TPD (version 1.1.0)

uniqueness: Functional Uniqueness of Ecological Units

Description

uniqueness estimates the functional uniqueness of species, communities by comparing the TPD of lower levels (i.e. species), with that of higher levels (i.e. communities). TPD's are compared by means of overlap. High overlap means low uniqueness (i.e. the species traits are frequent in the community), whereas low overlap means high uniqueness. Uniqueness is then estimated as 1-overlap. The function is hence basically the same as 'dissim', with some slight modifications. Despite functional uniqueness can be estimated at any scale, current implementation is limited to species within communities (although communities can be easily created to represent regions, or regional pools of species).

Usage

uniqueness(TPDs = NULL, TPDc = NULL)

Arguments

TPDs

An object of class "TPDsp", generated with the TPDs function, containing the TPDs of the considered species

TPDc

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

Value

uniqueness returns a matrix, with the communities in rows and the species in columns. The values in the matrix represent the functional uniqueness of each species in each community. Very unique species will have values close to 1, whereas non-unique species will have values close to 0.

Examples

# NOT RUN {
# 1.  Compute the TPDs of three different species
traits_iris <- iris[, c("Sepal.Length", "Sepal.Width")]
sp_iris <- iris$Species
example_TPDs <- TPDs(species = sp_iris, traits = traits_iris)

#2. Three different communities with different abundances of each species
example_abundances <- matrix(c(c(0.5, 0.3, 0.2,
                                 0.1, 0.8, 0.1,
                                 0.5, 0,   0.5)), #I. virg. dominates; setosa absent
                         ncol = 3, byrow = TRUE, dimnames = list(paste0("Comm.",1:3),
                         unique(iris$Species)))
example_TPDc <- TPDc (TPDs = example_TPDs, sampUnit = example_abundances)

#3. Calculate the uniqueness of each species in each community
example_uniqueness <- uniqueness (TPDs = example_TPDs, TPDc = example_TPDc)

# }