Acoustic monitoring is an increasingly common technique for surveying avian species in the field. Low-cost autonomous recording units (ARUs) are driving this increase in acoustic field surveys, which allows for occupancy and abundance data to be collected without a human observer present. Coupled with software that can detect avian species by their call, this method of passive observation allows for large amounts of recorded audio to be analyzed with less manual processing and validation effort required. During 2023, we completed a pilot study deploying 40 ARUs across northern California public hunting areas (n = 8) to monitor ring-necked pheasants. Units recorded 2.5 hours per day for 45 days and were subsequently recovered from the field. The recordings were uploaded to an avian species detection software program (BirdNET Analyzer) that processes sound data and outputs a list of detections with time stamps and confidence estimates. A subset of the total detections was validated (87 percent total accuracy above 0.1 confidence threshold), and we created distributional maps of relative pheasant abundance using an inverse distance weighting function. Using ARUs can facilitate an increase in the capacity to monitor managed game and non-game species of concern over larger areas and in remote regions.