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Research Article | Open Access

Markovian switching induced dynamics of a predator-prey system with prey refuge and habitat selection

Yuan Tian1( )Jing Zhu1Haiyan Gao2( )Kaibiao Sun3( )
School of Science, Dalian Maritime University, Dalian 116026, China
Department of Public Education, Dalian University of Finance and Economics, Dalian 116622, China
School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China
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Abstract

In natural ecosystems, population dynamics are influenced by white and colored noise, which drive the population system to transition between multiple states. Therefore, it is essential to investigate predator-prey models that incorporate the concurrent impacts of white and colored noise. In this paper, we examined a three-dimensional stochastic predator-prey model involving dual prey species and a single predator by incorporating the refuge effect and habitat selection behavior under Markovian switching. By leveraging the theoretical framework of stochastic differential equations, its stochastic persistence was analyzed. Additionally, by constructing suitable Lyapunov functions, the conditions for an ergodic stationary distribution were deduced. Additionally, the extinction of populations and the asymptotic properties of solutions were explored. The findings revealed that habitat selection behavior has a significant and detrimental impact on the corresponding prey, while the refuge effect positively influences the prey and the predator. Ultimately, numerical simulations were performed to validate the theoretical outcomes. The results of these simulations strongly confirm the accuracy of the theoretical deductions.

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Electronic Research Archive
Pages 962-996

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Cite this article:
Tian Y, Zhu J, Gao H, et al. Markovian switching induced dynamics of a predator-prey system with prey refuge and habitat selection. Electronic Research Archive, 2026, 34(2): 962-996. https://doi.org/10.3934/era.2026045

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Received: 17 December 2025
Revised: 19 January 2026
Accepted: 23 January 2026
Published: 29 January 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)