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Spatial coupling in cyclic population dynamics: models and data.

D T Haydon1, P E Greenwood

  • 1Centre for Tropical Veterinary Medicine, Easter Bush, Roslin, Midlothian, EH25 9RG, United Kingdom. Daniel.Haydon@ed.ac.uk

Theoretical Population Biology
|December 20, 2000
PubMed
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This study models coupled oscillators to understand population synchrony. New methods distinguish intermittent and continuous coupling, revealing weaker lynx population coupling in the 20th century.

Area of Science:

  • Mathematical modeling
  • Ecology
  • Time series analysis

Background:

  • Coupled oscillators exhibit complex dynamics influenced by noise and coupling forces.
  • Understanding spatial synchrony in populations is crucial for ecological studies.
  • Previous analyses of Canadian lynx data suggest varying interpopulation coupling.

Purpose of the Study:

  • To develop a dynamic random field model for spatial coupled oscillators.
  • To define and measure asynchrony in discrete time stochastic dynamics.
  • To differentiate between intermittent and continuous phase synchronizing events.

Main Methods:

  • Modeling cyclic populations with discrete time stochastic dynamics, random noise, and coupling forces.
  • Deriving expressions for asynchrony measurement.

Related Experiment Videos

  • Developing robust methods for phase estimation, coupling strength estimation, and local noise variance measurement.

    • Main Results:

    • The model successfully distinguishes intermittent, large-scale synchrony from continuous, local coupling.
    • Analysis of Canadian lynx data indicates weaker interpopulation coupling in the 20th century compared to the 1800s.
    • Synchrony in lynx populations is primarily maintained by continuous local coupling with infrequent large phase adjustments.

    Conclusions:

    • The proposed modeling approach provides robust tools for analyzing spatial time series data.
    • Ecological synchrony can be driven by different coupling mechanisms, impacting population dynamics.
    • The findings suggest a historical shift in the coupling dynamics of Canadian lynx populations.