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Rich dynamics in a spatial predator–prey model with delay

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  • Chang, Lili
  • Sun, Gui-Quan
  • Wang, Zhen
  • Jin, Zhen

Abstract

In this paper, we study the spatiotemporal dynamics of a diffusive Holling–Tanner predator–prey model with discrete time delay. Via analytically and numerically analysis, we unveil six types of patterns with and without time delay. Among them, of particular novel is the observation of linear pattern (consisting of a series of parallel lines), whose formation is closely related with the temporal Hopf bifurcation threshold. Moreover, we also find that larger time delay or diffusion of predator may induce the extinction of both prey and predator. Theoretical analysis and numerical simulations validate the well-known conclusion: diffusion is usually beneficial for stabilizing pattern formation, yet discrete time delay plays a destabilizing role in the generation of pattern.

Suggested Citation

  • Chang, Lili & Sun, Gui-Quan & Wang, Zhen & Jin, Zhen, 2015. "Rich dynamics in a spatial predator–prey model with delay," Applied Mathematics and Computation, Elsevier, vol. 256(C), pages 540-550.
    • Handle: RePEc:eee:apmaco:v:256:y:2015:i:c:p:540-550
    DOI: 10.1016/j.amc.2015.01.052
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    References listed on IDEAS

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    1. Banerjee, Malay & Zhang, Lai, 2014. "Influence of discrete delay on pattern formation in a ratio-dependent prey–predator model," Chaos, Solitons & Fractals, Elsevier, vol. 67(C), pages 73-81.
    2. Sun, Gui-Quan & Jin, Zhen & Liu, Quan-Xing & Li, Li, 2008. "Dynamical complexity of a spatial predator–prey model with migration," Ecological Modelling, Elsevier, vol. 219(1), pages 248-255.
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    Cited by:

    1. Zhao, Dawei & Wang, Lianhai & Xu, Lijuan & Wang, Zhen, 2015. "Finding another yourself in multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 599-604.
    2. Wu, Zeyan & Li, Jianjuan & Liu, Shuying & Zhou, Liuting & Luo, Yang, 2019. "A spatial predator–prey system with non-renewable resources," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 381-391.
    3. Zhang, Huayong & Ma, Shengnan & Huang, Tousheng & Cong, Xuebing & Yang, Hongju & Zhang, Feifan, 2018. "A new finding on pattern self-organization along the route to chaos," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 118-130.
    4. Wang, Jinliang & Li, You & Zhong, Shihong & Hou, Xiaojie, 2019. "Analysis of bifurcation, chaos and pattern formation in a discrete time and space Gierer Meinhardt system," Chaos, Solitons & Fractals, Elsevier, vol. 118(C), pages 1-17.
    5. Huang, Tousheng & Zhang, Huayong, 2016. "Bifurcation, chaos and pattern formation in a space- and time-discrete predator–prey system," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 92-107.
    6. Moussaoui, Ali, 2015. "A reaction-diffusion equations modelling the effect of fluctuating water levels on prey-predator interactions," Applied Mathematics and Computation, Elsevier, vol. 268(C), pages 1110-1121.
    7. Huang, Chengdai & Cao, Jinde & Xiao, Min & Alsaedi, Ahmed & Alsaadi, Fuad E., 2017. "Controlling bifurcation in a delayed fractional predator–prey system with incommensurate orders," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 293-310.
    8. Chang, Lili & Jin, Zhen, 2018. "Efficient numerical methods for spatially extended population and epidemic models with time delay," Applied Mathematics and Computation, Elsevier, vol. 316(C), pages 138-154.
    9. Gökçe, Aytül, 2021. "A mathematical study for chaotic dynamics of dissolved oxygen- phytoplankton interactions under environmental driving factors and time lag," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).

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