Estimating species richness in hyper-diverse large tree communities

Publication date

2017-05

Authors

ter Steege, HansISNI 0000000041555396
Sabatier, Daniel
Mota de Oliveira, S.ISNI 0000000389791752
Magnusson, William E.
Molino, Jean-François
Gomes, Vitor F
Pos, E.T.ISNI 0000000492957167
Salomão, Rafael P

Editors

Advisors

Supervisors

Document Type

Article
Open Access logo

License

taverne

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.

Keywords

Amazon, logseries, nonparametric estimators, species estimation, species richness, tropicalforests, Taverne

Citation

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