indicspecies (version 1.6.7)

signassoc: Statistical significance of species site-group associations

Description

This function computes the permutation p-value of the association between a species vector and a vector of memberships to a site-group. Four different tests of hypotheses arise from considering either presence/absence or quantitative species data, and from using a non-equalized or group-equalized approach.

Usage

signassoc(X, U = NULL, cluster = NULL, mode = 1, alternative = "greater", control = permControl(), print.perm = FALSE)

Value

Returns a matrix of p-values, where species are in rows and groups are in columns. Two additional columns indicate the group with lowest p-value and the p-value for this group after Sidak's correction for multiple testing.

encoding

UTF-8

Details

Input data for this function is the species matrix X and either a matrix of group memberships (U) or a vector of numeric group labels (cluster). This R function works for both presence/absence and quantitative species data, depending on the values of the input matrix X. If mode = 0, the null ecological hypothesis is that the frequency (or abundance) of the species of interest in sites belonging to the site group is not higher than the frequency (or abundance) in sites not belonging to it. If mode = 1, the null ecological hypothesis is that the relative frequency (average abundance) of the species of interest is not higher in the target site group than in other groups. See De Cáceres and Legendre for more details. Complex permutation designs are allowed through the function permControl from package "permute".

References

Bakker, J. 2008. Increasing the utility of Indicator Species Analysis. Journal of Applied Ecology 45: 1829-1835.

De Cáceres{Caceres}, M. and Legendre, P. 2009. Associations between species and groups of sites: indices and statistical inference. Ecology 90(12): 3566-3574.

See Also

strassoc, multipatt, permControl

Examples

library(stats)

data(wetland) ## Load species data

wetkm = kmeans(wetland, centers=3)## Create three clusters using

## Look for species whose abundance is significantly higher in one of the three groups
signassoc(wetland, cluster=wetkm$cluster, mode=1, control = permControl(nperm=999))

## Look for species whose abundance is significantly higher in sites belonging to one group as opposed to sites not belonging to it.
signassoc(wetland, cluster=wetkm$cluster, mode=0, control = permControl(nperm=999))