PS 75-149
Singing on the nest in Mimus polyglottos: An automated approach
Bird song serves numerous functions that contribute to reproductive success, including mate attraction and territory defense. A potential cost of singing is the risk that vocalizations give away an individual’s location to predators. Since bird nests are not mobile, any attention drawn to a nest can increase the likelihood of the nest being discovered by predators. Nest predation has been hypothesized to be a major force structuring bird communities, so if singing increases nest predation, it should be strongly selected against. While the phenomenon of singing on the nest should be extremely rare, this behavior has not been studied extensively. In this study, a team of undergraduate researchers and their faculty advisors obtained video footage of 128 Northern Mockingbird (Mimus polyglottos) nests to quantify the frequency of this behavior. A custom Python program was written to comprehensively sample these video files by automating the process of reading large sound files and detecting potential singing times. Using various signal processing techniques, the underlying algorithm finds the most significant parts of the sound and eliminates background noise making it easier to isolate potential bird song. Each potential instance of singing on the nest was flagged and then confirmed by a researcher.
Results/Conclusions
Singing on the nest is present in 63% of nests (n = 27) based on a preliminary random sample of 43 nests, demonstrating this behavior occurs far more frequently than ornithologists presently appreciate. We are currently screening the remaining nests and documenting the occurrence of factors that correlate with the frequency of this behavior. Future research will investigate if predation rates are higher for nests where singing has occurred. Given the frequency of this behavior in mockingbirds, the topic of singing on the nest needs to be more systematically studied across a range of bird species. With the increasing use of video monitoring systems on bird nests and our Python program, further investigations of singing on the nest by numerous research groups should be possible.