Giants of the Amazon: How does environmental variation drive the diversity patterns of large trees?

de Lima, Robson Borges;Görgens, Eric Bastos;da Silva, Diego Armando S.;de Oliveira, Cinthia Pereira;Batista, Anderson Pedro B.;Caraciolo Ferreira, Rinaldo L.;Costa, Flávia R.C.;Ferreira de Lima, Renato A.;da Silva Aparício, Perseu;de Abreu, Jadson Coelho;da Silva, José Antônio Aleixo;Guimaraes, Aretha Franklin;Fearnside, Philip M.;Sousa, Thaiane R.;Perdiz, Ricardo;Higuchi, Niro;Berenguer, Erika;Resende, Angélica F.;Elias, Fernando;de Castilho, Carolina Volkmer;de Medeiros, Marcelo Brilhante;de Matos Filho, João Ramos;Sardinha, Maurício Alves;Freitas, Márcio André Furtado;da Silva, José Jussian;da Cunha, Aldemir Pereira;Santos, Renan Mendes;Muelbert, Adriane Esquivel;Guedes, Marcelino Carneiro;Imbrózio, Reinaldo;de Sousa, Carla Samara Campelo;da Silva Aparício, Wegliane Campelo;da Silva e Silva, Breno Marques;Silva, Celice Alexandre;Marimon, Beatriz;Marimon Junior, Ben Hur;Morandi, Paulo S.;Storck-Tonon, Danielle;Vieira, Ima Célia Guimarães;Schietti, Juliana;Coelho, Fernanda;Alves de Almeida, Danilo R.;Castro, Wendeson;Carvalho, Samuel P.C.;da Silva, Robson dos Santos A.;Silveira, Juliana;Camargo, José Luís;Melgaço, Karina;de Freitas, Lucas Jose Mazzei;Vedovato, Laura;Benchimol, Maíra;de Oliveira de Almeida, Gabriel;Prance, Ghillean;da Silveira, Alan Bernardes;Simon, Marcelo Fragomeni;Garcia, Marcos Leandro;Silveira, Marcos;Vital, Marcos;Andrade, Maryane B.T.;Silva, Natalino;de Araújo, Raimunda Oliveira;Cavalheiro, Larissa;Carpanedo, Rainiellen;Fernandes, Letícia;Manzatto, Angelo Gilberto;de Andrade, Ricardo T.G.;Magnusson, William E.;Laurance, Bill;Nelson, Bruce Walker;Peres, Carlos;Daly, Douglas C.;Rodrigues, Domingos;Zopeletto, Ana Paula;De Oliveira, Edmar Almeida;Dugachard, Estelle;Barbosa, Flávia Rodrigues;Santana, Flavia;Do Amaral, Iêda Leão;Ferreira, Leandro V.;Charão, Leandro S.;Ferreira, Joice;Barlow, Jos;Blanc, Lilian;Aragão, Luiz;Sist, Plinio;de Paiva Salomão, Rafael;da Silva, Antônio Sérgio Lima;Laurance, Susan;Feldpausch, Ted R.;Gardner, Toby;Santiago, Wagner;Balee, William;Laurance, William F.;Malhi, Yadvinder;Phillips, Oliver L.

William Laurance

Abstract

For more than three decades, major efforts in sampling and analyzing tree diversity in South America have focused almost exclusively on trees with stems of at least 10 and 2.5 cm diameter, showing highest species diversity in the wetter western and northern Amazon forests. By contrast, little attention has been paid to patterns and drivers of diversity in the largest canopy and emergent trees, which is surprising given these have dominant ecological functions. Here, we use a machine learning approach to quantify the importance of environmental factors and apply it to generate spatial predictions of the species diversity of all trees (dbh ≥ 10 cm) and for very large trees (dbh ≥ 70 cm) using data from 243 forest plots (108,450 trees and 2832 species) distributed across different forest types and biogeographic regions of the Brazilian Amazon. The diversity of large trees and of all trees was significantly associated with three environmental factors, but in contrasting ways across regions and forest types. Environmental variables associated with disturbances, for example, the lightning flash rate and wind speed, as well as the fraction of photosynthetically active radiation, tend to govern the diversity of large trees. Upland rainforests in the Guiana Shield and Roraima regions had a high diversity of large trees. By contrast, variables associated with resources tend to govern tree diversity in general. Places such as the province of Imeri and the northern portion of the province of Madeira stand out for their high diversity of species in general. Climatic and topographic stability and functional adaptation mechanisms promote ideal conditions for species diversity. Finally, we mapped general patterns of tree species diversity in the Brazilian Amazon, which differ substantially depending on size class.

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Global Change Biology

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1365-2486

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John Wiley & Sons Ltd

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DOI

10.1111/gcb.16821