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Dynamical behaviour of a delayed three species predator–prey model with cooperation among the prey species

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Abstract

In this paper we have discussed about the dynamics of three species (two preys and one predator) delayed predator–prey model with cooperation among the preys against predation. We accept that the rate of change of density of population relies on the growth, death and in addition intra-species competition for the predators. The growth rate for preys is thought to be logistic. Delays are taken just in the growth components for each of the species. With this model we have demonstrated that the system has permanence. Taking the delays as the bifurcation parameter, the stability of the interior equilibrium point has been discussed analytically and numerically. Critical value of the delay is obtained where the Hopf-bifurcation happens. In presence of delay by constructing a Lyapunov function local asymptotic stability of the positive equilibrium point is discussed.

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References

  1. Alfred, J.: Lotka, elements of physical biology (baltimore: Williams and wilkins,); vito volterra. Variazioni e fluttuazioni del numero dindividui in specie animali conviventi (1925)

  2. Arino, J., Wang, L., Wolkowicz, G.S.: An alternative formulation for a delayed logistic equation. J. Theor. Biol. 241(1), 109–119 (2006)

    Article  MathSciNet  Google Scholar 

  3. Begon, M., Harper, J.L., Townsend, C.R., et al.: Ecology. Individuals, Populations and Communities. Blackwell, New York (1986)

    Google Scholar 

  4. Castro, R., Sierra, W., Stange, E.: Bifurcations in a predator–prey model with general logistic growth and exponential fading memory. Appl. Math. Model. 45, 134–147 (2017)

    Article  MathSciNet  Google Scholar 

  5. Chen, F.: The permanence and global attractivity of Lotka–Volterra competition system with feedback controls. Nonlinear Anal. Real World Appl. 7(1), 133–143 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  6. Chen, F.: Permanence of a discrete n-species food-chain system with time delays. Appl. Math. Comput. 185(1), 719–726 (2007)

    MathSciNet  MATH  Google Scholar 

  7. Chen, F., You, M.: Permanence for an integrodifferential model of mutualism. Appl. Math. Comput. 186(1), 30–34 (2007)

    MathSciNet  MATH  Google Scholar 

  8. Choudhury, S.R.: On bifurcations and chaos in predator–prey models with delay. Chaos Solitons Fractals 2(4), 393–409 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  9. Dhar, J., Jatav, K.S.: Mathematical analysis of a delayed stage-structured predator–prey model with impulsive diffusion between two predators territories. Ecol. Complex. 16, 59–67 (2013)

    Article  Google Scholar 

  10. Elettreby, M.: Two-prey one-predator model. Chaos Solitons Fractals 39(5), 2018–2027 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  11. Fan, Y.H., Li, W.T.: Permanence for a delayed discrete ratio-dependent predator–prey system with holling type functional response. J. Math. Anal. Appl. 299(2), 357–374 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  12. Goh, B.: Stability in models of mutualism. Am. Nat. 113(2), 261–275 (1979)

    Article  MathSciNet  Google Scholar 

  13. Greenhalgh, D., Khan, Q.J., Pettigrew, J.S.: An eco-epidemiological predator–prey model where predators distinguish between susceptible and infected prey. Math. Methods Appl. Sci. 40(1), 146–166 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  14. Hou, Z.: On permanence of Lotka–Volterra systems with delays and variable intrinsic growth rates. Nonlinear Anal. Real World Appl. 14(2), 960–975 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  15. Hu, H., Teng, Z., Jiang, H.: On the permanence in non-autonomous Lotka–Volterra competitive system with pure-delays and feedback controls. Nonlinear Anal. Real World Appl. 10(3), 1803–1815 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  16. Hugie, D.M.: Applications of Evolutionary Game Theory to the Study of Predator–Prey Interactions. Simon Fraser University, Burnaby (1999)

    Google Scholar 

  17. Hutchinson, G.E.: Circular causal systems in ecology. Ann. N. Y. Acad. Sci. 50(4), 221–246 (1948)

    Article  Google Scholar 

  18. Keshet, E.L.: Mathematical Models in Biology. McGraw-Hill, New York (1988)

    MATH  Google Scholar 

  19. Kingsland, S.: The refractory model: the logistic curve and the history of population ecology. Q. Rev. Biol. 57(1), 29–52 (1982)

    Article  Google Scholar 

  20. Kot, M.: Elements of Mathematical Ecology. Cambridge University Press, Cambridge (2001)

    Book  MATH  Google Scholar 

  21. Kundu, S., Maitra, S.: Stability and delay in a three species predator–prey system. In: AIP Conference Proceedings, vol. 1751, p. 020004. AIP Publishing (2016)

  22. Kuniya, T., Nakata, Y.: Permanence and extinction for a nonautonomous seirs epidemic model. Appl. Math. Comput. 218(18), 9321–9331 (2012)

    MathSciNet  MATH  Google Scholar 

  23. Li, C.H., Tsai, C.C., Yang, S.Y.: Analysis of the permanence of an sir epidemic model with logistic process and distributed time delay. Commun. Nonlinear Sci. Numer. Simul. 17(9), 3696–3707 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  24. Liao, X., Zhou, S., Chen, Y.: Permanence and global stability in a discrete n-species competition system with feedback controls. Nonlinear Ana. Real World Appl. 9(4), 1661–1671 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  25. Liu, M., Bai, C.: Optimal harvesting of a stochastic mutualism model with Lévy jumps. Appl. Math. Comput. 276, 301–309 (2016)

    MathSciNet  Google Scholar 

  26. Liu, S., Chen, L.: Necessary-sufficient conditions for permanence and extinction in Lotka–Volterra system with distributed delays. Appl. Math. Lett. 16(6), 911–917 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  27. Lynch, S.: Dynamical Systems with Applications Using MATLAB. Springer, Berlin (2004)

    Book  MATH  Google Scholar 

  28. Ma, J., Zhang, Q., Gao, Q.: Stability of a three-species symbiosis model with delays. Nonlinear Dyn. 67(1), 567–572 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  29. MacLean, M., Willard, A.: The logistic curve applied to Canada’s population. Can. J. Econ. Polit. Sci. 3(02), 241–248 (1937)

    Article  Google Scholar 

  30. Muroya, Y.: Permanence and global stability in a Lotka–Volterra predator–prey system with delays. Appl. Math. Lett. 16(8), 1245–1250 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  31. Pearl, R., Reed, L.J.: The logistic curve and the census count of i930. Science 72(1868), 399–401 (1930)

    Article  Google Scholar 

  32. Saha, T., Bandyopadhyay, M.: Dynamical analysis of a delayed ratio-dependent prey–predator model within fluctuating environment. Appl. Math. Comput. 196(1), 458–478 (2008)

    MathSciNet  MATH  Google Scholar 

  33. Teng, Z., Zhang, Y., Gao, S.: Permanence criteria for general delayed discrete nonautonomous n-species kolmogorov systems and its applications. Comput. Math. Appl. 59(2), 812–828 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  34. Verhulst, P.F.: Notice sur la loi que la population suit dans son accroissement. Correspondance mathématique et physique publiée par a. Quetelet 10, 113–121 (1838)

    Google Scholar 

  35. Xu, C., Wu, Y.: Dynamics in a Lotka–Volterra predator–prey model with time-varying delays. In: McKibben, M. (ed.) Abstract and Applied Analysis, vol. 2013. Hindawi Publishing Corporation, Cairo, Egypt (2013). https://doi.org/10.1155/2013/956703

    Google Scholar 

  36. Zhao, J., Jiang, J.: Average conditions for permanence and extinction in nonautonomous Lotka–Volterra system. J. Math. Anal. Appl. 299(2), 663–675 (2004)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

We thank the anonymous referee for valuable suggestions. The first author is thankful to DST, New Delhi, India, for its financial support under INSPIRE fellowship, without which this research would not have been possible.

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Correspondence to Soumen Kundu.

Appendix

Appendix

$$\begin{aligned} L= & {} \frac{1}{x^*}, M=\frac{1}{y^*}, N=\frac{1}{z^*}\\ k_1= & {} \frac{1}{2l_1K_1L}+\left( c_2L+l_1c_2\tau _1\right. \\&+\,\frac{c_1c_2\tau _3+2c_2^2\tau _3+2c_2c_3\tau _3}{2} +\frac{a_1c_2\tau _1}{2}\\&+\,\frac{a_2L}{N}+\frac{l_2c_2\tau _1 K_2}{2K_1}+\frac{bc_2\tau _3}{2}+\frac{l_1c_3\tau _3}{2}\\&+\,\frac{a_2c_2\tau _3}{2L}+\frac{a_2c_2\tau _3}{2M}\\&\left. +\,\frac{2a_2c_2\tau _3}{N}+\frac{a_2c_3\tau _3}{2N}\right) \Big /\left( 2l_1L\left( -a_1N\right. \right. \\&-\,bN+\frac{a_2N}{L}+\frac{a_2N}{M}+\frac{a_1c_2\tau _3}{2}\\&+\,\frac{bc_2\tau _3}{2}+\frac{a_1c_2\tau _3}{2}+\frac{bc_3\tau _3}{2}+\frac{a_2c_2\tau _3}{2L}\\&+\,\frac{a_2c_3\tau _3}{2L}+\frac{a_2c_2\tau _3}{2M}+\frac{a_2c_3\tau _3}{2M}\\&\left. \left. +\,\frac{-2c_1N+c_1c_2\tau _3+c_1c_3\tau _3}{2}\right) \right) ,\\ k_2= & {} \frac{1}{2l_2K_2M}+\left( c_3M+l_2c_2\tau _2\right. \\&+\,\frac{c_1c_3\tau _3+2c_3^2\tau _3+2c_2c_3\tau _3}{2}+\frac{bc_3\tau _2}{2}\\&+\,\frac{a_2L}{N}+\frac{l_2c_3\tau _2 K_2}{2K_1}+\frac{bc_3\tau _3}{2}\\ \end{aligned}$$
$$\begin{aligned}&+\,\frac{l_2c_3\tau _3}{2}+\frac{a_2c_2\tau _3}{2L}+\frac{a_2c_3\tau _3}{2M}\\&\left. +\,\frac{2a_2c_3\tau _3}{N}+\frac{a_2c_3\tau _3}{2N}\right) \Big /(2l_1L(-a_1N-bN\\&+\,\frac{a_2N}{L}+\frac{a_2N}{M}+\frac{a_1c_2\tau _3}{2}+\frac{bc_2\tau _3}{2}\\&+\,\frac{a_1c_2\tau _3}{2}+\frac{bc_3\tau _3}{2}+\frac{a_2c_2\tau _3}{2L}\\&+\,\frac{a_2c_3\tau _3}{2L}+\frac{a_2c_2\tau _3}{2M}+\frac{a_2c_3\tau _3}{2M}\\&+\,\frac{-2c_1N+c_1c_2\tau _3+c_1c_3\tau _3}{2}\Bigg )\Bigg ),\\ k_3= & {} c_3N+\frac{a_2N}{M}+\frac{bc_2\tau _3}{2}+\frac{a_1c_3\tau _1}{2}\\&+\,\frac{a_2c_3\tau _2}{2}+bc_3\tau _3+\frac{bc_3\tau _2}{2}+\frac{a_2c_3\tau _1}{2M}\\&+\,\frac{a_2c_3\tau _3}{2L}+\frac{a_2c_3\tau _3}{2M}\\&+\,\frac{3a_2c_3\tau _3}{2L}+\frac{1}{2}(2c_2c_3\tau _3\\&+\,2c_3^2\tau _3\Bigg )\Big /\left( -a_1N-bN+\frac{a_2N}{L}\right. \\&+\,\frac{a_2N}{M}+\frac{a_1c_2\tau _3}{2}+\frac{bc_2\tau _3}{2}\\&+\,\frac{a_1c_2\tau _3}{2}+\frac{bc_3\tau _3}{2}+\frac{a_2c_2\tau _3}{2L}\\&+\,\frac{a_2c_3\tau _3}{2L}+\frac{a_2c_2\tau _3}{2M}+\frac{a_2c_3\tau _3}{2M}\\&+\,\frac{-2c_1N+c_1c_2\tau _3+c_1c_3\tau _3}{2}\Bigg ),\\ \end{aligned}$$
$$\begin{aligned} k_4= & {} k_5=k_6=1/\left( -a_1N-bN\right. \\&+\,\frac{a_2N}{L}+\frac{a_2N}{M}\\&+\,\frac{a_1c_2\tau _3}{2}+\frac{bc_2\tau _3}{2}+\frac{a_1c_2\tau _3}{2}\\&+\,\frac{bc_3\tau _3}{2}+\frac{a_2c_2\tau _3}{2L}+\frac{a_2c_3\tau _3}{2L}\\&+\,\frac{a_2c_2\tau _3}{2M}+\frac{a_2c_3\tau _3}{2M}\\&+\,\frac{-2c_1N+c_1c_2\tau _3+c_1c_3\tau _3}{2}\Bigg ),\\ \varLambda _1= & {} k_1\frac{l_1}{K_1}\left( -\frac{2}{x^*}+\frac{2l_1 \tau _1}{K_1}\right. \\&\left. +\,a_1 \tau _1-a_2 y^* \tau _1-a_2 z^* \tau _1\right) -k_2 \frac{l_2 a_2 z^* \tau _2}{K_2}\\&+\,k_3 \Bigg (2c_2^2\tau _3+2c_2 c_3 \tau _3-c_1 c_2 \tau _3\Bigg )+k_4\left[ \frac{c_2}{x^*}\right. \\&+\,\frac{a_2 c_2 z^*\tau _1}{2}-\frac{a_1c_2\tau _1}{2}+\frac{a_2c_2y^* \tau _1}{2}\\&-\,\frac{l_1}{K_1}\Bigg (-c_2 \tau _1+\frac{c_3 \tau _3}{2}\\&+\,\frac{c_3 \tau _1}{2}\left. -\frac{c_1 \tau _1}{2}+\frac{c_2 \tau _1}{2}\Bigg )\right] \\ \end{aligned}$$
$$\begin{aligned}&+\,k_5\left[ \frac{a_2 z^*}{x^*}+\frac{l_1 l_2}{K_1 K_2}\Bigg (\frac{\tau _2}{2}+\frac{\tau _1}{2}\Bigg )\right. \\&\left. -\,\frac{l_1}{2K_1}(2a_2 \tau _1 z^*-b\tau _1+a_2x^*\tau _1\Bigg )\right] \\&+\,k_6\left[ a_2c_2z^*\tau _3+\frac{a_2c_33z^*\tau _2}{2}-\frac{c_2l_2\tau _2}{2K_2}\right. \\&\left. +\,\frac{a_2c_2x^*\tau _3}{2}-\frac{bc_2\tau _3}{2}-\frac{l_2c_2\tau _3}{2K_2}\right] ,\\ \varLambda _2= & {} k_1\frac{-l_1 a_2z^*\tau _1}{K_1}+k_2\frac{l_2}{K_2}\left( -\frac{-2}{y^*}\right. \\&\left. +\,\frac{2l_2 \tau _2}{K_2}+b\tau _2-a_2\tau _2z^*-a_22\tau _2x^*\right) \\&+\,k_3\Bigg (2c_3^2\tau _3+2c_2c_3\tau _3-c_1c_3\tau _3\Bigg )\\&+k_4\Bigg (\frac{a_2c_2z^*\tau _1}{2}-\,\frac{c_3l_1\tau _1}{2K_1}+\frac{a_3c_3z^*\tau _3}{2}\\&+\frac{a_2c_3z^*\tau _3}{2}-\,\frac{l_1c_3\tau _3}{2K_1}+\frac{a_2c_3y^*\tau _3}{2}-\frac{a_1c_3\tau _3}{2}\Bigg )\\&+\,k_5\left[ \frac{a_2z^*}{y^*}+\frac{l_1l_2}{K_1K_2}\left( \frac{\tau _1+\tau _2}{2}\right) \right. \\&\left. -\,\frac{l_2}{2K_2}\left( a_2\tau _2 z^*-a_1\tau _2-\,a_2\tau _2y^*-a_1\tau _2z^*\right) \right] \\&+\,k_6\left[ \frac{c_3}{y^*}+\frac{a_2c_3\tau _2z^*}{2}\right. \\&+\,\frac{a_2c_3\tau _2x^*}{2}-\frac{bc_3\tau _2}{2}\\&\left. -\,\frac{l_2}{2K_2}(c_2\tau _3+4c_3\tau _2+c_2\tau _2-c_1\tau _2)\right] ,\\ \varLambda _3= & {} k_1\frac{l_1}{K_1}(a_1\tau _1-a_2y^*\tau _1)+\,k_2\frac{l_2}{K_2}(b\tau _2-a_2x^*\tau _2)\\&+\,k_3\left( -\frac{2c_1}{z^*}-c_1c_2\tau _3-c_1c_3\tau _3\right) \\&+\,k_4\Bigg (\frac{a_2y^*}{z^*}-\frac{a_1}{z^*}+\frac{c_1l_1\tau _1}{2K_1}-\,\frac{a_1c_2\tau _1}{2}\\&+\frac{a_2c_2y^*\tau _1}{2}+\,\frac{a_2c_3y^*\tau _3}{2}-\frac{a_1c_3\tau _3}{2}\Bigg )\\&+\,k_5\left[ \frac{l_1}{2K_1}(b\tau _1-a_2\tau _1x^*)\right. \\&\left. +\,\frac{l_2}{2K_2}(a_1\tau _2-a_2\tau _2y^*)\right] \\&+\,k_6\Bigg [\frac{a_2x^*-b}{z^*}+\frac{a_2c_2\tau _3x^*}{2}\\&-\,\frac{bc_2\tau _3}{2}+\frac{a_2c_3\tau _2x^*}{2}+\,\frac{c_1l_2\tau _2}{2K_2}-\frac{bc_3\tau _2}{2}\Bigg ]. \end{aligned}$$

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Kundu, S., Maitra, S. Dynamical behaviour of a delayed three species predator–prey model with cooperation among the prey species. Nonlinear Dyn 92, 627–643 (2018). https://doi.org/10.1007/s11071-018-4079-3

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