Many animals produce individually distinctive vocalizations with increased outputs during the breeding season. Many animals, including birds, can recognize other individuals based on the distinctive features of their songs and researchers can use bioacoustics tools to discriminate among individuals. Typically, bioacoustics analyses use recordings made with highly directional microphones that are free of background noise and spectral overlap. However, recent technological advances in automated recording have made it possible to record remotely and cover larger areas simultaneously. We tested whether spectrogram cross-correlation can be used to discriminate among songs of 19 individual Ovenbirds (Seiurus aurocapillus). We used two microphone types: directional (Sennheiser MKH-70) and omnidirectional (SMX-II) microphones. Because birds may vary in their distance from the SMX-II microphones, songs were selected as either high-quality (close to the recorder) or low-quality (further away from the recorder). We found that all recording types could be used to discriminate the songs of individual male Ovenbirds from other males in the population. Discrimination among directional recordings was significantly better than among omnidirectional recordings, and high-quality recordings could be used to discriminate among individuals significantly better than low-quality recordings. Taken together, our results suggest that automated omnidirectional recording could be valuable for future behavioural research allowing individuals to be followed over an entire breeding season. In addition, acoustic surveys of communities could provide information about abundance as well as presence and/or absence of species.
individual distinctiveness, automated recording, spectrogram cross-correlation, Ovenbird