Estimating total species richness: fitting rarefaction by asymptotic approximation

Estimating the number of species in a community is important for assessments of biodiversity. Previous species richness estimators are mainly based on non-parametric approaches. Although parametric asymptotic models have been applied, they received limited attention due to specific limitations. Here, we introduce parametric models fitting the probability-based rarefied species richness curve that allow us to estimate the ‘Total Expected Species’ (TES) in a community based on species’ abundance data. We develop two approaches to calculate TES (termed ‘TESa’ and ‘TESb’), based on two slightly different mathematical assumptions regarding Expected Species (ES) models. We provide R functions to calculate both these estimation approaches and their standard deviation. The function also enables users to visualize the estimation. We test the performance of TESa, TESb and their average (TESab) across simulated and empirical data, and compare their bias, precision and accuracy with other, commonly...