IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v573y2021ics037843712100203x.html
   My bibliography  Save this article

Time-dependent probability density function for general stochastic logistic population model with harvesting effort

Author

Listed:
  • Otunuga, Olusegun Michael

Abstract

We derive and analyze the time-dependent probability density function for the number of individuals in a population at a given time in a general logistic population model with harvesting effort using the Fokker–Planck equation. The time-dependent probability density function (obtained as the unique principal solution of the Fokker–Planck equation corresponding to certain initial value and boundary conditions) is used to describe how the distribution of the population process changes with time. We assume the environment is randomly varying and the population is subject to a continuous spectrum of disturbances, with fluctuations in the intrinsic growth rate and the harvesting effort. The randomness is expressed as independent white noise processes. The effect of changes in the intrinsic growth rate, harvesting effort, and noise intensities on the distribution is investigated. In addition, conditions for the existence of optimal harvesting policy are obtained using properties of the time-dependent probability density function. The results obtained in this work are validated using population and published parameters.

Suggested Citation

  • Otunuga, Olusegun Michael, 2021. "Time-dependent probability density function for general stochastic logistic population model with harvesting effort," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    • Handle: RePEc:eee:phsmap:v:573:y:2021:i:c:s037843712100203x
    DOI: 10.1016/j.physa.2021.125931
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843712100203X
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2021.125931?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. Bulsara, A.R. & Lindenberg, K. & Seshadri, V. & Shuler, K.E. & West, B.J., 1979. "Stochastic processes with non-additive fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 97(2), pages 234-243.
    2. West, B.J. & Bulsara, A.R. & Lindenberg, K. & Seshadri, V. & Shuler, K.E., 1979. "Stochastic processes with non-additive fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 97(2), pages 211-233.
    3. Yang, Bin & Cai, Yongli & Wang, Kai & Wang, Weiming, 2019. "Optimal harvesting policy of logistic population model in a randomly fluctuating environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(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. Peña, Guillermo & Puente-Ajovín, Miguel & Ramos, Arturo & Sanz-Gracia, Fernando, 2022. "Log-growth rates of CO2: An empirical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    2. Arturo Ramos & Till Massing & Atushi Ishikawa & Shouji Fujimoto & Takayuki Mizuno, 2023. "Composite distributions in the social sciences: A comparative empirical study of firms' sales distribution for France, Germany, Italy, Japan, South Korea, and Spain," Papers 2301.09438, arXiv.org.
    3. Cortés, J.-C. & Moscardó-García, A. & Villanueva, R.-J., 2022. "Uncertainty quantification for hybrid random logistic models with harvesting via density functions," Chaos, Solitons & Fractals, Elsevier, vol. 155(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. L. Ingber, 1981. "Towards a unified brain theory," Lester Ingber Papers 81tu, Lester Ingber.
    2. Liu, Qun & Jiang, Daqing & Hayat, Tasawar & Alsaedi, Ahmed & Ahmad, Bashir, 2020. "A stochastic SIRS epidemic model with logistic growth and general nonlinear incidence rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    3. Chengyuan Li & Haoran Zhu & Hanjun Luo & Suyang Zhou & Jieping Kong & Lei Qi & Congjun Rao, 2023. "Spread Prediction and Classification of Asian Giant Hornets Based on GM-Logistic and CSRF Models," Mathematics, MDPI, vol. 11(6), pages 1-26, March.
    4. Karim, Md Aktar Ul & Aithal, Vikram & Bhowmick, Amiya Ranjan, 2023. "Random variation in model parameters: A comprehensive review of stochastic logistic growth equation," Ecological Modelling, Elsevier, vol. 484(C).
    5. Tiancai Liao & Hengguo Yu & Chuanjun Dai & Min Zhao, 2019. "Impact of Cell Size Effect on Nutrient-Phytoplankton Dynamics," Complexity, Hindawi, vol. 2019, pages 1-23, November.

    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:phsmap:v:573:y:2021:i:c:s037843712100203x. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.