Mantel correlogram
Calculates simple Mantel correlograms.
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)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. |
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.
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
Legendre, P. and M. Fortin. 1989. Spatial pattern and ecological analysis. Vegetatio 80:107-138.
# 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))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.