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Extended logistic model for growth of single-species populations

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  • Sakanoue, Seiichi

Abstract

A procedure for constructing models of population growth is presented. It consists of three assumptions: resource availability changes with population size as a variable, resource supply to a population and population demand for resources function as a field and a boundary, respectively, and the variables move on the field to the boundary. These are organized into an equation similar in form to Verhulst’s model. The equation can determine boundaries necessary for classical models at a certain field. It is shown that most of the models include complex boundaries. The equation also provides a new growth model when the field and boundary are approximated using a linear function and a quadratic function, respectively, of resource availability and population size. One of the parameters in this model is defined as the type and intensity of intraspecific interaction.

Suggested Citation

  • Sakanoue, Seiichi, 2007. "Extended logistic model for growth of single-species populations," Ecological Modelling, Elsevier, vol. 205(1), pages 159-168.
    • Handle: RePEc:eee:ecomod:v:205:y:2007:i:1:p:159-168
    DOI: 10.1016/j.ecolmodel.2007.02.013
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    Citations

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    Cited by:

    1. Sakanoue, Seiichi, 2013. "Integration of logistic and kinetics equations of population growth," Ecological Modelling, Elsevier, vol. 261, pages 93-97.
    2. Barker, Daniel & Sibly, Richard M., 2008. "The effects of environmental perturbation and measurement error on estimates of the shape parameter in the theta-logistic model of population regulation," Ecological Modelling, Elsevier, vol. 219(1), pages 170-177.
    3. Boland, John & Huang, Jing & Ridley, Barbara, 2013. "Decomposing global solar radiation into its direct and diffuse components," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 749-756.
    4. Skalski, John R. & Millspaugh, Joshua J. & Ryding, Kristen E., 2008. "Effects of asymptotic and maximum age estimates on calculated rates of population change," Ecological Modelling, Elsevier, vol. 212(3), pages 528-535.
    5. Sakanoue, Seiichi, 2009. "A resource-based approach to modelling the dynamics of interacting populations," Ecological Modelling, Elsevier, vol. 220(11), pages 1383-1394.
    6. Colomer, M. Àngels & Montori, Albert & García, Eder & Fondevilla, Cristian, 2014. "Using a bioinspired model to determine the extinction risk of Calotriton asper populations as a result of an increase in extreme rainfall in a scenario of climatic change," Ecological Modelling, Elsevier, vol. 281(C), pages 1-14.
    7. Melica, Valentina & Invernizzi, Sergio & Caristi, Gabriella, 2014. "Logistic density-dependent growth of an Aurelia aurita polyps population," Ecological Modelling, Elsevier, vol. 291(C), pages 1-5.
    8. 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.
    9. Colomer, M. Àngels & Margalida, Antoni & Sanuy, Delfí & Pérez-Jiménez, Mario J., 2011. "A bio-inspired computing model as a new tool for modeling ecosystems: The avian scavengers as a case study," Ecological Modelling, Elsevier, vol. 222(1), pages 33-47.

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