Please use this identifier to cite or link to this item: https://repositorio.inpa.gov.br/handle/1/17122
Title: Estimating species richness in hyper-diverse large tree communities
Authors: 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
Keywords: Data Set
Estimation Method
Plant Community
Species Richness
Tropical Forest
Amazonia
Biodiversity
Ecology
Forest
Tree
Biodiversity
Ecology
Forests
Trees
Issue Date: 2017
metadata.dc.publisher.journal: Ecology
metadata.dc.relation.ispartof: 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
metadata.dc.identifier.doi: 10.1002/ecy.1813
Appears in Collections:Artigos

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