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Bazykin’s Predator–Prey Model Includes a Dynamical Analysis of a Caputo Fractional Order Delay Fear and the Effect of the Population-Based Mortality Rate on the Growth of Predators

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Abstract

In this paper, we investigate a system of two differential equations of fractional order for the fear effect in prey-predator interactions, in which the density of predators controls the mortality pace of the prey population. The non-integer order differential equation is interpreted in terms of the Caputo derivative, and the development of the non-integer order scheme is described in terms of the influence of memory on population increase. The primary goal of existing research is to explore how the changing aspects of the current scheme are impacted by various types of parameters, including time delay, fear effect, and fractional order. The solutions’ positivity, existence-uniqueness, and boundedness are established with precise mathematical conclusions. The requirements necessary for the local asymptotic stability of different equilibrium points and the global stability of coexistence equilibrium are established. Hopf bifurcation occurs in the system at various delay times. The model’s fractional-order derivatives enhance the model behaviours and provide stability findings for the solutions. We have observed that fractional order plays an important role in population dynamics. Also, Hopf bifurcation for the proposed system have been observed for certain values of order of derivatives. Thus, the stability conditions of the equilibrium points may be changed by changing the order of the derivatives without changing other parametric values. Finally, a numerical simulation is run to verify our conclusions.

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References

  1. Lotka, A.: Elements of Physical Biology. Williams and Wilkins, Baltimore (1925)

    Google Scholar 

  2. Volterra, V.: Variazioni e fluttuazioni del numero di individui in specie animali conviventi. Mem. Acad. Lincei. 2, 31–113 (1926)

    Google Scholar 

  3. Berryman, A.A.: The origins and evolution of predator-prey theory. Ecology 73, 1530–1535 (1992)

    Google Scholar 

  4. Hassel, M.: The Dynamics of Arthropod Predator-Prey Systems. Princeton University Press, Princeton (1978)

    Google Scholar 

  5. Creel, S., Christianson, D.: Relationships between direct predation and risk effects. Trends Ecol. Evol. 23(4), 194–201 (2008)

    Google Scholar 

  6. Cresswell, W.: Non-lethal effects of predation in birds. Ibis 150(1), 3–17 (2008)

    Google Scholar 

  7. Holt, R.H., Davies, Z.G., Staddon, S.: Meta-analysis of the effects of predation on animal prey abundance: evidence from UK vertebrates. PLoS ONE 3(6), 1–8 (2008)

    Google Scholar 

  8. Zanette, L.Y., Clinchy, M.: Perceived predation risk reduces the number of off-spring songbirds produce per year. Science 334(6061), 1398–1401 (2011)

    Google Scholar 

  9. Wang, X., Zanette, L., Zou, X.: Modelling the fear effect in predator-prey interactions. J. Math. Biol. 73(5), 1–26 (2016)

    MathSciNet  Google Scholar 

  10. Wang, X., Zou, X.: Modeling the fear effect in predator-prey interactions with adaptive avoidance of predators. Bull. Math. Biol. 79(6), 1–35 (2017)

    MathSciNet  Google Scholar 

  11. Sasmal, S.: Population dynamics with multiple Allee effects induced by fear factors - a mathematical study on prey-predator. Appl. Math. Model. 64, 1–14 (2018)

    MathSciNet  Google Scholar 

  12. Mondal, S., Maiti, A., Samanta, G.P.: Effects of fear and additional food in a delayed predator-prey model. Biophys. Rev. Lett. 13(4), 157–177 (2018)

    Google Scholar 

  13. Mukherjee, D.: Study of fear mechanism in predator-prey system in the presence of competitor for the prey. Ecol. Genet. Genom. 15, 1–22 (2020)

    Google Scholar 

  14. McCauley, S.J., Rowe, L., Fortin, M.J.: The deadly effects of “nonlethal” predators. Ecology 92, 2043–2048 (2011)

    Google Scholar 

  15. Siepielski, A.M., Wang, J., Prince, G.: Non-consumptive predator-driven mortality causes natural selection on prey. Evolution 68(3), 696–704 (2014)

    Google Scholar 

  16. Mukherjee, D.: Role of fear in predator–prey system with intraspecific competition. Math. Comput. Simul 177, 263–275 (2020)

    MathSciNet  Google Scholar 

  17. Meng, X., Jiao, J., Chen, L.: The dynamics of an age structured predator–prey model with disturbing pulse and time delays. Nonlinear Anal. Real World Appl. 9(2), 547–561 (2008)

    MathSciNet  Google Scholar 

  18. Xia, Y., Cao, J., Cheng, S.: Multiple periodic solutions of a delayed stage-structured predator–prey model with nonmonotone functional responses. Appl. Math. Model. 31(9), 1947–1959 (2007)

    Google Scholar 

  19. Zhang, J.F.: Bifurcation analysis of a modified Holling-Tanner predator–prey model with time delay. Appl. Math. Model. 36(3), 1219–1231 (2012)

    MathSciNet  Google Scholar 

  20. Javidi, M., Nyamoradi, N.: Dynamic analysis of a fractional order prey–predator interaction with harvesting. Appl. Math. Model. 37, 8946–8956 (2013)

    MathSciNet  Google Scholar 

  21. Rivero, M., Trujillo, J., Vazquez, L., Velasco, M.: Fractional dynamics of populations. Appl. Math. Comput. 218(3), 1089–1095 (2011)

    MathSciNet  Google Scholar 

  22. El-Sayed, A., El-Mesiry, A.E.M., El-Saka, H.A.A.: On the fractional order logistic equation. Appl. Math. Lett. 20(7), 817–823 (2007)

    MathSciNet  Google Scholar 

  23. Rihan, F.A., Abdel Rahman, D.H.: Delay differential model for tumor-immune dynamics with HIV infection of CD+t-cells. Int. J. Comput. Math. 90(3), 594–614 (2013)

    MathSciNet  Google Scholar 

  24. Debnath, L.: Recent applications of fractional calculus to science and engineering. Int. J. Math. Math. Sci. 54, 3413–3442 (2003)

    MathSciNet  Google Scholar 

  25. Machado, J.: Entropy analysis of integer and fractional dynamical systems. Non-linear Dyn. 62(1), 371–378 (2010)

    MathSciNet  Google Scholar 

  26. Caputo, M.: Linear models of dissipation whose q is almost frequency independent-II. Geophys. J. R. Astron. Soc. 13(5), 529–539 (1967)

    Google Scholar 

  27. Ghaziani, R., Alidousti, J., Eshkaftaki, A.B.: Stability and dynamics of a fractional order Leslie-Gower prey-predator model. Appl. Math. Model. 40(3), 2075–2086 (2016)

    MathSciNet  Google Scholar 

  28. Matouk, A.E., Elsadany, A.A.: Dynamical analysis, stabilization and discretization of a chaotic fractional-order GLV model. Nonlinear Dyn. 85(3), 1597–1612 (2016)

    MathSciNet  Google Scholar 

  29. Moustafa, M., Mohd, M.H., Ismail, A.I.: Dynamical analysis of a fractional-order Rosenzweig-Macarthur model incorporating a prey refuge. Chaos Solitons Fractals 109, 1–13 (2018)

    MathSciNet  Google Scholar 

  30. Das, M., Samanta, G.P.: A prey-predator fractional order model with fear effect and group defense. Int. J. Dyn. Control. 9, 334–349 (2020)

    MathSciNet  Google Scholar 

  31. McGehee, E.A., Schutt, N., Vasquez, D.A., Peacock-Lopez, E.: Bifurcations and temporal and spatial patterns of a modified Lotka-Volterra model. Int. J. Bif. Chaos. 18(8), 2223–2248 (2008)

    MathSciNet  Google Scholar 

  32. Kot, M.: Elements of Mathematical Biology. Cambridge University Press, New York (2001)

    Google Scholar 

  33. Bazykin, A. D.: Volterra system and Michaelis-Menten equation in: voprosy matematich-eskoi genetiki. Nauka Novosibirsk Russia; 103–43 (1974)

  34. Bazykin, A.D., Khibnik, A.I., Krauskopf, B.: Nonlinear Dynamics of Interacting Populations. World Scientific Publishing, Singapore (1998)

    Google Scholar 

  35. Podlubny, I.: Fractional Differential Equations. Academic Press, New York (1993)

    Google Scholar 

  36. Xiao, M., Jiang, G., Cao, J., Zheng, W.: Local bifurcation analysis of a delayed fractional-order dynamic model of dual congestion control algorithms. IEEE/CAA J. Autom. Sin. 4, 361–369 (2017)

    MathSciNet  Google Scholar 

  37. Deng, W., Li, C., Lu, J.: Stability analysis of linear fractional differential system with multiple time delays. Nonlinear Dyn. 48, 409–416 (2007)

    MathSciNet  Google Scholar 

  38. Li, C., Zhang, F.: A survey on the stability of fractional differential equations. Eur. Phys. J. Spec. Top. 193, 27–47 (2011)

    Google Scholar 

  39. Muth, E.: Transform Methods with Applications to Engineering and Operations Research. Prentice-Hall, New Jersey (1977)

    Google Scholar 

  40. Khan, A., Alshehri, H.M., Gómez-Aguilar, J.F., Khan, Z.A., Fernández-Anaya, G.: A predator–prey model involving variable-order fractional differential equations with Mittag-Leffler kernel. Adv. Differ. Equ. 183, 1–18 (2021)

    MathSciNet  Google Scholar 

  41. Devi, A., Kumar, A., Baleanu, D., Khan, A.: On stability analysis and existence of positive solutions for a general non-linear fractional differential equation. Adv. Differ. Equ. 300, 1–16 (2020)

    MathSciNet  Google Scholar 

  42. Venkatesan, G., Sivaraj, P., Suresh Kumar, P., Balachandran, K.: Asymptotic stability of fractional Langevin systems. J. Appl. Nonlinear Dyn. 11(03), 635–650 (2022)

    MathSciNet  Google Scholar 

  43. Poovarasan, R., Kumar, P., Nisar, K.S., Govindaraj, V.: The existence, uniqueness, and stability analyses of the generalized Caputo-type fractional boundary value problems. AIMS Math. 8(7), 16757–16772 (2023)

    MathSciNet  Google Scholar 

  44. Sene, N.: Fundamental results about the fractional integro-differential equation described with Caputo derivative. Adv. Nonlinear Anal. Appl. 2022, 1–10 (2022)

    Google Scholar 

  45. Thomas, E.: Applied Delay Differential Equations. Springer, New York (2009)

    Google Scholar 

  46. Das, M., Maiti, A., Samanta, G.P.: Stability analysis of a prey-predator fractional order model incorporating prey refuge. Ecol. Genet. Genom. 7–8, 33–46 (2018)

    Google Scholar 

  47. Das, M., Samanta, G.P.: A delayed fractional order food chain model with fear effect and prey refuge. Math. Comput. Simul 178, 218–245 (2020)

    MathSciNet  Google Scholar 

  48. Das, M., Samanta, G.P.: Evolutionary dynamics of a competitive fractional order model under the influence of toxic substances. SeMA 78, 595–621 (2021)

    MathSciNet  Google Scholar 

  49. Samanta, G.: Deterministic, Stochastic and Thermodynamic Modelling of Some Interacting Species. Springer, Singapore (2021)

    Google Scholar 

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Acknowledgements

The authors are grateful to all the reviewers for their careful reading, valuable comments and helpful suggestions, which have helped us to improve the presentation of this work significantly. Also, the authors Aziz Khan and Thabet Abdeljawad would like to thank Prince Sultan University, Saudi Arabia for paying the APC and the support through TAS research lab.

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All authors contributed equally and significantly in writing this paper and typed, read, and approved the final manuscript.

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Correspondence to K. Ramesh or Thabet Abdeljawad.

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Kumar, G.R., Ramesh, K., Khan, A. et al. Bazykin’s Predator–Prey Model Includes a Dynamical Analysis of a Caputo Fractional Order Delay Fear and the Effect of the Population-Based Mortality Rate on the Growth of Predators. Qual. Theory Dyn. Syst. 23, 130 (2024). https://doi.org/10.1007/s12346-024-00981-6

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