Estimating Habitat and Species Occupancy Dynamics when Detection Probability is Less Than 100%
Larissa Bailey, Department of Fish, Wildlife and Conservation Biology
Monday, April 12, 2010
4:00 p.m., Weber 223
Relationships between animal populations and their habitats are well known and commonly acknowledged to be important by animal ecologists, conservation biologists and wildlife managers. Such relationships are most often viewed as static: even recently developed dynamic patch occupancy models commonly view habitats as fixed over the study period. Surprisingly few empirical studies have simultaneously modeled habitat suitability and corresponding occupancy states of organisms over large landscapes, despite clear management implications. Motivated by three different systems, we develop a framework to simultaneously estimate dynamics of both habitat state and animal occupancy state. Specifically, we characterize sample units by both habitat state and focal species occupancy state and then develop models to estimate parameters that describe the dynamics of such systems. The models permit inference about transition probabilities for both habitat and focal species occupancy, such that habitat transitions may influence focal species transitions and vice versa. The approach to inference falls within the general framework of multistate occupancy dynamics and we present likelihood-based inference methods using available software.