The potential of models and modeling for social-ecological systems research: the reference frame ModSES

Author(s): Schlüter, M., B. Müller, and K. Frank.
In: Ecology and Society 24(1):31.https://doi.org/10.5751/ES-10716-240131
Year: 2019
Type: Journal / article
Theme affiliation: Complex Adaptive Systems
Link to centre authors: Schlüter, Maja
Full reference: Schlüter, M., B. Müller, and K. Frank. 2019. The potential of models and modeling for social-ecological systems research: the reference frame ModSES. Ecology and Society 24(1):31.https://doi.org/10.5751/ES-10716-240131

Summary

 Dynamic models have long been a common tool to support management of ecological and economic systems and played a prominent role in the early days of resilience research. Model applications have largely focused on policy assessment, the development of optimal management strategies, or analysis of system stability. However, modeling can serve many other purposes such as understanding system responses that emerge from complex interactions of system components, supporting participatory processes, and analyzing consequences of human behavioral complexity. The diversity of purposes, types, and applications of models offers great potential for social-ecological systems (SESs) research, but has created much confusion because modeling approaches originate from different disciplines, are based on different assumptions, focus on different levels of analysis, and use different analytical methods. This diversity makes it difficult to identify which approach is most suitable for addressing a specific question. Here, our aims are: (1) to introduce the most common types of dynamic models used in SESs research and related fields, and (2) to align these models with SESs research aims to support the selection and communication of the most suitable approach for a given study. To this end, we organize modeling approaches into a reference scheme called “modelling for social-ecological systems research” (ModSES) along two dimensions: the degree of realism and the degree of knowledge integration. These two dimensions capture key challenges of SESs research related to the need to account for context dependence and the intertwined nature of SESs as systems of humans embedded in nature across multiple scales, as well as to acknowledge different problem framings, understandings, interests, and values. We highlight the need to be aware of the potentials, limitations, and conceptual backgrounds underlying the different approaches. Critical engagement with modeling for different aims of SESs research can contribute to developing integrative understanding and action toward enhanced resilience and sustainability.

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