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Research Article | Open Access

Asymptotic stability of deterministic and stochastic prey-predator models with prey herd immigration

Department of Mathematics, College of Sciences, Majmaah University, Al-Majmaah 11952, Saudi Arabia
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Abstract

This paper aimed to study the influence of herd immigration in prey species on the stability of the prey–predator interaction, in which prey immigration is modeled as a herd movement for defensive purposes. A stochastic version of the model was formulated to incorporate the influence of random noises. Positivity and boundedness are discussed for both deterministic and stochastic models, which validate the model biologically. For the deterministic model, the local asymptotic stability of the feasible equilibrium points is discussed, and the Hopf bifurcation is exhibited with respect to an immigration factor. Using a suitable Lyapunov function, sufficient conditions for global asymptotic stability are established for deterministic and stochastic models. Numerical simulations are carried out to verify and clarify our analytical findings. It is demonstrated that increasing prey herd immigration rates stabilizes the systems. Numerical simulations of the stochastic system reveal that population density fluctuations grow more consistently as prey herd immigration increases; these simulations also exhibit diverse dynamics, including quasi-steady states and quasi-limit cycles. It is concluded that the immigration of prey herds improves the survival of both species in deterministic and stochastic systems. Thus, it may be beneficial for prey to immigrate in groups to support unstable systems.

CLC number: 34D05, 37H30, 60H10, 92-10

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AIMS Mathematics
Pages 4620-4640

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Cite this article:
Alebraheem J. Asymptotic stability of deterministic and stochastic prey-predator models with prey herd immigration. AIMS Mathematics, 2025, 10(3): 4620-4640. https://doi.org/10.3934/math.2025214

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Received: 06 December 2024
Revised: 05 February 2025
Accepted: 17 February 2025
Published: 15 March 2025
©2025 the Author(s), licensee AIMS Press.

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