No abstract

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 lowquality (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.

Autonomous recording is commonly used to examine the structure of avian communities in a variety of landscapes. Many birds return to the breeding grounds in May yet acoustic surveys typically begin in June. In many species, singing activity declines through the breeding season and so detections may be lower later in the season. The aim of our study was to compare the species richness and the community composition measured early (mid-late May) and later (mid-late June) in the breeding season. We recorded the community of singing birds at 13 locations in York Region, Ontario, Canada woodlots over two days using autonomous recorders. We used spectrographic analysis to scan recordings and identify all vocalizing species. We found that species richness was significantly higher in early recordings compared to later recordings with detections of both migrants and residents displaying this trend. Most food and foraging guilds were also detected significantly less often later in the season. Despite changes in species richness, the proportion of the community represented by each foraging guild did not vary between early and late recordings. Our results suggest that acoustic recordings could be collected earlier in the breeding season, extending the survey period into May. If the primary goal of monitoring is to document species presence/absence then earlier recordings may be advantageous.