Raw acceleration, gyroscope and depth profiles associated with the observed behaviours of free-ranging immature green turtles in Martinique

The identification of sea turtle behaviours is a prerequisite to predicting the activities and time-budget of these animals in their natural habitat over long term. However, this is hampered by a lack of reliable methods that enable the detection and monitoring of certain key behaviours such as feeding. This study proposes a combined approach that automatically identifies the different behaviours of free-ranging sea turtles through the use of animal-borne multi-sensor recorders (accelerometer, gyroscope and time-depth recorder), validated by animal-borne video-recorder data. We show here that the combination of supervised learning algorithms and multi-signal analysis tools can provide accurate inferences of the behaviours expressed, including behaviours that are of crucial ecological interest for sea turtles, such as feeding and scratching. Our procedure uses multi-sensor miniaturised loggers that can be deployed on free-ranging animals with minimal disturbance. It provides an easily ad...