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Memory keeps you at home: a mechanistic model for home range emergence

Authors

  • Bram Van Moorter,

  • Darcy Visscher,

  • Simon Benhamou,

  • Luca Börger,

  • Mark S. Boyce,

  • Jean-Michel Gaillard


B. Van Moorter (bram.van.moorter@gmail.com) and J.-M. Gaillard, Unité Mixte de Recherche No. 5558 « Biométrie et Biologie Evolutive », Bâtiment 711, Univ. Claude Bernard Lyon 1, 43 Boulevard du 11 novembre 1918, FR–69622 Villeurbanne Cedex, France. Present address for BVM: Dept of Biology, NTNU, Høgskoleringen 5, NO–7491 Trondheim, Norway. – D. Visscher and M. S. Boyce, Dept of Biological Sciences, Univ. of Alberta, Edmonton, AB T6G 2E9, Canada. – S. Benhamou, Unité Mixte de Recherche No. 5175 «Ecologie Fonctionnelle et Evolutive », 1919 Route de Mende, FR–34293 Montpellier cedex 5, France. – L. Börger, Dept of Integrative Biology, Univ. of Guelph, Guelph, ON N1G 2W1, Canada.

Abstract

Despite its central place in animal ecology no general mechanistic movement model with an emergent home-range pattern has yet been proposed. Random walk models, which are commonly used to model animal movement, show diffusion instead of a bounded home range and therefore require special modifications. Current approaches for mechanistic modeling of home ranges apply only to a limited set of taxa, namely territorial animals and/or central place foragers. In this paper we present a more general mechanistic movement model based on a biased correlated random walk, which shows the potential for home-range behavior. The model is based on an animal tracking a dynamic resource landscape, using a biologically plausible two-part memory system, i.e. a reference- and a working-memory. Our results show that by adding these memory processes the random walker produces home-range behavior as it gains experience, which also leads to more efficient resource use. Interestingly, home-range patterns, which we assessed based on home-range overlap and increase in area covered with time, require the combined action of both memory components to emerge. Our model has the potential to predict home-range size and can be used for comparative analysis of the mechanisms shaping home-range patterns.

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