Animal resource selection is a complex, hierarchical decision-making process, yet resource selection studies often focus on the presence and absence of an animal rather than the animal's behavior at resource use locations. In this study, we investigate foraging and vocalization resource selection in a population of Willow Flycatchers, Empidonax traillii adastus, using Bayesian spatial generalized linear models. These models produce “behavioral landscapes” in which space use and resource selection is linked through behavior. Radio telemetry locations were collected from 35 adult Willow Flycatchers (n = 14 males, n = 13 females, and n = 8 unknown sex) over the 2003 and 2004 breeding seasons at Fish Creek, Utah. Results from the 2-stage modeling approach showed that habitat type, perch position, and distance from the arithmetic mean of the home range (in males) or nest site (in females) were important factors influencing foraging and vocalization resource selection. Parameter estimates from the individual-level models indicated high intraspecific variation in the use of the various habitat types and perch heights for foraging and vocalization. On the population level, Willow Flycatchers selected riparian habitat over other habitat types for vocalizing but used multiple habitat types for foraging including mountain shrub, young riparian, and upland forest. Mapping of observed and predicted foraging and vocalization resource selection indicated that the behavior often occurred in disparate areas of the home range. This suggests that multiple core areas may exist in the home ranges of individual flycatchers, and demonstrates that the behavioral landscape modeling approach can be applied to identify spatially and behaviorally distinct core areas. The behavioral landscape approach is applicable to a wide range of animal taxa and can be used to improve our understanding of the spatial context of behavior and resource selection.
Additional publication details
Elucidating spatially explicit behavioral landscapes in the Willow Flycatcher