Epsilon Archive for Student Projects

Abstract

Foragers in patchy environments need to decide what patches to use and how to allocate their time
between them. Optimal foraging theory describes these choices through the relationship between
energy expenditure and energy gain. Very few studies testing this have had spatiotemporally
overlapping data on both predator & prey movement, but in this study an autonomous sail drone
(USV) equipped with an echosounder was used to map the prey abundance with high resolution
around a guillemot colony. Hydroacoustic data was combined with movement tracking data of
common guillemots from the colony to determine how prey distribution and abundance affects
foraging behaviour. Patch selection was investigated by comparing abundance of different patches
with utilization, while GAMMs were used to describe the dive behaviour in patches with different
prey abundance and depth distributions. It was found that guillemots mostly utilized patches with
shallow prey and that time of day affected the depth and duration of dives, indicating that diel
vertical migration patterns of prey influences dive behaviour of guillemots. The total foraging effort
per trip did not decrease when dive duration increased, indicating that patches are only of acceptable
quality, as total foraging effort did not decrease. It was also found that guillemots targeted patches
with more available biomass further from the colony. This study increases the understanding of how
guillemots are likely to be affected by further changes in prey populations and as seabirds are good
indicators of overall ecosystem health this method can possibly also be used for several different
species within different monitoring programmes. Mapping prey distribution with an USV is also a
pioneering method that offers a time-and cost-effective method for obtaining data with high
spatiotemporal resolution.