Chaos Control of a Delayed Tri-Trophic Food Chain Model with Fear and Its Carry Over Effects

Abstract

One of the main objectives of theoretical ecologists involves finding mechanisms to control the chaos in ecological models to maintain positive densities of the species. Numerous researchers have suggested that, apart from the direct killing in the prey–predator relationship, there are some indirect effects, such as fear of predation. Induced fear can lead to slowing down the growth rate of the prey species, and this non-chemical strategy can be carried over to successive seasons or upcoming generations. In this work, we explore the impact of fear due to predation and its carry-over effect (COE) in a delayed tri-trophic food chain model, whereas the Holling type-II functional response is used to determine the interference among the species. The proposed model is an asymmetric interaction food chain model since the species in this model only kills other species. The growth rate of prey and middle predators is affected due to the respective fear of predation by middle and special predators. The non-delayed model considered in this paper generalizes the models developed by Hastings–Powell and Panday et al. The gestation delay in the special predator’s growth term is incorporated into the proposed model. We determined the essential conditions for the existence of ecologically feasible equilibrium points and their local and global stability. Furthermore, we developed the conditions for the occurrence of the Hopf bifurcation around an interior equilibrium to seek periodic behaviors of delayed and non-delayed models. Numerical examples were performed to justify the proposed theoretical findings and to show the impacts of fear and its COE parameters on the system dynamics through phase portraits, the time series of solutions, and bifurcation diagrams. We discovered that the chaotic behavior of the food chain model can be controlled by using the fear effect and its COE parameters. The dynamics of the delayed food chain model with the fear effect and its COEs are further explored in our findings. Our theoretical findings clearly provide a mechanism to protect and control species populations in ecological systems. It is also essential for developing optimized harvesting strategies in fisheries and pest management in agriculture.

Complex Dynamics Analysis and Chaos Control of a Fractional-Order Three-Population Food Chain Model

“…Finally, the numerical simulation is conducted to validate the theoretical analysis. This study extends the work previously conducted by Ramasamy et al [1].…”

“…Moreover, arg(λ 1 ) = π > απ 2 and |arg(λ 2,3 )| = 1.0933 > απ 2 for α < 0.6960. According to Theorem 2, the equilibrium point E 3 = (0.8192, 1 8 , 9.8075) is stable for α < 0.9269.…”

“…The rest of the parameters are selected from Equation ( 6) when the fear-related terms are selected in the proposition. The equilibrium point E 3 = (0.7824, 1 8 , 9.6090), and the characteristic equation at E 3 is given below:…”

“…The study of population models remains a prominent area of research [1,2]. Various mathematical models have been proposed to investigate the dynamic behavior of populations, encompassing ordinary differential equation models, partial differential equation models [3], fractional differential equation models [4][5][6][7], stochastic models [8], models with time delays [9], models with state feedback control [10], network models [11], and more.…”