- Nearly all birds communicate through sound, and there has been much study of avian populations and communities using song and other vocalizations. Owls are no exception as they defend territories, advertise for mates, and defend against threats using various vocalizations. However, due to their generally nocturnal habits, some owl species have not been well-studied. With the advent of passive acoustic monitoring using autonomous recording units (ARUs), we can now collect large amounts of nocturnal acoustic data without disturbing target species and with relatively low field effort. In this thesis I used ARUs to evaluate their ability to detect calls of northern spotted owls and barred owls in three study areas in the Pacific Northwest (Chapter 2), and to quantify landscape use by five species of owls of an area in Southwest Oregon burned two years prior by a mixed-severity wildfire (Chapter 3).
Northern spotted owl (Strix occidentalis caurina) populations have been monitored since the mid-1980s using mark-recapture survey methods. To evaluate an alternative survey method, I used ARUs to detect calls of northern spotted owls and barred owls (S. varia) (Chapter 2), a congener that has expanded its historic range into the Pacific Northwest and now threatens northern spotted owl persistence primarily through interference competition. From March-July 2017, I set ARUs to record continuously each night at 30, 500ha hexagons (150 ARU stations) with recent northern spotted owl activity, and high barred owl use in Oregon and Washington. I reviewed spectrograms (visual representations of sound) and manually tagged target vocalizations to extract calls from ~160,000 hours of recordings. Even in a study area with low occupancy rates on historic territories (Washington’s Olympic Peninsula), the probability of detecting a northern spotted owl when it was present in a hexagon exceeded 0.95 after 3 weeks of ARU deployment. Background noise, mainly from streams, rain, and wind negatively affected detection probability for both species over all study areas. Using known demographic information about northern spotted owl pair locations I quantified patterns in northern spotted owl vocalization intensity that could help distinguish paired vs. single birds using only passive acoustic data. I found that weekly detection probabilities of northern spotted owls were higher for ARUs placed closer to northern spotted owl nests and activity centers. Examination of vocal activity patterns of both northern spotted and barred owls revealed strong synchrony between the two species through the lunar cycle with calling peaks near the full moon, but asynchrony over the diel period. Northern spotted owls called more frequently during the crepuscular period, while barred owl calling was highest in the nocturnal period, suggesting there may be fine-scale temporal partitioning of calling activity. These results demonstrate that ARUs can be used to effectively detect northern spotted owls when they are present, even in a landscape with high barred owl density, thereby facilitating the use of passive, occupancy-based study designs to monitor northern spotted owl populations.
Mixed-severity fire is the dominant fire type in southwest Oregon, yet its effects on wildlife communities is complex and poorly understood. In particular, little attention has been paid to the use of burned landscapes by owls. I performed passive acoustic surveys using ARUs in and around the area of a ~10,500 hectare mixed-severity wildfire two years post-fire (Chapter 3). I detected the vocalizations of six owl species including northern spotted owls, barred owls, great horned owls (Bubo virginianus), western screech-owls (Megascops kennicottii), northern pygmy-owls (Glaucidium gnoma), and northern saw-whet owls (Aegolius acadicus). I did not detect enough northern spotted owl vocalizations, so they were excluded from analyses. I evaluated landscape use (barred owls and great horned owls; large home ranges prevent estimation of true occupancy) or occupancy (three small owl species), with a single-species, single-season occupancy model using detection data gathered on the remaining five owl species. Western screech-owls had higher probability of occupancy at more severely burned sites, northern pygmy-owls were widely distributed but increased their occupancy as burn severity increases, and northern saw-whet owls appeared to avoid nearly all burned areas, no matter the severity. Barred owls were somewhat less likely to use areas deeper within the fire’s perimeter than unburned areas outside the fire, but ARUs did detect them in burned areas. Great horned owls showed patterns of landscape use unrelated to fire severity. Four out of five species of owls occupied or used recently burned areas without salvage logging. Thus, the high level of landscape heterogeneity and unique forest conditions that result from mixed-severity fire appear to be suitable for use by many owl species. These two studies evaluated the use of passive acoustic detection of forest owl species both as a potential long-term monitoring method, and to gain understanding of spatial patterns within a single survey season. I established that northern spotted owls and barred owls are highly detectable with ARUs using a landscape-level sampling scheme, and identified environmental factors that affect the ability to detect both species. Even with relatively few individuals in an area, ARUs can detect owls due to large spatial coverage and long duration of recording. This is particularly advantageous and may have management implications when it comes to monitoring threatened and endangered species. Additionally, I identified previously undocumented patterns of use in a post-fire landscape by five species of forest owls, adding to the growing body of literature regarding wildfire’s effects on wildlife communities.