TY - JOUR
T1 - Quantifying song behavior in a free-living, light-weight, mobile bird using accelerometers
AU - Eisenring, Elena
AU - Eens, Marcel
AU - Pradervand, Jean Nicolas
AU - Jacot, Alain
AU - Baert, Jan
AU - Ulenaers, Eddy
AU - Lathouwers, Michiel
AU - Evens, Ruben
N1 - Funding Information:
The authors wish to thank J. Elst, M. Evens, and L. Schramme for help during fieldwork. F. Liechti, E. Bächler, R. Spaar, K. Thijs, A. Loenders, K. Vanmarcke, G. Eens, and Fien and Fleur Evens for support. Belgian permissions were granted by the Belgian military (military area of Klein Schietveld), Agency for Nature and Forest and Royal Belgian Institute for Natural Sciences. Swiss permissions were granted by the Laboratoire cantonal et affaires vétérinaires Valais (VS032018). R.E. was funded by the FWO (12T3922N) and also wishes to thank Dr. Bart Kempenaers from the Max Planck Institute for Ornithology for his financial and intellectual support. The Swiss federal office for environment contributed financial support for the development of the data loggers (UTF‐Nr. 254, 332, 363, 400).
Funding Information:
The authors wish to thank J. Elst, M. Evens, and L. Schramme for help during fieldwork. F. Liechti, E. B?chler, R. Spaar, K. Thijs, A. Loenders, K. Vanmarcke, G. Eens, and Fien and Fleur Evens for support. Belgian permissions were granted by the Belgian military (military area of Klein Schietveld), Agency for Nature and Forest and Royal Belgian Institute for Natural Sciences. Swiss permissions were granted by the Laboratoire cantonal et affaires v?t?rinaires Valais (VS032018). R.E. was funded by the FWO (12T3922N) and also wishes to thank Dr. Bart Kempenaers from the Max Planck Institute for Ornithology for his financial and intellectual support. The Swiss federal office for environment contributed financial support for the development of the data loggers (UTF-Nr. 254, 332, 363, 400).
Publisher Copyright:
© 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
PY - 2022/1
Y1 - 2022/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85123763003&partnerID=8YFLogxK
U2 - 10.1002/ece3.8446
DO - 10.1002/ece3.8446
M3 - Article
AN - SCOPUS:85123763003
SN - 2045-7758
VL - 12
JO - Ecology and Evolution
JF - Ecology and Evolution
IS - 1
M1 - e8446
ER -