Abstract

Remotely estimating prey-capture rates in wild animals is key to assess foraging success. In diving animals, accelerometers have been particularly useful to remotely detect prey captures and have been shown to be more precise than traditional estimates relying on depth-derived measures (e.g., wiggles). However, validations of the accelerometry technique using a gold standard (i.e., with supervision) have been mostly restricted to shallow diving species, which can be equipped with camera-loggers for visual validation of prey-capture events. In species diving near the euphotic limit (150–200 m), accelerometers remain mostly untested due to the difficulty of validating such methods in darkness at extreme depth in the wild. In addition, prey-pursuits in low-light conditions might not result in intense and long-duration acceleration signatures, as predator–prey perception likely occurs at close-range in the dark (i.e., the “visual-interactions hypothesis”). We combined accelerometers with beak-opening sensors (for validation) and depth recorders on a wild deep-diving seabird, the king penguin Aptenodytes patagonicus, to describe prey captures at depth and create predictive models using accelerometers. Surprisingly, prey pursuits and captures were similar in duration (3.9 ± 3.5 s) and intensity (0.78 ± 0.31 g) as shallow-diving species reported by similar studies. As accelerometry signatures were distinct, accelerometry-derived variables were almost twice as accurate (Mean-squared error = 8.6) at predicting prey-capture events as depth-derived variables (“wiggles”, Mean-squared error = 16.0). As in the shallow-diving species, accelerometry outperforms traditional depth-derived models at measuring the foraging intake in deep-diving animals, highlighting the usefulness of accelerometers for measuring animal behavior.

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