Evidence map›Paper›PMID 41084952›Full record

ArticleThe New phytologist2026

Mapping the density of giant trees in the Amazon.

Robson Borges de Lima, Diego Armando Silva da Silva, Matheus Henrique Nunes, Paulo R de Lima Bittencourt, Peter Groenendyk, Cinthia Pereira de Oliveira, Daniela Granato-Souza, Rinaldo L Caraciolo Ferreira, José A Aleixo da Silva, Jesús Aguirre-Gutiérrez and 11 more

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In one paragraph

Article in The New phytologist, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Robson Borges de LimaLaboratório de Manejo Florestal, Universidade do Estado do Amapá, 68901-262, Macapá, AP, Brazil.ORCID https://orcid.org/0000-0001-5915-4045
Diego Armando Silva da SilvaInstituto Federal de Educação Ciência e Tecnologia do Amapá, 68.920-000, Laranjal do Jari, AP, Brazil.ORCID https://orcid.org/0000-0003-1018-3640
Matheus Henrique NunesDepartment of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA.ORCID https://orcid.org/0000-0001-9979-6456
Paulo R de Lima BittencourtSchool of Earth and Environment Sciences, Cardiff University, CF10 3AT, Cardiff, UK.ORCID https://orcid.org/0000-0002-1618-9077
Peter GroenendykDepartment of Plant Biology, Institute of Biology, University of Campinas, PO Box 6109, 13083-970, Campinas, SP, Brazil.ORCID https://orcid.org/0000-0003-2752-6195
Cinthia Pereira de OliveiraLaboratório de Manejo Florestal, Universidade do Estado do Amapá, 68901-262, Macapá, AP, Brazil.ORCID https://orcid.org/0000-0001-5158-7866
Daniela Granato-SouzaDepartment of Natural Resources and Environmental Sciences College of Agricultural, Alabama A & M University, Huntsville, 35762, AL, USA.ORCID https://orcid.org/0000-0002-7011-0892
Rinaldo L Caraciolo FerreiraDepartamento de Ciência Florestal, Universidade Federal Rural de Pernambuco, 52171-900, Recife, PE, Brazil.ORCID https://orcid.org/0000-0001-7349-6041
José A Aleixo da SilvaDepartamento de Ciência Florestal, Universidade Federal Rural de Pernambuco, 52171-900, Recife, PE, Brazil.ORCID https://orcid.org/0000-0003-0675-3524
Jesús Aguirre-GutiérrezEnvironmental Change Institute, University of Oxford, Oxford, OX13QY, UK.ORCID https://orcid.org/0000-0001-9190-3229
Toby JacksonSchool of Biological Sciences, University of Bristol, Bristol, BS8 1QU, UK.ORCID https://orcid.org/0000-0001-8143-6161
João R de Matos FilhoPromotoria de Justiça do Meio Ambiente, Conflitos Agrários, Ministério Público, 68903-883, Macapá, AP, Brazil.
Perseu da Silva AparícioLaboratório de Manejo Florestal, Universidade do Estado do Amapá, 68901-262, Macapá, AP, Brazil.ORCID https://orcid.org/0000-0002-6696-529X
Joselane P Gomes da SilvaLaboratório de Manejo Florestal, Universidade do Estado do Amapá, 68901-262, Macapá, AP, Brazil.ORCID https://orcid.org/0000-0002-2496-9516
José Julio de ToledoUniversidade Federal do Amapá, 68903-419, Macapá, AP, Brazil.ORCID https://orcid.org/0000-0002-1778-0117
Marcelino Carneiro GuedesEmpresa Brasileira de Pesquisa Agropecuária, 68903-419, Macapá, AP, Brazil.ORCID https://orcid.org/0000-0003-2702-5614
Danilo R Alves de AlmeidaDepartment of Forest Sciences, 'Luiz de Queiroz' College of Agriculture, University of São Paulo, 13418-900, Piracicaba, SP, Brazil.ORCID https://orcid.org/0000-0002-8747-0085
Niro HiguchiInstituto Nacional de Pesquisas da Amazônia, Coordenação de Pesquisas em Silvicultura Tropical, 69080-971, Manaus, AM, Brazil.ORCID https://orcid.org/0000-0002-1203-4502
Fabien H WagnerJet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove, Pasadena, CA, 91109, USA.ORCID https://orcid.org/0000-0002-9623-1182
Jean Pierre OmettoInstituto Nacional de Pesquisas Espaciais, 12227-010, São José dos Campos, SP, Brazil.ORCID https://orcid.org/0000-0002-4221-1039
Eric Bastos GörgensDepartamento de Engenharia Florestal, Universidade Federal dos Vales do Jequitinhonha e Mucuri, 39100-000, Diamantina, MG, Brazil.ORCID https://orcid.org/0000-0003-2517-0279

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 301432/2022-8Conselho Nacional de Desenvolvimento Científico e Tecnológico 301661/2019-7Conselho Nacional de Desenvolvimento Científico e Tecnológico 403297/2016-8Conselho Nacional de Desenvolvimento Científico e Tecnológico 444350/2024-1Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Finance Code 001Fundação de Amparo à Pesquisa do Estado de São Paulo 2018/01847-0Fundação de Amparo à Pesquisa do Estado de São Paulo #2018/21338-3Fundação de Amparo à Pesquisa do Estado de São Paulo #2019/14697-0Fundo Amazônia grant 14.2.0929.1National Academy of Sciences and US Agency for International Development grant AID-OAA-A-11-00012UK Natural Environment Research Council grant NE/ S010750/1Universidade do Estado do Amapá Processes 0022.0279.1202.0018/2021
6 · The paper itself

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.

Indexed as

TreesBiomassBrazilForestsGeographyPopulation Densityairborne LiDARbiogeographic provincesenvironmental factorsspatial modelingtallest trees

Identifiers

PMID41084952
PMCPMC12676077

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.