by dtempel » Wed Apr 06, 2011 5:30 pm
It's the latter case. We have some sites that I believe have different detection probabilities but I lack covariate data that might explain why they're different. I'm going to use reproductive status during each year as a site-specific covariate, but I suspect there's some other reason for the variation. It seems like we have some sites where the birds are consistently detected on nearly every survey, but other sites where we consistently have only one (or maybe two) detections each year. This is a spotted owl data set, and the sites are owl territories that have been surveyed every breeding season for a number of years.
My intuition tells me that the birds at those sites may be moving around a lot, so they may not be "available" for detection on every survey. I know that violates a model assumption, which would lead me to interpret occupancy in this case as the proportion of sites that are "used" each year.
It looks like Program MARK has the option to run multi-season heterogeneity models, but I also want to run some models with survey-specific covariates (e.g., detection probability changes after the initial detection at a site during a given year). It's not clear to me how I would input survey-specific data in MARK. Site-specific covariates are simple enough, but I haven't figured out survey-specific covariates.
Thanks!