Canopy functional trait variation across Earth’s tropical forests
Aguirre-Gutiérrez, Jesús | Rifai, Sami W. | Deng, Xiongjie | ter Steege, Hans | Thomson, Eleanor | Corral-Rivas, Jose Javier | Guimaraes, Aretha Franklin | Muller, Sandra | Klipel, Joice | Fauset, Sophie | Resende, Angelica F. | Wallin, Göran | Joly, Carlos A. | Abernethy, Katharine | Adu-Bredu, Stephen | Alexandre Silva, Celice | de Oliveira, Edmar Almeida | Almeida, Danilo R.A. | Alvarez-Davila, Esteban | Asner, Gregory P. | Baker, Timothy R. | Benchimol, Maíra | Bentley, Lisa Patrick | Berenguer, Erika | Blanc, Lilian | Bonal, Damien | Bordin, Kauane | Borges de Lima, Robson | Both, Sabine | Cabezas Duarte, Jaime | Cardoso, Domingos | de Lima, Haroldo C. | Cavalheiro, Larissa | Cernusak, Lucas A. | dos Santos Prestes, Nayane Cristina C. | da Silva Zanzini, Antonio Carlos | da Silva, Ricardo José | dos Santos Alves da Silva, Robson | de Andrade Iguatemy, Mariana | De Sousa Oliveira, Tony César | Dechant, Benjamin | Derroire, Géraldine | Dexter, Kyle G. | Rodrigues, Domingos J. | Espírito-Santo, Mário | Silva, Letícia Fernandes | Domingues, Tomas Ferreira | Ferreira, Joice | Simon, Marcelo Fragomeni | Girardin, Cécile A.J. | Hérault, Bruno | Jeffery, Kathryn J. | Kalpuzha Ashtamoorthy, Sreejith | Kavidapadinjattathil Sivadasan, Arunkumar | Klitgaard, Bente | Laurance, William F. | Dan, Maurício Lima | Magnusson, William E. | Campos-Filho, Eduardo Malta | Manoel dos Santos, Rubens | Manzatto, Angelo Gilberto | Silveira, Marcos | Marimon-Junior, Ben Hur | Martin, Roberta E. | Vieira, Daniel Luis Mascia | Metzker, Thiago | Milliken, William | Moonlight, Peter | Moraes de Seixas, Marina Maria | Morandi, Paulo S. | Muscarella, Robert | Nava-Miranda, María Guadalupe | Nyirambangutse, Brigitte | Silva, Jhonathan Oliveira | Oliveras Menor, Imma | Francisco Pena Rodrigues, Pablo José | Pereira de Oliveira, Cinthia | Pereira Zanzini, Lucas | Peres, Carlos A. | Punjayil, Vignesh | Quesada, Carlos A. | Réjou-Méchain, Maxime | Riutta, Terhi | Rivas-Torres, Gonzalo | Rosa, Clarissa | Salinas, Norma | Bergamin, Rodrigo Scarton | Marimon, Beatriz Schwantes | Shenkin, Alexander | Silva Rodrigues, Priscyla Maria | Figueiredo, Axa Emanuelle Simões | Garcia, Queila Souza | Spósito, Tereza | Storck-Tonon, Danielle | Sullivan, Martin J.P. | Svátek, Martin | Vieira Santiago, Wagner Tadeu | Arn Teh, Yit | Theruvil Parambil Sivan, Prasad | Nascimento, Marcelo Trindade | Veenendaal, Elmar | Zo-Bi, Irie Casimir | Dago, Marie Ruth | Traoré, Soulemane | Patacca, Marco | Badouard, Vincyane | de Padua Chaves e Carvalho, Samuel | White, Lee J.T. | Zhang-Zheng, Huanyuan | Zibera, Etienne | Zwerts, Joeri Alexander | Burslem, David F.R.P. | Silman, Miles | Chave, Jérôme | Enquist, Brian J. | Barlow, Jos | Phillips, Oliver L. | Coomes, David A. | Malhi, Yadvinder
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.
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