# 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 presented in Grenié et al. (2017) .

`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:

## Installation

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

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

## Dependencies

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

## Example vignettes

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.

Access the vignette through R using the `vignette()` function.

## References

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

# funrar 1.2.0

• Split `rarity_dimensions()` in two more explicit functions: `uniqueness_dimensions()` and `distinctiveness_dimensions()` split corresponding tests;
• Add internal function to compute multiple functional distance matrix using a single trait table (`combination_trait_dist()`);
• `distinctiveness()` now fully conserve the dimnames of the provided site-species matrix.

# funrar 1.1.1

• Add tests for `rarity_dimensions()`;
• `rarity_dimensions()` now comprises both Uniqueness and Distinctiveness;
• Remove packages `StatMatch`, `microbenchmark` & `reshape2` from suggested packages.

# funrar 1.1.0

• Made `make_absolute()` defunct because it was based on false assumptions and would not give back matrices of relative abundances;
• Improved examples of `make_relative()`, `uniqueness()`, `distinctiveness()` to compute across single communities or regional pools;
• Add `rarity_dimensions()` function to measure the different facets of rarity according to the trait;
• Add `center` and `scale` arguments in `compute_dist_matrix()` to scale traits before computing distance, these arguments are sensitive to the specific distance metric used;
• Use markdown with `roxygen2` to generates documentation.

# funrar 1.0.3

• Corrected bug so that dense matrices can be transformed to stack data frame using `matrix_to_stack()` (#19),
• Updated citation for Violle et al. 2017,
• Use package `goodpractice` to enforce better code style,
• Add `is_relative()` function to test if matrix contains relative abundances, `scarcity()` and `distinctiveness()` now warns if it is not the case (#21),
• Conditionnally use `microbenchmark` following CRAN advices.

# 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

install.packages("funrar")

1.2.1 by Matthias Grenié, a day 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 Grenié [aut, cre] (<https://orcid.org/0000-0002-4659-7522>), Pierre Denelle [aut] (<https://orcid.org/0000-0001-5037-2281>), Caroline Tucker [aut] (<https://orcid.org/0000-0002-4871-2010>), François Munoz [ths] (<https://orcid.org/0000-0001-8776-4705>), Cyrille Violle [ths] (<https://orcid.org/0000-0002-2471-9226>)

Documentation:   PDF Manual