Modeling and simulation of the fish collective behavior with risk perception and startle cascades

IF 3.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Physica A: Statistical Mechanics and its Applications Pub Date : 2025-02-01 Epub Date: 2024-12-30 DOI:10.1016/j.physa.2024.130337
Zhijie Zhao , Qichen Shi , Yong Liu
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Abstract

In this paper, an improved model of fish collective behavior is proposed, which combines social interactions with the risk perception and startle cascades behavior. By modeling the fast-start of fish individual and the startle propagation processes in fish school, the sudden collective evasion phenomenon during the fish collective behavior is studied. Utilizing this model, the paper focuses on investigating the impacts of cluster patterns and individual heterogeneity in social behavior and risk perception on the collective evasion process through simulations. The results show that the density of cluster aggregation is crucial in determining the propagation capability of startle responses. Conversely, the sudden startle propagation may completely change the type of cluster pattern for the cases in transitional zones. In some scenarios, a very small number of behaviorally heterogeneous individuals can dominate the cluster pattern of the entire group. Finally, it is found that distributing individuals with strong perception abilities around the periphery of the group while clustering those with weaker perception abilities within the inner group enhances the overall perception ability of the entire group.
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具有风险感知和惊吓级联的鱼群集体行为建模与仿真
本文提出了一种改进的鱼类集体行为模型,该模型将社会互动与风险感知和惊吓级联行为相结合。通过对鱼群个体快速启动和惊吓传播过程的建模,研究了鱼群集体行为中的突然集体逃避现象。利用该模型,通过模拟研究了社会行为和风险感知的集群模式和个体异质性对集体逃避过程的影响。结果表明,簇聚集的密度是决定惊吓反应传播能力的关键因素。相反,突发性惊吓传播可能完全改变过渡带病例的群集模式类型。在某些情况下,极少数行为异质的个体可以支配整个群体的集群模式。最后发现,将感知能力较强的个体分布在群体外围,将感知能力较弱的个体聚集在群体内部,可以提高整个群体的整体感知能力。
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来源期刊
CiteScore
7.20
自引率
9.10%
发文量
852
审稿时长
6.6 months
期刊介绍: Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.
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