Correlated random walks in heterogeneous landscapes: Derivation, homogenization, and invasion fronts

Many models for the movement of particles and individuals are based on the diffusion equation, which, in turn, can be derived from an uncorrelated random walk or a position-jump process. In those models, individuals have a location but no well-defined velocity. An alternative, and sometimes more acc...

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Main Authors: Frithjof Lutscher, Thomas Hillen
Format: Article
Language:English
Published: AIMS Press 2021-06-01
Series:AIMS Mathematics
Subjects:
Online Access:https://www.aimspress.com/article/doi/10.3934/math.2021518?viewType=HTML
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spelling doaj-c694b07f1a474c13879183a4aa4c903c2021-06-22T07:04:47ZengAIMS PressAIMS Mathematics2473-69882021-06-01688920894810.3934/math.2021518Correlated random walks in heterogeneous landscapes: Derivation, homogenization, and invasion frontsFrithjof Lutscher0Thomas Hillen11. Department of Mathematics and Statistics, and Department of Biology, University of Ottawa, Ottawa, ON, K1N6N5, Canada2. Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, T6G 2G1, CanadaMany models for the movement of particles and individuals are based on the diffusion equation, which, in turn, can be derived from an uncorrelated random walk or a position-jump process. In those models, individuals have a location but no well-defined velocity. An alternative, and sometimes more accurate, model is based on a correlated random walk or a velocity-jump process, where individuals have a well defined location and velocity. The latter approach leads to hyperbolic equations for the density of individuals, rather than parabolic equations that result from the diffusion process. Almost all previous work on correlated random walks considers a homogeneous landscape, whereas diffusion models for uncorrelated walks have been extended to spatially varying environments. In this work, we first derive the equations for a correlated random walk in a one-dimensional spatially varying environment with either smooth variation or piecewise constant variation. Then we show how to derive the so-called parabolic limit from the resulting hyperbolic equations. We develop homogenization theory for the hyperbolic equations, and show that taking the parabolic limit and homogenization are commuting actions. We illustrate our results with two examples from ecology: the persistence and spread of a population in a patchy heterogeneous landscape.https://www.aimspress.com/article/doi/10.3934/math.2021518?viewType=HTMLcorrelated random walkhyperbolic differential equationmulti-scalehomogenizationheterogeneous landscapepopulation persistencepopulation spread rate
collection DOAJ
language English
format Article
sources DOAJ
author Frithjof Lutscher
Thomas Hillen
spellingShingle Frithjof Lutscher
Thomas Hillen
Correlated random walks in heterogeneous landscapes: Derivation, homogenization, and invasion fronts
AIMS Mathematics
correlated random walk
hyperbolic differential equation
multi-scale
homogenization
heterogeneous landscape
population persistence
population spread rate
author_facet Frithjof Lutscher
Thomas Hillen
author_sort Frithjof Lutscher
title Correlated random walks in heterogeneous landscapes: Derivation, homogenization, and invasion fronts
title_short Correlated random walks in heterogeneous landscapes: Derivation, homogenization, and invasion fronts
title_full Correlated random walks in heterogeneous landscapes: Derivation, homogenization, and invasion fronts
title_fullStr Correlated random walks in heterogeneous landscapes: Derivation, homogenization, and invasion fronts
title_full_unstemmed Correlated random walks in heterogeneous landscapes: Derivation, homogenization, and invasion fronts
title_sort correlated random walks in heterogeneous landscapes: derivation, homogenization, and invasion fronts
publisher AIMS Press
series AIMS Mathematics
issn 2473-6988
publishDate 2021-06-01
description Many models for the movement of particles and individuals are based on the diffusion equation, which, in turn, can be derived from an uncorrelated random walk or a position-jump process. In those models, individuals have a location but no well-defined velocity. An alternative, and sometimes more accurate, model is based on a correlated random walk or a velocity-jump process, where individuals have a well defined location and velocity. The latter approach leads to hyperbolic equations for the density of individuals, rather than parabolic equations that result from the diffusion process. Almost all previous work on correlated random walks considers a homogeneous landscape, whereas diffusion models for uncorrelated walks have been extended to spatially varying environments. In this work, we first derive the equations for a correlated random walk in a one-dimensional spatially varying environment with either smooth variation or piecewise constant variation. Then we show how to derive the so-called parabolic limit from the resulting hyperbolic equations. We develop homogenization theory for the hyperbolic equations, and show that taking the parabolic limit and homogenization are commuting actions. We illustrate our results with two examples from ecology: the persistence and spread of a population in a patchy heterogeneous landscape.
topic correlated random walk
hyperbolic differential equation
multi-scale
homogenization
heterogeneous landscape
population persistence
population spread rate
url https://www.aimspress.com/article/doi/10.3934/math.2021518?viewType=HTML
work_keys_str_mv AT frithjoflutscher correlatedrandomwalksinheterogeneouslandscapesderivationhomogenizationandinvasionfronts
AT thomashillen correlatedrandomwalksinheterogeneouslandscapesderivationhomogenizationandinvasionfronts
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