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Predator overcomes the Allee effect due to indirect prey–taxis

Y. Tyutyunov,Deeptajyoti Sen,L. Titova,M. Banerjee

Published 2019 in Ecological Complexity : An International Journal on Biocomplexity in the Environment and Theoretical Ecology

ABSTRACT

Abstract A mathematical model for spatiotemporal dynamics of prey–predator system was studied by means of linear analysis and numerical simulations. The model is a system of PDEs of taxis–diffusion–reaction type, accounting for the ability of predators to detect the locations of higher prey density, which is formalized as indirect prey–taxis, according to hypothesis that the taxis stimulus is a substance being continuously emitted by the prey, diffusing in space and decaying with constant rate in time (e.g. odour, pheromone, exometabolit). The local interactions of the prey and predators are described by the classical Rosenzweig – MacArthur system, which is modified in order to take into account the Allee effect in the predator population. The boundary conditions determine the absence of fluxes of population densities and stimulus concentration through the habitat boundaries. The obtained results suggest that the prey–taxis activity of the predator can destabilize both the stationary and periodic spatially-homogeneous regimes of the species coexistence, causing emergence of various heterogeneous patterns. In particular, it is demonstrated that formation of local dense aggregations induced by prey–taxis allows the predators to overcome the Allee effect in its population growth, avoiding the extinction that occurs in the model in the absence of spatial effects.

PUBLICATION RECORD

  • Publication year

    2019

  • Venue

    Ecological Complexity : An International Journal on Biocomplexity in the Environment and Theoretical Ecology

  • Publication date

    2019-08-01

  • Fields of study

    Biology, Mathematics, Environmental Science

  • Identifiers
    DOI 10.1016/J.ECOCOM.2019.100772
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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