Stochastic modelling of bird flocks – accounting for the cohesiveness of collective motion

A - Papers appearing in refereed journals

Reynolds, A. M., McIvor, G. E., Thornton, A., Yang, P. and Ouellette, N. T. 2022. Stochastic modelling of bird flocks – accounting for the cohesiveness of collective motion. Journal of the Royal Society Interface. 19, p. 20210745. https://doi.org/10.1098/rsif.2021.0745

AuthorsReynolds, A. M., McIvor, G. E., Thornton, A., Yang, P. and Ouellette, N. T.
Abstract

Collective behaviour can be difficult to discern because it is not limited to animal aggregations such as flocks of birds and schools of fish wherein individuals spontaneously move in the same way despite the absence of leadership. Insect swarms are, for example, a form of collective behaviour, albeit one lacking the global order seen in bird flocks and fish schools. Their collective behaviour is evident in their emergent macroscopic properties. These properties are predicted by close relatives of Okubo’s [1986] stochastic model. Here we argue that Okubo’s stochastic model also encapsulates the cohesiveness mechanism at play in bird flocks, namely the fact that birds within a flock behave on average as if they are trapped in an elastic potential well. That is, each bird effectively behaves as if it is bound to the flock by a force that on average increases linearly as the distance from the flock centre increases. We uncover this key but until now overlooked feature of flocking in empirical data. This gives us a means of identifying what makes a given system collective. We show how the model can be extended to account for intrinsic velocity correlations and differentiated social relationships.

KeywordsCollective behaviours; Cohesiveness; Flocks; Swarms; Stochastic modelling
Year of Publication2022
JournalJournal of the Royal Society Interface
Journal citation19, p. 20210745
Digital Object Identifier (DOI)https://doi.org/10.1098/rsif.2021.0745
Open accessPublished as green open access
FunderBBSRC Industrial Strategy Challenge
Funder project or codeSmart Crop Protection WP1
Output statusPublished
Publication dates
Online20 Apr 2022
PublisherRoyal Society Publishing
ISSN1742-5689

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