Data/hora: 10/06/2024 15:19:47

Provedor de dados: | 99
País: | Argentina
Título: | Choosing the best non-parametric richness estimator for benthic macroinvertebrates databases
Autores: | Basualdo,Carola V.
Data: | 2011-06-01
Ano: | 2011
Palavras-chave: | Richness estimation; Neotropical streams; Environmental management.
Resumo: | Non-parametric estimators allow to compare the estimates of richness among data sets from heterogeneous sources. However, since the estimator performance depends on the species-abundance distribution of the sample, preference for one or another is a difficult issue. The present study recovers and revalues some criteria already present in the literature in order to choose the most suitable estimator for streams macroinvertebrates, and provides some tools to apply them. Two abundance and four incidence estimators were applied to a regional database at family and genus level. They were evaluated under four criteria: sub-sample size required to estimate the observed richness; constancy of the sub-sample size; lack of erratic behavior and similarity in curve shape through different data sets. Among incidence estimators, Jack1 had the best performance. Between abundance estimators, ACE was the best when the observed richness was small and Chao1 when the observed richness was high. The uniformity of curves shapes allowed to describe the general sequences of curves behavior that could act as references to compare estimations of small databases and to infer the possible behavior of the curve (i.e the expected richness) if the sample were larger. These results can be very useful for environmental management, and update the state of knowledge of regional macroinvertebrates.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.org.ar/scielo.php?script=sci_arttext&pid=S0373-56802011000100003
Editor: | Sociedad Entomológica Argentina
Formato: | text/html
Fonte: | Revista de la Sociedad Entomológica Argentina  v.70 n.1-2 2011
Fonte: | info:eu-repo/semantics/openAccess