Acceleration predicts energy expenditure in a fat, flightless, diving bird

Olivia Hicks* (Corresponding Author), Akiko Kato, Frederic Angelier, Danuta M Wisniewska, Catherine Hambly, John R Speakman, Coline Marciau, Yan Ropert-Coudert

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
4 Downloads (Pure)


Energy drives behaviour and life history decisions, yet it can be hard to measure at fine scales in free-moving animals. Accelerometry has proven a powerful tool to estimate energy expenditure, but requires calibration in the wild. This can be difficult in some environments, or for particular behaviours, and validations have produced equivocal results in some species, particularly air-breathing divers. It is, therefore, important to calibrate accelerometry across different behaviours to understand the most parsimonious way to estimate energy expenditure in free-living conditions. Here, we combine data from miniaturised acceleration loggers on 58 free-living Adélie penguins with doubly labelled water (DLW) measurements of their energy expenditure over several days. Across different behaviours, both in water and on land, dynamic body acceleration was a good predictor of independently measured DLW-derived energy expenditure (R2 = 0.72). The most parsimonious model suggested different calibration coefficients are required to predict behaviours on land versus foraging behaviour in water (R2 = 0.75). Our results show that accelerometry can be used to reliably estimate energy expenditure in penguins, and we provide calibration equations for estimating metabolic rate across several behaviours in the wild.

Original languageEnglish
Article number21493
Number of pages9
JournalScientific Reports
Publication statusPublished - 9 Dec 2020

Bibliographical note

The project was supported logistically by the French Polar Institute and funded by the PEW fellowship to Y.R.-C., the WWF-UK, and the Zone Atelier Antarctique et Terres Australes from the CNRS. D.M.W. received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska‐Curie Individual Fellowship Grant Agreement No. 748026.


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