tSamp: Trait Values Sampling

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

Description

tSamp samples (with replacement) trait values from populations, species or communities. The probability of sampling each trait –or combination of traits in multidimensional cases– is proportional to the value of TPDs or TPDc for the corresponding cell (the trait space is divided in a grid composed of cells, see TPDs for further information).

Usage

tSamp(TPDc = NULL, TPDs = NULL, size = 1)

Arguments

TPDc	An object of class "TPDcomm", generated with the TPDc function, containing the TPDc of the considered communities.
TPDs	An object of class "TPDsp", generated with the TPDs function, containing the TPDs of the considered populations or species.
size	Non-negative integer giving the number of observations to choose. Defaults to 1.

Value

tSamp returns a list containing sampled trait values for each community of TPDc or species/populations from TPDs.

Examples

# 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. Sample 1,000 trait values from each species and community
example_sampling <- tSamp(TPDc = example_TPDc, TPDs = example_TPDs,
                                 size = 1000)

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