Functional Rarity Indices Computation

Computes functional rarity indices as proposed by Violle et al. (2017) . Various indices can be computed using both regional and local information. Functional Rarity combines both the functional aspect of rarity as well as the extent aspect of rarity.


funrar is a package to compute functional rarity indices, it quantifies how species are rare both from a functional and an extent point of view. Following the different facets of rarity proposed by Rabinowitz 1981. See this reference for more details on Functional Rarity indices:

The package is on CRAN, you can install it using:

install.packages("funrar")

If you want to have the latest development version use devtools:

# install.packages("devtools") # If 'devtools' is not installed yet
devtools::install_github("Rekyt/funrar")

Apart from base packages dependencies, funrar depends on dplyr and cluster.

In addition to code example included in help of functions, two vignettes explain how to use the package. The functional rarity indices vignette explains in details the different indices and function provided; while the sparse matrices vignette shows how to use sparse matrices to gain speed in memory when computing functional rarity indices.

Rabinowitz D., Seven forms of rarity In The Biological Aspects of Rare Plant Conservation (1981), pp. 205-217

News

funrar 1.0.2

  • Added functions to convert absolute abundance matrix to relative abundance matrix, make_relative() and reverse function make_absolute(),
  • Added a NEWS.md file to track changes to the package.

Reference manual

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install.packages("funrar")

1.2.0 by Matthias GreniƩ, 3 months ago


https://github.com/Rekyt/funrar


Report a bug at https://github.com/Rekyt/funrar/issues


Browse source code at https://github.com/cran/funrar


Authors: Matthias GreniƩ [aut, cre], Pierre Denelle [aut], Caroline Tucker [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports cluster, dplyr, methods, stats

Suggests ade4, ggplot2, knitr, Matrix, rmarkdown, testthat


See at CRAN