Individual-based modelling (IBM) is an important option in ecology for the study of specific properties of complex ecological interaction networks. The main application of this model type is the analysis of population characteristics at high resolution. IBM also contributes to the advancement of ecological theory. One of the remarkable potentials of the approach is the possibility of studying self-organization and emergent properties that arise from individual actions on higher integration levels, especially on the population level.This review outlines the background and different application fields of individual-based models together with a short description of the technical implications of model setup. The limitations of this modelling approach result from the technical basis of model construction, which can handle a limited number of active entities only. Limits in biological knowledge also restrict the application of this model type. The paper presents some individual-based models that have been developed for different purposes and briefly discusses these models. Concerning the perspective of IBM, a coincidence with developments in artificial life research is explained. IBM shifts the focus of ecological analysis of dynamic systems from structurally fixed settings to the analysis of self-organizing interaction patterns that are variable in quantity and quality.
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