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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.
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.
Abrupt (i. e. step) environmental changes, such as natural disasters or the intervention of predators, can alter the internal dynamics of groups with active units, leading to the rapid destruction and/or restructuring of the group, with the emergence of new collective structures that endow the system with adaptability. Few studies, to date, have considered the influence of abrupt environmental changes on emergent behavior. Here, we use a model of active matter, the Belousov‐Zhabotinsky (BZ) self‐oscillating gel, to study the mechanism of formation and transition between modes of collective locomotion caused by changes of illumination intensity in arrays of interacting photosensitive active units. New forms of collective motion can be generated by step changes of illumination intensity. These transformations arise from the phase resetting and wave‐signal regeneration induced by the abrupt parameter variation, while gradual change results in different evolution of collective motion. Our results not only suggest a novel mechanism for emergence, but also imply that new collective behaviors could be accessible via discontinuous parameter changes.
Parental brood care greatly affects offspring’s fitness, but the specific effects of care on the collective behaviour of independent offspring are less well understood. It has been suggested that the loss of care induces increased sibling cooperation to compensate parental contributions. However, the empirical evidence is ambiguous. Here, we examined how the loss of early parental care affects the collective behaviour, i.e. shoaling performance of independent juveniles in a genetically heterogeneous lab-population of the biparental cichlid fish Pelvicachromis pulcher. Applying a split-clutch design, we reared in- and outbred offspring with or without parents. In the experiment, we examined shoal density (inter-individual distance) in relation to body size of the shoaling fish. Dense shoaling reduces predation risk and small fish may benefit strongest because they are particularly vulnerable to predation by gape-limited predators. Juveniles reared without parents formed denser shoals and they adjusted shoaling behaviour depending on own body size compared to juveniles reared with parents; especially smaller fish formed dense shoals. Inbreeding did not significantly affect shoaling performance. This indicates that juveniles compensate missing parental care by adjusting their shoaling behaviour depending on own vulnerability. Our study contributes to the understanding of the co-evolution of brood care and sibling cooperation.
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