Cargando…

The devil is in the detail: estimating species richness, density, and relative abundance of tropical island herpetofauna

BACKGROUND: One of the basic premises of drawing samples from populations is that the samples are representative of the populations. However, error in sampling is poorly recognized, and it goes unnoticed especially in community ecology. By combining traditional open quadrats used for sampling forest...

Descripción completa

Detalles Bibliográficos
Autores principales: Surendran, Harikrishnan, Vasudevan, Karthikeyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4482038/
https://www.ncbi.nlm.nih.gov/pubmed/26112641
http://dx.doi.org/10.1186/s12898-015-0049-5
Descripción
Sumario:BACKGROUND: One of the basic premises of drawing samples from populations is that the samples are representative of the populations. However, error in sampling is poorly recognized, and it goes unnoticed especially in community ecology. By combining traditional open quadrats used for sampling forest floor herpetofauna with intensive bounded quadrats, we explore the effect of sampling error on estimates of species richness, diversity, and density in the Andaman Islands. RESULTS: Fisher’s α measure of species diversity and second order jackknife estimate of species richness were not sensitive to number of individuals sampled. Sampling error resulted in underestimation of density in both frogs and lizards. It influenced relative abundance of individual species resulting in underestimation of abundance of small or camouflaged species; and also resulted in low precision in lizard species richness estimates. CONCLUSIONS: Sampling error resulted in underestimation of abundance of small, fossorial or camouflaged species. Imperfect detection from less intensive sampling method results incorrect estimates of abundance of herpetofauna. Fisher’s α for species diversity and second order jackknife for species richness were robust measures. These have strong implications on inferences made from previous studies as well as sampling strategies for future studies. It is essential that these shortfalls are accounted for while communities are sampled or when datasets are compared. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12898-015-0049-5) contains supplementary material, which is available to authorized users.