Estimating species richness in hyper-diverse large tree communities

H. ter Steege, D. Sabatier, S. Mota de Oliveira, W.E. Magnusson, J.-F. Molino, V. F. Gomes, E. T. Pos, R. P. Salomão

Research output: Contribution to JournalArticleAcademicpeer-review

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.
Original languageEnglish
Pages (from-to)1444-1454
Number of pages11
JournalEcology
Volume98
Issue number5
DOIs
Publication statusPublished - 2017

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species richness
tropical forest
sampling

Bibliographical note

M1 - 5

Keywords

  • Amazon logseries nonparametric estimators species estimation species richness tropical forests

Cite this

ter Steege, H., Sabatier, D., Mota de Oliveira, S., Magnusson, W. E., Molino, J-F., Gomes, V. F., ... Salomão, R. P. (2017). Estimating species richness in hyper-diverse large tree communities. Ecology, 98(5), 1444-1454. https://doi.org/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. / Estimating species richness in hyper-diverse large tree communities. In: Ecology. 2017 ; Vol. 98, No. 5. pp. 1444-1454.
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ter Steege, H, Sabatier, D, Mota de Oliveira, S, Magnusson, WE, Molino, J-F, Gomes, VF, Pos, ET & Salomão, RP 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

Estimating species richness in hyper-diverse large tree communities. / ter Steege, H.; Sabatier, D.; Mota de Oliveira, S.; Magnusson, W.E.; Molino, J.-F.; Gomes, V. F.; Pos, E. T.; Salomão, R. P.

In: Ecology, Vol. 98, No. 5, 2017, p. 1444-1454.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Estimating species richness in hyper-diverse large tree communities

AU - ter Steege, H.

AU - Sabatier, D.

AU - Mota de Oliveira, S.

AU - Magnusson, W.E.

AU - Molino, J.-F.

AU - Gomes, V. F.

AU - Pos, E. T.

AU - Salomão, R. P.

N1 - M1 - 5

PY - 2017

Y1 - 2017

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AB - 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.

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ter Steege H, Sabatier D, Mota de Oliveira S, Magnusson WE, Molino J-F, Gomes VF et al. Estimating species richness in hyper-diverse large tree communities. Ecology. 2017;98(5):1444-1454. https://doi.org/10.1002/ecy.1813