Spreading and Vanishing for a Monostable Reaction–Diffusion Equation with Forced Speed

By J. Bouhours, Thomas Giletti. Journal of Dynamics and Differential Equations, 2018

58 citations recorded by the source corpus.

Invasion phenomena for heterogeneous reaction–diffusion equations are contemporary and challenging questions in applied mathematics. In this paper we are interested in the question of spreading for a reaction–diffusion equation when the subdomain where the reaction term is positive is shifting/contracting at a given speed c. This problem arises in particular in the modelling of the impact of climate change on population dynamics. By placing ourselves in the appropriate moving frame, this leads us to consider a reaction–diffusion–advection equation with a heterogeneous in space reaction term, in dimension N≥1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N\ge 1$$\end{document}. We investigate the behaviour of the solution u depending on the value of the advection constant c, which typically stands for the velocity of climate change. We find that, when the initial datum is compactly supported, there exists precisely three ranges for c leading to drastically different situations. In the lower speed range the solution always spreads, while in the upper range it always vanishes. More surprisingly, we find that both spreading and vanishing may occur in an intermediate speed range. The threshold between those two outcomes is always sharp, both with respect to c and to the initial condition. We also briefly consider the case of an exponentially decreasing initial condition, where we relate the decreasing rate of the initial condition with the range of values of c such that spreading occurs.

Subfields: Genetics, Modeling and Simulation, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/99e64715ce591c1316edad2d151e7d3079990130

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In Genetics

  1. Jong-Shenq Guo
  2. Wonhyung Choi
  3. Xiao-Qiang Zhao
  4. Taishan Yi
  5. Thomas Giletti
  6. Mingxin Wang
  7. Pierre Magal
  8. Horst R. Thieme

In Modeling and Simulation

  1. Jong-Shenq Guo
  2. Taishan Yi
  3. Xiao-Qiang Zhao
  4. Wonhyung Choi
  5. Thomas Giletti
  6. Jian Fang
  7. Feng-Bin Wang
  8. Arnaud Ducrot

In Public Health, Environmental and Occupational Health

  1. Jong-Shenq Guo
  2. Xiao-Qiang Zhao
  3. Taishan Yi
  4. Wonhyung Choi
  5. Thomas Giletti
  6. Wenxian Shen
  7. Wan-Tong Li
  8. Mingxin Wang

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