mgram {ecodist} R Documentation

Mantel correlogram

Description

Calculates simple Mantel correlograms.

Usage

mgram(species.d, space.d, breaks, nclass, stepsize, nperm = 1000,
mrank = FALSE, nboot = 500, pboot = 0.9, cboot = 0.95,
alternative = "two.sided", trace = FALSE)


Arguments

 species.d lower-triangular dissimilarity matrix. space.d lower-triangular matrix of geographic distances. breaks locations of class breaks. If specified, overrides nclass and stepsize. nclass number of distance classes. If not specified, Sturge's rule will be used to determine an appropriate number of classes. stepsize width of each distance class. If not specified, nclass and the range of space.d will be used to calculate an appropriate default. nperm number of permutations to use. If set to 0, the permutation test will be omitted. mrank if this is set to FALSE (the default option), Pearson correlations will be used. If set to TRUE, the Spearman correlation (correlation ranked distances) will be used. nboot number of iterations to use for the bootstrapped confidence limits. If set to 0, the bootstrapping will be omitted. pboot the level at which to resample the data for the bootstrapping procedure. cboot the level of the confidence limits to estimate. alternative default is "two.sided", and returns p-values for H0: rM = 0. The alternative is "one.sided", which returns p-values for H0: rM <= 0. trace if TRUE, returns progress indicators.

Details

This function calculates Mantel correlograms. The Mantel correlogram is essentially a multivariate autocorrelation function. The Mantel r represents the dissimilarity in variable composition (often species composition) at a particular lag distance.

Value

Returns an object of class mgram, which is a list with two elements. mgram is a matrix with one row for each distance class and 6 columns:

 lag  midpoint of the distance class. ngroup  number of distances in that class. mantelr  Mantel r value. pval  p-value for the test chosen. llim  lower bound of confidence limit for mantelr. ulim  upper bound of confidence limit for mantelr.

resids is NA for objects calculated by mgram().

Sarah Goslee

References

Legendre, P. and M. Fortin. 1989. Spatial pattern and ecological analysis. Vegetatio 80:107-138.

mantel, plot.mgram, pmgram

Examples


# generate a simple surface
x <- matrix(1:10, nrow=10, ncol=10, byrow=FALSE)
y <- matrix(1:10, nrow=10, ncol=10, byrow=TRUE)
z <- x + 3*y
image(z)

# analyze the pattern of z across space
space <- cbind(as.vector(x), as.vector(y))
z <- as.vector(z)
space.d <- distance(space, "eucl")
z.d <- distance(z, "eucl")
z.mgram <- mgram(z.d, space.d, nperm=0)
plot(z.mgram)

#

data(graze)
space.d <- dist(graze$sitelocation) forest.d <- dist(graze$forestpct)

grasses <- graze[, colnames(graze) %in% c("DAGL", "LOAR10", "LOPE", "POPR")]
legumes <- graze[, colnames(graze) %in% c("LOCO6", "TRPR2", "TRRE3")]

grasses.bc <- bcdist(grasses)
legumes.bc <- bcdist(legumes)

# Does the relationship of composition with distance vary for
# grasses and legumes?
par(mfrow=c(2, 1))
plot(mgram(grasses.bc, space.d, nclass=8))
plot(mgram(legumes.bc, space.d, nclass=8))



[Package ecodist version 2.0.9 Index]