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Tier 1 — Meta-analysis / systematic reviewPeer-reviewed

Biased-corrected richness estimates for the Amazonian tree flora

Hans ter Steege, Paulo Inácio Prado, Renato A. Ferreira de Lima, Edwin Pos, Luiz de Souza Coêlho, Diógenes de Andrade Lima Filho, Rafael P. Salomão, Iêda Leão do Amaral, Francisca Dionízia de Almeida Matos, Carolina Volkmer de Castilho, Oliver Lawrence Phillips, Juan Ernesto Guevara, Marcelo de Jesus Veiga Carim, Dairon Cárdenas López, William E. Magnusson, Florian Wittmann, Maria Pires Martins, Daniel Sabatier, Mariana Victória Irume, José Renan da Silva Guimarães, Jean‐François Molino, Olaf Bánki, María Teresa Fernández Piedade, Nigel C. A. Pitman, José Ferreira Ramos, Abel Monteagudo Mendoza, Eduardo Martins Venticinque, Bruno Garcia Luize, Percy Núñez Vargas, Thiago Sanna Freire Silva, Evlyn Márcia Moraes de Leão Novo, Neidiane Farias Costa Reis, John Terborgh, Ângelo Gilberto Manzatto, Katia Regina Casula, Eurídice N. Honorio Coronado, Juan Carlos Montero, Alvaro Duque, Flávia R. C. Costa, Nicolás Castaño Arboleda, Jochen Schöngart, Charles Eugene Zartman, Timothy J. Killeen, Beatriz Schwantes Marimon, Ben Hur Marimon-Junior, Rodolfo Vásquez, Bonifacio Mostacedo, Layon Oreste Demarchi, Ted R. Feldpausch, Julien Engel, Pascal Petronelli, Christopher Baraloto, Rafael L. Assis, Hernán Castellanos, Marcelo Fragomeni Simon, Marcelo Brilhante de Medeiros, Adriano Costa Quaresma, Susan G. W. Laurance, Lorena M. Rincón, Ana Andrade, Thaiane Rodrigues de Sousa, José Luís Camargo, Juliana Schietti, Susan G. W. Laurance, Helder Lima de Queiroz, Henrique Eduardo Mendonça Nascimento, Maria Aparecida Lopes, Emanuelle de Sousa Farias, José Leonardo Lima Magalhães, Roel Brienen, Gerardo A. Aymard C., Juan David Cardenas Revilla, Ima Célia Guimarães Vieira, Bruno Barçante Ladvocat Cintra, Pablo R. Stevenson, Yuri Oliveira Feitosa, Joost F. Duivenvoorden, Hugo F. Mogollón, Alejandro Araujo-Murakami, Leandro Valle Ferreira, José Rafael Lozada, James A. Comiskey, José Júlio de Toledo, Gabriel Damasco, Nállarett Dávila, Aline Lopes, Roosevelt García-Villacorta, Frederick C. Draper, Alberto Vicentini, Fernando Cornejo Valverde, Jon Lloyd, Vitor H. F. Gomes, David Neill, Alfonso Alonso, Francisco Dallmeier, Fernanda Coelho de Souza, Rogério Gribel, Luzmila Arroyo, Fernanda Antunes Carvalho, Daniel P. P. de Aguiar

Scientific Reports · 2020

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Summary

This large-scale analysis applied an ensemble of bias-corrected richness estimators to an extended database of Amazonian forest plots to resolve longstanding debate over tree species diversity. The authors demonstrated that Amazonian species abundance follows a logseries distribution with increasing aggregation among rare species, and confirmed estimates of over 15,000 tree species. The work highlights that even tenfold increases in sampling effort would capture only ~50% of the estimated total diversity, suggesting fundamental limits to field-based inventory approaches.

Regional applicability

This study focuses on tropical Amazonian forests in South America and has limited direct applicability to United Kingdom farming or land management systems. The methodological approach to bias-corrected richness estimation may be transferable to UK woodland and grassland biodiversity assessments, though temperate systems have vastly different species pools and spatial structures.

Key measures

Species richness estimates, species abundance distribution modelling, conspecific spatial aggregation patterns, sampling completeness curves

Outcomes reported

The study estimated total tree species richness in Amazonia using ensemble parametric estimators and a novel spatial aggregation technique applied to forest plot data. The analysis confirmed approximately 15,000 tree species occur in Amazonia and assessed sampling adequacy.

Theme
Farming systems, soils & land use
Subject
Other / interdisciplinary
Study type
Research
Study design
Meta-analysis
Source type
Peer-reviewed study
Status
Published
Geography
Brazil
System type
Other
DOI
10.1038/s41598-020-66686-3
Catalogue ID
BFmucmwxjd-1ad8sd

Topic tags

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