Using NPMR to compare multiple hypotheses: Is Bayes factor appropriate?

[Pablo Bacon]

Hey all,

First, I want to say that reading these posts (and the ones from the PC-ORD group) has been extremely insightful.

I am fairly new to NPMR/ HyperNiche and still exploring some of the applications.  I am wanting to test multiple hypotheses regarding land-use land cover variables at multiple scales on the presence/absence of an aquatic beetle.  The models are based on select lulc variables and have very low xr2 values.  This may be due to other factors we did not quantitatively address in initial distributional surveys such as presence/absence of predators and competitors, indirect effects, etc. in addition to the environment and all interactions.  However, the focus of my analyses are aimed at testing multiple hypotheses about these select variables at multiple spatial scales and how they interact (for example, at 80% forest cover at the local riparian scale the watershed scale urbanization effect seems to have less of an effect on p/a of the beetle).

So here is the question:  Is it appropriate to use this approach to compare multiple hypotheses using the Bayes factor despite poor model fit/xr2? 

Thank you for your time,

Pablo Andres Bacon