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      <ref-type name="Journal Article">17</ref-type>
      <work-type>ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES</work-type>
      <contributors>
        <authors>
          <author>
            <style face="bold" font="default" size="100%">Faugeras, Blaise</style>
          </author>
          <author>
            <style face="bold" font="default" size="100%">Maury, Olivier</style>
          </author>
        </authors>
      </contributors>
      <titles>
        <title>Modeling fish population movements : From an individual-based representation to an advection-diffusion equation</title>
        <secondary-title>Journal of Theoretical Biology</secondary-title>
      </titles>
      <pages>837-848</pages>
      <keywords>
        <keyword>population dynamics</keyword>
        <keyword>biased random walk</keyword>
        <keyword>individual based model</keyword>
        <keyword>partial differential equation</keyword>
      </keywords>
      <dates>
        <year>2007</year>
      </dates>
      <call-num>fdi:010040753</call-num>
      <language>ENG</language>
      <periodical>
        <full-title>Journal of Theoretical Biology</full-title>
      </periodical>
      <isbn>0022-5193</isbn>
      <accession-num>CC:0002489907-0023</accession-num>
      <number>4</number>
      <electronic-resource-num>10.1016/j.jtbi.2007.04.012</electronic-resource-num>
      <urls>
        <related-urls>
          <url>https://www.documentation.ird.fr/hor/fdi:010040753</url>
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        <pdf-urls>
          <url>https://www.documentation.ird.fr/intranet/publi/2007/10/010040753.pdf</url>
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      <volume>247</volume>
      <remote-database-provider>Horizon (IRD)</remote-database-provider>
      <abstract>In this paper, we address the problem of modeling fish population movements. We first consider a description of movements at the level of individuals. An individual -based model is formulated as a biased random walk model in which the velocity of each fish has both a deterministic and a stochastic component. These components are function of a habitat suitability index, h, and its spatial gradient Vh. We derive an advection-diffusion partial differential equation (PDE) which approximates this individual- based model (IBM). The approximation process enables us to obtain a mechanistic representation of the advection and diffusion coefficients which improves the heuristic approaches of former studies. Advection and diffusion are linked and exhibit antagonistic behaviors: strong advection goes with weak diffusion leading to a directed movement of fish. On the contrary weak advection goes with strong diffusion corresponding to a searching behavior. Simulations are conducted for both models which are compared by computing spatial statistics. It is shown that the PDE model is a good approximation to the IBM.</abstract>
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