MuFFIN - Modelling Foraging Fitness in Marine predators

MuFFIN - Modelling Foraging Fitness in Marine predatorsRecent technological advances have permitted the collection of novel high-frequency information about animal behaviour,physiology and characteristics of the environment in which animals move.

Such technology-driven achievements areexciting, but it is important to analyse these data with a view to their original objectives: understanding individual behaviour,predicting population processes and optimizing species monitoring and conservation programs. Despite a growing number oftracked animals, long term movement dataset are a present-day achievement.

As a consequence, while many studies ofanimal movements are motivated by questions on population dynamics, the explicit connection between the two is rarelyattained.

Through MUFFIN, I will make use of nearly ten years of high resolution bio-logging datasets collected on threespecies of top marine predators moving in environments difficult to monitor: Little penguins, Adelie penguins and Southernelephant seals.

With these unique data, MUFFIN will answer questions related to effects of changes of availability of marineresources on breeding success, predators foraging behaviour, decision making and habitat use.

I will (I) quantify changes inforaging behaviour across spatio-temporal scales, characterise type of foraging patches visited and energy spent.

I will (II)model the effect of foraging patches visited, energy spent and environment encountered aiming to understand animaldecision making, use of environmental features and changes in space used.

I will (III) link foraging behaviours, effort spentand type of patch to breeding success, highlighting fitness consequences of changes of behavioural patterns.

Inaccomplishing MUFFIN's objectives I will open powerful new avenues for the use and analysis of large high resolutionmovement data. These approaches are key for research seeking to optimise strategies for habitat management, speciesmonito