Stability, bifurcation, and chaos of a stage-structured predator-prey model under fear-induced and delay

The motivation of this paper is inspired by the research of Zanette et al. (2011) [4], which reveals that the perception of predation risk can reduce the number of juvenile prey. To investigate how fear affects the behavior of prey population, we formulate a predator-prey model with a stage structur...

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Veröffentlicht in:Applied mathematics and computation 2024-09, Vol.476, p.128780, Article 128780
Hauptverfasser: Qi, Haokun, Liu, Bing, Li, Shi
Format: Artikel
Sprache:eng
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Zusammenfassung:The motivation of this paper is inspired by the research of Zanette et al. (2011) [4], which reveals that the perception of predation risk can reduce the number of juvenile prey. To investigate how fear affects the behavior of prey population, we formulate a predator-prey model with a stage structure for prey in which adult prey is undergoing the interference of fear. First, the dynamic properties of the model are analyzed, including the existence and stability of equilibria, bifurcations dynamics, such as transcritical, saddle-node, and Hopf bifurcations. Our results reveal that fear can promote the formation of the stability of the model by transforming it from an unstable state to a stable state. Numerical simulations and theoretical analysis indicated that when the level of fear reaches 25.4, the number of juvenile prey affected by fear decreases by 40% compared to those not affected by fear. Terrifyingly, the predators are on the brink of extinction in high levels of fear. Moreover, we examine the impact of time delay on fear in the previous model as prey needs some time to assess the predation risk. Some dynamic characteristics of this delayed model are also analyzed. Results indicate that the fear effect is conducive to generating a stable state, while delay is detrimental to generating a stable state, leading to limit cycles or even chaos. •A stage-structure predator-prey model with fear and delay is proposed.•The feasibility equilibria and bifurcation dynamics of the model are studied.•Fear can transform a model from an unstable state to a stable state.•Delay is detrimental to generating a stable state, leading to limit cycles or chaos.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2024.128780