Individual-based models: Past, present and future

Viktoriia Radchuk, Stephanie Kramer-Schadt and Cédric Scherer, Department of Ecological Dynamics, Leibniz Institute for Zoo and Wildlife Research (IZW), Berlin, Germany, Uta Berger and Pia Backmann, Institute of Forest Growth and Computer Sciences, TU Dresden, Tharandt, Germany, Volker Grimm, Department of Ecological Modeling, Helmholtz Centre for Ecological Research - UFZ, Leipzig, Germany

Background/Question/Methods
Individual-based models (IBMs, also known as agent-based models) are mechanistic models in which demographic population trends emerge from processes at the individual level. IBMs are used instead of more aggregated approaches whenever one or more of the following aspects are deemed too relevant to be ignored: intraspecific trait variation, local interactions, adaptive behaviour, and response to spatially and temporally heterogeneous environments. IBMs offer a high degree of flexibility and therefore vary widely in structure and resolution, depending on the research question, the system under investigation and the available data. The data used to parameterize an IBM can be divided into two broad categories: species and environmental data. In addition, unlike other model types, qualitative empirical knowledge can be taken into account via probabilistic rules.
Results/Conclusions
We present three examples of IBMs: a vole-mustelid model used to understand the mechanisms underlying population cycles in rodents; a wild boar-virus model to study the persistence of wildlife diseases in heterogeneous landscapes; and a wild tobacco-moth caterpillar model to study the emergence of delayed chemical plant defence against insect herbivores. These examples demonstrate the ability of IBMs to decipher the mechanisms driving observed phenomena at the population level and their role in planning applied conservation measures. IBMs typically require more data and effort than other model types, but the rewards in terms of structural realism, understanding and decision support are high.