| Abstract |
Difficulties quantifying in situ prey patch quality have limited our understanding of how marine predators respond to variation within and between patches, and throughout their foraging range. In the present study, animal-borne video, GPS, accelerometer and dive behaviour data loggers were used to investigate the fine-scale foraging behaviour of Macaroni penguins (Eudyptes chrysolophus) in response to prey type, patch density and temporal variation in diving behaviour. Individuals mainly dived during the day and utilised two strategies, targeting different prey types. Subantarctic krill (Euphausia vallentini) were consumed during deep dives, while small soft-bodied fish were captured on shallow dives or during the ascent phase of deep dives. Despite breeding in large colonies individuals seemed to be solitary foragers and did not engage with conspecifics in coordinated behaviour as seen in other group foraging penguin species. This potentially reflects the high abundance and low manoeuvrability of krill. Video data were used to validate prey capture signals in accelerometer data and a Support Vector Machine learning algorithm was developed to identify prey captures that occurred throughout the entire foraging trip. Prey capture rates indicated that Macaroni penguins continued to forage beyond the optimal give up time. However, bout-scale analysis revealed individuals terminated diving behaviour for reasons other than patch quality. These findings indicate that individuals make complex foraging decisions in relation to their proximate environment over multiple spatio-temporal scales. |
