Turing-like patterns induced by the competition between two stable states in a discrete-time predator–prey model

Huimin Zhang, Jian Gao, Changgui Gu, Yongshang Long, Chuansheng Shen and Huijie Yang

Chaos, Solitons & Fractals, 2024, vol. 180, issue C

Abstract: Patterns, typical spatiotemporal ordered structures, are widely present in a variety of systems, which are the results of the emergence of complex systems. The theory of Turing, occupying a long-range inhibitor and a short-range activator, provides an explanation for the diversity of Turing patterns. Turing-like patterns, caused by various non-Turing mechanisms, have also been investigated in various models. Patterns resulting from Turing or non-Turing mechanisms have predominantly focused on continuous-time models, however, for populations with non-overlapping generations, discrete-time models are more realistic than continuous-time ones. Here, we investigated a type of Turing-like patterns in a discrete-time model. The results show that the competition between two stable states can lead to the formation of Turing-like patterns. Specifically, we obtained a type of Turing-like patterns in a discrete-time model, which exist outside the parameter regions of Turing instability. Only by applying strong impulse noise to the homogeneous stable state can the patterns be excited. And the excitation threshold is related to the control parameter. Analysis shows that the Turing-like patterns are the results of competition between two stable states corresponding to adjacent orbits, and the excitation threshold is determined by the relative position between orbits. This findings exemplify the multitude of mechanisms observed in nature that give rise to the emergence of Turing or Turing-like patterns, and shed light on the pattern formation for Turing/Turing-like patterns.

Keywords: Pattern formation; Turing instability; Turing-like pattern; Discrete-time system (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:180:y:2024:i:c:s0960077924000328

DOI: 10.1016/j.chaos.2024.114481

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