untb (version 1.7-2)

optimal.params.gst: Estimation of local immigration using GST(k) statistics

Description

Functions optimal.params.gst(), GST.k() and I.k() apply to count data collected over a network of community samples k (species by sample matrix). A theoretical relationship between GST(k) statistics and local immigration numbers I(k), in the context of a spatially-implicit neutral community model (Munoz et al 2008), is used to provide GST(k) and I(k) statistics any sample k. If requested, optimal.params.gst() further provides the user with confidence bounds.

Usage

optimal.params.gst(D, exact = TRUE, ci = FALSE, cint = c(0.025, 0.975), nbres = 100) GST.k(D, exact = TRUE) I.k(D, exact = TRUE)

Arguments

D
A data table including species counts in a network of community samples (columns)
exact
If TRUE, exact similarity statistics are calculated (sampling without replacement) while, if false, approximate statistics (sampling with replacement) are considered (see Munoz et al 2008 for further statistical discussion)
ci
Specifies whether bootstraps confidence intervals of immigration estimates are to be calculated
cint
Bounds of the confidence interval, if ci = TRUE
nbres
Number of rounds of the bootstrap procedure for confidence interval calculation, if ci = T

Value

GST
A vector of 0 to 1 GST(k) numbers (specific output of GST.k)
nk
Number of individuals within samples (length = number of samples)
distrib
Species counts of the merged dataset (output of GST.k and I.k)
I
Immigration estimates (output of I.k and optimal.params.gst)
m
Corresponding immigration rates (output of I.k and optimal.params.gst). Specific outputs of optimal.params.gst when ci = T (bootstrap procedure)
Ici
Confidence interval of I(k)
mci
Confidence interval of m(k)
Iboot
Table of bootstrapped values of I(k)
mboot
Table of bootstrapped values of im(k)

References

Francois Munoz, Pierre Couteron and B.R. Ramesh (2008). “Beta-diversity in spatially implicit neutral models: a new way to assess species migration.” The American Naturalist 172(1): 116-127

See Also

optimal.params,optimal.params.sloss

Examples

Run this code
data(ghats)
optimal.params.gst(ghats)

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