Passive acoustic monitoring is a useful method for tracking a wide range of vocalizing taxa (e.g., avian, mammalian, amphibian) in the field. This method reduces cost and time associated with traditional survey methods, as bioacoustic data is collected with autonomous recording units (ARUs) and processed with detection algorithms to identify species by vocalization patterns. From this single data stream, researchers can estimate biodiversity, population size, spatial distribution, occupancy, and habitat relationships. During 2024 and 2025, we collected bioacoustic data from 734 ARUs deployed across California within 16 state wildlife areas, three national wildlife refuges, and one national forest. Units recorded continuously for up to 13 hours per day for a minimum of two weeks during March – August each year. Audio recordings were processed through BirdNET Analyzer to identify species, and a random subset of the total BirdNET predictions were validated. We estimated local species diversity and detected rare, cryptic, and invasive species that are important to managers. For species with frequent detections, we estimated call densities, created distributional maps of relative abundance, and estimated occupancy and habitat relationship curves. Our results showcase an integrative method of capturing various latent ecological states to inform multiple conservation and management objectives.