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Manual Versus Semi-Automated Bioacoustic Analysis Methods of Multiple Vocalizations in Tricolored Blackbird Colonies

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Bioacoustic monitoring can reveal aspects of animal behavior as many species vocalize in association with certain behaviors. Despite this, bioacoustics remain infrequently used to monitor animal behavior due to lack… Click to show full abstract

Bioacoustic monitoring can reveal aspects of animal behavior as many species vocalize in association with certain behaviors. Despite this, bioacoustics remain infrequently used to monitor animal behavior due to lack of knowledge of how vocalizations relate to behavior and the challenge of efficiently analyzing the large acoustic datasets necessary to capture relevant behaviors. Vocalizations and associated behaviors have been previously established for the colonial tricolored blackbird Agelaius tricolor, but efficient analysis of the acoustic data remains a challenge. Previous work with tricolored blackbird acoustic data relied on manually listening to recordings, which is not practical on large scales. Using software to automatically detect vocalizations of interest has potential to reduce analysis time. However, automated detection is prone to errors often caused by faint vocalizations, overlapping calls, and background noise. Thus, incorporating components of manual and automated analysis of acoustic datasets remains essential. To address these challenges, we deployed autonomous recording units at three tricolored blackbird colonies from 2019 to 2021 and analyzed acoustic data using a manual and a semi-automated analysis method. Specifically, we used tricolored blackbird male song, male chorus, female song, hatchling call, nestling call, and fledgling call to determine the approximate timing of breeding stages and number of breeding attempts, or pulses, for each colony. We found that using a semi-automated approach was more time efficient than manual analysis, while using comparable numbers of recordings and obtaining equivalent information from the colonies. The odds of correct detections of vocalizations using the semi-automated method were generally lower for fainter vocalizations and colonies with high background noise. Overall, the semi-automated approach had tolerable rates of recall, precision, false positives, and false negatives. Our methodology adds to a growing body of literature addressing acoustic analysis, especially for colonial species and where questions of breeding phenology are important.

Keywords: acoustic data; tricolored blackbird; semi automated; analysis; blackbird colonies

Journal Title: Journal of Fish and Wildlife Management
Year Published: 2023

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