To all,

I have a simple question, which I think I already know the answer to, but I'd like to get some responses to verify my thoughts.

The species I'm working with is a widely distributed darter that lives in small headwater streams (i.e., its movement is likely highly limited). I collected my data using 4 equally sized, and equally spaced, spatial replicates at a site to obtain my detection histories. Initially, I ran the simple, single season model to obtain early estimates of psi and p. Then, I decided to use the spatial dependence model to approximate thetapi due to the fact that I used spatial replicates in my study design and expected detections to be correlated due to the low mobility of my target species. With that being said, early estimates from the simple, single season model indicate that the darter has a high estimate for psi. Therefore, two control for high beta estimates, I fixed this value when running the spatial dependence model for it. With that being said, by fixing psi, you obviously cannot properly estimate this parameter using the spatial dependence model. I would assume that all site covariates relationships to psi would also be spurious due to the fixed nature of the parameter. So, my question is: is it ok to use the simple single season estimates for psi and then simply approximate p and theta using the spatial dependence model? As far as I can tell, this is really my only option.

Thanks,

Josh