IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v175y2023ip2s096007792300944x.html
   My bibliography  Save this article

Coexistence and extinction for a stochastic vegetation-water model motivated by Black–Karasinski process

Author

Listed:
  • Han, Bingtao
  • Jiang, Daqing

Abstract

In this paper, we examine a stochastic vegetation-water model, where the Black–Karasinski process is introduced to characterize the random fluctuations in vegetation evolution. It turns out that Black–Karasinski process is a both mathematically and biologically reasonable assumption by comparison with existing stochastic modeling approaches. First, it is theoretically proved that the solution of the stochastic model is unique and global. Then two critical values ℛ0E and ℛ0S are obtained to classify the dynamical behavior of vegetation. It is shown that: (i) If ℛ0S>1, the stochastic model has a stationary distribution ℓ(⋅), which reflects the long-term coexitence of vegetation and the water environment. (ii) The vegetation will go extinct exponentially if ℛ0E<1. (iii) ℛ0E=ℛ0S=ℛ0 if there are no random noises in vegetation dynamics, where ℛ0 is the basic reproduction number of deterministic model. Furthermore, by solving the associated Fokker–Planck equation, the approximate expression for probability density function of the distribution ℓ(⋅) around a quasi-positive equilibrium is studied. Finally, several numerical examples are provided to support our theoretical findings.

Suggested Citation

  • Han, Bingtao & Jiang, Daqing, 2023. "Coexistence and extinction for a stochastic vegetation-water model motivated by Black–Karasinski process," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
  • Handle: RePEc:eee:chsofr:v:175:y:2023:i:p2:s096007792300944x
    DOI: 10.1016/j.chaos.2023.114043
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096007792300944X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2023.114043?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.

    References listed on IDEAS

    as
    1. Zhang, Hongxia & Xu, Wei & Han, Ping & Qiao, Yan, 2020. "Stochastic dynamic balance of a bi-stable vegetation model with pulse control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    2. Cai, Yongli & Jiao, Jianjun & Gui, Zhanji & Liu, Yuting & Wang, Weiming, 2018. "Environmental variability in a stochastic epidemic model," Applied Mathematics and Computation, Elsevier, vol. 329(C), pages 210-226.
    3. Zhang, Xiaofeng & Yuan, Rong, 2021. "A stochastic chemostat model with mean-reverting Ornstein-Uhlenbeck process and Monod-Haldane response function," Applied Mathematics and Computation, Elsevier, vol. 394(C).
    4. Ying, Zhixia & Liao, Jinbao & Liu, Yongjie & Wang, Shichang & Lu, Hui & Ma, Liang & Chen, Dongdong & Li, Zhenqing, 2017. "Modelling tree-grass coexistence in water-limited ecosystems," Ecological Modelling, Elsevier, vol. 360(C), pages 387-398.
    5. Zhou, Baoquan & Jiang, Daqing & Han, Bingtao & Hayat, Tasawar, 2022. "Threshold dynamics and density function of a stochastic epidemic model with media coverage and mean-reverting Ornstein–Uhlenbeck process," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 196(C), pages 15-44.
    6. Chen, Zheng & Wu, Yong-Ping & Feng, Guo-Lin & Qian, Zhong-Hua & Sun, Gui-Quan, 2021. "Effects of global warming on pattern dynamics of vegetation: Wuwei in China as a case," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    7. Li, Xiao-Ping & Din, Anwarud & Zeb, Anwar & Kumar, Sunil & Saeed, Tareq, 2022. "The impact of Lévy noise on a stochastic and fractal-fractional Atangana–Baleanu order hepatitis B model under real statistical data," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    8. Kefi, Sonia & Rietkerk, Max & Katul, Gabriel G., 2008. "Vegetation pattern shift as a result of rising atmospheric CO2 in arid ecosystems," Theoretical Population Biology, Elsevier, vol. 74(4), pages 332-344.
    9. Mao, Xuerong & Marion, Glenn & Renshaw, Eric, 2002. "Environmental Brownian noise suppresses explosions in population dynamics," Stochastic Processes and their Applications, Elsevier, vol. 97(1), pages 95-110, January.
    10. Laaribi, Aziz & Boukanjime, Brahim & El Khalifi, Mohamed & Bouggar, Driss & El Fatini, Mohamed, 2023. "A generalized stochastic SIRS epidemic model incorporating mean-reverting Ornstein–Uhlenbeck process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Haile & Zuo, Wenjie & Jiang, Daqing, 2023. "Dynamical analysis of a stochastic epidemic HBV model with log-normal Ornstein–Uhlenbeck process and vertical transmission term," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).

    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. Han, Cheng & Wang, Yan & Jiang, Daqing, 2023. "Dynamics analysis of a stochastic HIV model with non-cytolytic cure and Ornstein–Uhlenbeck process," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    2. Zhou, Baoquan & Jiang, Daqing & Han, Bingtao & Hayat, Tasawar, 2022. "Threshold dynamics and density function of a stochastic epidemic model with media coverage and mean-reverting Ornstein–Uhlenbeck process," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 196(C), pages 15-44.
    3. Liu, Qun & Jiang, Daqing, 2023. "Analysis of a stochastic inshore–offshore hairtail fishery model with Ornstein–Uhlenbeck process," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    4. Shi, Zhenfeng & Jiang, Daqing, 2022. "Dynamical behaviors of a stochastic HTLV-I infection model with general infection form and Ornstein–Uhlenbeck process," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    5. Yang, Ying & Zhang, Jingwen & Wang, Kaiyuan & Zhang, Guofang, 2024. "Stationary distribution, density function and extinction of a stochastic SIQR epidemic model with Ornstein–Uhlenbeck process," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    6. Wang, Haile & Zuo, Wenjie & Jiang, Daqing, 2023. "Dynamical analysis of a stochastic epidemic HBV model with log-normal Ornstein–Uhlenbeck process and vertical transmission term," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    7. Yang, Xiaochen & Yang, Zhanwen & Zhang, Chiping, 2023. "Numerical analysis of the Linearly implicit Euler method with truncated Wiener process for the stochastic SIR model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 208(C), pages 1-14.
    8. Chen, Zheng & Liu, Jieyu & Li, Li & Wu, Yongping & Feng, Guolin & Qian, Zhonghua & Sun, Gui-Quan, 2022. "Effects of climate change on vegetation patterns in Hulun Buir Grassland," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).
    9. Wang, Lei & Wang, Kai & Jiang, Daqing & Hayat, Tasawar, 2018. "Nontrivial periodic solution for a stochastic brucellosis model with application to Xinjiang, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 522-537.
    10. Zou, Xiaoling & Ma, Pengyu & Zhang, Liren & Lv, Jingliang, 2022. "Dynamic properties for a stochastic food chain model," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    11. Yang, Bo, 2018. "A stochastic Feline immunodeficiency virus model with vertical transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 448-458.
    12. Lu, Minmin & Wang, Yan & Jiang, Daqing, 2021. "Stationary distribution and probability density function analysis of a stochastic HIV model with cell-to-cell infection," Applied Mathematics and Computation, Elsevier, vol. 410(C).
    13. Han, Bingtao & Zhou, Baoquan & Jiang, Daqing & Hayat, Tasawar & Alsaedi, Ahmed, 2021. "Stationary solution, extinction and density function for a high-dimensional stochastic SEI epidemic model with general distributed delay," Applied Mathematics and Computation, Elsevier, vol. 405(C).
    14. Su, Tan & Yang, Qing & Zhang, Xinhong & Jiang, Daqing, 2023. "Stationary distribution, extinction and probability density function of a stochastic SEIV epidemic model with general incidence and Ornstein–Uhlenbeck process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    15. Liu, Qun & Jiang, Daqing, 2020. "Threshold behavior in a stochastic SIR epidemic model with Logistic birth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    16. Bao, Kangbo & Zhang, Qimin & Rong, Libin & Li, Xining, 2019. "Dynamics of an imprecise SIRS model with Lévy jumps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 489-506.
    17. Zhou, Baoquan & Han, Bingtao & Jiang, Daqing, 2021. "Ergodic property, extinction and density function of a stochastic SIR epidemic model with nonlinear incidence and general stochastic perturbations," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    18. Gao, Miaomiao & Jiang, Daqing & Ding, Jieyu, 2023. "Dynamical behavior of a nutrient–plankton model with Ornstein–Uhlenbeck process and nutrient recycling," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    19. Tong, Jinying & Zhang, Zhenzhong & Bao, Jianhai, 2013. "The stationary distribution of the facultative population model with a degenerate noise," Statistics & Probability Letters, Elsevier, vol. 83(2), pages 655-664.
    20. Huang, Zaitang & Cao, Junfei, 2018. "Ergodicity and bifurcations for stochastic logistic equation with non-Gaussian Lévy noise," Applied Mathematics and Computation, Elsevier, vol. 330(C), pages 1-10.

    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:eee:chsofr:v:175:y:2023:i:p2:s096007792300944x. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.