Bifurcation Analysis of Food Chain with Release of Fear, Additional Food and Anti-predator Behavior for the Top Predator Species

Authors

DOI:

https://doi.org/10.30526/39.4.4416

Keywords:

food chain , bifurcation

Abstract

This paper investigates the bifurcation analysis of a three-species food chain model with a Holling type II functional response, focusing on the effect of fear and additional food on both middle and top predators, respectively, accompanied by the presence of anti-predatory behavior. The system boundedness had been proven, the existence of all the equilibrium under certain conditions examined, the local stability of the system’s equilibrium point demonstrated, and local and Hopf bifurcations have been proved with certain determinations according to specific parameters included in the food chain model. The theoretical results of the system were simulated numerically with phase diagrams to assure local stability at a specific set of the parameters' values with time series for the included populations. Furthermore, the system's bifurcations were verified around the interior equilibrium point during growth parameter versus prey population, creating saddle-node bifurcation, as well as top predator versus predation parameter through Hopf bifurcation. Finally, the conclusion presents the most important results and future recommendations that were submitted

Author Biographies

  • Saba Noori Majeed, Computer Department, College of Education for Women, University of Baghdad, Baghdad, Iraq.

    Computer Department - 

  • Rana Noori Majeed, Department of Mathematics, College of Education for Pure Science (Ibn Al Haitham), University of Baghdad, Baghdad, Iraq

    -

     

References

1. Nguyen T, Do T, Nguyen HT. Dynamical analysis of a stage-structured food-chain model under fear effect and anti-predator behavior. J Appl Math Comput. 2025;71:5867–5890. https://doi.org/10.1007/s12190-025-02451-x

2. Ramasamy S, Banjerdpongchai D, Park P. Stability and bifurcation analysis of delayed tri-trophic food chain model in poisoned environment with fear effect and additional food. Math Methods Appl Sci. 2023;48(7):1–28, https://doi.org/10.1002/mma.9330

3. Ogethakpo AJ, Ojobor SA. The Lotka–Volterra predator–prey model with disturbance. SSRN [Preprint]. 2021 https://doi.org/10.2139/ssrn.5503361.

4. Karjanto N, Sriraman B. Sustainability or otherwise: the lotka-volterra model in population ecology and socio-economic systems. bioRxiv [Preprint]. 2025. https://doi.org/10.1101/2025.05.01.651785

5. Majeed SJ, Dakhil RA. Three-species Lotka–Volterra food chain model with fear effect and hunting cooperation. Univ Thi-Qar J. 2023;18(1). https://doi.org/10.32792/utj.v18i1.328

6. Panja P, Jana S, Mondal SK. Effects of additional food on the dynamics of a three-species food chain model incorporating refuge and harvesting. Int J Nonlinear Sci Numer Simul. 2019;20: 787-801. https://doi.org/10.1515/ijnsns-2018-0313.

7. Chu J, Jin HY. Global dynamics of a three-species Lotka–Volterra food chain model with intraguild predation and taxis mechanisms. J Nonlinear Sci. 2025; 35:56 . https://doi.org/10.1007/s00332-025-10151-w.

8. Manaf ZIA, Zamri NZA, Izani NA, Norzan SNASM, Nor NM, Ramli WKHW. Bifurcation analysis of food chain dynamics with intraspecific competition in middle predators. In: Decision Mathematics, Statistical Learning and Data Mining Proceedings of ICMSCT. Singapore: Springer. 2024: 19–32. https://doi.org/10.1007/978-981-97-3450-4_2.

9. Therthar AA, Majeed SJ, Alqudah MA, Panja P, Abdeljawad T. Fear effect in a predator–prey model with additional food, prey refuge and harvesting on super predator. Chaos Solitons Fractals. 2022; 159:112091. https://doi.org/10.1016/j.chaos.2022.112091.

10. Xu X, Qiu Y, Chen X, Zhang H, Liang Z, Tian B. Bifurcation analysis of a food chain chemostat model with Michaelis–Menten functional response and double delays. AIMS Math. 2022;7(7):12154–12176. https://doi.org/10.3934/math.2022676.

11. Eskandari Z, Avazzadeh Z, Ghaziani RK, Li B. Dynamics and bifurcations of a discrete-time Lotka–Volterra model using nonstandard finite difference discretization method. Math Methods Appl Sci. 2022; 4 (7):7197–7212. https://doi.org/10.1002/mma.8859.

12. Saha S, Pal S, Melnik R. Analysis of the impact of fear in the presence of additional food and prey refuge with nonlocal predator–prey models. Ecological Modelling. 2025;505:111103. https://doi.org/10.1016/j.ecolmodel.2025.111103

13. Pal S, Tiwari PK, Misra AK, Wang H. Fear effect in a three-species food chain model with generalist predator. Math Biosci Eng. 2024;21(1):1–33. https://doi.org/10.3934/mbe.2024001.

14. Gunog S, DeAngelis DL. A predator–prey model with a Holling type I functional response including a predator mutual interference. J Nonlinear Sci. 2011; 21:811–833. https://doi.org/10.1007/s00332-011-9101-6.

15. Holling CS. The functional response of predators to prey density and its role in mimicry and population regulation. Mem Entomol Soc Can. 1965;97(S45):5–60. https://doi.org/10.4039/entm9745fv.

16. Sarkar M, Das T, Mukherjee RN. Bifurcation and stability of prey–predator model with Beddington–DeAngelis functional response. Appl Appl Math. 2017;12(1):350–366.

17. Lima SL. Stress and decision making under the risk of predation: Recent developments from behavioral, reproductive, and ecological perspectives. Adv Study Behav. 1998;27:215–290. https://doi.org/10.1016/S0065-3454(08)60366-6.

18. Tollrian R. Predator-induced morphological defenses: Costs, life history shifts, and maternal effects in Daphnia pulex. Ecology. 1995;76(6):1691-1705. https://doi.org/10.2307/1940703

19. Choh Y, Ignacio M, Sabelis MW, Janssen A. Predator–prey role reversals, juvenile experience and adult antipredator behavior. Sci Rep. 2012;2:728. https://doi.org/10.1038/srep00728.

20. Janssen A, Faraji F, van der Hammen T, Magalhaes S, Sabelis MW. Interspecific infanticide deters predators. Ecol Lett. 2002;5(4):490–494. https://doi.org/10.1046/j.1461-0248.2002.00349.x.

21. Saito Y. Prey kills predator: Counter-attack success of a spider mite against its specific phytoseiid predator. Exp Appl Acarol. 1986;2:47–62. https://doi.org/10.1007/BF01193354.

22. Kostov V. On Descartes’ Rule of signs for Hyperbolic Polynomials. Serdica Math. J. 2023; 49 (4):251-268. https://doi.org/10.55630/serdica.2023.49.251-268

23. Cai J, Pinto M, Xia Y. Stability and bifurcation analysis of a commensal model with Allee effect and herd behavior. Int J Bifurcat Chaos. 2022;32(14):2250217. https://doi.org/10.1142/S0218127422502170.

24. Majeed SN, Naji RK. Dynamical behavior of two predators–one prey ecological system with refuge and Beddington–DeAngelis functional response. Iraqi J Sci. 2023;64(12):6383–6400. https://doi.org/10.24996/ijs.2023.64.12.24.

25. Salihu A, Lawan A. A comparative study of 4th-order and 6th-stage 5th-order Runge–Kutta methods for solving autonomous differential equations. J Stat Sci Comput Intell. 2025;1(2):138–148. https://doi.org/10.64497/jssci.52.

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Published

20-Oct-2026

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Section

Mathematics

How to Cite

[1]
Majeed, S. and Majeed, R.N. 2026. Bifurcation Analysis of Food Chain with Release of Fear, Additional Food and Anti-predator Behavior for the Top Predator Species. Ibn AL-Haitham Journal For Pure and Applied Sciences. 39, 4 (Oct. 2026), 248–260. DOI:https://doi.org/10.30526/39.4.4416.