redundancy: Functional Redundancy of Communities

In TPD: Methods for Measuring Functional Diversity Based on Trait Probability Density

Description

redundancy calculates the functional redundancy of communities, considering single or multiple traits. The functional volume (indicated by Functional Richness) occupied by a community with high functional redundancy should not decrease substantially when some species are lost, and vice versa.

Usage

redundancy(TPDc = NULL)

Arguments

TPDc	An object of class "TPDcomm", generated with the TPDc function, containing the TPDc of the considered communities.

Value

redundancy returns a list containing the functional redundancy values of all the communities from TDPc, along with the number of species of each community. It also returns a vector with the values of relative redundancy (i.e. redundancy divided by richness minus one).

Examples

#1. Compute the TPDs of three different species.
traits_iris <- iris[, c("Sepal.Length", "Sepal.Width")]
sp_iris <- iris$Species
TPDs_iris <- TPDs(species = sp_iris, traits_iris)

#2. Compute the TPDc of five different communities:
abundances_comm_iris <- matrix(c(c(0.9,  0.05, 0.05), #I. setosa dominates
                                 c(0.0,  0.5,  0.5 ), #I. setosa absent
                                 c(0.33, 0.33, 0.33), #Equal abundances
                                 c(0.1,  0.45, 0.45), #Versicolor and virginica dominate
                                 c(0.5,  0,    0.5)), #versicolor absent
                           ncol = 3, byrow = TRUE, dimnames = list(paste0("Comm.",1:5),
                           unique(iris$Species)))
TPDc_iris <- TPDc( TPDs = TPDs_iris, sampUnit = abundances_comm_iris)

#3. Estimate functional redundancy
FRed_iris <- redundancy(TPDc = TPDc_iris)

Example output

Loading required package: ggplot2
Loading required package: ks
-------Calculating densities for One population_Multiple species-----------

TPD documentation built on July 3, 2019, 1:05 a.m.