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Understanding the ontogeny of foraging behaviour: insights from combining marine predator bio-logging with satellite-derived oceanography in hidden Markov models

Research output: Contribution to journalArticle

Author(s)

W. James Grecian, Jude Lane, Théo Michelot, Helen M. Wade, Keith C. Hamer

School/Research organisations

Abstract

The development of foraging strategies that enable juveniles to efficiently identify and exploit predictable habitat features is critical for survival and long-term fitness. In the marine environment, meso- and sub-mesoscale features such as oceanographic fronts offer a visible cue to enhanced foraging conditions, but how individuals learn to identify these features is a mystery. In this study, we investigate age-related differences in the fine-scale foraging behaviour of adult (aged ≥ 5 years) and immature (aged 2-4 years) northern gannets Morus bassanus. Using high-resolution GPS-loggers, we reveal that adults have a much narrower foraging distribution than immature birds and much higher individual foraging site fidelity. By conditioning the transition probabilities of a hidden Markov model on satellite-derived measures of frontal activity, we then demonstrate that adults show a stronger response to frontal activity than immature birds, and are more likely to commence foraging behaviour as frontal intensity increases. Together, these results indicate that adult gannets are more proficient foragers than immatures, supporting the hypothesis that foraging specialisations are learned during individual exploratory behaviour in early life. Such memory-based individual foraging strategies may also explain the extended period of immaturity observed in gannets and many other long-lived species.
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Details

Original languageEnglish
Article number20180084
Number of pages9
JournalJournal of the Royal Society Interface
Volume15
Issue number143
Early online date6 Jun 2018
DOIs
Publication statusPublished - 6 Jun 2018

    Research areas

  • Animal telemetry, Foraging ecology, Finite-size Lyapunov exponent, Learning, Marine vertebrate, Movement ecology

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