Social networks improve leaderless group navigation by facilitating long-distance communication

Abstract

Group navigation is of great importance for many animals, such as migrating flocks of birds or shoals of fish. One theory states that group membership can improve navigational accuracy compared to limited or less accurate individual navigational ability in groups without leaders (“Many-wrongs principle”). Here, we simulate leaderless group navigation that includes social connections as preferential interactions between individuals. Our results suggest that underlying social networks can reduce navigational errors of groups and increase group cohesion. We use network summary statistics, in particular network motifs, to study which characteristics of networks lead to these improvements. It is networks in which preferences between individuals are not clustered, but spread evenly across the group that are advantageous in group navigation by effectively enhancing long-distance information exchange within groups. We suggest that our work predicts a base-line for the type of social structure we might expect to find in group-living animals that navigate without leaders [Current Zoology 58 (2): 329-341, 2012].

Keywords

• Collective motion
• Social networks
• Group navigation
• Network motifs
• Many-wrongs principle
• Individual-based model