Use este identificador para citar ou linkar para este item: https://repositorio.inpa.gov.br/handle/1/17122
Título: Estimating species richness in hyper-diverse large tree communities
Autor: ter Steege, H.
Sabatier, Daniel
Oliveira, Sylvia Mota de
Magnusson, William Ernest
Molino, Jean François
Gomes, Vitor H.F.
Pos, Edwin T.
Salomão, Rafael Paiva
Palavras-chave: Data Set
Estimation Method
Plant Community
Species Richness
Tropical Forest
Amazonia
Biodiversity
Ecology
Forest
Tree
Biodiversity
Ecology
Forests
Trees
Data do documento: 2017
Revista: Ecology
É parte de: Volume 98, Número 5, Pags. 1444-1454
Abstract: Species richness estimation is one of the most widely used analyses carried out by ecologists, and nonparametric estimators are probably the most used techniques to carry out such estimations. We tested the assumptions and results of nonparametric estimators and those of a logseries approach to species richness estimation for simulated tropical forests and five data sets from the field. We conclude that nonparametric estimators are not suitable to estimate species richness in tropical forests, where sampling intensity is usually low and richness is high, because the assumptions of the methods do not meet the sampling strategy used in most studies. The logseries, while also requiring substantial sampling, is much more effective in estimating species richness than commonly used nonparametric estimators, and its assumptions better match the way field data is being collected. © 2017 by the Ecological Society of America
DOI: 10.1002/ecy.1813
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