Hello all,

I'm new in the list so I apologize for any repeated subject.

I'm currently analyzing the influence of highway proximity on marten space
use.

I computed the Utilization Distribution (UD) 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)

Would anyone have any comment or a better option?

Thanks in advance

sample data
 Marten      x       y VolUD           UD Habitat   DistA6
1 Deolinda 558645 4277578 89.14 8.222391e-08       2 960.0000
2 Deolinda 558745 4277578 85.83 9.814430e-08       2 960.0000
3 Deolinda 558845 4277578 84.82 1.013881e-07       2 960.0000
4 Deolinda 558945 4277578 83.58 1.052588e-07       1 960.0000
5 Deolinda 559045 4277578 82.31 1.074694e-07       2 961.8732
6 Deolinda 559145 4277578 82.63 1.072279e-07       2 971.6481

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