Abstract
Original language | English |
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Article number | 2351 |
Number of pages | 12 |
Journal | Nature Communications |
Volume | 16 |
DOIs | |
Publication status | Published - 10 Mar 2025 |
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- 10.1038/s41467-025-56175-4Licence: CC BY
- Sullivan_2025_NC_Variation-wood-density-South-American-tropical-forests_CC
© The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), 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.
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This data package contains data from: Variation in wood density across South American tropical forests
Honorio Coronado, E. N. (Creator) & Roucoux, K. (Creator), ForestPlot, 2025
DOI: 10.5521/forestplots.net/2024_4
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In: Nature Communications, Vol. 16, 2351, 10.03.2025.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Variation in wood density across South American tropical forests
AU - Sullivan, Martin J.P.
AU - Phillips, Oliver L.
AU - Galbraith, David
AU - Almeida, Everton
AU - de Oliveira, Edmar Almeida
AU - Almeida, Jarcilene
AU - Dávila, Esteban Álvarez
AU - Alves, Luciana F.
AU - Andrade, Ana
AU - Aragão, Luiz
AU - Araujo-Murakami, Alejandro
AU - Arets, Eric
AU - Arroyo, Luzmila
AU - Cruz, Omar Aurelio Melo
AU - Baccaro, Fabrício
AU - Baker, Timothy R.
AU - Banki, Olaf
AU - Baraloto, Christopher
AU - Barlow, Jos
AU - Barroso, Jorcely
AU - Berenguer, Erika
AU - Blanc, Lilian
AU - Blundo, Cecilia
AU - Bonal, Damien
AU - Bongers, Frans
AU - Bordin, Kauane Maiara
AU - Brienen, Roel J.W.
AU - Broggio, Igor S.
AU - Burban, Benoit
AU - Cabral, George
AU - Camargo, José Luís
AU - Cardoso, Domingos
AU - Carniello, Maria Antonia
AU - Castro, Wendeson
AU - de Lima, Haroldo Cavalcante
AU - Cavalheiro, Larissa
AU - Ribeiro, Sabina Cerruto
AU - Ramos, Sonia Cesarina Palacios
AU - Moscoso, Victor Chama
AU - Chave, Jerôme
AU - Coelho, Fernanda
AU - Comiskey, James A.
AU - Valverde, Fernando Cornejo
AU - Costa, Flávia
AU - Coutinho, Italo Antônio Cotta
AU - da Costa, Antonio Carlos Lola
AU - de Medeiros, Marcelo Brilhante
AU - del Aguila Pasquel, Jhon
AU - Derroire, Géraldine
AU - Dexter, Kyle G.
AU - Disney, Mat
AU - do Espírito Santo, Mário M.
AU - Domingues, Tomas F.
AU - Dourdain, Aurélie
AU - Duque, Alvaro
AU - Rangel, Cristabel Durán
AU - Elias, Fernando
AU - Esquivel-Muelbert, Adriane
AU - Farfan-Rios, William
AU - Fauset, Sophie
AU - Feldpausch, Ted
AU - Fernandes, G. Wilson
AU - Ferreira, Joice
AU - Nunes, Yule Roberta Ferreira
AU - Figueiredo, João Carlos Gomes
AU - Cabreara, Karina Garcia
AU - Gonzalez, Roy
AU - Hernández, Lionel
AU - Herrera, Rafael
AU - Honorio Coronado, Eurídice N.
AU - Huasco, Walter Huaraca
AU - Iguatemy, Mariana
AU - Joly, Carlos A.
AU - Kalamandeen, Michelle
AU - Killeen, Timothy
AU - Klipel, Joice
AU - Klitgaard, Bente
AU - Laurance, Susan G.
AU - Laurance, William F.
AU - Levesley, Aurora
AU - Lewis, Simon L.
AU - Lima Dan, Maurício
AU - Lopez-Gonzalez, Gabriela
AU - Magnusson, William
AU - Malhi, Yadvinder
AU - Malizia, Lucio
AU - Malizia, Augustina
AU - Manzatto, Angelo Gilberto
AU - Peña, Jose Luis Marcelo
AU - Marimon, Beatriz S.
AU - Marimon Junior, Ben Hur
AU - Martínez-Villa, Johanna Andrea
AU - Reis, Simone Matias
AU - Metzker, Thiago
AU - Milliken, William
AU - Monteagudo-Mendoza, Abel
AU - Moonlight, Peter
AU - Morandi, Paulo S.
AU - Moser, Pamela
AU - Müller, Sandra C.
AU - Nascimento, Marcelo
AU - Negreiros, Daniel
AU - Lima, Adriano Nogueira
AU - Vargas, Percy Núñez
AU - Oliveira, Washington L.
AU - Palacios, Walter
AU - Pallqui Camacho, Nadir C.
AU - Gutierrez, Alexander Parada
AU - Pardo Molina, Guido
AU - Pedra de Abreu, Karla Maria
AU - Peña-Claros, Marielos
AU - Pena Rodrigues, Pablo José Francisco
AU - Pennington, R. Toby
AU - Pickavance, Georgia C.
AU - Pipoly, John
AU - Pitman, Nigel C.A.
AU - Playfair, Maureen
AU - Pontes-Lopes, Aline
AU - Poorter, Lourens
AU - Prestes, Nayane Cristina Candida dos Santos
AU - Ramírez-Angulo, Hirma
AU - Réjou-Méchain, Maxime
AU - Reynel Rodriguez, Carlos
AU - Rivas-Torres, Gonzalo
AU - Rodrigues, Priscyla M.S.
AU - de Jesus Rodrigues, Domingos
AU - de Sousa, Thaiane Rodrigues
AU - Rodrigues Pinto, José Roberto
AU - Rodriguez M, Gina M.
AU - Roucoux, Katherine
AU - Ruokolainen, Kalle
AU - Ryan, Casey M.
AU - Revilla, Norma Salinas
AU - Salomão, Rafael
AU - Santos, Rubens M.
AU - Sarkinen, Tiina
AU - Scabin, Andressa
AU - Bergamin, Rodrigo Scarton
AU - Schietti, Juliana
AU - de Meira Junior, Milton Serpa
AU - Serrano, Julio
AU - Silman, Miles
AU - Silva, Richarlly C.
AU - Silva, Camila V.J.
AU - Silva, Jhonathan Oliveria
AU - Silveira, Marcos
AU - Simon, Marcelo F.
AU - Soto-Shareva, Yahn Carlos
AU - Souza, Priscila
AU - Souza, Rodolfo
AU - Sposito, Tereza
AU - Talbot, Joey
AU - ter Steege, Hans
AU - Terborgh, John
AU - Thomas, Raquel
AU - Toledo, Marisol
AU - Torres-Lezama, Armando
AU - Trujillo, William
AU - van der Hout, Peter
AU - Veloso, Maria das Dores Magalhães
AU - Vieira, Simone A.
AU - Vilanova, Emilio
AU - Villalobos Cayo, Jeanneth M.
AU - Villela, Dora M.
AU - Viscarra, Laura Jessica
AU - Vos, Vincent A.
AU - Wortel, Verginia
AU - Ishida, Francoise Yoko
AU - Zuidema, Pieter A.
AU - Zwerts, Joeri A.
N1 - Funding: Funding: For supporting the networks, we thank the European Research Council (ERC Advanced Grant 291585 – ‘T-FORCES’), the Gordon and Betty Moore Foundation (#1656 ‘RAINFOR’, and ‘MonANPeru’), the European Union’s Fifth, Sixth and Seventh Framework Programme (EVK2-CT-1999-00023 – ‘CARBONSINK-LBA’, 283080 – ‘GEOCARBON’, 282664 – ‘AMAZALERT), the Natural Environment Research Council (NE/ D005590/1 – ‘TROBIT’, NE/F005806/1 – ‘AMAZONICA’, E/M0022021/1 - ‘PPFOR’), several NERC Urgency and New Investigators Grants, the NERC/State of São Paulo Research Foundation (FAPESP) consortium grants ‘BIO-RED’ (NE/N012542/1), ‘ECOFOR’ (NE/K016431/1, 2012/51872-5, 2012/51509-8), ‘ARBOLES’ (NE/S011811/1, FAPESP 2018/15001-6), ‘SEOSAW’ (NE/P008755/1), ‘SECO’ (NE/T01279X/1), Brazilian National Research Council (PELD/CNPq 403710/2012-0), the Royal Society (University Research Fellowships and Global challenges Awards) (ICA/R1/180100 - ‘FORAMA’), the National Geographic Society, US National Science Foundation (DEB 1754647) and Colombia’s Colciencias. We thank the National Council for Science and Technology Development of Brazil (CNPq) for support to the Cerrado/Amazonia Transition Long-Term Ecology Project (PELD/441244/2016-5), the PPBio Phytogeography of Amazonia/Cerrado Transition Project (CNPq/PPBio/457602/2012-0), PELD-RAS (CNPq, Process 441659/2016-0), RESFLORA (Process 420254/2018-8), Synergize (Process 442354/2019-3), the Empresa Brasileira de Pesquisa Agropecuária – Embrapa (SEG: 02.08.06.005.00), the Fundação de Amparo à Pesquisa do Estado de São Paulo – FAPESP (2012/51509-8 and 2012/51872-5), the Goiás Research Foundation (FAPEG/PELD: 2017/10267000329) the EcoSpace Project (CNPq 459941/2014-3), PELD 441572/2020-0, the FATE project (03/12595-7) and several PVE and Productivity Grants. We also thank the “Investissement d’Avenir” program (CEBA, ref. ANR-10LABX-25-01), the São Paulo Research Foundation (FAPESP 03/12595-7, 2016/21043-8) and the Sustainable Landscapes Brazil Project (through Brazilian Agricultural Research Corporation (EMBRAPA), the US Forest Service, USAID, and the US Department of State) for supporting plot inventories in the Atlantic Forest sites in Sao Paulo, Brazil. We thank to the National Council for Technological and Scientific Development (CNPq) for the financial support of the PELD project (441244/2016-5, 441572/2020-0) and FAPEMAT (0346321/2021). We thank Reserva Particular do Patrimônio Natural Serra das Almas for supporting our research at the reserve. This paper also includes plots where recensuses and data assimilation were funded by SECO (NE/T01279X/1), and plots established by Darwin Initiative funded project 20-021, NERC-Newton-FAPESP project Nordeste (NE/N01247X/1; NE/N012550/1) and the USAID funded Partnerships for Enhanced Engagement in Research project. This manuscript is an output of ForestPlots.net Research Project 75A. “Mapping LATAM Forest Wood Density”, which is part of the NERC-FAPESP funded project ARBOLES (NE/S011811/1). ForestPlots.net is a meta-network and cyber-initiative developed at the University of Leeds that unites permanent plot records and supports tropical forest scientists. We acknowledge the contributions of the ForestPlots.net Collaboration and Data Request Committee (B.S.M., E.N.H.C., O.L.P., T.R.B., B. Sonké, C. Ewango, J. Muledi, S.L.L., L. Qie) for facilitating this project and associated data management. The development of ForestPlots.net and curation of data has been funded by several grants including NE/B503384/1, NE/N012542/1 - ‘BIO-RED’, ERC Advanced Grant 291585 - ‘T-FORCES’, NE/F005806/1 - ‘AMAZONICA’, NE/N004655/1 - ‘TREMOR’, NERC New Investigators Awards, the Gordon and Betty Moore Foundation (‘RAINFOR’, ‘MonANPeru’), ERC Starter Grant 758873 -‘TreeMort’, EU Framework 6, a Royal Society University Research Fellowship, and a Leverhulme Trust Research Fellowship. For supporting M.S. we thank NERC (NE/N012542/1 and NE/W003872/1) and the Royal Society (a Royal Society Global Challenges grant “Sensitivity of Tropical Forest Ecosystem Services to Climate Changes”). F.E. was supported by BJT-FAPESPA Program (Process No. 2021/658588) and the Serrapilheira Institute fellowship/FAPESPA (grant number – R-2401–46863), T.F.D. received support from the Brazilian National Council for Scientific and Technological Development (CNPq - 312589/2022-0 Research Productivity Grant) and FAPESP grant 2015/50488-5, G.W.F was supported by APQ 00031-19 FAPEMIG/Renova and J.P. was supported by a CNPq productivity scholarship (312571/2021-6).
PY - 2025/3/10
Y1 - 2025/3/10
N2 - Wood density is a critical control on tree biomass, so poor understanding of its spatial variation can lead to large and systematic errors in forest biomass estimates and carbon maps. The need to understand how and why wood density varies is especially critical in tropical America where forests have exceptional species diversity and spatial turnover in composition. As tree identity and forest composition are challenging to estimate remotely, ground surveys are essential to know the wood density of trees, whether measured directly or inferred from their identity. Here, we assemble an extensive dataset of variation in wood density across the most forested and tree-diverse continent, examine how it relates to spatial and environmental variables, and use these relationships to predict spatial variation in wood density over tropical and sub-tropical South America. Our analysis refines previously identified east-west Amazon gradients in wood density, improves them by revealing fine-scale variation, and extends predictions into Andean, dry, and Atlantic forests. The results halve biomass prediction errors compared to a naïve scenario with no knowledge of spatial variation in wood density. Our findings will help improve remote sensing-based estimates of aboveground biomass carbon stocks across tropical South America.
AB - Wood density is a critical control on tree biomass, so poor understanding of its spatial variation can lead to large and systematic errors in forest biomass estimates and carbon maps. The need to understand how and why wood density varies is especially critical in tropical America where forests have exceptional species diversity and spatial turnover in composition. As tree identity and forest composition are challenging to estimate remotely, ground surveys are essential to know the wood density of trees, whether measured directly or inferred from their identity. Here, we assemble an extensive dataset of variation in wood density across the most forested and tree-diverse continent, examine how it relates to spatial and environmental variables, and use these relationships to predict spatial variation in wood density over tropical and sub-tropical South America. Our analysis refines previously identified east-west Amazon gradients in wood density, improves them by revealing fine-scale variation, and extends predictions into Andean, dry, and Atlantic forests. The results halve biomass prediction errors compared to a naïve scenario with no knowledge of spatial variation in wood density. Our findings will help improve remote sensing-based estimates of aboveground biomass carbon stocks across tropical South America.
U2 - 10.1038/s41467-025-56175-4
DO - 10.1038/s41467-025-56175-4
M3 - Article
C2 - 40064856
AN - SCOPUS:105000085493
SN - 2041-1723
VL - 16
JO - Nature Communications
JF - Nature Communications
M1 - 2351
ER -