wassermann: Partial Mantel tests on costdistance matrices

In PopGenReport: A Simple Framework to Analyse Population and Landscape Genetic Data

Partial Mantel tests on costdistance matrices

Description

This function implements the Causal modelling approach as suggested by Wassermann et al. 2010 and Cushman et al. 2010. It tests for the effect of landscape features using a cost distance matrix on the genetic structure of subpopulation/individuals.

Usage

wassermann(gen.mat, cost.mats, eucl.mat = NULL, plot = TRUE, nperm = 999)

Arguments

gen.mat	pairwise genetic distance matrix
cost.mats	pairwise cost distance matrix
eucl.mat	pairwise Eukclidean distance matrix
plot	switch for control plots of the partial mantel test
nperm	number of permutations for the partial mantel test

Details

see landgenreport

Value

A table with the results of the partial mantel test. Using plot=TRUE results in diagnostic plots for the partial mantel tests.

Author(s)

Bernd Gruber ([e-mail])

References

Wassermann, T.N., Cushman, S. A., Schwartz, M. K. and Wallin, D. O. (2010). Spatial scaling and multi-model inference in landscape genetics: Martes americana in northern Idaho. Landscape Ecology, 25(10), 1601-1612.

See Also

popgenreport, genleastcost, landgenreport, lgrMMRR

Examples

library(raster)
fric.raster <- readRDS(system.file("extdata","fric.raster.rdata", package="PopGenReport"))
glc <- genleastcost(landgen, fric.raster, "D", NN=8)
wassermann(eucl.mat = glc$eucl.mat, cost.mats = glc$cost.mats, gen.mat = glc$gen.mat)

PopGenReport documentation built on Oct. 11, 2023, 9:07 a.m.