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The ability to quantify animals’ feeding activity and the resulting
changes in their body condition as they move in the environment is
fundamental to our understanding of a population’s ecology. We use
satellite tracking data from northern elephant seals (Mirounga
angustirostris), paired with simultaneous diving information, to develop a
Bayesian state-space model that concurrently estimates an individual’s
location, feeding activity, and changes in condition. The model identifies
important foraging areas and times, the relative amount of feeding
occurring therein and thus the different behavioral strategies in which
the seals engage. The fitness implications of these strategies can be
assessed by looking at the resulting variation in individuals’ condition,
which in turn affects the condition and survival of their offspring.
Therefore, our results shed light on the processes affecting an
individual’s decision-making as it moves and feeds in the environment. In
addition, we demonstrate how the model can be used to simulate realistic
patterns of disturbance at different stages of the trip, and how the
predicted accumulation of lipid reserves varies as a consequence.
Particularly, disturbing an animal in periods of high feeding activity or
shortly after leaving the colony was predicted to have the potential to
lead to starvation. In contrast, an individual could compensate even for
very severe disturbance if such disturbance occurred outside the main
foraging grounds. Our modelling approach is applicable to marine mammal
species that perform drift dives, and can be extended to other species
where an individual’s buoyancy can be inferred from its diving behavior.
202 views reported since publication in 2018.