vegetarian (version 1.2)

sim.table: Similarity Summary Table

Description

Creates a summary table of community overlap for all possible pairwise combinations of samples (e.g. sites, plots) using the similarity function.

Usage

sim.table(abundances, q = 1, labels = FALSE, half = TRUE, diag = TRUE, boot = FALSE, boot.arg = list(s.sizes = NULL, num.iter = 100))

Arguments

abundances

Community data as a matrix where columns are individual species and rows are sites. Matrix elements are abundance data (e.g. counts, percent cover estimates).

q

Order of the diversity measure. Defaults to the Shannon case where q = 1.

labels

Logical statement. If labels=TRUE, then site names are given as the first column of the abundance matrix. The default is labels=FALSE where no site names are given in the abundance matrix.

half

Logical statement that changes the display of the resulting matrix. The default is half=TRUE, where the similarities are not repeated and are given as NaN values on one side of the diagonal in the resulting matrix. If half=FALSE, then the displayed similarities are repeated on either side of the diagonal of the resulting matrix.

diag

Logical statement that changes the display of the resulting matrix. The default is diag=TRUE, where the elements in the diagonal of the resulting similarity matrix are all equal to one because a sample should be completely identical to itself. If diag=FALSE, then then the elements in the diagonal of the resulting similarity matrix are given NaN values.

boot

Logical indicating whether to use bootstrapping to estimate uncertainty. If boot=TRUE, only standard errors will be output in table; to get both values and standard error of similarities, must call sim.groups twice, setting boot to both TRUE and FALSE

boot.arg

(optional) List of arguments to pass bootstrapping function: list(s.sizes=number you specify, num.iter=number you specify)

Value

Details

This function calculates pairwise similarity for two or more samples, so the abundance data must be a matrix with two or more rows (samples). Depending on the specification of the order (q), other different similarity indices may be calculated (e.g. Sorenson index when q=0, Horn index when q=1, Morisita-Horn index when q=2) (Jost 2007).

References

Jost, L. 2007. Partitioning diversity into independent alpha and beta components. Ecology 88(10): 2427-2439.

See Also

similarity, sim.groups

Examples

data(simesants)
sim.table(simesants[,-1])
sim.table(simesants,labels=TRUE)
sim.table(simesants,labels=TRUE, diag=FALSE)
sim.table(simesants,labels=TRUE, half=FALSE)
sim.table(simesants,labels=TRUE,boot=TRUE)#standard errors only
sim.table(simesants,labels=TRUE,boot=TRUE, boot.arg=list(num.iter=200), q=2)#standard errors only