Tropical forest canopies are the biosphere's most concentrated atmospheric interface for carbon, water and energy1,2. However, in most Earth System Models, the diverse and heterogeneous tropical forest biome is represented as a largely uniform ecosystem with either a singular or a small number of fixed canopy ecophysiological properties3. This situation arises, in part, from a lack of understanding about how and why the functional properties of tropical forest canopies vary geographically4. Here, by combining field-collected data from more than 1,800 vegetation plots and tree traits with satellite remote-sensing, terrain, climate and soil data, we predict variation across 13 morphological, structural and chemical functional traits of trees, and use this to compute and map the functional diversity of tropical forests. Our findings reveal that the tropical Americas, Africa and Asia tend to occupy different portions of the total functional trait space available across tropical forests. Tropical American forests are predicted to have 40% greater functional richness than tropical African and Asian forests. Meanwhile, African forests have the highest functional divergence-32% and 7% higher than that of tropical American and Asian forests, respectively. An uncertainty analysis highlights priority regions for further data collection, which would refine and improve these maps. Our predictions represent a ground-based and remotely enabled global analysis of how and why the functional traits of tropical forest canopies vary across space.

AMAP Université de Montpellier IRD CNRS CIRAD INRAE Montpellier France

Biological and Environmental Sciences University of Stirling Stirling UK

Birmingham Institute of Forest Research University of Birmingham Birmingham UK

Botany School of Natural Sciences Trinity College Dublin Dublin Ireland

Brazilian Platform on Biodiversity and Ecosystem Services Campinas Brazil

Center for Energy Environment and Sustainability Wake Forest University Winston Salem NC USA

Center for Global Discovery and Conservation Science Arizona State University Tempe AZ USA

Centre de Recherche Biodiversité Environnement CNRS UPS IRD Université de Toulouse INPT Toulouse France

Centro de Ciências Biológicas e da Natureza Universidade Federal do Acre Rio Branco Brazil

Centro de Pesquisa Desenvolvimento e Inovação Sul Instituto Capixaba de Pesquisa Assistência Técnica e Extensão Rural Cachoeiro de Itapemirim Brazil

CESAM Centro de Estudos do Ambiente e do Mar Departamento de Biologia Pesquisador Colaborador Universidade de Aveiro Aveiro Portugal

Cirad UMR EcoFoG Campus Agronomique Kourou French Guiana

Colegiado de Ecologia Universidade Federal do Vale do São Francisco Senhor do Bonfim Brazil

Colegio de Ciencias y Humanidades Universidad Juárez del Estado de Durango Durango Mexico

College of Science and Engineering James Cook University Cairns Queensland Australia

Conservation Research Institute and Department of Plant Sciences University of Cambridge Cambridge UK

Coordenação de Biodiversidade Instituto Nacional de Pesquisas da Amazônia Manaus Brazil

Coordenação de Dinâmica Ambiental Instituto Nacional de Pesquisas da Amazônia Manaus Brazil

CSIR Forestry Research Institute of Ghana Kumasi Ghana

Departamento de Biologia Geral Universidade Estadual de Montes Claros Montes Claros Brazil

Departamento de Biologia Universidade Federal de Rondônia Porto Velho Brazil

Departamento de Biologia Vegetal Instituto de Biologia Universidade Estadual de Campinas Campinas Brazil

Departamento de Engenharia Florestal Universidade de Brasília Brasília Brazil

Departamento de Engenharia Florestal Universidade do Estado de Mato Grosso Caceres Brazil

Departamento de Engenharia Florestal Universidade Federal de Lavras Lavras Brazil

Department for Accelerated Taxonomy Royal Botanic Gardens Kew Richmond UK

Department of Biological and Environmental Sciences University of Gothenburg Gothenburg Sweden

Department of Biology Sonoma State University Rohnert Park CA USA

Department of Biology Wake Forest University Winston Salem NC USA

Department of Ecology and Evolutionary Biology University of Arizona Tucson AZ USA

Department of Ecology Universidade Federal do Rio Grande do Sul Porto Alegre Brazil

Department of Forest Botany Dendrology and Geobiocoenology Faculty of Forestry and Wood Technology Mendel University in Brno Brno Czech Republic

Department of Forest Sciences Luiz de Queiroz College of Agriculture University of São Paulo Piracicaba Brazil

Department of Geography University of Exeter Exeter UK

Department of Life Sciences and Systems Biology University of Turin Turin Italy

Department of Natural Resources Management CSIR College of Science and Technology Kumasi Ghana

Department of Natural Sciences Manchester Metropolitan University Manchester UK

Embrapa Amazônia Oriental Belém Brazil

Embrapa Recursos Genéticos e Biotecnologia Brasília Brazil

Environmental and Rural Science University of New England Armidale New South Wales Australia

Environmental Change Institute School of Geography and the Environment University of Oxford Oxford UK

Escuela de Ciencias Agrícolas Pecuarias y Ambientales ECAPMA Universidad Nacional Abierta y a Distancia Bogota Colombia

Escuela Politécnica Superior de Ingeniería Universidad de Santiago de Compostela Campus Terra Lugo España

Estación de Biodiversidad Tiputini Colegio de Ciencias Biológicas y Ambientales Universidad San Francisco de Quito Quito Ecuador

Faculdade de Filosofia Ciências e Letras de Ribeirão Preto Ribeirão Preto Brazil

Facultad de Ciencias Forestales y Ambientales Universidad Juárez del Estado de Durango Durango Mexico

Faculty of Communication and Environment Hochschule Rhein Waal Kamp Lintfort Germany

Federal Rural University of Rio de Janeiro Seropedica Brazil

Forest Ecology and Forest Management Group Wageningen University and Research Wageningen The Netherlands

Forest Ecology Department KSCSTE Kerala Forest Research Institute Kerala India

Forêts et Sociétés Université de Montpellier CIRAD Montpellier France

German Centre for Integrative Biodiversity Research Halle Jena Leipzig Leipzig Germany

Global Green Growth Institute Rwanda Program Kigali Rwanda

IBAM Instituto Bem Ambiental Belo Horizonte Brazil

INRAE Université de Lorraine AgroParisTech UMR Silva Nancy France

Institut de Recherche en Écologie Tropicale Libreville Gabon

Institute for Nature Earth and Energy Pontificia Universidad Católica del Perú Lima Peru

Institute of Biogeosciences IBG2 Plant Sciences Forschungszentrum Jülich GmbH Jülich Germany

Institute of Ecology Leuphana University of Lüneburg Lüneburg Germany

Instituto de Biologia Universidade Federal da Bahia Salvador Brazil

Instituto de Ciências Biológicas Departamento de Botânica Universidade Federal de Minas Gerais Belo Horizonte Brazil

Instituto de Pesquisas Jardim Botânico do Rio de Janeiro Rio de Janeiro Brazil

Instituto Internacional para Sustentabilidade Rio de Janeiro Brazil

Instituto Socioambiental São Paulo Brazil

Jardín Botánico de Bogotá Bogotá Colombia

Laboratório de Ciências Ambientais CBB Universidade Estadual do Norte Fluminense Darcy Ribeiro Campos dos Goytacazes Brazil

Laboratório de Ecologia Aplicada à Conservacão Departamento de Ciências Biológicas Universidade Estadual de Santa Cruz Ilhéus Brazil

Laboratório de Ecologia Vegetal Universidade do Estado de Mato Grosso Nova Xavantina Brazil

Laboratório de Fitogeografia e Ecologia Evolutiva Departamento de Ciências Florestais Universidade Federal de Lavras Lavras Brazil

Laboratório de Manejo Florestal Universidade do Estado do Amapá Macapá Brazil

Lancaster Environment Centre Lancaster University Lancaster UK

Leipzig University Leipzig Germany

Leverhulme Centre for Nature Recovery University of Oxford Oxford UK

Ministry of Water and Forests Abidjan Côte d'Ivoire

Myr Projetos Sustentáveis Belo Horizonte Brazil

Naturalis Biodiversity Center Leiden The Netherlands

Plant Ecology and Evolution Department of Ecology and Genetics Uppsala University Uppsala Sweden

Plant Ecology and Nature Conservation Group Wageningen University and Research Wageningen The Netherlands

Plant Ecology Lab Ecology Department Universidade Federal do Rio Grande do Sul Porto Alegre Brazil

PPG Ecology and Conservation Universidade do Estado de Mato Grosso Nova Xavantina Brazil

Programa de Pós graduação em Ambiente e Sistemas de Produção Agrícola Universidade do Estado de Mato Grosso Tangará da Serra Brazil

Programa de Pós graduação em Ecologia e Conservação Universidade do Estado de Mato Grosso Nova Xavantina Brazil

Quantitative Biodiversity Dynamics Utrecht University Utrecht The Netherlands

Royal Botanic Garden Edinburgh Edinburgh UK

Royal Botanic Gardens Kew Richmond UK

School of Biological Sciences University of Aberdeen Aberdeen UK

School of Biological Sciences University of Adelaide Adelaide South Australia Australia

School of Environmental Sciences University of East Anglia Norwich UK

School of Forestry and Biodiversity and Biological Sciences College of Agriculture Animal Sciences and Veterinary Medicine University of Rwanda Musanze Rwanda

School of Geography Earth and Environmental Sciences University of Birmingham Birmingham UK

School of Geography Earth and Environmental Sciences University of Plymouth Plymouth UK

School of Geography University of Leeds Leeds UK

School of GeoSciences University of Edinburgh Edinburgh UK

School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff AZ USA

School of Natural and Environmental Sciences Newcastle University Newcastle upon Tyne UK

The Santa Fe Institute Santa Fe USA

UMRI SAPT Institut National Polytechnique Félix Houphouët Boigny Yamoussoukro Côte d'Ivoire

Universidad de los Andes Bogotá Colombia

Universidade de São Paulo São Paulo Brazil

Universidade do Estado de Mato Grosso Tangará da Serra Brazil

Universidade Federal de Mato Grosso Sinop Brazil

Universidade Federal do Acre Rio Branco Brazil

Universidade Paulista Polo Rio Branco Brazil

University of Rwanda Kigali Rwanda

Utrecht University Utrecht The Netherlands

Zobrazit více v PubMed

Gatti, R. C. et al. The number of tree species on Earth. Proc. Natl Acad. Sci. USA119, e2115329119 (2022). PubMed PMC

Barlow, J. et al. The future of hyperdiverse tropical ecosystems. Nature559, 517–526 (2018). PubMed

Silman, M. R. Functional megadiversity. Proc. Natl Acad. Sci. USA111, 5763–5764 (2014). PubMed PMC

Wieczynski, D. J. et al. Climate shapes and shifts functional biodiversity in forests worldwide. Proc. Natl Acad. Sci. USA116, 587–592 (2019). PubMed PMC

Mace, G. M., Norris, K. & Fitter, A. H. Biodiversity and ecosystem services: a multilayered relationship. Trends Ecol. Evol.27, 19–26 (2012). PubMed

Aguirre-Gutiérrez, J. et al. Pantropical modelling of canopy functional traits using Sentinel-2 remote sensing data. Remote Sens. Environ.252, 112122 (2021).

Jetz, W. et al. Monitoring plant functional diversity from space. Nat. Plants2, 16024 (2016). PubMed

Wallis, C. I. et al. Modeling tropical montane forest biomass, productivity and canopy traits with multispectral remote sensing data. Remote Sens. Environ.225, 77–92 (2019).

Diaz, S., Cabido, M. & Casanoves, F. Plant functional traits and environmental filters at a regional scale. J. Veg. Sci.9, 113–122 (1998).

Messier, J., McGill, B. J. & Lechowicz, M. J. How do traits vary across ecological scales? A case for trait‐based ecology. Ecol. Lett.13, 838–848 (2010). PubMed

Enquist, B. J. et al. Scaling from traits to ecosystems: developing a general trait driver theory via integrating trait-based and metabolic scaling theories. Adv. Ecol. Res.52, 249–318 (2015).

Asner, G. P. et al. Amazonian functional diversity from forest canopy chemical assembly. Proc. Natl Acad. Sci. USA111, 5604–5609 (2014). PubMed PMC

Fyllas, N. M. et al. Solar radiation and functional traits explain the decline of forest primary productivity along a tropical elevation gradient. Ecol. Lett.20, 730–740 (2017). PubMed

Brun, P. et al. Plant community impact on productivity: trait diversity or key(stone) species effects? Ecol. Lett.25, 913–925 (2022). PubMed PMC

Schmitt, S. et al. Functional diversity improves tropical forest resilience: insights from a long‐term virtual experiment. J. Ecol.108, 831–843 (2020).

Schnabel, F. et al. Species richness stabilizes productivity via asynchrony and drought-tolerance diversity in a large-scale tree biodiversity experiment. Sci. Adv.7, eabk1643 (2021). PubMed PMC

Butler, E. E. et al. Mapping local and global variability in plant trait distributions. Proc. Natl Acad. Sci. USA114, E10937–E10946 (2017). PubMed PMC

Moreno-Martínez, Á. et al. A methodology to derive global maps of leaf traits using remote sensing and climate data. Remote Sens. Environ.218, 69–88 (2018).

Vallicrosa, H. et al. Global maps and factors driving forest foliar elemental composition: the importance of evolutionary history. New Phytol.233, 169–181 (2022). PubMed

Dechant, B. et al. Intercomparing global foliar trait and canopy height maps: upscaling approaches and spatial patterns. In AGU Fall Meeting 2021 (AGU, 2021).

Gallagher, R. V. et al. Open Science principles for accelerating trait-based science across the Tree of Life. Nat. Ecol. Evol.4, 294–303 (2020). PubMed

Kattge, J. et al. TRY plant trait database—enhanced coverage and open access. Glob. Chang. Biol.26, 119–188 (2020). PubMed

ter Steege, H. et al. Biased-corrected richness estimates for the Amazonian tree flora. Sci. Rep.10, 10130 (2020). PubMed PMC

Díaz, S. et al. The global spectrum of plant form and function. Nature529, 167–171 (2016). PubMed

Wright, I. J. et al. The worldwide leaf economics spectrum. Nature428, 821–827 (2004). PubMed

Lamour, J. et al. The effect of the vertical gradients of photosynthetic parameters on the CO2 assimilation and transpiration of a Panamanian tropical forest. New Phytol.238, 2345–2362 (2023). PubMed

Malhi, Y. et al. African rainforests: past, present and future. Phil. Trans. R. Soc. B368, 20120312 (2013). PubMed PMC

Parmentier, I. et al. The odd man out? Might climate explain the lower tree α-diversity of African rain forests relative to amazonian rain forests? J. Ecol.95, 1058–1071 (2007).

Moore, S. et al. Forest biomass, productivity and carbon cycling along a rainfall gradient in West Africa. Glob. Chang. Biol.24, e496–e510 (2018). PubMed

Inagawa, T. et al. Radial and vertical variation of wood nutrients in Bornean tropical forest trees. Biotropica55, 1019–1032 (2023).

Malhi, Y. et al. The Global Ecosystems Monitoring network: monitoring ecosystem productivity and carbon cycling across the tropics. Biol. Conserv.253, 108889 (2021).

ForestPlots.net et al. Taking the pulse of Earth’s tropical forests using networks of highly distributed plots. Biol. Conserv.260, 108849 (2021).

Díaz, S. et al. The global spectrum of plant form and function: enhanced species-level trait dataset. Sci. Data9, 755 (2022). PubMed PMC

Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data5, 170191 (2018). PubMed PMC

Ploton, P. et al. Spatial validation reveals poor predictive performance of large-scale ecological mapping models. Nat. Commun.11, 4540 (2020). PubMed PMC

Sullivan, M. J. P. et al. Diversity and carbon storage across the tropical forest biome. Sci. Rep.7, 39102 (2017). PubMed PMC

Aguirre-Gutiérrez, J. et al. Long-term droughts may drive drier tropical forests towards increased functional, taxonomic and phylogenetic homogeneity. Nat. Commun.11, 3346 (2020). PubMed PMC

Allen, K. et al. Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes? Environ. Res. Lett.12, 023001 (2017).

Aguirre‐Gutiérrez, J. et al. Drier tropical forests are susceptible to functional changes in response to a long‐term drought. Ecol. Lett.22, 855–865 (2019). PubMed

Dinerstein, E. et al. An ecoregion-based approach to protecting half the terrestrial realm. Bioscience67, 534–545 (2017). PubMed PMC

Markesteijn, L., Poorter, L. & Bongers, F. Light‐dependent leaf trait variation in 43 tropical dry forest tree species. Amer. J. Bot.94, 515–525 (2007). PubMed

Poorter, H. et al. Biomass allocation to leaves, stems and roots: meta‐analyses of interspecific variation and environmental control. New Phytol.193, 30–50 (2012). PubMed

Yachi, S. & Loreau, M. Biodiversity and ecosystem productivity in a fluctuating environment: the insurance hypothesis. Proc. Natl Acad. Sci. USA96, 1463–1468 (1999). PubMed PMC

Aguirre‐Gutiérrez, J. et al. Functional susceptibility of tropical forests to climate change. Nat. Ecol. Evol.6, 878–889 (2022). PubMed

Carmona, C. P., de Bello, F., Mason, N. W. & Lepš, J. Traits without borders: integrating functional diversity across scales. Trends Ecol. Evol.31, 382–394 (2016). PubMed

Kraft, N. J. B. et al. The relationship between wood density and mortality in a global tropical forest data set. New Phytol.188, 1124–1136 (2010). PubMed

Malhi, Y. et al. The variation of productivity and its allocation along a tropical elevation gradient: a whole carbon budget perspective. New Phytol.214, 1019–1032 (2017). PubMed

Vitousek, P. M. & Sanford, R. L. Jr Nutrient cycling in moist tropical forest. Annu. Rev. Ecol. Syst.17, 137–167 (1986).

Runyan, C. W., Lawrence, D., Vandecar, K. L. & D’Odorico, P. Experimental evidence for limited leaching of phosphorus from canopy leaves in a tropical dry forest. Ecohydrology6, 806–817 (2013).

Oliveras, I. et al. The influence of taxonomy and environment on leaf trait variation along tropical abiotic gradients. Front. For. Glob. Chang.3, 18 (2020).

Piao, S. et al. Characteristics, drivers and feedbacks of global greening. Nat. Rev. Earth Environ.1, 14–27 (2020).

Vallé, C. et al. Species associations in joint species distribution models: from missing variables to conditional predictions. J. Biogeogr.51, 311–324 (2024).

Yan, P. et al. Integrating multiple plant functional traits to predict ecosystem productivity. Commun. Biol.6, 239 (2023). PubMed PMC

Franklin, J. Species distribution modelling supports the study of past, present and future biogeographies. J. Biogeogr.50, 1533–1545 (2023).

Newman, S. J. & Furbank, R. T. Explainable machine learning models of major crop traits from satellite-monitored continent-wide field trial data. Nat. Plants7, 1354–1363 (2021). PubMed

Schiller, C. et al. Deep learning and citizen science enable automated plant trait predictions from photographs. Sci. Rep.11, 16395 (2021). PubMed PMC

Lang, N. et al. A high-resolution canopy height model of the Earth. Nat. Ecol. Evol.7, 1778–1789 (2023). PubMed PMC

Cherif, E. et al. From spectra to plant functional traits: transferable multi-trait models from heterogeneous and sparse data. Remote Sens. Environ.292, 113580 (2023).

Lopez-Gonzalez, G., Lewis, S. L., Burkitt, M., Baker, T. R. & Phillips, O. L. ForestPlots.net Database (www.forestplots.net; 2009).

Lopez-Gonzalez, G., Lewis, S. L., Burkitt, M. & Phillips, O. L. ForestPlots.net: a web application and research tool to manage and analyse tropical forest plot data. J. Veg. Sci.22, 610–613 (2011).

Both, S. et al. Logging and soil nutrients independently explain plant trait expression in tropical forests. New Phytol.221, 1853–1865 (2019). PubMed

Martin, R. E. et al. Covariance of sun and shade leaf traits along a tropical forest elevation gradient. Front. Plant Sci.10, 1810 (2020). PubMed PMC

Enquist, B. J. et al. Assessing trait‐based scaling theory in tropical forests spanning a broad temperature gradient. Global Ecol. Biogeogr.26, 1357–1373 (2017).

Gvozdevaite, A. The Role of Economic, Venation and Morphological Leaf Traits in Plant and Ecosystem Function Along Forest-Savanna Gradients in the Tropics. PhD thesis, Oxford Univ. (2018).

Thomson, E. R. et al. Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data. Environ. Res. Lett.16, 055006 (2021).

Haralick, R. M., Shanmugam, K. & Dinstein, I. H. Textural features for image classification. IEEE Trans. Syst. Man Cybernet.3, 610–621 (1973).

Gorelick, N. et al. Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens. Environ.202, 18–27 (2017).

Harris, I. C. & Jones, P. D. CRU TS4.00: Climatic Research Unit (CRU) Time-Series (TS) version 4.00 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901–Dec. 2015) (Centre for Environmental Data Analysis, 2017).

Kobayashi, S. et al. The JRA-55 reanalysis: general specifications and basic characteristics. J. Meteorol. Soc. Jpn93, 5–48 (2015).

Malhi, Y. et al. Exploring the likelihood and mechanism of a climate-change-induced dieback of the Amazon rainforest. Proc. Natl Acad. Sci. USA106, 20610–20615 (2009). PubMed PMC

Farr, T. G. et al. The shuttle radar topography mission. Rev. Geophys.45, RG2004 (2007).

Meir, P. & Pennington, R. T. in Seasonally Dry Tropical Forests (eds. Dirzo, R. et al.) 279–299 (Springer, 2011).

Poggio, L. et al. SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty. Soil7, 217–240 (2021).

Breiman, L. Random forests. Mach. Learn.45, 5–32 (2001).

R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2023).

Boonman, C. et al. Assessing the reliability of predicted plant trait distributions at the global scale. Glob. Ecol. Biogeogr.29, 1034–1051 (2020). PubMed PMC

Ali, A. et al. Machine learning methods’ performance in radiative transfer model inversion to retrieve plant traits from Sentinel-2 data of a mixed mountain forest. Int. J. Digit. Earth14, 106–120 (2021).

Cai, L. et al. Global models and predictions of plant diversity based on advanced machine learning techniques. New Phytol.237, 1432–1445 (2023). PubMed

Simonetti, D., Pimple, U., Langner, A. & Marelli, A. Pan-tropical Sentinel-2 cloud-free annual composite datasets. Data in Brief39, 107488 (2021). PubMed PMC

ESA. Land Cover CCI Product User Guide Version 2. Available at: maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf.

Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science342, 850–853 (2013). PubMed

Carmona, C. P. et al. Erosion of global functional diversity across the tree of life. Sci. Adv.7, eabf2675 (2021). PubMed PMC

Aguirre-Gutiérrez, J. Sample R code for ‘Canopy functional trait variation across Earth’s tropical forests’. Zenodo10.5281/zenodo.14509493 (2024). PubMed PMC

Canopy functional trait variation across Earth's tropical forests