A review of Non-Parametric and Parametric Models for Species Richness Estimation.

Abstract

Species richness estimation is one of the key concepts in conservation biology. Many models have been developed to estimate species richness: ranging from commonly used non-parametric to parametric models. However, not all the models give excellent prediction of number of species in the community. Therefore, in this paper we present and compare the performances of 5 commonly used non-parametric and 9 parametric models. In this research we use Barro Colorado Island (BCI) dataset as the assemblage with 10%, 5%, 2%, and 1% of individuals being drawn for the estimations. The overall performances of the models were done using Akaike Information Criterion variances at 100 simulations. Five non-parametric models underestimate the species richness and nine parametric models overestimate the species richness. Among all the models, abundance coverage estimate model performed the best.