Mapping the density of giant trees in the Amazon

Tall trees (height ≥ 60 m) are keystone elements of tropical forests, strongly influencing biodiversity, carbon storage, and ecosystem resilience. Yet, their density and spatial distribution remain poorly quantified, especially in remote Amazonian regions, limiting our understanding of their ecological roles and contribution to forest-climate interactions. We combined airborne LiDAR data from 900 transects across the Brazilian Amazon with environmental predictors to model tall-tree density. Spatial extrapolations allowed us to generate regional distribution estimates and assess associations with climate, topography, and disturbance regimes. Our model predicts that tall trees are unevenly distributed, with c. 14% of the estimated density concentrated in c. 1% of the Amazon and c. 50% within c. 11%. The highest densities occur in Roraima and the Guiana Shield provinces, where water availability is high and lightning or storm incidence is low. Modeled density strongly correlates with aboveground biomass, highlighting the disproportionate contribution of tall trees to carbon stocks. We estimate c. 55.5 million tall trees across the Brazilian Amazon. These findings demonstrate that tall-tree distribution is a crucial but underused predictor for biomass models. Understanding their ecological and spatial dynamics is vital for forest conservation and climate-resilience strategies under increasing anthropogenic pressures.

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Publication Details

Journal
New Phytologist
Published
2025-10-14
DOI
https://doi.org/10.1111/nph.70634
Primary Topic
Forest ecology and management
Type
article
Field-Weighted Citation Impact
0.00

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article

Mapping the density of giant trees in the Amazon

Danilo Roberti Alves de Almeida, Diego Armando Silva da Silva, José Antônio Aleixo da Silva, João Ramos de Matos Filho et al.
New Phytologist
Forest ecology and management
article

Mapping the density of giant trees in the Amazon

Danilo Roberti Alves de Almeida, Diego Armando Silva da Silva, José Antônio Aleixo da Silva, João Ramos de Matos Filho, Rinaldo Luíz Caraciolo Ferreira, Eric Bastos Görgens, José Júlio de Toledo, Níro Higuchi, Fabien Hubert Wagner, Róbson Borges de Lima, Perseu da Silva Aparício, Jean Pierre Ometto, Jesús Aguirre‐Gutiérrez, Peter Groenendijk, Daniela Granato‐Souza, Matheus Henrique Nunes, Marcelino Carneiro Guedes, Toby Jackson, Paulo Bittencourt, Cinthia Pereira de Oliveira, Joselane Príscila Gomes da Silva
article en

Abstract

Tall trees (height ≥ 60 m) are keystone elements of tropical forests, strongly influencing biodiversity, carbon storage, and ecosystem resilience. Yet, their density and spatial distribution remain poorly quantified, especially in remote Amazonian regions, limiting our understanding of their ecological roles and contribution to forest-climate interactions. We combined airborne LiDAR data from 900 transects across the Brazilian Amazon with environmental predictors to model tall-tree density. Spatial extrapolations allowed us to generate regional distribution estimates and assess associations with climate, topography, and disturbance regimes. Our model predicts that tall trees are unevenly distributed, with c. 14% of the estimated density concentrated in c. 1% of the Amazon and c. 50% within c. 11%. The highest densities occur in Roraima and the Guiana Shield provinces, where water availability is high and lightning or storm incidence is low. Modeled density strongly correlates with aboveground biomass, highlighting the disproportionate contribution of tall trees to carbon stocks. We estimate c. 55.5 million tall trees across the Brazilian Amazon. These findings demonstrate that tall-tree distribution is a crucial but underused predictor for biomass models. Understanding their ecological and spatial dynamics is vital for forest conservation and climate-resilience strategies under increasing anthropogenic pressures.

New PhytologistVol. 249(1)
Jet Propulsion Laboratory (US), Alabama Agricultural and Mechanical University (US), Universidade Estadual de Campinas (UNICAMP) (BR), Instituto Nacional de Pesquisas da Amazônia (BR), Brazilian Agricultural Research Corporation (BR), University of Bristol (GB), University of Oxford (GB), Empresa de Pesquisa Agropecuária do Rio Grande do Norte (BR), Ministério da Justiça (PT), CRUK/MRC Oxford Institute for Radiation Oncology (GB), Forest Science and Research Institute (BR), Universidade Federal dos Vales do Jequitinhonha e Mucuri (BR), Instituto Federal do Amapá (BR), Universidade Federal do Amapá (BR), Universidade Estadual do Amapá (BR), Universidade Federal Rural de Pernambuco (BR), University of Maryland, College Park (US), Cardiff University (GB), Instituto Nacional de Pesquisas Espaciais (BR)
U.S. Department of Energy, National Aeronautics and Space Administration, United States Agency for International Development, Leverhulme Trust, Fundação de Amparo à Pesquisa do Estado de São Paulo, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado de Minas Gerais, Fundo Amazônia, Natural Environment Research Council
Openalex Percentile: Top 71%
Forest ecology and management
DOIOpen Access PDFOpenAlex
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