Predicting prey capture rates of southern elephant seals from track and dive parameters

• Published in: Marine Ecology Progress Series
• Main Authors: Vacquié-Garcia, Jade, Guinet, Christophe, Dragon, Anne-Cécile, Viviant, Morgane, El Ksabi, Nory, Bailleul, Frédéric
• Other Authors: Centre d'Études Biologiques de Chizé - UMR 7372 (CEBC), La Rochelle Université (ULR)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Collecte Localisation Satellites (CLS Argos)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2015
• Subjects: Biologging; Dive parameters; Foraging; Prey capture events; Marine predator; Southern elephant seals; Track parameters; [SDE]Environmental Sciences; Kerguelen; Kerguelen Islands; Elephant Seals; Mirounga leonina; Southern Elephant Seals
• Online Access: https://hal.archives-ouvertes.fr/hal-01294963; https://doi.org/10.3354/meps11511

International audience In the marine environment, track and dive parameter data (obtained using Argos or GPS tags and time–depth recorders) are commonly used to provide proxies for foraging behaviour of marine predators. However, their accuracy is rarely assessed. Recently, the addition of head-mounted accelerometers has allowed for detection of prey capture attempts (PCAs) at sea, allowing for more accurate estimations of foraging behaviour. Despite increased numbers of such devices being deployed, their use is still marginal compared with other tools which measure track and dive parameters. The objectives of our study were (1) to identify the most relevant combination of tracking and diving metrics in predicting the frequency of PCAs in female southern elephant seals Mirounga leonina from the Kerguelen Islands, and (2) to apply it to a broader range of individuals for which only tracking and diving data were available. The results of our models were consistent with the optimal foraging theory as well as the optimal diving theory. The model with the best predictive performance was the one that combined both tracking and diving information. However, most of the variability in the number of PCAs could be solely explained by changes in the diving behaviour of seals. Finally, we used the best predictive model on 20 individuals, which had not been fitted with accelerometers, to determine their main foraging zones. The behavioural indicators established in this study constitute a useful ecological tool for population monitoring and conservation purposes.