dissim: Overlap-Based Functional Dissimilarity and its Decomposition

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

Description

dissim calculates the functional dissimilarity between pairs of communities or populations, as well as its decomposition into shared and non-shared trait volume.

Usage

dissim(x = NULL)

Arguments

x	Either an object of class "TPDcomm", generated with the TPDc function, containing the TPDc of the considered communities, or an object of class "TPDsp", generated with the TPDs or TPDsMean functions, containing the TPDs of the considered populations or species.

Value

dissim returns the overlap-based functional dissimilarity between all pairs of populations/species/communities, along with the decomposition of dissimilarity between shared and non-shared trait volume.

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 three different communities:
abundances_comm_iris <- matrix(c(c(0.9, 0.1, 0), #I. setosa dominates
                         c(0.0, 0.9,  0.1 ), #I. Versic. dominates; setosa absent
                         c(0.0, 0.1,  0.9 )), #I. virg. dominates; setosa absent
                         ncol = 3, byrow = TRUE, dimnames = list(paste0("Comm.",1:3),
                          unique(iris$Species)))
TPDc_iris <- TPDc(TPDs = TPDs_iris, sampUnit = abundances_comm_iris)

#3. Estimate functional dissimilarity
example_dissimilarity_comm <- dissim (TPDc_iris)
example_dissimilarity_sps <- dissim (TPDs_iris)

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