Skip to Main content Skip to Navigation
Journal articles

From the Lotka–Volterra model to a spatialised population-driven individual-based model

Abstract : The modelling of predator–prey dynamics is of great importance in ecology. Models based on differential equations aim to understand the interactions between populations of prey and predators at population scale, but they are unable to handle spatial and individual behaviour heterogeneities (individual scale). In this study, a population-driven individual-based model is proposed that has been developed from the archetypical Lotka–Volterra model. The population scale was retained for processes with slower dynamics, such as reproduction for both species and the natural death of predators. The individual scale was only used for the predation process, defining local rules for individual movements of prey and predators (related to a perception distance of predators and the presence of shelters for prey in the spatial environment) and to locate births and deaths. This model was compared with the Lotka–Volterra model. Simulations were able to exhibit the overall classic periodic evolution of population sizes with local variations. The effects of spatial heterogeneity were then explored through a range of prey refuge densities. The model was implemented on the Netlogo platform. This work illustrates how both individual and population scales may be linked through methodological choices in order to focus on the impacts of spatialisation and take into account the effects of spatial and individual heterogeneities
Complete list of metadatas
Contributor : Marion Amalric <>
Submitted on : Friday, December 12, 2014 - 4:36:01 PM
Last modification on : Wednesday, May 27, 2020 - 5:51:25 PM



Hugo Thierry, David Sheeren, Nicolas Marilleau, Claude Monteil, Nathalie Corson, et al.. From the Lotka–Volterra model to a spatialised population-driven individual-based model. Ecological Modelling, Elsevier, 2014, 306 (June 2015), (2014). ⟨10.1016/j.ecolmodel.2014.09.022⟩. ⟨hal-01094650⟩



Record views