iNEXT.beta3D-package {iNEXT.beta3D}

Interpolation and extrapolation with beta diversity for three dimensions of biodiversity

Description

This package iNEXT.beta3D (iNterpolation and EXTrapolation with beta diversity for three dimensions of biodiversity) is a sequel to iNEXT. Here the three dimensions (3D) of diversity includes taxonomic diversity (TD), phylogenetic diversity (PD) and functional diversity (FD). An online version "iNEXT.beta3D Online" (https://chao.shinyapps.io/iNEXT_beta3D/) is also available for users without an R background.

A unified framework based on Hill numbers (for TD) and their generalizations (Hill-Chao numbers, for PD and FD) is adopted to quantify 3D. In this framework, TD quantifies the effective number of species, PD quantifies the effective total branch length or total evolutionary history, mean-PD (PD divided by tree depth) quantifies the effective number of lineages, and FD quantifies the effective number of virtual functional groups (or functional "species"). Thus, TD, mean-PD, and FD are all in the same units of species/lineage equivalents and can be meaningfully compared; see Chao et al. (2021) for a review of the unified framework.

For each of the three dimensions, iNEXT.beta3D focuses on the multiplicative diversity decomposition (gamma = alpha x beta) of orders q = 0, 1 and 2 based on sampling data. Beta diversity quantifies the extent of among-assemblage differentiation, or the changes in species/lineages/functional-groups composition and their abundance among assemblages. iNEXT.beta3D features standardized 3D estimates with a common sample size (for alpha and gamma diversity) or sample coverage (for alpha, beta and gamma diversity). iNEXT.beta3D also features standardized estimates of four classes of coverage-based dissimilarity measures. Based on the rarefaction and extrapolation (R/E) method for Hill numbers (TD) for q = 0, 1 and 2, Chao et al. (2023b) developed the pertinent R/E theory for taxonomic beta diversity with applications to real-world spatial, temporal and spatio-temporal data. An application to Gentry's global forest data along with a concise description of the theory is provided in Chao et al. (2023a). The extension to phylogenetic and functional beta diversity is generally parallel.

iNEXT.beta3D also features two types of R/E sampling curves:

* Sample-size-based (or size-based) R/E curves: This type of sampling curve plots standardized 3D gamma and alpha diversity with respect to sample size. Note that the size-based beta diversity is not a statistically valid measure (Chao et al. 2023b) and thus the corresponding sampling curve is not provided.

* Coverage-based R/E sampling curves: This type of sampling curve plots standardized 3D gamma, alpha, and beta diversity as well as four classes of dissimilarity measures with respect to sample coverage (an objective measure of sample completeness).

Sufficient data are needed to run iNEXT.beta3D. If your data comprise only a few species and their abundances/phylogenies/traits, it is probable that the data lack sufficient information to run iNEXT.beta3D.

This package contains three main functions:

1. iNEXTbeta3D computes standardized 3D estimates with a common sample size (for alpha and gamma diversity) or sample coverage (for alpha, beta and gamma diversity) for default sample sizes or coverage values. This function also computes coverage-based standardized 3D estimates of four classes of dissimilarity measures for default coverage values. In addition, this function also computes standardized 3D estimates with a particular vector of user-specified sample sizes or coverage values.

2. ggiNEXTbeta3D visualizes the output from the function iNEXTbeta3D.

3. DataInfobeta3D provides basic data information for (1) the reference sample in each assemblage, (2) the gamma reference sample in the pooled assemblage, and (3) the alpha reference sample in the joint assemblage.

Author(s)

Anne Chao, K.H. Hu

Maintainer: Anne Chao <[e-mail]>

References

Chao, A., Chiu, C.-H., Hu, K.-H., and Zeleny, D. (2023a). Revisiting Alwyn H. Gentry's forest transect data: a statistical sampling-model-based approach. Japanese Journal of Statistics and Data Science, 6, 861-884. https://doi.org/10.1007/s42081-023-00214-1

Chao, A., Henderson, P. A., Chiu, C.-H., Moyes, F., Hu, K.-H., Dornelas, M. and Magurran, A. E. (2021). Measuring temporal change in alpha diversity: a framework integrating taxonomic, phylogenetic and functional diversity and the iNEXT.3D standardization. Methods in Ecology and Evolution, 12, 1926-1940.

Chao, A., Thorn, S., Chiu, C.-H., Moyes, F., Hu, K.-H., Chazdon, R. L., Wu, J., Dornelas, M., Zeleny, D., Colwell, R. K., and Magurran, A. E. (2023b). Rarefaction and extrapolation with beta diversity under a framework of Hill numbers: The iNEXT.beta3D standardization. Ecological Monographs e1588. https://doi.org/10.1002/ecm.1588