Fine-scale body and head movements allow to determine prey capture events in the Magellanic Penguin (Spheniscus magellanicus)

Abstract

The identification of when, how and where animals feed is essential to estimate the amount of energy they obtain and to study the processes associated with prey search and consumption. We combined the use of animal-borne video cameras and accelerometers to characterise the body and head movements associated to four types of prey capture behaviours in the Magellanic Penguin (Spheniscus magellanicus). In addition, we evaluated how the K-Nearest Neighbour (K-NN) algorithm recognized these behaviours from acceleration data. Finally, we compared the total capture and the capture per unit time (CPUT) derived by identifying prey capture events using the K-NN algorithm to that derived by counting undulations in the dive profile ("wiggles"). During captures, body and head movements were highly variable in the tridimensional space. Energy expenditure (i.e., VeDBA values) during diving periods with prey captures was from three to four times higher than during controls diving periods (i.e., with no capture events). The K-NN classification resulted effective and showed accuracy scores above 90% when considering both head and body related features. In addition, when captures were estimated using the K-NN method, the CPUT was similar or higher to that estimated by counting wiggles. Our study contributes to the knowledge of the trophic ecology of this species and provides an alternative method for estimating prey consumption in the Magellanic Penguin and other diving seabirds.