This repository hosts an R package that is actively being developed for estimating biodiversity and the components of its change. The key innovations of this R package over other R packages that also carry out rarefaction (e.g., vegan, iNext) is that mobr is focused on 1) making empirical comparisons between treatments or gradients, and 2) our framework emphasizes how changes in biodiversity are linked to changes in community structure: the SAD, total abundance, and spatial aggregation.

Please use the dev branch for the beta version of the repository that has the most up-to-date methods. See examples of how to compute diversity metrics using the dev branch here: R script and pdf. Instructions are provided below on how to use devtools to install the dev branch using R

The concepts and methods behind this R package are described in three publications.

McGlinn, D.J. X. Xiao, F. May, N.J Gotelli, T. Engel, S.A Blowes, T.M. Knight, O. Purschke, J.M Chase, and B.J. McGill. 2019. MoB (Measurement of Biodiversity): a method to separate the scale-dependent effects of species abundance distribution, density, and aggregation on diversity change. Methods in Ecology and Evolution. 10:258–269. https://doi.org/10.1111/2041-210X.13102

McGlinn, D.J. T. Engel, S.A. Blowes, N.J. Gotelli, T.M. Knight, B.J. McGill, N. Sanders, and J.M. Chase. 2020. A multiscale framework for disentangling the roles of evenness, density, and aggregation on diversity gradients. Ecology. https://doi.org/10.1002/ecy.3233

Chase, J.M., B. McGill, D.J. McGlinn, F. May, S.A. Blowes, X. Xiao, T. Knight. 2018. Embracing scale-dependence to achieve a deeper understanding of biodiversity and its change across communities. Ecology Letters. 21: 1737–1751. https://doi.org/10.1111/ele.13151

Please cite mobr. Run the following to get the appropriate citation for the version you're using:

citation(package = "mobr")

install.packages('mobr')

Or, install development version

install.packages('devtools')
library(devtools)

Now that devtools is installed you can install `mobr using the following R code:

install_github('MoBiodiv/mobr')
# if dev branch wanted used
install_github('MoBiodiv/mobr', ref = 'dev')

The package vignette provides a useful walk-through the package tools, but below is some example code that uses the two key analyses and related graphics.

library(mobr)
data(inv_comm)
data(inv_plot_attr)
inv_mob_in = make_mob_in(inv_comm, inv_plot_attr, coord_names = c('x', 'y'))
inv_stats = get_mob_stats(inv_mob_in, 'group', ref_level = 'uninvaded')
plot(inv_stats)
inv_deltaS = get_delta_stats(inv_mob_in, 'group', ref_level='uninvaded',
                             type='discrete', log_scale=TRUE, n_perm = 5)
plot(inv_deltaS, 'b1')

• Please report any issues or bugs.
• License: MIT
• Get citation information for mobr in R doing citation(package = 'mobr')
• Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

• Gregor Seyer for providing a constructive review of our CRAN submission
• Kurt Hornik for helping us keep up with CRAN changes.