Investigating decision-rules in food-hoarding birds using agent-based modelling
Several bird species in the Paridae family have evolved food caching strategies in order to increase their survival during winter when food availability is low and highly variable. Caching creates a dependable food source and enables these birds to build up sufficient fat reserves to survive long and cold nights. Food hoarding occurs both on a short-term basis, when food is stored to be retrieved later in the day, and on a long-term basis when food is stored in autumn to be retrieved in winter. It is not yet fully understood what mechanisms underlie the food-hoarding decisions in these birds, what parameters are important for these processes and how they function on the two different timescales. With this project, we aim to investigate these decision rules in food-hoarding birds. The project takes a computational approach, using agent-based models applied to hoarding and non-hoarding birds with different sets of decision rules. These models will be validated and improved with data from the literature and a citizen-science project component. Doing so, we aim to better the understanding of the system that underlies these hoarding decisions and study if this could have evolved from the evolutionary conserved physiological system that controls eating motivation in all vertebrates.