Rarity-package: A package to calculate rarity indices for species and...

Description Details Author(s) References Examples

Description

This package allows calculation of rarity weights for species and indices of rarity for assemblages of species according to different methods (Leroy et al. 2012, In Press).

The methods developped in this package are based on occurrence (presence-absence) data. Species occurrence is transformed in rarity weights according to various methods. On the basis of the calculated rarity weights, the Index of Relative Rarity can be calculated for assemblages of species (see Leroy et al. 2012 and Leroy et al. in press)

Details

Package: Rarity
Type: Package
Version: 1.3
Date: 2013-10-28
License: GPL (>=2.0)
Depends: methods

This package works with two important functions.

First, the function rWeights is designed to calculate rarity weights according to different weighting function. This package implements the flexible weighting function integrating the rarity cutoff point (Leroy et al. 2012, in press).

Second, the function Irr is designed to calculate the Index of Relative Rarity for assemblages of species. The Index of Relative Rarity is the average of rarity weights of species in an assemblage, normalized between 0 and 1 (Leroy et al. 2012, in press).

Author(s)

Boris Leroy

Maintainer: Boris Leroy <[email protected]>

References

Leroy B., Petillon J., Gallon R., Canard A., & Ysnel F. (2012) Improving occurrence-based rarity metrics in conservation studies by including multiple rarity cut-off points. Insect Conservation and Diversity, 5, 159-168.

Leroy B., Canard A., & Ysnel F. In Press. Integrating multiple scales in rarity assessments of invertebrate taxa. Diversity and Distributions, 19, 794-803.

Examples

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# Example dataset: occurrences of spider species at two different scales
data(spid.occ)
head(spid.occ)

# Calculation of rarity weights
rarity.weights <- rWeights(occData = spid.occ, rCutoff = "Gaston")

# Generation of a random assemblage matrix
assemblages.matrix <- cbind(assemblage.1 = sample(c(0, 1), 50, replace = TRUE),
                            assemblage.2 = sample(c(0, 1), 50, replace = TRUE),
                            assemblage.3 = sample(c(0, 1), 50, replace = TRUE),
                            assemblage.4 = sample(c(0, 1), 50, replace = TRUE),
                            assemblage.5 = sample(c(0, 1), 50, replace = TRUE))
# Random attribution of species names
rownames(assemblages.matrix) <- sample(rownames(spid.occ), 50, replace = FALSE)
head(assemblages.matrix)

# Calculation of rarity indices of assemblages
Irr(assemblages = assemblages.matrix, W = rarity.weights)

Example output

                         occurMA occurWP
Acartauchenius scurrilis       3      22
Achaearanea riparia            2      27
Achaearanea simulans           3      26
Aculepeira ceropegia           2      41
Aelurillus v-insignitus       10      35
Agalenatea redii              28      51
Rarity cut-off points:
 occurMA 0.0357142857142857 / 2
 occurWP 0.339285714285714 / 19 
                      assemblage.1 assemblage.2 assemblage.3 assemblage.4
Xysticus ninnii                  1            0            0            1
Tegenaria parietina              0            1            1            0
Dictyna uncinata                 0            0            1            1
Philodromus praedatus            1            0            1            0
Walckenaeria alticeps            0            0            0            1
Dictyna civica                   0            1            1            0
                      assemblage.5
Xysticus ninnii                  1
Tegenaria parietina              1
Dictyna uncinata                 1
Philodromus praedatus            1
Walckenaeria alticeps            0
Dictyna civica                   1
                   Irr Richness
assemblage.1 0.1549423       26
assemblage.2 0.1364000       20
assemblage.3 0.1984375       24
assemblage.4 0.1668000       25
assemblage.5 0.1420476       21

Rarity documentation built on May 30, 2017, 8:21 a.m.