The range expansion of the barred owl (Strix varia) into western North America over the last century has emerged as a major threat not only to northern spotted owls (S. occidentalis caurina), but to many other species. A better understanding of barred owl natal dispersal, one of the primary driving mechanisms of range expansion, is needed for the implementation of effective management. Our research team attached satellite-GPS tags to juvenile barred owls in the Coastal Redwood Region of northern California in order to characterize their movement, survival, and habitat use as they disperse from natal territories. These tags allow for fully remote tracking of owls and have the potential to provide locations up to 1.5 years past the date of deployment, making our study the first of its kind. We have been following 31 juvenile barred owls tagged in summer 2020 and 2021. Preliminary data have revealed the capacity for juvenile barred owls to move up to 146 km from their natal territory as they disperse, and that dispersing greater than 50 km is common. Survival rates and habitat use, including use of post-wildfire landscapes, during dispersal will also be discussed.

Winegrape growers in Napa Valley, California install nest boxes to encourage the presence of barn owls, natural enemies thought to provide vertebrate pest control services. Barn owls in this system select wooden nest boxes at least 3 meters high, with high proportions of grasslands surrounding the nest box. According to the adaptive breeding-habitat selection hypothesis, these habitat preferences should be adaptive, with increased fitness in preferred habitats. We found only modest association between reproductive success and nest box preferences, with substantial unaccounted variation in annual reproduction. Variation in the intrinsic quality of individual owls could also contribute to annual reproductive success, so we tested the hypothesis that habitat preferences and measures of intrinsic quality better predict reproductive success than either does alone. We measured annual reproductive success as the number of offspring that approached fledging age. Data on morphometrics, age, and breast plumage variation on adults served as measures of intrinsic quality of adults. Annual reproductive success served as the response variable in Generalized Additive Models, predicted by observed habitat preferences and measures of intrinsic quality. We found varying strength of association between the response variable and predictors, further emphasizing the complexity of annual reproductive success.

Many raptor species exhibit plumage polymorphism. Through the expression of a particular phenotype, polymorphism allows individuals to exploit alternative spatial or temporal environments and food resources most successfully. Barn owls display variation in their ventral plumage, ranging from reddish to whitish and from heavily spotted to no spots at all. In heterogeneous landscapes in Switzerland and Israel, reddish barn owls (Tyto alba) inhabit territories with proportionally more arable fields and consume proportionally more voles than their whiter counterparts. This is consistent with the habitat-matching choice hypothesis, but whether this also occurs in other regions and with the American barn owl has not yet been tested. This study sought to examine the relationships among prey composition, landscape composition, and degree of reddishness in barn owls throughout Napa Valley, CA. Pellet analysis was used to determine the proportion of mice (Peromyscus, Reithrodontomys, and Mus), voles (Microtus), and gophers (Thomomys) in the owls’ diet. The results show clear evidence for the existence of polymorphism in the heterogeneous landscapes within and surrounding vineyards, though the role of habitat heterogeneity remains incompletely resolved. These data also further reveal insights into predator-prey relationships and potentially provide vineyard producers with information about pest removal services.

Nest boxes are often installed in agricultural landscapes to attract barn owls for the pest control services they provide. For this practice to be effective, farmers need actionable guidelines on nest box design and placement to optimize nest box occupancy. Ongoing research has revealed nest box selection patterns in winegrape vineyards of Napa Valley, California. However, it remains unclear whether these patterns are generalizable to other years and regions with different crops. Based on 6 years of occupancy data from Napa Valley (n = 268 boxes), we developed a nest box selection model and evaluated the model’s predictive performance in other regions and years. We hypothesized the model would perform better in regions with similar crops and landcover than in areas more ecologically dissimilar. We found that the top model performed well for predicting future nest box occupancy in Napa, but it performed poorly in ecologically similar Sonoma, and in dissimilar Fresno, Madera, and Merced Counties. These results suggest models predicting barn owl nest box occupancy from a single region may not be generalizable to others. Instead, ecologists should consider the need to develop region-specific models to better understand barn owl habitat ecology and the ecosystem services they provide to farmers.

Land managers in Napa Valley, CA place nest boxes in wine grape vineyards to attract barn owls who can provide valuable rodent pest control. Previous studies in this region found that barn owls prefer to occupy boxes made of wood, placed at least 3 meters above the ground, and with uncultivated habitat, such as grassland, nearby. However, landscape configuration can also strongly affect animals’ use of heterogeneous environments, but its role in shaping nest box occupancy has not yet been examined for barn owls. We examined whether there is a relationship between occupancy and several configuration metrics in the land surrounding boxes including: the edge density of different land cover classes, interspersion and juxtaposition index of the landscape, and mean patch sizes of different classes. Finally, we created a predictive map that uses relevant configurational and compositional metrics to provide farmers a visual representation of where boxes should be deployed to optimize the probability of a box being occupied.