Congener Conflict: Invasive Barred Owl Landscape Use Across the Range of the Northern Spotted Owl

ABSTRACT Aim To map the probability of landscape use of invading barred owls ( Strix varia ) across the range of the threatened northern spotted owl ( S. Occidentallis Caurina ) in the Pacific Northwest, USA , identifying environmental drivers of barred owl landscape use to inform targeted management interventions. Location Forests of the Pacific Northwest, USA. Taxon Barred Owl ( Strix varia ). Methods We deployed 4081 autonomous recording units ( ARUs ) within 1027 randomly selected long‐term monitoring sites consisting of 5‐km 2 hexagons in 2023. We processed audio recordings using convolutional neural networks to detect vocalisations. We applied single‐season occupancy models at both ARU station and hexagon scales to estimate barred owl landscape use and assess associations with environmental variables. Using top models, we mapped barred owl landscape use across the full US range of the northern spotted owl, an umbrella species for conservation of the pacific northwest old‐growth forest community. Results Barred owls were widely detected, with naïve occupancy at 86.8% at the 5‐km 2 hexagon scale. We observed regional variation, with the highest landscape use in the Oregon Coast region and lower landscape use in California regions and the Washington Eastern Cascades. Landscape use was positively associated with mature forest characteristics at both broad and fine scales and negatively associated with elevation and climatic water deficit. Cumulative detection probability exceeded 90% after 2 weeks at the hexagon scale and 4 weeks at the station scale, providing guidance for future barred owl monitoring efforts. Main Conclusions Our study reveals extensive, but not ubiquitous, barred owl distribution across the range of the northern spotted owl. The findings offer a decision‐support framework for prioritising targeted management actions, particularly in regions with lower rates of barred owl landscape use. The integration of passive acoustic monitoring and AI‐based detection demonstrates a scalable approach for invasive species monitoring and conservation planning to meet management objectives in dynamic forest landscapes.