rarestR: An R package using rarefaction metrics to estimate α-diversity (species richness) and β-diversity (species shared) for incomplete samples

Author:

Zou YiORCID,Zhao Peng,Wu Naicheng,Lai Jiangshan,Peres-Neto Pedro R.,Axmacher Jan C.

Abstract

AbstractSpecies abundance data is commonly used to study biodiversity patterns. In this context, estimating α- and β-diversity based on incomplete samples can lead to ‘undersampling biases’. It is therefore essential to employ methods that enable accurate comparisons of α- and β-diversity across varying sample sizes. This involves relying on biodiversity measures that are focused on accurately estimating the total number of species within a community, as well as the total number of species shared by two communities. Rarefaction offers such a method, where α-diversity is estimated for standardized sample sizes. Rarefaction methods can also be used as a basis for β-diversity calculations for standardized sample sizes. In this application note, we introduce a new R package,rarestR, designed to estimate abundance-based α- and β-diversity measures for inconsistent samples using rarefaction metrics. Additionally, the package offers parametric extrapolations to estimate the total expected number of species within a single community and the total expected number of species shared between two communities. Furthermore, it provides visualization for the curve fitting associated with these estimators. Overall, therarestRpackage is useful in estimating α- and β-diversity values for incomplete samples, for example in studies involving highly mobile or species-rich taxa. These species estimators offer a complementary approach to non-parametric methods, such as the Chao series of estimators.

Publisher

Cold Spring Harbor Laboratory

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