Self-organization of collective escape in pigeon flocks

Abstract

Bird flocks under predation demonstrate complex patterns of collective escape. These patterns may emerge by self-organization from simple interactions among group-members. Computational models have been shown to be valuable for identifying the behavioral rules that may govern these interactions among individuals during collective motion. However, our knowledge of such rules for collective escape is limited by the lack of quantitative data on bird flocks under predation in the field. In the present study, we analyze the first dataset of GPS trajectories of pigeons in airborne flocks attacked by a robotic falcon in order to build a species-specific model of collective escape. We use our model to examine a recently identified distance-dependent pattern of collective behavior that shows an increase in the escape frequency of pigeons when the predator is closer. We first extract from the empirical data the characteristics of pigeon flocks regarding their shape and internal structure (bearing angle and distance to nearest neighbours). Combining these with information on their coordination from the literature, we build an agent-based model tuned to pigeons collective escape. We show that the pattern of increased escape frequency closer to the predator arises without flock-members prioritizing escape when the predator is near. Instead, it emerges through self-organization from an individual rule of predator-avoidance that is independent of predator-prey distance. During this self-organization process, we uncover a role of hysteresis and show that flock members increase their consensus over the escape direction and turn collectively as the predator gets closer. Our results suggest that coordination among flock-members, combined with simple escape rules, reduces the cognitive costs of tracking the predator. Such rules that are independent of predator-prey distance can now be examined in other species. Finally, we emphasize on the important role of computational models in the interpretation of empirical findings of collective behavior. Author summaryBird flocks show fascinating patterns of collective motion, particularly when escaping a predator. Little is however known about their underlying mechanisms. We fill this gap by firstly analyzing GPS data of pigeon flocks under attack by a robotic-predator and secondly, studying their collective escape in a computer simulation. Previous research on pigeons has revealed that flock-members turn away from the predator more the closer the predator gets. Using computer simulations that are based on pigeon-specific characteristics of motion and coordination among individuals, we study what escape rules at the individual level may underlie this distance-dependent pattern. We show that even if individuals do not intend to escape more when the predator is closer, their escape frequency still increases the closer they get to the predator. This happens by self-organization from the coordination among individuals and despite their tendency to turn away from the predator being constant. A key aspect of this process is the increasing consensus among flock members over the escape direction when the predator gets closer.