Hey Jeff,

I just sent an email to R-sig-geo, but you might already have a good opinion
on this.

It's about testing the influence of distance to highway in marten space use.

I computed the Utilization Distribution (UD) using the BRB for each animal
(4 martens, with partial overlapping territories), from which I set the home
range as all cells with volume UD < 90%. For each grid cell (x,y) within
home range I extracted the distance to the highway (DistA6).

My idea was to use the UD values as response variable in model with Dist.hwy
as explanatory variable.
The question is how to address the severe spatial autocorrelation within
each animal UD and among martens?

I thought I could use (with nlme package):

mod <- lme(fixed = UD~DistA6, random=~1|Marten, correlation =corGaus(form =
~ x + y|Marten), method = "ML", data = mydata)

What do you think?

Hierarchical Bayesian Spatial Models? Never worked with those. I know you're
familiarized with Bayesian theory.

Cheers!

F

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