Calovi Daniel S, Lopez Ugo, Schuhmacher Paul, Chaté Hugues, Sire Clément, Theraulaz Guy
Centre de Recherches sur la Cognition Animale, UMR-CNRS 5169, Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse Cedex 9, France CNRS, Centre de Recherches sur la Cognition Animale, Toulouse 31062, France
Centre de Recherches sur la Cognition Animale, UMR-CNRS 5169, Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse Cedex 9, France LAPLACE (Laboratoire Plasma et Conversion d'Energie), Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse Cedex 9, France CNRS, Centre de Recherches sur la Cognition Animale, Toulouse 31062, France.
J R Soc Interface. 2015 Mar 6;12(104):20141362. doi: 10.1098/rsif.2014.1362.
Fish schools are able to display a rich variety of collective states and behavioural responses when they are confronted by threats. However, a school's response to perturbations may be different depending on the nature of its collective state. Here we use a previously developed data-driven fish school model to investigate how the school responds to perturbations depending on its different collective states, we measure its susceptibility to such perturbations, and exploit its relation with the intrinsic fluctuations in the school. In particular, we study how a single or a small number of perturbing individuals whose attraction and alignment parameters are different from those of the main population affect the long-term behaviour of a school. We find that the responsiveness of the school to the perturbations is maximum near the transition region between milling and schooling states where the school exhibits multistability and regularly shifts between these two states. It is also in this region that the susceptibility, and hence the fluctuations, of the polarization order parameter is maximal. We also find that a significant school's response to a perturbation only happens below a certain threshold of the noise to social interactions ratio.
当鱼群面临威胁时，它们能够展现出丰富多样的集体状态和行为反应。然而，鱼群对扰动的反应可能因其集体状态的性质而有所不同。在这里，我们使用先前开发的数据驱动鱼群模型来研究鱼群如何根据其不同的集体状态对扰动做出反应，我们测量其对这种扰动的敏感性，并利用它与鱼群内部波动的关系。特别是，我们研究具有不同于主要鱼群的吸引和对齐参数的单个或少数几个扰动个体如何影响鱼群的长期行为。我们发现，在鱼群表现出多稳定性并在这两种状态之间定期转换的打转和集群状态之间的过渡区域附近，鱼群对扰动的反应能力最大。极化序参量的敏感性以及因此的波动也在这个区域最大。我们还发现，只有当噪声与社会互动比率低于某个阈值时，鱼群才会对扰动做出显著反应。
