Modeling and analysis of a prey-predator system with prey habitat selection in an environment subject to stochastic disturbances

Yuan Tian , Jing Zhu , Jie Zheng , Kaibiao Sun

Electronic Research Archive ›› 2025, Vol. 33 ›› Issue (2) : 744 -767.

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Electronic Research Archive ›› 2025, Vol. 33 ›› Issue (2) :744 -767. DOI: 10.3934/era.2025034
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Modeling and analysis of a prey-predator system with prey habitat selection in an environment subject to stochastic disturbances
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Abstract

In natural ecosystems, the external environment is constantly changing, and is affected by various factors, thus presenting a certain degree of randomness and uncertainty. Therefore, having a suitable habitat is essential for the reproductive success of many species. Understanding the impact of habitat selection provides valuable insights into how species locate and adapt to suitable living environments based on their specific needs. For this purpose, a prey-predator system model with prey habitat selection in an environment subject to stochastic disturbances is formulated. The properties of the proposed model without and with stochastic disturbances are investigated, including the existence of a unique ergodic stationary distribution, the stochastically ultimate bounded-ness of the solutions, and the extinction and persistence of the populations. The study demonstrates that prey can persist at a low intensity noise, whereas stronger stochastic disturbances may lead to the extinction of both the prey and predator species. To illustrate the theoretical results, numerical simulations are presented step by step. This work provides a theoretical reference for further studies on populations with habitat selection in an environment subject to stochastic disturbances.

Keywords

stochastic prey-predator model / habitat selection / stationary distribution / stochastically ultimate bounded-ness / persistence

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Yuan Tian, Jing Zhu, Jie Zheng, Kaibiao Sun. Modeling and analysis of a prey-predator system with prey habitat selection in an environment subject to stochastic disturbances. Electronic Research Archive, 2025, 33 (2) : 744-767 DOI:10.3934/era.2025034

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