Modelling collective motion in animals and the impact of underlying social networks

Nature is rich with examples of the collective motion of animal groups, such as flocks of birds or shoals of fish. The mechanisms of self-organization resulting in these spectacular phenomena have received wide attention. Individual-based models are a popular and promising approach to investigate and explain features of animal collective motion. The first part of this thesis gradually develops a novel modelling framework for the collective motion of animals and justifies it by comparison to empirical findings. Key aspects of the model are stochastic asynchronous updates and sensory zone sampling of individuals. Higher updating frequencies are related to increased levels of perceived threat and reduced stochastic effects leading to synchronisation in moving groups. Sensory zone sampling, biased according to the distance between individuals, provides a possible mechanism for the empirical finding that animals on average only interact with a fixed number of nearest neighbours. Many group-living animals show social preferences for relatives, familiar conspecifics or individuals of similar attributes, such as size. How such preferences could affect the collective motion of animal groups has been rather unexplored. The second part of this thesis reviews previous theoretical work that combines the concepts of social networks and collective motion. Although many of the models reviewed have not been explored with ecology in mind, they present a current context in which a biologically relevant theory can be developed. The modelling framework from the first part is extended to include social connections as preferential reactions between individuals. This is used to show that the structure of social networks could influence the cohesion of groups, the spatial position of individuals within groups and the hierarchical dynamics within such groups. This thesis aims to contribute possible mechanisms, testable hypotheses and an informed starting point for future research on how social networks could affect animal group movement.