Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/36840
Title: | Quantifying song behavior in a free‐living, light‐weight, mobile bird using accelerometers | Authors: | Eisenring, Elena Eens, Marcel Pradervand, Jean-Nicolas Jacot, Alain Baert, Jan ULENAERS, Eddy LATHOUWERS, Michiel EVENS, Ruben |
Issue Date: | 2022 | Publisher: | WILEY | Source: | Ecology and Evolution, 12 (1) (Art N° e8446) | Abstract: | To acquire a fundamental understanding of animal communication, continuous observations in a natural setting and at an individual level are required. Whereas the use of animal-borne acoustic recorders in vocal studies remains challenging, light-weight accelerometers can potentially register individuals' vocal output when this coincides with body vibrations. We collected one-dimensional accelerometer data using light-weight tags on a free-living, crepuscular bird species, the European Nightjar (Caprimulgus europaeus). We developed a classification model to identify four behaviors (rest, sing, fly, and leap) from accelerometer data and, for the purpose of this study, validated the classification of song behavior. Male nightjars produce a distinctive "churring" song while they rest on a stationary song post. We expected churring to be associated with body vibrations (i.e., medium-amplitude body acceleration), which we assumed would be easy to distinguish from resting (i.e., low-amplitude body acceleration). We validated the classification of song behavior using simultaneous GPS tracking data (i.e., information on individuals' movement and proximity to audio recorders) and vocal recordings from stationary audio recorders at known song posts of one tracked individual. Song activity was detected by the classification model with an accuracy of 92%. Beyond a threshold of 20 m from the audio recorders, only 8% of the classified song bouts were recorded. The duration of the detected song activity (i.e., acceleration data) was highly correlated with the duration of the simultaneously recorded song bouts (correlation coefficient = 0.87, N = 10, S = 21.7, p = .001). We show that accelerometer-based identification of vocalizations could serve as a promising tool to study communication in free-living, small-sized birds and demonstrate possible limitations of audio recorders to investigate individual-based variation in song behavior. | Notes: | Evens, R (corresponding author), Univ Antwerp, Dept Biol, Behav Ecol & Ecophysiol Grp, Univ Pl 1, B-2610 Antwerp, Belgium. ruben.evens@uantwerpen.be |
Keywords: | audio recordings;behavior classification;bioacoustics;biologging;birdsong;Caprimulgus europaeus;European nightjar;telemetry;vocalizations | Document URI: | http://hdl.handle.net/1942/36840 | ISSN: | 2045-7758 | e-ISSN: | 2045-7758 | DOI: | 10.1002/ece3.8446 | ISI #: | WOS:000747845400031 | Rights: | 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2023 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Quantifying song behavior in a free‐living, light‐weight, mobile bird using accelerometers.pdf | Published version | 1.11 MB | Adobe PDF | View/Open |
WEB OF SCIENCETM
Citations
3
checked on Sep 28, 2024
Page view(s)
32
checked on Sep 7, 2022
Download(s)
4
checked on Sep 7, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.