FilotasGrantParrottEtAl2008

Référence

Filotas, E., Grant, M., Parrott, L., Rikvold, P.A. (2008) Community-driven dispersal in an individual-based predator-prey model. Ecological Complexity, 5(3):238-251. (URL )

Résumé

We present a spatial, individual-based predator-prey model in which dispersal is dependent on the local community. We determine species suitability to the biotic conditions of their local environment through a time and space varying fitness measure. Dispersal of individuals to nearby communities occurs whenever their fitness falls below a predefined tolerance threshold. The spatiotemporal dynamics of the model is described in terms of this threshold. We compare this dynamics with the one obtained through density-independent dispersal and find marked differences. In the community-driven scenario, the spatial correlations in the population density do not vary in a linear fashion as we increase the tolerance threshold. Instead we find the system to cross different dynamical regimes as the threshold is raised. Spatial patterns evolve from disordered, to scale-free complex patterns, to finally becoming well-organized domains. This model therefore predicts that natural populations, the dispersal strategies of which are likely to be influenced by their local environment, might be subject to complex spatiotemporal dynamics.

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@ARTICLE { FilotasGrantParrottEtAl2008,
    AUTHOR = { Filotas, E. and Grant, M. and Parrott, L. and Rikvold, P.A. },
    TITLE = { Community-driven dispersal in an individual-based predator-prey model },
    JOURNAL = { Ecological Complexity },
    YEAR = { 2008 },
    VOLUME = { 5 },
    PAGES = { 238-251 },
    NUMBER = { 3 },
    MONTH = { sep },
    ABSTRACT = { We present a spatial, individual-based predator-prey model in which dispersal is dependent on the local community. We determine species suitability to the biotic conditions of their local environment through a time and space varying fitness measure. Dispersal of individuals to nearby communities occurs whenever their fitness falls below a predefined tolerance threshold. The spatiotemporal dynamics of the model is described in terms of this threshold. We compare this dynamics with the one obtained through density-independent dispersal and find marked differences. In the community-driven scenario, the spatial correlations in the population density do not vary in a linear fashion as we increase the tolerance threshold. Instead we find the system to cross different dynamical regimes as the threshold is raised. Spatial patterns evolve from disordered, to scale-free complex patterns, to finally becoming well-organized domains. This model therefore predicts that natural populations, the dispersal strategies of which are likely to be influenced by their local environment, might be subject to complex spatiotemporal dynamics. },
    KEYWORDS = { Community-driven dispersal, Spatial model, Predator-prey dynamics, Individual-based modeling, Spatiotemporal patterns },
    OWNER = { brugerolles },
    TIMESTAMP = { 2008.08.26 },
    URL = { http://www.sciencedirect.com/science/article/B7CRV-4S02D9N-1/2/fb54735351074bb04bccd142d5f7e9d9 },
}

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