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.

Emergence of splits and collective turns in pigeon flocks under predation

“…Data accessibility. The agent-based model (HoPE) is available on GitHub: https://github.com/marinapapa/a-new-HoPEmodel and the version used for this research work has been archived within the Zenodo repository: https://doi.org/ 10.5281/zenodo.5889123 [107]. Data and relevant code for this research work are stored in GitHub: https://github.…”

Diffusion during collective turns in bird flocks under predation

“…To reduce the complexity of our model, we set the preferred speed of all individuals to be the same (u, Table 1). To reflect the inability of individuals to infinitely increase or decrease their speed, our agents are dragged back to their preferred speed based on a speed-control steering vector, similar to the drag force used in previous data-inspired models of bird flocks (Papadopoulou et al, 2022a;Papadopoulou et al, 2022b).…”

“…In this case, the vector points to the direction away from the heading of the predator (Figure 2BII). For this, we model a dummy predator-agent that follows the flock from behind (from a given distance and bearing angle, similar to previous models of bird flocks; Papadopoulou et al, 2022b). The strength of the force is such that individuals perform a turn with a predefined angular velocity (e.g.…”

“…Collective turns are a major method by which flocks of birds respond to predators (Papadopoulou et al, 2022b;Storms et al, 2022b). It is observed in many bird species, from small flocks of crows and homing pigeons to large flocks of jackdaws and starlings, and across many ecological contexts, during foraging and mobbing (Ling et al, 2019c), roosting (circling around roost) (Ballerini et al, 2008a;Yomosa et al, 2015), and evading predators (Papadopoulou et al, 2022a).…”

“…When under threat, prey may, for instance, increase the frequency of interacting with each other (referred to as reaction or update frequency) which can lead to more frequent changes in their relative position (Bode et al, 2010;Herbert-Read et al, 2017). Prey may also increase their tendency to align with (Sankey et al, 2021) or stay close to (Herbert-Read et al, 2017) each other, which can increase the density of the group offering a high anti-predator benefit (Carere et al, 2009;King et al, 2012) or facilitate their collective escape by dodging a predator's attack (Papadopoulou et al, 2022a;Papadopoulou et al, 2022b).…”