adehabitatHR: calculation of UDOI using adaptive and fixed kernels
I am trying to quantify the utilization distribution overlap index (UDOI;
e.g., Fieberg and Kochanny 2005) for several birds using the package
adehabitatHR (v. 0.4.2). I have already generated utilization distributions
(UD) for the birds using adaptive and fixed kernel methods in Animal Space
Use (Horne and Garton 2006a, Horne and Garton 2006b, Horne and Garton
2007). Specifically, the information theoretic approach available in Animal
Space Use was used to determine the most appropriate method to estimate
home ranges for each of our birds, which resulted in a mix of adaptive and
fixed kernels. Preferably, I would like to pass the UDs generated in Animal
Space Use to the function kerneloverlap (or perhaps kerneloverlaphr) in
adehabitatHR, but I cant find the methods/documentation to do so.
Alternatively, I could generate UDs using the kernelUD function in
adehabitatHR. However, as far as I can tell, adaptive and fixed kernel
methods are not available in the kernelUD function.
A sample of the UD data (output as a .txt) from Animal Space Use for two
birds (I added Name):
X Y Name Probability
3687857.115 452370.15 A 0.000000002
3687857.115 452371.85 A 0.000000002
3687857.115 452373.55 A 0.000000003
3687857.115 452375.25 A 0.000000003
3687857.115 452376.95 A 0.000000003
3687857.115 452378.65 A 0.000000003
3687875.5 452350.31 B 0.000000031
3687875.5 452352.05 B 0.000000039
3687875.5 452353.79 B 0.000000048
3687875.5 452355.53 B 0.00000006
3687875.5 452357.27 B 0.000000073
3687875.5 452359.01 B 0.000000088
1) Is there a way to pass the UDs generated in Animal Space Use to
kerneloverlap/kerneloverlaphr in adehabitatHR? If so, how might I go about
2) If currently there is no solution to my first question, is there a
way use adaptive and fixed kernel methods to generate UDs using kernelUD?
I am using R version 2.14.2.
Thanks in advance,
Fieberg, J., and C.O. Kochanny. 2005. Quantifying home-range overlap: the
importance of the utilization distribution. Journal of Wildlife Management
Horne, J.S., and E.O. Garton. 2006a. Selecting the best home range model:
an Information Theoretic approach. Ecology 87: 11461152.
Horne, J.S., and E.O. Garton. 2006b. Likelihood cross-validation versus
least squares cross-validation for choosing the smoothing parameter in
kernel home-range analysis. Journal of Wildlife Management 70: 641648.
Horne, J.S., and E.O. Garton. 2007. Animal space use 1.3. Available at: <
Accessed 16 Nov 2011.
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