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Apex predators exert suppressive effects on mesocarnivores; however, they also provide important carrion subsidies. Optimal foraging theory predicts that individuals respond to resource competition by using high-value resources, while competition theory predicts that individuals respond by partitioning resources. This study investigated how the return of wolves ( Canis lupus Linneas, 1758) to Washington state impacted the diet of a subordinate carnivore—the coyote ( Canis latrans Say, 1823). We collected coyote scats from two areas of northern Washington with differing wolf densities and used traditional analysis of undigested remains to infer diet. We tested for differences in the volumes of prey categories, the proportion of ungulate prey that was scavenged, and diet diversity between seasons, study sites, and inside and outside of wolf pack territories. Coyote scats contained more adult ungulate remains inside of wolf pack territories (27%) compared to outside (14%), while seeds and berries were more commonly consumed outside of wolf pack territories (23%) than inside of wolf pack territories (4%). These findings suggest that coyotes are taking advantage of wolf kills to increase ungulate carrion consumption, as predicted by optimal foraging theory, which may substantially affect plant and wildlife communities as wolves continue to recover and coyote diets shift in response. 

Abstract Estimating habitat and spatial associations for wildlife is common across ecological studies and it is well known that individual traits can drive population dynamics and vice versa. Thus, it is commonly assumed that individual‐ and population‐level data should represent the same underlying processes, but few studies have directly compared contemporaneous data representing these different perspectives. We evaluated the circumstances under which data collected from Lagrangian (individual‐level) and Eulerian (population‐level) perspectives could yield comparable inference to understand how scalable information is from the individual to the population. We used Global Positioning System (GPS) collar (Lagrangian) and camera trap (Eulerian) data for seven species collected simultaneously in eastern Washington (2018–2020) to compare inferences made from different survey perspectives. We fit the respective data streams to resource selection functions (RSFs) and occupancy models and compared estimated habitat‐ and space‐use patterns for each species. Although previous studies have considered whether individual‐ and population‐level data generated comparable information, ours is the first to make this comparison for multiple species simultaneously and to specifically ask whether inferences from the two perspectives differed depending on the focal species. We found general agreement between the predicted spatial distributions for most paired analyses, although specific habitat relationships differed. We hypothesize the discrepancies arose due to differences in statistical power associated with camera and GPS‐collar sampling, as well as spatial mismatches in the data. Our research suggests data collected from individual‐based sampling methods can capture coarse population‐wide patterns for a diversity of species, but results differ when interpreting specific wildlife‐habitat relationships.