Investigate spatial autocorrelation of environmental covariables within a set of occurrences as a function of distance.
Usage
ecospat.mantel.correlogram (dfvar, colxy, n, colvar, max, nclass, nperm)
Arguments
dfvar
A dataframe object with the environmental variables.
colxy
The range of columns for x and y in df.
n
The number of random occurrences used for the test.
colvar
The range of columns for variables in df.
max
The maximum distance to be computed in the correlogram.
nclass
The number of classes of distances to be computed in the correlogram.
nperm
The number of permutations in the randomization process.
Value
Draws a plot with distance vs. the mantel r value. Black circles indicate that the values are significative different from zero. White circles indicate non significant autocorrelation. The selected distance is at the first white circle where values are non significative different from cero.
Details
Requires ecodist library. Note that computation time increase tremendously when using more than 500 occurrences (n>500)
References
Legendre, P. and M.J. Fortin. 1989. Spatial pattern and ecological analysis. Vegetatio, 80, 107-138.