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Fish shoals resemble a stochastic excitable system driven by environmental perturbations

Luis Gómez-Nava, Robert Tjarko Lange, Pascal Klamser, Juliane Lukas, Lenin Arias‐Rodríguez, David Bierbach, Jens Krause, Henning Sprekeler, Paweł Romańczuk

2023Nature Physics49 citationsDOIOpen Access PDF

Abstract

Abstract Groups of animals can perform highly coordinated collective behaviours that confer benefits to the participating individuals by facilitating social information exchange and protection from predators 1 . Some of these characteristics could arise when groups operate at critical points between two structurally and functionally different states, leading to maximal responsiveness to external stimuli and effective propagation of information 2,3 . It has been proposed that animal groups constitute examples of self-organized systems at criticality 2,3 ; however, direct empirical evidence of this hypothesis—in particular in the wild—is mostly absent. Here we show that highly conspicuous, repetitive and rhythmic collective dive cascades produced by many thousands of freshwater fish under high predation risk resemble a stochastic excitable system driven by environmental perturbations. Together with the results of an agent-based model of the system, this suggests that these fish shoals might operate at a critical point between a state of high individual diving activity and low overall diving activity. We show that the best fitting model, which is located at a critical point, allows information about external perturbations—such as predator attacks—to propagate most effectively through the shoal. Our results suggest that criticality might be a plausible principle of distributed information processing in large animal collectives.

Topics & Concepts

ShoalCriticalityPredationPhysicsStatistical physicsCritical point (mathematics)Fish <Actinopterygii>EcologyComputer scienceBiologyFisheryMathematicsMathematical analysisGeologyOceanographyNuclear physicsstochastic dynamics and bifurcationNeural dynamics and brain functionNonlinear Dynamics and Pattern Formation