Over the next decade, IIASA research will address itself to transformational changes towards sustainable social-economic-environmental systems. To underpin this research with methodological advances, the Exploratory Modeling of Human-natural Systems Research Group (EM) focuses on three modeling areas:
EM deploys a flexible multi-model approach that involves stylized models, intermediate-complexity models, and micro-level detailed simulators. To account for socioeconomic complexity, EM exploits the digital revolution and makes use of the progress in computing capabilities to develop micro-level detailed economic simulators, such as agent-based models that allow studying the economy out of equilibrium, account for heterogeneous agents, and relaxes the assumption of rational expectations.
Intermediate complexity models of Earth systems enable investigating these systems on long timescales or at reduced computational cost and make the inclusion of previously unincorporated earth-systems and feedback effects feasible. Furthermore, EM contributes to the development of methods and models for eco-evolutionary dynamics, in particular the theory of adaptive dynamics and more detailed eco-genetic models to address biodiversity in Earth’s ecosystems.
Stylized models of different processes are developed and used for hypothesis testing and to explore the richness of systems dynamics including, non-linearities, tipping points, etc. Model processing and analysis addresses itself to methods and approaches from the theory of dynamic systems, adaptive dynamics, evolutionary game theory, optimal control theory, stochastic optimization, mathematical statistics, model linkage, and reinforcement learning, among other areas.
Last edited: 21 April 2021
Mukhortova, L., Shchepashchenko, D. , Moltchanova, E., Shvidenko, A., Khabarov, N. , & See, L. (2021). Respiration of Russian soils: climatic drivers and response to climate change. Science of the Total Environment 785, e147314. 10.1016/j.scitotenv.2021.147314.
Choruma, D.J., Balkovič, J. , Pietsch, S. , & Odume, O.N. (2021). Using EPIC to simulate the effects of different irrigation and fertilizer levels on maize yield in the Eastern Cape, South Africa. Agricultural Water Management 254, e106974. 10.1016/j.agwat.2021.106974.
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