Skip to content
Open access

Dynamical Analysis of a Delayed Fractional-Order Food Chain Model with the Allee Effect and Prey Refuge

Aug 2026 · Axioms · Vol 15, pp. 609 · 0 citations · 33 references

Abstract

In this paper, a delayed fractional-order three-trophic-level food chain model with Allee effect and prey shelter is proposed and analyzed. The model adopts the Caputo fractional derivative to describe the memory effect, and introduces two discrete time delays which represent the gestation and response delays of predators, respectively. We establish the positivity, boundedness, existence, uniqueness and continuity of solutions. By using Jacobian matrix analysis and fractional stability theory, we investigate the equilibrium points and their local stability. The corrected characteristic equation is derived, and sufficient conditions for a Hopf-type stability switch induced by the delays are obtained. In the integer-order case α=1, the critical delay and transversality condition are verified numerically, supporting a classical Hopf-bifurcation conclusion subject to the usual nondegeneracy assumptions. Numerical simulations verify the theoretical results and illustrate the combined effects of time delays, fractional memory, prey shelter and Allee effect on system dynamics. The results show that time delays may destabilize the system and produce persistent oscillatory numerical behaviour, while stronger memory effects, shelter strength and Allee effects enhance system stability and suppress oscillatory behaviors.

Read PDF

Similar papers

Open access Sep 2026

Stability and Intelligent Control of a Fractional Predator–Prey System with Time Delay and Holling Type-III Functional Response

This paper presents an analytical and control model for a fractional-order delayed predator–prey system with a Holling Type-III functional response. In the model, Caputo fractional derivatives capture long-term memory and hereditary effects in population dynamics, while the finite-delay terms model gestation and enviro...

Dipesh, David Amilo, K. Sadri et al. · 0 citations
Open access Sep 2026

A Fractional Lotka–Volterra Predator–Prey Model with Strong Allee Effects, Nonlinear Harvesting, and Memory

This work develops a fractional Lotka–Volterra predator–prey model incorporating a strong Allee effect, nonlinear anthropogenic harvesting, and memory-dependent dynamics through the Atangana–Baleanu–Caputo (ABC) fractional operator. The model describes the interactions between two prey populations and a predator under...

M. I. Youssef, Munkaila Dasumani · 0 citations
Open access Sep 2026

Well-posedness, stability, and bifurcation of a fractional-order predator-prey model with fear and predator interference

We study a fractional-order predator-prey model with fear in predator interference and a non-monotonic functional response, formulated via the Caputo derivative. The fractional-order setting incorporates memory effects in the population dynamics and extends the corresponding integer-order system. We first prove well-po...

Seonguk Kim, Jung-Tae Park · 0 citations
Open access 2026

A stage structured predator–prey system with time delays and fear effect

Results indicate that stage structure coupled with dual maturation delays can significantly enrich the bifurcation structure and long-term dynamical behavior of the system.

Ling-Rui Li, Jun-Li Liu, Tai-Lei Zhang · 0 citations
Open access Sep 2026

Harvesting-induced bifurcation and memory-driven stability in a fractional-order predator-prey model with Beddington-DeAngelis functional response

This paper develops a fractional-order ecological model describing one prey and two predator species with harvesting, predator interference, and a Beddington-DeAngelis functional response. Caputo fractional derivatives are incorporated to capture memory effects in population dynamics. The model admits a biologically fe...

G. K. Edessa, Bhagya Laxmi Koyada, Shiva Reddy Konda et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.