishing Group
- Date published
- 2026
- DOI
- 10.1038/s41598-026-61888-7
- ISSN
- 2045-2322
- Copyright note
- 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/.
- Data Availability
- Tree-by-tree data from ForestPlots.net and GFBI are not publicly available due to data-sharing agreements. Raw forest inventory data are commonly subject to a wide array of confidentiality clauses in regard to open access policies. Despite recent efforts to make some of these data fully open78,79, some governments and private data owners, especially those from developing countries, have decided to keep their data confidential. This decision is based on well-founded arguments to protect certain trees or forests (because of their large size or protected taxonomic status) from illegal logging or trespassing and to protect landowners’ privacy against the misuse of plot information such as the geographic coordinates. Researchers interested in accessing the tree-by-tree data may submit a formal data request to ForestPlots.net and to the Global Forest Biodiversity Initiative (GFBI) (via Science-i.org). Requests are reviewed on a case-by-case basis and are subject to approval by the original data contributors. However, a summary dataset containing plot-level data (without geographic coordinates and without plot IDs), together with the code used to reproduce the analyses, is publicly available at https://doi.org/10.5281/zenodo.21169203 (see LICENSE for full terms)80. If you encounter issues reproducing the analyses using this code, or have questions about collaboration, please contact the corresponding author: Pauline Depoortere (depoort.p@gmail.com). Data from Panama used in this study are publicly available via permanent archives: Barro Colorado 50-ha plot: https://doi.org/10.15146/5xcp-0d46, BCI plot taxonomy: https://doi.org/10.15146/R3FH61, Panama 65 plot network: https://doi.org/10.15146/mdpr-pm59. French NFI campaigns (Raw Data) 2005 and following annual surveys were downloaded from https://inventaire-forestier.ign.fr/spip.php?rubrique159, site accessed on December 13th, 2015. All climate data were retrieved (https://earthengine.google.com), except for CHELSA data which are publicly available at https://chelsa-climate.org, WorldClim at https://www.worldclim.org, and CRU at https://crudata.uea.ac.uk/cru/data/hrg. All data were processed using Google Earth Engine. In addition, topographic data (elevation and slope) at 30 m resolution from the Shuttle Radar Topography Mission (SRTM) and soil data (clay content, sand content, organic carbon content, water content, bulk density, and pH) at 250 m resolution from the SoilGrids250m system were also accessed and processed through Google Earth Engine. All references and download links for the environmental datasets used in this study are provided in the Methods section and Extended Data Table 3.
- Grant note
- P.D. was supported by the Belgian National Fund for Scientific Research (FNRS) under grant FC41175. G.A. acknowledges support from the Italian National Recovery Plan (PNRR) through the National Biodiversity Future Centre [NBFC – Missione 4 Componente 2, Investimento 1.4 – D.D. 1034 17/06/2022, CN00000033]. T.F. and O.P. were supported by the Natural Environment Research Council (grants NE/W001691/1 and NE/N011570/1). T.F., B.M., and B.Ma. were supported by the Brazilian Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) through project PVE-177-2012. J.A. was supported by the Natural Environment Research Council (grants NE/Z504191/1 and NE/T011084/1), the Royal Society (grant RG\R1\251370), and the Leverhulme Trust (grant RPG-2024-342). W.H. acknowledges support from the Belgian Science Policy Office (BELSPO) through the grants FED-tWIN2019-prf-075-CongoFORCE, EF/211/TREE4FLUX, and B2/233/P1/DAMOCO; from the Belgian Directorate-General for Development Cooperation and Humanitarian Aid (DGD) through the PilotMABplus project; and from the Flemish Research Council (FWO) via the grants G014123N-COBARCHIVES and O.0026.22-CANOPI. B.M. was supported by the National Council for Scientific and Technological Development (CNPq), Brazil, through the PELD projects 441572/2020-0 and 445984/2024-4, and the Productivity Grant PQ-CNPq 303492/2022-8. B.Ma. was supported by the National Council for Scientific and Technological Development (CNPq), Brazil, through a Productivity Grant (Bolsa Produtividade em Pesquisa) PQ-CNPq. L.A. was supported by the National Council for Scientific and Technological Development (CNPq), Brazil, through the Productivity Fellowship PQ-CNPq 314416/2020-0. J.M. was supported by NASA (A.7 Biodiversity Grant Award 80NSSC21K1146) and the U.S. National Science Foundation (CNH-2 Grant Award 2009669). C.Z. was supported by DOB Ecology and a European Research Council (ERC) Consolidator Grant under the European Union’s Horizon Europe research and innovation programme (grant agreement No. 101229851, CHILL-TIME). H.P. was supported by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. H2020-MSCA-ITN-2020–956355 as part of the Skill for Action project. A.H. was supported by the German Research Foundation (DFG), grant HE 2719/14-1. J.Do. was supported by the Ministry of Education, Youth and Sports of the Czech Republic (MSMT) through the INTER-ACTION project LUAUS24258. J.Da. was supported by the Science & Engineering Research Board, Department of Science & Technology, Government of India (SRG/2022/002286), and by a Seed Grant from SRM University-AP (SRMAP/URG/E&PP/2022-23/012). S.K. was supported by the Science & Engineering Research Board, Department of Science & Technology, Government of India (PDF/2021/003742/LS). L.W. was supported by the Gabonese Government. G.N. was supported by the Horizon Europe project SUPERB (grant 101036849). H.C. was supported by the Natural Sciences and Engineering Research Council of Canada (grants RGPIN-2019-05109 and STPGP 506284). J.Ba. acknowledges funding support from the Francqui Foundation in Belgium, from BELSPO through theSTEREO IV AFRO-CARDS (SR/00/410) and Biodiversa+ CoForFunc (RT/24/CoForFunc) projects, and from the FNRS EOS callthrough the CANOPi project (O.0026.22).
- Organisation Unit
- Tropical Forests and People Research Centre; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991254328302621
- Output Type
- Journal article
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