Brownian Bugs and Superprocesses

Abstract

Advection-diffusion-reaction (ADR) models link physical oceanography and biological oceanography. These models, which describe biology using continuous concentration fields, usually neglect individual-scale fluctuations. I describe a stochastic individual-based model, called the Brownian bug process, which illustrates some of the surprising issues associated with the neglect of fluctuations by ADR descriptions. The Brownian bug model is an ensemble of random walkers which suffer birth and death at constant mean rates. (Probabilists will recognize the Brownian bug model as the simplest example of a "superprocess.") Binary division puts two bugs (parent and progeny) at the same position and the accumulation of these small-scale density fluctuations can produce palpable nonuniformities on large scales. In other words, provided that the diffusion is not too strong relative to the reproduction rate, a spatially homogeneous initial condition spontaneously develops patches and voids. The wavenumber signature of these reproductive pair correlations is that the spectrum of density fluctuations remains white but rises linearly with time. Diffusion opposes this reproductive forcing, most effectively at large wavenumbers, so that a red spectrum develops.

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Document Details

Document Type
Technical Report
Publication Date
Jan 19, 2001
Accession Number
ADP013589

Entities

People

  • W. R. Young

Organizations

  • Scripps Institution of Oceanography

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Agent-Based Simulations
  • Biology
  • Brownian Motion
  • Differential Equations
  • Diffusion
  • Diffusivity
  • Equations
  • Fluid Mechanics
  • Marine Biology
  • Mechanics
  • Mixing
  • Oceanography
  • Probability
  • Random Variables
  • Random Walk
  • Simulations
  • Stochastic Processes

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Educational Psychology
  • Mathematical Modeling and Probability Theory.