| Summary: | How animals move through their environment defines their ecology at an individual and population level. All animals must search for food to survive and how they do this can be influenced by the world around them as well as their own internal state. Our understanding of animal ecology has been dramatically expanded thanks to the continued development and miniaturisation of data loggers that can be attached to animals. Data from these biologgers remain challenging to interpret, but shed light on the behavioural ecology of individual animals. In this thesis, I use movement data from seabirds to explore the mechanisms behind foraging and how these are underpinned by the movement of individual animals. In chapter 1, I provide an introductory overview of the literature and introduce my study species. In chapter 2, I examine the methods available to interpreting behaviour from animal relocation data showing that Hidden Markov Models (HMMs) outcompete other behavioural annotation methods – successfully identifying 81% of plunge dives in northern gannets, Morus bassanus. I then provide recommendations for best practice when defining periods of search and prey capture behaviour. In chapter 3, I show how environmental features may ultimately disrupt the expected movement of optimal foraging, and show that Atlantic puffins, Fratercula arctica, in southeast Ireland have departed from classic Area Restricted Search (ARS). These findings are considered in an energetic perspective and suggest that puffins may be saving between 28-46% of the energy required to fly the same distance. In chapter 4, I utilise acceleration data to document the bioenergetic sex differences of prey capture attempts in northern gannets, examining the links between diet, movement, and energy expenditure. Stable isotope analysis showed dietary differences between the sexes, but energetic content of divergent diets was the same. Prey capture attempts are not energetically expensive for gannets (<4% of energy expenditure in all northern gannets) and ...
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