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Estimating species richness in hyper-diverse large tree communities

Authors :
Vitor Hugo Freitas Gomes
Rafael de Paiva Salomão
Daniel Sabatier
Edwin Pos
William E. Magnusson
Sylvia Mota de Oliveira
Hans ter Steege
Jean-François Molino
Naturalis Biodiversity Center
Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP)
Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])
Instituto Nacional de Pesquisas da Amazônia (INPA)
Museu Paraense Emílio Goeldi
ANR-10-LABX-0025, PVE–MEC/MCTI/CAPES/CNPq/FAPs. Grant Number: 407232/2013-3
Sub Ecology and Biodiversity
Ecology and Biodiversity
Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD [France-Sud])
Museu Paraense Emílio Goeldi [Belém, Brésil] (MPEG)
Systems Ecology
Naturalis Biodiversity Center [Leiden]
Source :
Ecology, 98(5), 1444. Ecological Society of America, Ecology, Ecology, Ecological Society of America, 2017, 98 (5), pp.1444-1454. ⟨10.1002/ecy.1813⟩, ter Steege, H, Sabatier, D, Mota de Oliveira, S, Magnusson, W E, Molino, J-F, Gomes, V F, Pos, E T & Salomão, R P 2017, ' Estimating species richness in hyper-diverse large tree communities ', Ecology, vol. 98, no. 5, pp. 1444-1454 . https://doi.org/10.1002/ecy.1813, Ecology, 98(5), 1444-1454. Ecological Society of America
Publication Year :
2017

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.

Details

Language :
English
ISSN :
00129658
Volume :
98
Issue :
5
Database :
OpenAIRE
Journal :
Ecology
Accession number :
edsair.doi.dedup.....8031c70d0a2c14e32f2e8a914209a74c
Full Text :
https://doi.org/10.1002/ecy.1813⟩