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Extinction of oscillating populations.

Naftali R Smith1, Baruch Meerson1

  • 1Racah Institute of Physics, Hebrew University of Jerusalem, Jerusalem 91904, Israel.

Physical Review. E
|April 15, 2016
PubMed
Summary

This study models oscillating predator-prey populations facing extinction. Using a WKB approximation, it reveals how stochasticity drives extinction and how entropic barriers change near the Hopf bifurcation.

Area of Science:

  • Ecology
  • Mathematical Biology
  • Statistical Physics

Background:

  • Established populations often exhibit size oscillations, theoretically represented as limit cycles.
  • In isolated populations, intrinsic stochasticity can lead to extinction.
  • Previous WKB theories have addressed population extinction from fixed points.

Purpose of the Study:

  • To investigate the extinction dynamics of oscillating populations within a stochastic Rosenzweig-MacArthur predator-prey model.
  • To develop and apply a WKB approximation for analyzing extinction in these systems.
  • To examine the influence of the Hopf bifurcation on extinction barriers.

Main Methods:

  • Development of a WKB approximation to the master equation, using characteristic population size as the large parameter.

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  • Application of Floquet theory to the dynamics of an effective four-dimensional WKB Hamiltonian.
  • Evaluation of extinction rates and identification of most probable extinction pathways.
  • Main Results:

    • Quantification of extinction rates for oscillating populations.
    • Identification of the most probable paths to extinction from the limit cycle.
    • Demonstration of nonanalytic changes in entropic barriers to extinction at the Hopf bifurcation.
    • Analysis of subleading pre-exponential factors in the WKB approximation.

    Conclusions:

    • The WKB approximation provides a powerful tool for studying stochastic extinction in oscillating populations.
    • Hopf bifurcations significantly alter extinction dynamics and entropic barriers.
    • Understanding these dynamics is crucial for predicting population persistence.