I'm interested in analyzing a long-term data set (spotted owl) with two goals:

(1) perform a variance components analysis with a spatial component (i.e., territory) so that the relative contribution of spatial variation to process variance can be estimated;

(2) obtain territory-specific survival estimates where territory is treated as a random effect (i.e., territory-specific shrinkage estimates).

I'm familiar with using MARK to conduct variance components analyses to estimate process variation, but I would further like to know how much spatial variation contributes to the process variation. Can territory be treated as a random effect in MARK to do this? If not, is there an alternative approach or software that might be used? I'm less familiar with Bayesian analysis, but it seems like the problem might be more tractable using MCMC (e.g., WinBUGS). Any suggestions or help would be greatly appreciated!