Skip to main content
Log in

On some Markov models of certain interacting populations

  • Published:
Bulletin of Mathematical Biology Aims and scope Submit manuscript

Abstract

We give a stochastic foundation to the Volterra prey-predator population in the following case. We take Volterra's predator equations and let a free host birth and death process support the evolution of the predator population. The purpose of this article is to present a rigorous population sample path construction of this interacted predator process and study the properties of this interacted process. The constructions yields a strong Markov process. The existence of steady-state distribution for the interacted predator process means the existence of equilibrium population level. We find a necessary and sufficient condition for the existence of a steady-state distribution. Next we see that if the host process possesses a steady-state distribution, so does the interacted predator process and this distribution satisfies a difference equation. For special choices of the auto death and interaction parametersa andb of the predator, whenever the host process visits the particular statea *=a/b the predator takes rest (saturates) from its evolution. We find the probability of asymptotic saturating of the predator.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Literature

  • Becker, N. G. 1975. “A stochastic model for two interacting populations.”J. Appl. Prob. 7, 544–564.

    Article  Google Scholar 

  • Bharucha-Reid, A. T. 1960.Elements of the Theory of Markov Processes and Their Applications. New York: McGraw-Hill.

    Google Scholar 

  • Blumenthal, R. M. and R. K. Getoor. 1968.Markov Processes and potential Theory. New York: Academic Press.

    Google Scholar 

  • Doob, J. L. 1953.Stochastic Processes. New York: Wiley.

    Google Scholar 

  • Dynkin, E. B. 1965.Markov Processes. Vol. I. New York: Springer-Verlag.

    Google Scholar 

  • Feller, W. 1966.An Introduction to Probability Theory and its Applications, Vol. II. New York: Wiley.

    Google Scholar 

  • Gard, T. C. and D. Kannan. 1976. “On a stochastic differential equation modeling of prey-predator evolution”J. Appl. Prob.,13.

  • Goel, N. S., S. C. Maitra and E. W. Montroll. 1971. “On the Volterra and other non-linear models of interacting populations.”Rev. Mod. Phys.,43, 231–276.

    Article  MathSciNet  Google Scholar 

  • Hille, E. 1969.Lectures in Ordinary Differential Equations. Massachusetts: Addison-Wesley.

    Google Scholar 

  • Moyal, J. E. 1957. “Discontinous Markoff Processes.”Acta Math.,98, 221–264.

    Article  MATH  MathSciNet  Google Scholar 

  • Neveu, J. 1965.Mathematical Foundations of the Calculus of Probability. San Francisco: Holden-Day.

    Google Scholar 

  • Puri, P. S. 1975. “A linear birth and death process under the influence of another process.”J. Appl. Prob.,12, 1–17.

    Article  MATH  MathSciNet  Google Scholar 

  • Rescigno, A. and I. W. Richardson. 1973. “The deterministic theory of population dynamics.” InFoundations of Mathematical Biology, Vol. III, ed. R. Rosen, New York: Academic Press.

    Google Scholar 

  • Watanabe, T. 1968. “Approximation of uniform transport process on a find interval to Brownian motion.”Nagoya Math. J.,32, 297–314.

    MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kannan, D. On some Markov models of certain interacting populations. Bltn Mathcal Biology 38, 723–738 (1976). https://doi.org/10.1007/BF02458646

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02458646

Keywords

Navigation