<p>In this paper, we investigate a tri-trophic eco-epidemiological model incorporating fear effect, multiple nonlinear functional responses, and top predator harvesting, where the disease only affects the intermediate predator population. The local stability of all equilibria are analyzed using the Routh-Hurwitz criterion, while the global stability of the interior equilibrium is studied through the Li-Muldowney geometric approach. Moreover, the system undergoes transcritical bifurcation, pitchfork bifurcation, and Hopf bifurcation, with the stability and direction criteria for bifurcating limit cycles being rigorously derived. We particularly focus on the chaotic dynamics induced by disease transmission and fear effect. As the infection rate increases, the system transitions from multiple high-period oscillations to chaotic states and then to high-period oscillations. And increasing the fear effect has a stabilizing effect on the system dynamics. Finally, the sensitivity analysis on solutions of the state variables with respect to the system parameters are performed.</p>

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Dynamics of a multi-trophic eco-epidemiological model incorporating fear effect, nonlinear functional response and harvesting

  • Xiaoli Pang,
  • Yuanhua Qiao

摘要

In this paper, we investigate a tri-trophic eco-epidemiological model incorporating fear effect, multiple nonlinear functional responses, and top predator harvesting, where the disease only affects the intermediate predator population. The local stability of all equilibria are analyzed using the Routh-Hurwitz criterion, while the global stability of the interior equilibrium is studied through the Li-Muldowney geometric approach. Moreover, the system undergoes transcritical bifurcation, pitchfork bifurcation, and Hopf bifurcation, with the stability and direction criteria for bifurcating limit cycles being rigorously derived. We particularly focus on the chaotic dynamics induced by disease transmission and fear effect. As the infection rate increases, the system transitions from multiple high-period oscillations to chaotic states and then to high-period oscillations. And increasing the fear effect has a stabilizing effect on the system dynamics. Finally, the sensitivity analysis on solutions of the state variables with respect to the system parameters are performed.