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Stationary Distribution, Extinction and Probability Density Function of a Stochastic Vegetation–Water Model in Arid Ecosystems

  • Baoquan Zhou
  • , Bingtao Han
  • , Daqing Jiang
  • , Tasawar Hayat
  • , Ahmed Alsaedi
  • China University of Petroleum (East China)
  • King Abdulaziz University
  • Quaid-I-Azam University

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

In this paper, we study a three-dimensional stochastic vegetation–water model in arid ecosystems, where the soil water and the surface water are considered. First, for the deterministic model, the possible equilibria and the related local asymptotic stability are studied. Then, for the stochastic model, by constructing some suitable stochastic Lyapunov functions, we establish sufficient conditions for the existence and uniqueness of an ergodic stationary distribution ϖ(·). In a biological interpretation, the existence of the distribution ϖ(·) implies the long-term persistence of vegetation under certain conditions. Taking the stochasticity into account, a quasi-positive equilibrium D¯ related to the vegetation-positive equilibrium of the deterministic model is defined. By solving the relevant Fokker–Planck equation, we obtain the approximate expression of the distribution ϖ(·) around the equilibrium D¯ . In addition, we obtain sufficient condition R0E<1 for vegetation extinction. For practical application, we further estimate the probability of vegetation extinction at a given time. Finally, based on some actual vegetation data from Wuwei in China and Sahel, some numerical simulations are provided to verify our theoretical results and study the impact of stochastic noise on vegetation dynamics.

Original languageEnglish
Article number30
JournalJournal of Nonlinear Science
Volume32
Issue number3
DOIs
StatePublished - Jun 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • Climatic variations
  • Ergodicity
  • Extinction
  • Probability density function
  • Stationary distribution
  • Stochastic vegetation–water model

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