iNEXT: an R package for rarefaction and extrapolation of species diversity (<scp>H</scp>ill numbers)

TLDR

Hill numbers, or effective species counts, are increasingly used to quantify taxonomic diversity, and sample‑size‑ and coverage‑based rarefaction and extrapolation provide a unified standard for comparing assemblages. The authors review Hill numbers and two standardization approaches to clarify their conceptual foundations. They introduce the iNEXT R package, which computes and plots seamless rarefaction/extrapolation curves for species richness, Shannon, and Simpson indices from abundance or incidence data, and demonstrates applications such as non‑asymptotic and asymptotic analysis, sample‑coverage assessment, and point‑diversity comparison. Two illustrative examples using the package’s built‑in datasets show all functions and graphical outputs in practice.

Abstract

Summary Hill numbers (or the effective number of species) have been increasingly used to quantify the species/taxonomic diversity of an assemblage. The sample‐size‐ and coverage‐based integrations of rarefaction (interpolation) and extrapolation (prediction) of H ill numbers represent a unified standardization method for quantifying and comparing species diversity across multiple assemblages. We briefly review the conceptual background of H ill numbers along with two approaches to standardization. We present an R package iNEXT (i N terpolation/ EXT rapolation) which provides simple functions to compute and plot the seamless rarefaction and extrapolation sampling curves for the three most widely used members of the H ill number family (species richness, S hannon diversity and S impson diversity). Two types of biodiversity data are allowed: individual‐based abundance data and sampling‐unit‐based incidence data. Several applications of the iNEXT packages are reviewed: (i) Non‐asymptotic analysis: comparison of diversity estimates for equally large or equally complete samples. (ii) Asymptotic analysis: comparison of estimated asymptotic or true diversities. (iii) Assessment of sample completeness (sample coverage) across multiple samples. (iv) Comparison of estimated point diversities for a specified sample size or a specified level of sample coverage. Two examples are demonstrated, using the data (one for abundance data and the other for incidence data) included in the package, to illustrate all R functions and graphical displays.