As population declines threaten avian species throughout California, standardized monitoring strategies are increasingly important for habitat management and conservation. Passive acoustic monitoring reduces the need for human observers, creating the opportunity to monitor species with limited funding or staff. Using a novel approach, we deployed autonomous recording units (ARUs) across nine public wildlife areas and refuges in northern California to assess occupancy and relative abundance of vocalizing avian species during spring and summer of 2024. ARUs were deployed using a random sampling design within a hexagonal tessellation grid. Recordings from 284 ARU stations were processed using BirdNET Analyzer, from which a subsample of vocalization detections were validated and detection probability thresholds developed. Maps of relative abundance were created using Kriging interpolation, and occupancy was estimated using single-site single-season models. While previous large-scale ARU studies have provided valuable data, making inference at local scales creates a powerful tool to inform and improve habitat management practices. Further, this passive monitoring technique can be applied to any vocalizing species that is detected by BirdNET, including anuran and mammalian species. The broad applicability of this work emphasizes the significance of integrating and standardizing acoustic monitoring in an increasingly fragmented landscape.