IDEAS home Printed from https://ideas.repec.org/a/gam/jstats/v4y2021i2p20-307d531532.html
   My bibliography  Save this article

Optimal Sampling Regimes for Estimating Population Dynamics

Author

Listed:
  • Rebecca E. Atanga

    (Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA
    These authors contributed equally to this work.)

  • Edward L. Boone

    (Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA
    These authors contributed equally to this work.)

  • Ryad A. Ghanam

    (Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA
    Department of Statistical Sciences and Operations Research, Virginia Commonwealth University—Qatar, Education City, Doha 8095, Qatar
    These authors contributed equally to this work.)

  • Ben Stewart-Koster

    (Australian Rivers Institute, Griffith University, Southport 4222, Australia)

Abstract

Ecologists are interested in modeling the population growth of species in various ecosystems. Specifically, logistic growth arises as a common model for population growth. Studying such growth can assist environmental managers in making better decisions when collecting data. Traditionally, ecological data is recorded on a regular time frequency and is very well-documented. However, sampling can be an expensive process due to available resources, money and time. Limiting sampling makes it challenging to properly track the growth of a population. Thus, this design study proposes an approach to sampling based on the dynamics associated with logistic growth. The proposed method is demonstrated via a simulation study across various theoretical scenarios to evaluate its performance in identifying optimal designs that best estimate the curves. Markov Chain Monte Carlo sampling techniques are implemented to predict the probability of the model parameters using Bayesian inference. The intention of this study is to demonstrate a method that can minimize the amount of time ecologists spend in the field, while maximizing the information provided by the data.

Suggested Citation

  • Rebecca E. Atanga & Edward L. Boone & Ryad A. Ghanam & Ben Stewart-Koster, 2021. "Optimal Sampling Regimes for Estimating Population Dynamics," Stats, MDPI, vol. 4(2), pages 1-17, April.
    • Handle: RePEc:gam:jstats:v:4:y:2021:i:2:p:20-307:d:531532
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2571-905X/4/2/20/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2571-905X/4/2/20/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. F. R. Oliver, 1964. "Methods of Estimating the Logistic Growth Function," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 13(2), pages 57-66, June.
    2. D Williamson & M Goldstein, 2012. "Bayesian policy support for adaptive strategies using computer models for complex physical systems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(8), pages 1021-1033, August.
    3. Lin, Bo-qiang & Liu, Jiang-hua, 2010. "Estimating coal production peak and trends of coal imports in China," Energy Policy, Elsevier, vol. 38(1), pages 512-519, January.
    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. Wang, Chengjin & Ducruet, César, 2014. "Transport corridors and regional balance in China: the case of coal trade and logistics," Journal of Transport Geography, Elsevier, vol. 40(C), pages 3-16.
    2. Catherine Bobtcheff & Christian Gollier & Richard Zeckhauser, 2008. "Resource allocations when projects have ranges of increasing returns," Journal of Risk and Uncertainty, Springer, vol. 37(1), pages 93-93, August.
    3. Kahrl, Fredrich & Williams, Jim & Jianhua, Ding & Junfeng, Hu, 2011. "Challenges to China's transition to a low carbon electricity system," Energy Policy, Elsevier, vol. 39(7), pages 4032-4041, July.
    4. Wang, Qiang & Song, Xiaoxin, 2021. "How UK farewell to coal – Insight from multi-regional input-output and logarithmic mean divisia index analysis," Energy, Elsevier, vol. 229(C).
    5. Lin, Boqiang & Liu, Jianghua & Yang, Yingchun, 2012. "Impact of carbon intensity and energy security constraints on China's coal import," Energy Policy, Elsevier, vol. 48(C), pages 137-147.
    6. Erhu Bai & Xueyi Li & Wenbing Guo & Yi Tan & Mingjie Guo & Peng Wen & Zhibao Ma, 2022. "Characteristics and Formation Mechanism of Surface Residual Deformation above Longwall Abandoned Goaf," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    7. Tang, Erzi & Peng, Chong, 2017. "A macro- and microeconomic analysis of coal production in China," Resources Policy, Elsevier, vol. 51(C), pages 234-242.
    8. Massimo Florio & Sara Colautti, 2005. "A logistic growth theory of public expenditures: A study of five countries over 100 years," Public Choice, Springer, vol. 122(3), pages 355-393, March.
    9. Lin, Boqiang & Ouyang, Xiaoling, 2014. "Analysis of energy-related CO2 (carbon dioxide) emissions and reduction potential in the Chinese non-metallic mineral products industry," Energy, Elsevier, vol. 68(C), pages 688-697.
    10. Dmitry Alexandrovich Izotov, 2012. "Russian – Chinese Trade and Exchange Rate," Spatial Economics=Prostranstvennaya Ekonomika, Economic Research Institute, Far Eastern Branch, Russian Academy of Sciences (Khabarovsk, Russia), issue 3, pages 34-54.
    11. Zhang, Yujiang & Feng, Guorui & Zhang, Min & Ren, Hongrui & Bai, Jinwen & Guo, Yuxia & Jiang, Haina & Kang, Lixun, 2016. "Residual coal exploitation and its impact on sustainable development of the coal industry in China," Energy Policy, Elsevier, vol. 96(C), pages 534-541.
    12. Yang, D.L. & Tang, G.H. & Fan, Y.H. & Li, X.L. & Wang, S.Q., 2020. "Arrangement and three-dimensional analysis of cooling wall in 1000 MW S–CO2 coal-fired boiler," Energy, Elsevier, vol. 197(C).
    13. Xu Tang & Benjamin C. McLellan & Simon Snowden & Baosheng Zhang & Mikael Höök, 2015. "Dilemmas for China: Energy, Economy and Environment," Sustainability, MDPI, vol. 7(5), pages 1-13, May.
    14. Wang, Jianzhou & Dong, Yao & Wu, Jie & Mu, Ren & Jiang, He, 2011. "Coal production forecast and low carbon policies in China," Energy Policy, Elsevier, vol. 39(10), pages 5970-5979, October.
    15. Yu Hao & Shang Gao & Yunxia Guo & Zhiqiang Gai & Haitao Wu, 2021. "Measuring the nexus between economic development and environmental quality based on environmental Kuznets curve: a comparative study between China and Germany for the period of 2000–2017," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16848-16873, November.
    16. Wang, Feng & Wu, Min & Du, Xuyang, 2023. "Does industrial upgrading improve eco-efficiency? Evidence from China's industrial sector," Energy Economics, Elsevier, vol. 124(C).
    17. Gardebroek, Cornelis & Jongeneel, Roelof A., 2004. "The Growth In Organic Agriculture: Temporary Shift Or Structural Change?," 2004 Annual meeting, August 1-4, Denver, CO 20074, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    18. Lin, Boqiang & Wang, Ting, 2012. "Forecasting natural gas supply in China: Production peak and import trends," Energy Policy, Elsevier, vol. 49(C), pages 225-233.
    19. Zehua Yu & Zheng Li & Linwei Ma, 2023. "Strategies for the Resilience of Power-Coal Supply Chains in Low-Carbon Energy Transition: A System Dynamics Model and Scenario Analysis of China up to 2060," Sustainability, MDPI, vol. 15(9), pages 1-19, April.
    20. Ahmad Abubakar Suleiman & Hanita Daud & Narinderjit Singh Sawaran Singh & Mahmod Othman & Aliyu Ismail Ishaq & Rajalingam Sokkalingam, 2023. "A Novel Odd Beta Prime-Logistic Distribution: Desirable Mathematical Properties and Applications to Engineering and Environmental Data," Sustainability, MDPI, vol. 15(13), pages 1-25, June.

    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:jstats:v:4:y:2021:i:2:p:20-307:d:531532. 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.