biostudies-literaturede Lima RBUniversidade do Estado do AmapáConselho Nacional de Desenvolvimento Científico e TecnológicoFundo AmazôniaNational Academy of Sciences and US Agency for International DevelopmentUK Natural Environment Research CouncilCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São Paulo152-168https://www.ebi.ac.uk/biostudies/studies/S-EPMC12676077biostudies-literatureUnknown249(1)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% withinThe New phytologistMapping the density of giant trees in the Amazon.PMC12676077403297/2016-8grant NE/ S010750/1Finance Code 001444350/2024-1403297/2016‐8grant AID-OAA-A-11-00012Processes 0022.0279.1202.0018/2021301661/2019-7#2018/21338‐3#2019/14697‐0#2019/14697-0#2018/21338-3301661/2019‐7301432/2022-8444350/2024‐1301432/2022‐82018/01847-0grant 14.2.0929.12018/01847‐0Higuchi NJackson TOmetto JPAleixo da Silva JAde Lima RBGroenendyk PWagner FHNunes MHAparicio PDSde Matos Filho JRde Toledo JJCaraciolo Ferreira RLda Silva JPGBittencourt PRLde Oliveira CPGuedes MCGranato-Souza Dda Silva DASde Almeida DRAGorgens EBAguirre-Gutierrez JfalseMapping 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% within2026-01-01T00:00:00Z2026 Jan2026-06-05T22:15:23.772Z2026-05-22T03:15:51.05ZS-EPMC126760774108495210.1111/nph.70634