IDEAS home Printed from https://ideas.repec.org/a/spr/metcap/v25y2023i4d10.1007_s11009-023-10064-9.html
   My bibliography  Save this article

Stochastic Dynamics of a Hybrid Delay Food Chain Model with Harvesting and Jumps in a Polluted Environment

Author

Listed:
  • Sheng Wang

    (Henan Polytechnic University)

  • Lijuan Dong

    (Henan Polytechnic University)

Abstract

In this paper, the stochastic dynamics of a hybrid delay food chain model with harvesting and Lévy jumps in a polluted environment is studied by using stochastic analysis techniques. Under some basic assumptions, criterions about stochastic persistence in mean and extinction of each species are established, as well as global attractivity and the existence of optimal harvesting strategy (OHS) of the system. The accurate expressions for the optimal harvesting effort (OHE) and the maximum of expectation of sustainable yield (MESY) are given. Our results show that the stochastic dynamics and OHS of the system are closely correlated with both time delays and environmental noises. Finally, some numerical simulations are introduced to illustrate the main results.

Suggested Citation

  • Sheng Wang & Lijuan Dong, 2023. "Stochastic Dynamics of a Hybrid Delay Food Chain Model with Harvesting and Jumps in a Polluted Environment," Methodology and Computing in Applied Probability, Springer, vol. 25(4), pages 1-31, December.
  • Handle: RePEc:spr:metcap:v:25:y:2023:i:4:d:10.1007_s11009-023-10064-9
    DOI: 10.1007/s11009-023-10064-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11009-023-10064-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11009-023-10064-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:spr:metcap:v:25:y:2023:i:4:d:10.1007_s11009-023-10064-9. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.