Collective response to perturbations in a data-driven fish school model

TL;DR

This study uses a data-driven fish school model to analyze how schools respond to perturbations, revealing maximum responsiveness near state transitions and dependence on noise levels.

Contribution

It introduces a detailed analysis of how perturbations influence fish school behavior depending on the collective state and noise conditions.

Findings

Maximum responsiveness occurs near transition between milling and schooling states.

School response depends on the noise to social interactions ratio.

Perturbation effects vary with collective state and perturbing individual parameters.

Abstract

Fish schools are able to display a rich variety of collective states and behavioural responses when they are confronted to threats. However a school's response to perturbations may be different depending on its collective state. Here we use a previously developed data-driven fish school model to investigate how a single or a small number of perturbing individuals affect the long-term behaviour of a school depending on its collective state. These perturbing fish are characterised by a set of attraction and alignment parameters different from those of the main population. We find that the responsiveness of the school to the perturbation is maximum near the transition region between milling and schooling states where the school exhibits multistability and regularly shifts between these two states. 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.