IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i15p2474-d1714706.html
   My bibliography  Save this article

Spatiotemporal Dynamics of a Predator–Prey Model with Harvest and Disease in Prey

Author

Listed:
  • Jingen Yang

    (School of Mathematics and Statistics, Huanghuai University, Zhumadian 463000, China)

  • Zhong Zhao

    (School of Mathematics and Statistics, Huanghuai University, Zhumadian 463000, China)

  • Yingying Kong

    (School of Mathematics and Statistics, Huanghuai University, Zhumadian 463000, China)

  • Jing Xu

    (School of Mathematics and Statistics, Hubei Normal University, Huangshi 435000, China)

Abstract

In this paper, we propose a diffusion-type predator–prey interaction model with harvest and disease in prey, and conduct stability analysis and pattern formation analysis on the model. For the temporal model, the asymptotic stability of each equilibrium is analyzed using the linear stability method, and the conditions for Hopf bifurcation to occur near the positive equilibrium are investigated. The simulation results indicate that an increase in infection force might disrupt the stability of the model, while an increase in harvesting intensity would make the model stable. For the spatiotemporal model, a priori estimate for the positive steady state is obtained for the non-existence of the non-constant positive solution using maximum principle and Harnack inequality. The Leray–Schauder degree theory is used to study the sufficient conditions for the existence of non-constant positive steady states of the model, and pattern formation are achieved through numerical simulations. This indicates that the movement of prey and predators plays an important role in pattern formation, and different diffusions of these species may play essentially different effects.

Suggested Citation

  • Jingen Yang & Zhong Zhao & Yingying Kong & Jing Xu, 2025. "Spatiotemporal Dynamics of a Predator–Prey Model with Harvest and Disease in Prey," Mathematics, MDPI, vol. 13(15), pages 1-22, July.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:15:p:2474-:d:1714706
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/15/2474/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/13/15/2474/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chakraborty, Bhaskar & Ghorai, Santu & Bairagi, Nandadulal, 2020. "Reaction-diffusion predator-prey-parasite system and spatiotemporal complexity," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    2. Manoj Kumar Singh & Arushi Sharma & Luis M. Sánchez-Ruiz, 2025. "Impact of the Allee Effect on the Dynamics of a Predator–Prey Model Exhibiting Group Defense," Mathematics, MDPI, vol. 13(4), pages 1-19, February.
    3. Gao, Xubin & Pan, Qiuhui & He, Mingfeng & Kang, Yibin, 2013. "A predator–prey model with diseases in both prey and predator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5898-5906.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chakraborty, Bhaskar & Marick, Sounov & Bairagi, Nandadulal, 2024. "Diffusion-driven instabilities in a tri-trophic food web model: From Turing to non-Turing patterns and waves," Chaos, Solitons & Fractals, Elsevier, vol. 189(P1).
    2. Juneja, Nishant & Agnihotri, Kulbhushan & Kaur, Harpreet, 2018. "Effect of delay on globally stable prey–predator system," Chaos, Solitons & Fractals, Elsevier, vol. 111(C), pages 146-156.
    3. Sarangi, B.P. & Raw, S.N., 2023. "Dynamics of a spatially explicit eco-epidemic model with double Allee effect," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 206(C), pages 241-263.
    4. Marick, Sounov & Bhattacharya, Santanu & Bairagi, Nandadulal, 2023. "Dynamic properties of a reaction–diffusion predator–prey model with nonlinear harvesting: A linear and weakly nonlinear analysis," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    5. Bhunia, Bidhan & Ghorai, Santu & Kar, Tapan Kumar & Biswas, Samir & Bhutia, Lakpa Thendup & Debnath, Papiya, 2023. "A study of a spatiotemporal delayed predator–prey model with prey harvesting: Constant and periodic diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    6. Ghorai, Santu & Chakraborty, Bhaskar & Bairagi, Nandadulal, 2021. "Preferential selection of zooplankton and emergence of spatiotemporal patterns in plankton population," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:13:y:2025:i:15:p:2474-:d:1714706. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.