Assessing the utility of two- and three-dimensional behavioural metrics in habitat usage models

• Published in: Marine Ecology Progress Series
• Main Authors: Pascoe, P, Lea, MA, Mattlin, RH, McMahon, CR, Harcourt, R, Thompson, D, Torres, L, Vinette-Herrin, K, Hindell, MA
• Format: Article in Journal/Newspaper
• Language: English
• Published: Inter-Research 2016
• Subjects: Environmental Sciences; Environmental Science and Management; Wildlife and Habitat Management; Southern Ocean; Pacific; Campbell Islands; Elephant Seals; Mirounga leonina; Southern Elephant Seals
• Online Access: https://doi.org/10.3354/meps11947; http://ecite.utas.edu.au/114523

For deep-diving, wide-ranging marine predators, foraging behaviour is often inferred from movement data. Various metrics are used to do this, and recently, metrics have been developed that consider both horizontal movement and vertical dive behaviour to better describe the use of the 3-dimensional environment these animals inhabit. However, the efficacy of these different metrics in predicting behavioural state is poorly understood. We used first passage time (2-dimensional) and first bottom time (3-dimensional) analyses on tracks derived from satellite-relayed data loggers to quantify and determine seal behavioural state while foraging at sea. Movement and dive data were collected from 38 southern elephant seals Mirounga leonina from Macquarie and Campbell Islands (in the Pacific sector of the Southern Ocean). Using a suite of environmental variables, linear mixed-effect models were derived for the 2 broad habitats visited by the seals: shelf and open ocean. The best-fitting models for each foraging metric in each habitat were then compared using a cross validation analysis to identify which foraging metric produced the best predictions of habitat use. In shelf habitats, the 3-dimensional foraging metric provided better predictions than the 2-dimensional metric, while the 2-dimensional foraging metric resulted in the best predictive capacity in the open ocean habitats. These findings highlight the importance of considering the appropriate foraging metrics when modelling foraging behaviour.