Emergence of splits and collective turns in pigeon flocks under predation

Abstract

Complex patterns of collective behaviour may emerge through self-organization, from local interactions among individuals in a group. To understand what behavioural rules underlie these patterns, computational models are often necessary. These rules have not yet been systematically studied for bird flocks under predation. Here, we study airborne flocks of homing pigeons attacked by a robotic falcon, combining empirical data with a species-specific computational model of collective escape. By analysing GPS trajectories of flocking individuals, we identify two new patterns of collective escape: early splits and collective turns, occurring even at large distances from the predator. To examine their formation, we extend an agent-based model of pigeons with a ‘discrete’ escape manoeuvre by a single initiator, namely a sudden turn interrupting the continuous coordinated motion of the group. Both splits and collective turns emerge from this rule. Their relative frequency depends on the angular velocity and position of the initiator in the flock: sharp turns by individuals at the periphery lead to more splits than collective turns. We confirm this association in the empirical data. Our study highlights the importance of discrete and uncoordinated manoeuvres in the collective escape of bird flocks and advocates the systematic study of their patterns across species.

Flock Stasis Drives Flying Speed in Pigeons, While Artificial Mass Additions Do Not

“…This is a question, which we provide some foundational principles toward, but which will require a collective effort by empiricists (both wild and captive behaviourists) and theoreticians to address. This work also further adds to the body of work demonstrating the opportunities that homing pigeons offer in terms of researching flocking dynamics, personality, energetics and collective behaviour [98][99][100][101][102][103][104][105][106][107][108][109][110].…”

Dynamics of collective motion across time and species

“…Data of homing pigeons were collected in field experiments [ 41 ], comprising GPS trajectories (sampling frequency of 0.2 s) of pigeons in flocks of 8, 10, 27 and 34 individuals being released to start their homing route [ 4 , 41 ]. We use ‘control’ flights from the study where pigeons were flying undisturbed [ 53 ]. The average duration of each track is 30 s. GPS data of free-ranging goats in Namibia [ 39 ] and chacma baboons in South Africa [ 42 ] were collected using SHOALgroup collars (modified F2HKv2 on the goats and F2HKv3 on the baboons).…”

“…We therefore randomly sampled ‘snapshots’ from these events ranging from 1 to 30 s and calculated the group's polarization and shape for each snapshot separately. Group shape was defined simply, as the angle (0°–90°) between the group's heading and the direction of the short side of a minimum bounding box that includes all group members [ 53 , 55 , 56 ]. An angle of 0 ° thus represents a group that is perfectly wider than longer, while an angle for 90° a group that is perfectly oblong (elongated in the moving direction).…”

Characterization of bird formations using fuzzy modelling

“…This is the case of starlings [ 8 ], pigeons [ 9 ] or even mixed-species flocks [ 10 ]. For a long time, scientists have been studying this type of flocking behaviour, trying to figure out how birds manage this high level of coordination and cohesion without colliding [ 11 , 12 ], especially during turning, landing, taking off or under predation [ 13 , 14 ].…”