Research article Special Issues

The survival analysis of a stochastic Lotka-Volterra competition model with a coexistence equilibrium

  • Received: 01 January 2019 Accepted: 17 March 2019 Published: 27 March 2019
  • In this paper, we propose and analyze a two-species Lotka-Volterra competition model with random perturbations that relate to the inter-specific competition rates and the coexistence equilibrium of the corresponding deterministic system. The stochasticity in inter-specific competition (between species) is more important than that in intra-specific competition (within species). We pose two assumptions and then obtain su cient conditions for coexistence and for competitive exclusion respectively, and find that small random perturbations will not destroy the dynamic behaviors of the corresponding deterministic system. Moreover, if one species goes extinct, the convergence rate to zero is obtained by investigating the Lyapunov exponent. Finally, we provide several numerical examples to illustrate our mathematical results.

    Citation: Junjing Xiong, Xiong Li, Hao Wang. The survival analysis of a stochastic Lotka-Volterra competition model with a coexistence equilibrium[J]. Mathematical Biosciences and Engineering, 2019, 16(4): 2717-2737. doi: 10.3934/mbe.2019135

    Related Papers:

  • In this paper, we propose and analyze a two-species Lotka-Volterra competition model with random perturbations that relate to the inter-specific competition rates and the coexistence equilibrium of the corresponding deterministic system. The stochasticity in inter-specific competition (between species) is more important than that in intra-specific competition (within species). We pose two assumptions and then obtain su cient conditions for coexistence and for competitive exclusion respectively, and find that small random perturbations will not destroy the dynamic behaviors of the corresponding deterministic system. Moreover, if one species goes extinct, the convergence rate to zero is obtained by investigating the Lyapunov exponent. Finally, we provide several numerical examples to illustrate our mathematical results.


    加载中


    [1] J. D. Murray, Mathematical Biology, Springer-Verlag, Berlin, Heidelberg, 2002.
    [2] X. Mao, S. Sabais and E. Renshaw, Asymptotic behavior of stochastic Lotka-Volterra model, J. Math. Anal. Appl., 287 (2003), 141–156.
    [3] N. H. Du and V. H. Sam, Dynamics of a stochastic Lotka-Volterra model perturbed by white noise, J. Math. Anal. Appl., 324 (2006), 82–97.
    [4] D. Jiang, C. Ji, X. Li, et al., Analysis of autonomous Lotka-Volterra competition systems with random perturbation, J. Math. Anal. Appl., 390 (2012), 582–595.
    [5] M. Liu and K. Wang, Population dynamical behavior of Lotka-Volterra cooperative systems with random perturbations, Discrete Contin. Dyn. Syst., 33 (2013), 2495–2522.
    [6] R. Rudnicki, Long-time behaviour of a stochastic prey-predator model, Stochastic Process. Appl., 108 (2003), 93–107.
    [7] D. H. Nguyen, N. H. Du and T. V. Ton, Asymptotic behavior of predator-prey systems perturbed by white noise, Acta Appl. Math., 115 (2011), 351–370.
    [8] D. H. Nguyen and G. Yin, Coexistence and exclusion of stochastic competitive Lotka-Volterra models, J. Differ. Equations, 262 (2017), 1192–1225.
    [9] M. Liu, K. Wang and Q. Wu, Survival analysis of stochastic competitive models in a polluted environment and stochastic competitive exclusion principle, Bull. Math. Biol., 73 (2011), 1969– 2012.
    [10] X. Mao, Stationary distribution of stochastic population systems, Syst. Control Lett., 60 (2011), 398–405.
    [11] A. Bahar and X. Mao, Stochastic delay Lotka-Volterra model, J. Math. Anal. Appl., 292 (2004), 364–380.
    [12] Q. Liu, The effects of time-dependent delays on global stability of stochastic Lotka-Volterra competitive model, Physica A., 420 (2015), 108–115.
    [13] J. J. Xiong, X. Li and H.Wang, Global asymptotic stability of a Lotka-Volterra competition model with stochasticity in inter-specific competition, Appl. Math. Letters., 89 (2019), 58–63.
    [14] A. V. Skorokhod, Asymptotic Methods in the Theory of Stochastic Differential Equations, American Mathematical Society, Providence, 1989.
    [15] L. R. Bellet, Ergodic properties of Markov processes, in Open Quantum System II, Springer, Berlin, Heidelberg, (2006), 1–39.
    [16] D. J. Higham, An algorithmic introduction to numerical simulation of stochastic differential equations, SIAM Rev., 43 (2001), 525–546.
  • Reader Comments
  • © 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(4370) PDF downloads(836) Cited by(2)

Article outline

Figures and Tables

Figures(4)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog