IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v395y2019icp45-50.html
   My bibliography  Save this article

Colonial population dynamics of Spartina alterniflora

Author

Listed:
  • Takahashi, Daisuke
  • Sim, Seung-Woo
  • Park, Eun-Jin

Abstract

Smooth cordgrass, Spartina alterniflora, is a perennial grass species that forms distinctive colonies on mudflats. Such colonies can increase their size by expanding clonally to surrounding open mudflats and their number by establishing new colonies on far away from the original colonies either by sexual reproduction or rhizome fragmentation. In this work, we aimed to link colony dynamics mechanisms, lateral growth and recruitment, to reproduce the overall population dynamics of Spartina alterniflora in an integrative manner. The proposed model describes a population as a collection of age-structured colonies randomly distributed in a habitat area. By applying a mean field approach for spatial dimensions, we derive dynamics of how the expected proportion of an area occupied by these colonies would disperse over time. We derive a parameter describing the contribution of lateral growth and recruitment to population, i.e., the growth potential. This growth potential is proportional to the geometrical mean of the lateral–growth speed and recruitment rate, representing the average growth rate including these two mechanisms. Moreover, we show that lateral growth, rather than recruitment, addresses transitional dynamics of stable–age-structure developments. The ratio between colony mortality and growth potential determines the equilibrium proportion of area occupied by these colonies. The application of this model to S. alterniflora population dynamics would be feasible across a wide range of populations determined by the spatial occupations of growing colonies.

Suggested Citation

  • Takahashi, Daisuke & Sim, Seung-Woo & Park, Eun-Jin, 2019. "Colonial population dynamics of Spartina alterniflora," Ecological Modelling, Elsevier, vol. 395(C), pages 45-50.
  • Handle: RePEc:eee:ecomod:v:395:y:2019:i:c:p:45-50
    DOI: 10.1016/j.ecolmodel.2019.01.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380019300274
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2019.01.013?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. Murphy, James T. & Johnson, Mark P., 2015. "A theoretical analysis of the Allee effect in wind-pollinated cordgrass plant invasions," Theoretical Population Biology, Elsevier, vol. 106(C), pages 14-21.
    2. James T. Murphy & Mark P. Johnson & Ray Walshe, 2013. "Modeling The Impact Of Spatial Structure On Growth Dynamics Of Invasive Plant Species," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 24(07), pages 1-20.
    3. Soetaert, Karline & Petzoldt, Thomas & Setzer, R. Woodrow, 2010. "Solving Differential Equations in R: Package deSolve," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i09).
    4. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    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. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2021. "Sustainable Supply Chains with Blockchain, IoT and RFID: A Simulation on Order Management," Sustainability, MDPI, vol. 13(11), pages 1-23, June.
    2. Makam, Vaishno Devi & Millossovich, Pietro & Tsanakas, Andreas, 2021. "Sensitivity analysis with χ2-divergences," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 372-383.
    3. Plischke, Elmar & Borgonovo, Emanuele, 2019. "Copula theory and probabilistic sensitivity analysis: Is there a connection?," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1046-1059.
    4. Wen Shi & Xi Chen & Jennifer Shang, 2019. "An Efficient Morris Method-Based Framework for Simulation Factor Screening," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 745-770, October.
    5. F. Wang & G. H. Huang & Y. Fan & Y. P. Li, 2020. "Robust Subsampling ANOVA Methods for Sensitivity Analysis of Water Resource and Environmental Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3199-3217, August.
    6. Daniel Harenberg & Stefano Marelli & Bruno Sudret & Viktor Winschel, 2019. "Uncertainty quantification and global sensitivity analysis for economic models," Quantitative Economics, Econometric Society, vol. 10(1), pages 1-41, January.
    7. Tobias Fissler & Silvana M. Pesenti, 2022. "Sensitivity Measures Based on Scoring Functions," Papers 2203.00460, arXiv.org, revised Jul 2022.
    8. Shang, Xiaobing & Su, Li & Fang, Hai & Zeng, Bowen & Zhang, Zhi, 2023. "An efficient multi-fidelity Kriging surrogate model-based method for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    9. Magni, Carlo Alberto, 2016. "Capital depreciation and the underdetermination of rate of return: A unifying perspective," Journal of Mathematical Economics, Elsevier, vol. 67(C), pages 54-79.
    10. Lu, Xuefei & Borgonovo, Emanuele, 2023. "Global sensitivity analysis in epidemiological modeling," European Journal of Operational Research, Elsevier, vol. 304(1), pages 9-24.
    11. Matteo Fontana & Massimo Tavoni & Simone Vantini, 2020. "Global Sensitivity and Domain-Selective Testing for Functional-Valued Responses: An Application to Climate Economy Models," Papers 2006.13850, arXiv.org, revised Apr 2024.
    12. Stefano Cucurachi & Carlos Felipe Blanco & Bernhard Steubing & Reinout Heijungs, 2022. "Implementation of uncertainty analysis and moment‐independent global sensitivity analysis for full‐scale life cycle assessment models," Journal of Industrial Ecology, Yale University, vol. 26(2), pages 374-391, April.
    13. Yun, Wanying & Lu, Zhenzhou & Feng, Kaixuan & Li, Luyi, 2019. "An elaborate algorithm for analyzing the Borgonovo moment-independent sensitivity by replacing the probability density function estimation with the probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 99-108.
    14. Fatima-Zahra Jaouimaa & Daniel Dempsey & Suzanne Van Osch & Stephen Kinsella & Kevin Burke & Jason Wyse & James Sweeney, 2021. "An age-structured SEIR model for COVID-19 incidence in Dublin, Ireland with framework for evaluating health intervention cost," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-25, December.
    15. Puppo, L. & Pedroni, N. & Maio, F. Di & Bersano, A. & Bertani, C. & Zio, E., 2021. "A Framework based on Finite Mixture Models and Adaptive Kriging for Characterizing Non-Smooth and Multimodal Failure Regions in a Nuclear Passive Safety System," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    16. Ziemele, Jelena & Gravelsins, Armands & Blumberga, Andra & Blumberga, Dagnija, 2017. "Sustainability of heat energy tariff in district heating system: Statistic and dynamic methodologies," Energy, Elsevier, vol. 137(C), pages 834-845.
    17. Thomas H. Jørgensen, 2023. "Sensitivity to Calibrated Parameters," The Review of Economics and Statistics, MIT Press, vol. 105(2), pages 474-481, March.
    18. Belém Barbosa & José Ramón Saura & Dag Bennett, 2024. "How do entrepreneurs perform digital marketing across the customer journey? A review and discussion of the main uses," The Journal of Technology Transfer, Springer, vol. 49(1), pages 69-103, February.
    19. Marchioni, Andrea & Magni, Carlo Alberto, 2018. "Investment decisions and sensitivity analysis: NPV-consistency of rates of return," European Journal of Operational Research, Elsevier, vol. 268(1), pages 361-372.
    20. Magni, Carlo Alberto & Marchioni, Andrea, 2020. "Average rates of return, working capital, and NPV-consistency in project appraisal: A sensitivity analysis approach," International Journal of Production Economics, Elsevier, vol. 229(C).

    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:ecomod:v:395:y:2019:i:c:p:45-50. 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/ecological-modelling .

    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.