Acoustic Detection of Gunshots to Improve Measurement and Mapping of Hunting Activity

Hunting can influence the abundance and distribution of animals and act as a source of conflict among recreational user groups. Thus, land managers benefit from tools that can generate information about when and where hunting occurs. We used passive acoustic monitoring to examine spatiotemporal patterns of hunting-related gunshots at 91 locations in a protected area in Alberta, Canada. We compared 2 methods for detecting gunshots from recordings: a recognizer that used complex pattern recognition and an energy detector that detected loud sounds regardless of their acoustic features. The recognizer primarily detected faint sounds, and multiple observers showed low levels of agreement (37%) with respect to whether sounds were gunshots or not, suggesting it produced ambiguous data. The recognizer also missed many loud, clear gunshots for unknown reasons. The energy detector, in contrast, detected loud sounds upon which observers showed near-unanimous agreement (99%) on their identity. Gunshots missed by the energy detector could be because they were too quiet (i.e., too far away to be detected). Thus, despite detecting fewer gunshots overall, the energy detector produced higher quality data that were easier to interpret. We analyzed 249 gunshots detected with the energy detector, and found that hunting was concentrated near vehicle access points and peaked on Saturdays, and that hunters largely abided by local regulations prohibiting Sunday hunting. We compared energy detector results with remote cameras, which revealed similar spatiotemporal patterns of hunting effort. Passive acoustic monitoring has the potential to allow hunting activity to be mapped and monitored with unprecedented resolution.