Dynamical analysis of a stochastic prey-predator model with fear effect and feedback control.

IF 1.8 4区 数学 Q3 ECOLOGY
Journal of Biological Dynamics Pub Date : 2025-12-01 Epub Date: 2025-03-17 DOI:10.1080/17513758.2025.2479461
Yan Zhang, Feng Lai, Shujing Gao, Yang Liu, Shuixian Yan
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引用次数: 0

Abstract

In this work, the intricacies and complexities of dynamical properties are extensively studied for the proposed deterministic and stochastic prey-predator models. The influence of fear effects, prey refuge and feedback control are considered and thorough theoretical research is conducted on the systems. It commences by establishing the global stability and uniqueness of the positive equilibrium of the deterministic model. Then for the stochastic system, the existence, uniqueness and boundedness of a global positive solution are analysed by constructing appropriate Lyapunov functions. Sufficient conditions are established for the extinction and persistence of the stochastic model. It can be observed that both the fear effect and prey refuge have a greatly impact on the dynamics of system. Intermediate values of feedback control intensity may be the most beneficial to species coexistence. It provides new insights into the sustainability of ecosystems.

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来源期刊
Journal of Biological Dynamics
Journal of Biological Dynamics ECOLOGY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
4.90
自引率
3.60%
发文量
28
审稿时长
33 weeks
期刊介绍: Journal of Biological Dynamics, an open access journal, publishes state of the art papers dealing with the analysis of dynamic models that arise from biological processes. The Journal focuses on dynamic phenomena at scales ranging from the level of individual organisms to that of populations, communities, and ecosystems in the fields of ecology and evolutionary biology, population dynamics, epidemiology, immunology, neuroscience, environmental science, and animal behavior. Papers in other areas are acceptable at the editors’ discretion. In addition to papers that analyze original mathematical models and develop new theories and analytic methods, the Journal welcomes papers that connect mathematical modeling and analysis to experimental and observational data. The Journal also publishes short notes, expository and review articles, book reviews and a section on open problems.
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