Individual- and Agent-based Modelling
In individual-based models (IBMs), organisms are explicitly represented as discrete and unique entities, for example individual trees or birds. IBMs are used if one or more of the following aspects, that are hard to deal with in analytical models, are considered important: trait variability among individuals, local interactions, adaptive behaviour that is based on decision making, and heterogeneous and dynamic environments. Agent-based models (ABMs) follow the same rationale but have a stronger focus on decision making. Most simulation models developed in the Department of Ecological Modelling (ÖSA) include at least an individual- or agent-based aspect. Our most prominent IBM, FORMIND, describes tropical rain forests and is based on photosynthesis and vertical competition for light. Further recent ÖSA IBMs address grasslands, tigers in national parks, animal species for risk assessment of pesticides, or human decision making in socio-ecological systems. The department also was involved producing the first monograph on IBMs in ecology and a first textbook in agent-based modelling. Both, the ODD protocol for communicating IBMs, and „pattern-oriented modelling“, a strategy to make models structurally realistic, were launched by ÖSA.
- DeAngelis, D.L., Grimm, V., (2014):
Individual-based models in ecology after four decades
F1000Prime Reports 6 , art. 39
full text (pdf)
- Fischer R, Bohn F, de Paula MD, Dislich C, Groeneveld J, Gutiérrez AG, Kazmierczak M, Knapp N, Lehmann S, Paulick S,
Pütz S, Roedig E, Taubert F, Köhler P, Huth A (2016):
Lessons learned from applying a forest gap model to understand ecosystem and carbon dynamics of complex tropical forests.
Ecological Modelling (in press)
- Grimm, V., Railsback, S. F. (2005) Individual-based modeling and ecology Princeton series in theoretical and computational biology. Princeton University Press, Princeton, 428 S.
- Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., Thulke, H.-H., Weiner, J., Wiegand, T., DeAngelis, D. L. (2005) Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science 310 (5750), 987-991. Abstract
- Stillman, R.A., Railsback, S.F., Giske, J., Berger, U., Grimm, V., (2015):
Making predictions in a changing world: the benefits of individual-based ecology
Bioscience 65 (2), 140 - 150
full text (pdf)
- More publications
- Modelling species-rich forests: FORMIND
- Modelling honeybee colonies: BEEHAVE
- ODD protocol for describing IBMs and ABMs
- TRACE documents for documenting model "evaludation"