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Diet of the northern river otter (Lontra canadensis (Schreber, 1777)) has been examined throughout much of its range and across many habitat types. Few studies have examined prey selection based on prey abundance estimates, however, and prey selection results have been inconsistent. We determined composition, seasonal variation, and prey selection of otter diet in northern Utah comprising multiple habitat types and prey communities. We evaluated the hypothesis that otters take prey according to availability and in inverse proportion to swimming ability. Fish was the primary class of prey taken by otters (96.5%), followed by crustaceans (16.9%). Among families, otter diet was composed primarily of Salmonidae and Cottidae, the two families that dominated the fish community of the main-channel habitat. Otter diet varied seasonally for nearly all classes (G [24] = 127.8, P < 0.001) and families (G [18] = 132.94, P < 0.001) of prey. In particular, fish occurrence was lower during summer than during other seasons (P ≤ 0.05), whereas crustacean (i.e., crayfish (Astacoidea)) occurrence was higher (G [3] = 71.1, P < 0.001). At the family level, occurrence of Salmonidae was greatest during fall (G [3] = 11.7, P < 0.01). Within one of our habitat types, we found otters to select for prey in proportion to abundance and in inverse proportion to swimming ability, with otters selecting for Catostomidae and Cyprinidae, against Salmonidae, and Cottidae according to its abundance. We conclude that habitat type may be the initial driver of prey selection, while factors such as abundance, agility, and life history of prey may be secondary drivers.Résumé : Le régime alimentaire de la loutre de rivière (Lontra canadensis (Schreber, 1777)) a été étudié dans la majeure partie de son aire de répartition et dans de nombreux types d'habitats. Peu d'études se sont toutefois penchées sur la sélection de proies à la lumière d'estimations de l'abondance des proies, et les résultats touchant à la sélection de proies se sont avérés peu cohérents. Nous avons déterminé la composition, les variations saisonnières et la sélection de proies de l'alimentation de la loutre dans le nord de l'Utah, une région qui comprend de nombreux types d'habitats et communautés de proies. Nous avons évalué l'hypothèse voulant que les loutres choisissent leurs proies selon leur disponibilité et de manière inversement proportionnelle à leur capacité natatoire. Les poissons constituaient la principale classe de proies prises par les loutres (96,5 %), suivis des crustacés (16,9 %). En ce qui concerne les familles, le régime des loutres était principalement composé de salmonidés et de cottidés, les deux familles dominantes de la communauté de poissons de l'habitat de chenal principal. Le régime alimentaire des loutres variait selon la saison pour presque toutes les classes (G [24] = 127,8, P < 0,001) et familles (G [18] = 132,94, P < 0,001) de proies. En particulier, la présence de poissons était plus faible durant l'été que durant d'autres saisons (P ≤ 0,05), alors que ...

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Greater sage-grouse populations have decreased steadily since European settlement in western North America. Reduced availability of brood-rearing habitat has been identified as a limiting factor for many populations. We used radio-telemetry to acquire locations of sage-grouse broods from 1998 to 2012 in Strawberry Valley, Utah. Using these locations and remotely-sensed NAIP (National Agricultural Imagery Program) imagery, we 1) determined which characteristics of brood-rearing habitat could be used in widely available, high resolution imagery 2) assessed the spatial extent at which sage-grouse selected brood-rearing habitat, and 3) created a predictive habitat model to identify areas of preferred brood-rearing habitat. We used AIC model selection to evaluate support for a list of variables derived from remotely-sensed imagery. We examined the relationship of these explanatory variables at three spatial extents (45, 200, and 795 meter radii). Our top model included 10 variables (percent shrub, percent grass, percent tree, percent paved road, percent riparian, meters of sage/tree edge, meters of riparian/tree edge, distance to tree, distance to transmission lines, and distance to permanent structures). Variables from each spatial extent were represented in our top model with the majority being associated with the larger (795 meter) spatial extent. When applied to our study area, our top model predicted 75% of naïve brood locations suggesting reasonable success using this method and widely available NAIP imagery. We encourage application of our methodology to other sage-grouse populations and species of conservation concern.