Abstract

In songbirds, song has traditionally been considered a vocalization mainly produced by males. However, recent research suggests that both sexes produce song. While the function and structure of male black-capped chickadee (Poecile atricapillus) fee-bee song have been well-studied, research on female song is comparatively limited. Past discrimination and playback studies have shown that male black-capped chickadees can discriminate between individual males via their fee-bee songs. Recently, we have shown that male and female black-capped chickadees can identify individual females via their fee-bee song even when presented with only the bee position of the song. Our results using discriminant function analyses (DFA) support that female songs are individually distinctive. We found that songs could be correctly classified to the individual (81%) and season (97%) based on several acoustic features including but not limited to bee-note duration and fee-note peak frequency. In addition, an artificial neural network was trained to identify individuals based on the selected DFA acoustic features and was able to achieve 90% accuracy by individual and 93% by season. While this study provides a quantitative description of the acoustic structure of female song, the perception and function of female song in this species requires further investigation.

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