Deterministic Chaos vs. Stochastic Fluctuation in an Eco-epidemic Model
Mathematical modelling of natural phenomena, Tome 7 (2012) no. 3, pp. 99-116.

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An eco-epidemiological model of susceptible Tilapia fish, infected Tilapia fish and Pelicans is investigated by several author based upon the work initiated by Chattopadhyay and Bairagi (Ecol. Model., 136, 103–112, 2001). In this paper, we investigate the dynamics of the same model by considering different parameters involved with the model as bifurcation parameters in details. Considering the intrinsic growth rate of susceptible Tilapia fish as bifurcation parameter, we demonstrate the period doubling route to chaos. Next we consider the force of infection as bifurcation parameter and demonstrate the occurrence of two successive Hopf-bifurcations. We identify the existence of backward Hopf-bifurcation when the death rate of predators is considered as bifurcation parameter. Finally we construct a stochastic differential equation model corresponding to the deterministic model to understand the role of demographic stochasticity. Exhaustive numerical simulation of the stochastic model reveals the large amplitude fluctuation in the population of fish and Pelicans for certain parameter values. Extinction scenario for Pelicans is also captured from the stochastic model.
DOI : 10.1051/mmnp/20127308

P.S. Mandal 1 ; M. Banerjee 1

1 Department of Mathematics and Statistics Indian Institute of Technology, Kanpur Kanpur - 208016, INDIA
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P.S. Mandal; M. Banerjee. Deterministic Chaos vs. Stochastic Fluctuation in an Eco-epidemic Model. Mathematical modelling of natural phenomena, Tome 7 (2012) no. 3, pp. 99-116. doi : 10.1051/mmnp/20127308. http://geodesic.mathdoc.fr/articles/10.1051/mmnp/20127308/

[1] E. Allen. Modeling with Itô Stochastic Differential Equations. Springer, The Netherlands, 2007.

[2] L. J. S. Allen. An Introduction to Stochastic Processes with Applications to Biology. Pearson Eduction Inc., New Jercy, 2003.

[3] L. J. S. Allen, M. A. Jones, C. F. Martin Math. Biosci. 1991 111 131

[4] O. Arino, A. El. Abdllaoui, J. Mikram, J. Chattopadhyay Nonlinearity 2004 1101 1116

[5] E. J. Allen, L. J. S. Allen, A. Arciniega, P. Greenwood Stoch. Anal. Appl. 2008 274 297

[6] F. G. Ball Math. Biosci. 1999 41 67

[7] E. Beltrami, T. O. Carroll J. Math. Biol. 1994 857 863

[8] F. Brauer, C. Castillo-Chàvez. Mathematical Models in Population Biolgy and Epidemiology Springer-Verlag, New York, 2001.

[9] T. Britton Math. Biosci. 2010 24 35

[10] T. Britton, D. Lindenstrand Math. Biosci. 2009 109 116

[11] J. Chattopadhyay, N. Bairagi Ecol. Model. 2001 103 112

[12] M. S. Chan, V. S. Isham Math. Biosci. 1998 179 198

[13] H. I. Freedman Math. Biosci. 1990 143 155

[14] T. C. Gard. Introduction to Stochastic Differential Equations. Marcel Decker, New York, 1987.

[15] C. W. Gardiner. Handbook of Stochastic Methods. Springer-Verlag, New York, 1983.

[16] D. T. Gillespie J. Comp. Phy. 1976 403 434

[17] D. T. Gillespie J. Chem. Phy. 2000 297 306

[18] N. S. Goel, N. Richter-Dyn. Stochastic Models in Biology. Academic Press, New York, 1974.

[19] D. Greenhalgh, M. Griffiths J. Math. Biol. 2009 1 36

[20] K. P. Hadeler, H. I. Freedman J. Math. Biol. 1989 609 631

[21] M. Haque, D. Greenhalgh M2AS 2006 911 929

[22] D. J. Higham SIAM Rev. 2001 525 546

[23] W. O. Kermack, A. G. Mckendrick Proc. Roy. Soc. Lond. A. 1927 700 721

[24] P. E. Kloeden, E. Platen. Numerical Solution of Stochastic Differential Equations. Springer, Berlin, 1999.

[25] M. Kot. Elements of Mathematical Biology. Cambridge University Press, Cambridge, 2001.

[26] Y. A. Kuznetsov. Elements of Applied Bifurcation Theory. Springer, Berlin, 1997.

[27] A. J. Lotka. Elements of physical biology. Williams Wilkins Co., Baltimore, 1925.

[28] J. Marsden, M. McCracken. The Hopf Bifurcation and its Applications. Springer, New York, 1976.

[29] H. Malchow, S. V. Petrovskii, E. Venturino. Spatiotemporal Patterns in Ecology and Epidemiology : Theory, Models and Simulations. Chapman Hall, London, 2008.

[30] J. D. Murray. Mathematical Biology. Springer, New York, 1993.

[31] R. J. Serfling. Approximation Theorems of Mathematical Statistics. John Wiley Sons, New York, 1980.

[32] D. Stiefs, E. Venturino, U. Feudel Math. Biosci. Eng. 2009 857 873

[33] R. K. Upadhyay, N. Bairagi, K. Kundu, J. Chattopadhyay Appl. Math. Comput. 2008 392 401

[34] E. Venturino Rocky Mountain Journal of Mathematics. 1994 381 402

[35] E. Venturino. Epidemics in predator-prey models : disease in the prey, In ‘Mathematical Population Dynamics, Analysis of Heterogeneity’. 1, O. Arino, D. Axelrod, M. Kimmel, M. Langlais (Eds), Wnertz Publisher Ltd, Canada, 381–393, 1995.

[36] V. Volterra. Variazioni e fluttuazioni del numero d’individui in specie animali conviventi. 2. Mem. R. Accad. Naz. dei Lincei. Ser. VI, 1926.

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