The STARFLAG handbook on collective animal behaviour: 1. Empirical methods

Cavagna, Andrea; Giardina, Irene; Orlandi, Alberto; Parisi, Giorgio; Procaccini, Andrea; Viale, Massimiliano; Zdravkovic, Vladimir

doi:10.1016/j.anbehav.2008.02.002

Cited by 108 publications

(111 citation statements)

References 29 publications

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“…From the STARFLAG project [109,110] that mapped the three-dimensional structure of free-flying starling flocks emerged strong experimental evidence for topological-like interactions [68]. Each bird seems to pay attention to approximately seven nearest neighbours [68], suggesting how cohesiveness can be maintained in groups that exhibit such density variability.…”

Section: Determining Which Neighbours a Fish Is Interacting Withmentioning

confidence: 99%

From behavioural analyses to models of collective motion in fish schools

et al. 2012

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Fish schooling is a phenomenon of long-lasting interest in ethology and ecology, widely spread across taxa and ecological contexts, and has attracted much interest from statistical physics and theoretical biology as a case of self-organized behaviour. One topic of intense interest is the search of specific behavioural mechanisms at stake at the individual level and from which the school properties emerges. This is fundamental for understanding how selective pressure acting at the individual level promotes adaptive properties of schools and in trying to disambiguate functional properties from non-adaptive epiphenomena. Decades of studies on collective motion by means of individual-based modelling have allowed a qualitative understanding of the self-organization processes leading to collective properties at school level, and provided an insight into the behavioural mechanisms that result in coordinated motion. Here, we emphasize a set of paradigmatic modelling assumptions whose validity remains unclear, both from a behavioural point of view and in terms of quantitative agreement between model outcome and empirical data. We advocate for a specific and biologically oriented re-examination of these assumptions through experimental-based behavioural analysis and modelling.

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Section: Determining Which Neighbours a Fish Is Interacting Withmentioning

confidence: 99%

From behavioural analyses to models of collective motion in fish schools

et al. 2012

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“…Only at this point, stereometric formulas can be applied to recover from each pair of matched individuals in the photo the physical 3D coordinates of the individual in space. The matching problem can become extremely severe when groups are large and compact: photographic images of flying flocks are typically very dense sets of almost featureless points (Cavagna et al, 2008c).…”

Section: Empirical Studiesmentioning

confidence: 99%

“…This work improved previous benchmarks in various respects. From a technical point of view, using statistical mechanics, optimization theory, and computer vision techniques, the matching problem was solved allowing for the 3D reconstructions of large groups (Cavagna et al, 2008c), see Fig. 4.…”

Section: Empirical Studiesmentioning

confidence: 99%

Collective behavior in animal groups: Theoretical models and empirical studies

2008

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“…However, there has been recent compelling evidence [1] that interactions within bird flocks are mostly metric free, as the birds react primarily with a limited number of their nearest neighbours irrespective of the distances between them. This observation has motivated the concept of "topological interaction", which has been widely echoed in the scientific literature [5,7,10,13,19].…”

Section: Introductionmentioning

confidence: 99%

Topological Interactions in a Boltzmann-Type Framework

Blanchet

Degond

2016

J Stat Phys

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We consider a finite number of particles characterised by their positions and velocities. At random times a randomly chosen particle, the follower, adopts the velocity of another particle, the leader. The follower chooses its leader according to the proximity rank of the latter with respect to the former. We study the limit of a system size going to infinity and, under the assumption of propagation of chaos, show that the limit equation is akin to the Boltzmann equation. However, it exhibits a spatial non-locality instead of the classical non-locality in velocity space. This result relies on the approximation properties of Bernstein polynomials. We illustrate the dynamics with numerical simulations.

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The STARFLAG handbook on collective animal behaviour: 1. Empirical methods

Cited by 108 publications

References 29 publications

From behavioural analyses to models of collective motion in fish schools

From behavioural analyses to models of collective motion in fish schools

Collective behavior in animal groups: Theoretical models and empirical studies

Topological Interactions in a Boltzmann-Type Framework

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