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A modeling approach of the chemostat

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  • Fritsch, Coralie
  • Harmand, Jérôme
  • Campillo, Fabien

Abstract

Population dynamics and in particular microbial population dynamics, though intrinsically discrete and random, are conventionally represented as deterministic differential equations systems. In these type of models, populations are represented by continuous population sizes or densities usually with deterministic dynamics.

Suggested Citation

  • Fritsch, Coralie & Harmand, Jérôme & Campillo, Fabien, 2015. "A modeling approach of the chemostat," Ecological Modelling, Elsevier, vol. 299(C), pages 1-13.
    • Handle: RePEc:eee:ecomod:v:299:y:2015:i:c:p:1-13
    DOI: 10.1016/j.ecolmodel.2014.11.021
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    References listed on IDEAS

    as
    1. Campillo, F. & Lobry, C., 2012. "Effect of population size in a predator–prey model," Ecological Modelling, Elsevier, vol. 246(C), pages 1-10.
    2. Deygout, C. & Lesne, A. & Campillo, F. & Rapaport, A., 2013. "Homogenised model linking microscopic and macroscopic dynamics of a biofilm: Application to growth in a plug flow reactor," Ecological Modelling, Elsevier, vol. 250(C), pages 15-24.
    3. Campillo, F. & Joannides, M. & Larramendy-Valverde, I., 2011. "Stochastic modeling of the chemostat," Ecological Modelling, Elsevier, vol. 222(15), pages 2676-2689.
    4. Hellweger, Ferdi L. & Bucci, Vanni, 2009. "A bunch of tiny individuals—Individual-based modeling for microbes," Ecological Modelling, Elsevier, vol. 220(1), pages 8-22.
    5. Campillo, F. & Champagnat, N., 2012. "Simulation and analysis of an individual-based model for graph-structured plant dynamics," Ecological Modelling, Elsevier, vol. 234(C), pages 93-105.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Sun, Shulin & Sun, Yaru & Zhang, Guang & Liu, Xinzhi, 2017. "Dynamical behavior of a stochastic two-species Monod competition chemostat model," Applied Mathematics and Computation, Elsevier, vol. 298(C), pages 153-170.
    2. Wade, M.J. & Harmand, J. & Benyahia, B. & Bouchez, T. & Chaillou, S. & Cloez, B. & Godon, J.-J. & Moussa Boudjemaa, B. & Rapaport, A. & Sari, T. & Arditi, R. & Lobry, C., 2016. "Perspectives in mathematical modelling for microbial ecology," Ecological Modelling, Elsevier, vol. 321(C), pages 64-74.
    3. Nguyen, Dang H. & Nguyen, Nhu N. & Yin, George, 2020. "General nonlinear stochastic systems motivated by chemostat models: Complete characterization of long-time behavior, optimal controls, and applications to wastewater treatment," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 4608-4642.
    4. Fritsch, Coralie & Campillo, Fabien & Ovaskainen, Otso, 2017. "A numerical approach to determine mutant invasion fitness and evolutionary singular strategies," Theoretical Population Biology, Elsevier, vol. 115(C), pages 89-99.
    5. Bouderbala, Ilhem & El Saadi, Nadjia & Bah, Alassane & Auger, Pierre, 2019. "A simulation study on how the resource competition and anti-predator cooperation impact the motile-phytoplankton groups’ formation under predation stress," Ecological Modelling, Elsevier, vol. 391(C), pages 16-28.

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