Community-driven dispersal in an individual-based predator–prey model

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 densityindependent 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 2 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.

Analyzing the spatial dynamics of a prey–predator lattice model with social behavior

“…In Filotas et al (2008) the authors state that because of a lack of common rules behind the dispersal of species, ecologists often have to make the simplest assumptions (e.g., a density independent rate of dispersion) when modeling such phenomenon; even if for many species factors such as the local population size, resource availability, or habitat quality influence the mobility of individuals. However, there has been efforts to develop strategies that better mimic the phenomena found in natural ecosystems (Li et al, 2005;Boccara et al, 1994;Rozenfeld and Albano, 2001;Szwabiń ski, 2012;Wang et al, 2012).…”

“…The dispersal of individuals is one of the central mechanisms behind pattern formation in spatially explicit models (Hosseini, 2006;Filotas et al, 2008). A good approach to model such phenomenon is to use transition rules that describe a diffusion process: in Comins et al (1992), the authors study a hostparasitoid model on a rectangular grid of patches.…”

Positive interactions and the emergence of community structure in metacommunities

“…We hence allow individuals with low reproductive probability to escape their community in the "hope" of finding a more suitable one. We follow in philosophy the metapopulation model of Ruxton and Rohani (1999) and set up a tolerance threshold called p d (Filotas et al 2008), which we will simply refer to as the rate of dispersal. At each generation of the model following the reproduction process, the reproduction probability of each species (Eq.…”

Evolutionary ecology of movement by predators and prey

“…These gaps between theory and real organisms have become widely recognized, and biologists now benefit from a large body of theory that has explored patterns resulting from more realistic movement mechanisms, including the spatial patterns arising from interacting predators and prey (e.g., Abrams and Matsuda 2003;Abrams 2007Abrams , 2009Alonzo 2002;Amarasekare 2008Amarasekare , 2010Bouskila 2001;Cressman and Garay 2009;Cressman et al 2004;Filotas et al 2008;Heithaus 2001;Hugie and Dill 1994;Iwasa 1982;Jackson et al 2004;Kimbrell and Holt 2005;Křivan 1997; Křivan and Cressman 2009;Rosenheim 2004;Schwinning and Rosenzweig 1990;Sih 1984;van Baalen and Sabelis 1999;Wang and Takeuchi 2009) and hosts and parasites (e.g., Comins and Hassell 1979;Comins et al 1992;Godfray 1994;Green 2009;Hassell and May 1974;Hassell and Pacala 1990;Hassell et al 1991Hassell et al , 1994Jones et al 1993;Pacala et al 1990). …”