Publications des scientifiques de l'IRD

ter Steege H., Sabatier Daniel, de Oliveira S. M., Magnusson W. E., Molino Jean-François, Gomes V. F., Pos E. T., Salomao R. P. (2017). Estimating species richness in hyper-diverse large tree communities. Ecology, 98 (5), p. 1444-1454. ISSN 0012-9658.

Titre du document
Estimating species richness in hyper-diverse large tree communities
Année de publication
2017
Type de document
Article référencé dans le Web of Science WOS:000400598500022
Auteurs
ter Steege H., Sabatier Daniel, de Oliveira S. M., Magnusson W. E., Molino Jean-François, Gomes V. F., Pos E. T., Salomao R. P.
Source
Ecology, 2017, 98 (5), p. 1444-1454 ISSN 0012-9658
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.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Sciences du monde végétal [076] ; Etudes, transformation, conservation du milieu naturel [082]
Description Géographique
AMAZONIE
Localisation
Fonds IRD [F B010070022]
Identifiant IRD
fdi:010070022
Contact