Modeling Socio-Environmental Systems

Full Title

Use of socio-environmental systems modelling in actionable science: state-of-the-art, open challenges and opportunities


Computer models are commonly used by researchers in actionable science to inform decision-making and policy design in complex socio-environmental problems. Models are useful for generating, synthesising, and validating existing knowledge to help understand the long terms effects of human decisions on socio-economic and environmental systems. To improve the utility and impact of using models to inform policy in the future, it is crucial to keep advancing the way we develop and use these models. Towards this end, the objective of the workshop is to bring together a cross- disciplinary group of researchers to synthesize existing knowledge and datasets on the use of models to inform decision making in socio-environmental problems. This synthesis will result in a position journal paper to consolidate the existing experiences and current discussions in the field, and illuminate the remaining challenges and opportunities in order to advance the science and practice of socio-environmental modelling. Key challenges and opportunities may include how to improve the way we incorporate human factors (e.g. behaviours, values) into models to improve their relevance for stakeholders. Findings from this synthesis project will inform future actionable science efforts in the crucial and increasingly important area of developing and using computer models to support decision-making.

Project Type
Team Synthesis Project
Principal Investigators
Albert Kettner, University of Colorado
Tony Jakeman, Australian National University
Tatiana Filatova, University of Technology Sydney
Isaac I. Ullah, San Diego State University
Jonathan Gilligan, Vanderbilt Univeristy
Marcus Alexander Janssen, Arizona State University
Moira Zellner, Northeastern University
Julie Rozenberg, World Bank
Ioannis Athanasiadis, Wageningen University
Rob Axtell, George Mason University
Dan Brown, UMICH
John Little, Virginia Tech

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