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MODELLING IN SCIENCE
As if the world isn’t complicated enough, tackling current sustainability challenges requires transdisciplinary understanding and action that is sensitive to the contexts where challenges emerge. Researchers thus aim to develop methods and tools that can help them navigate these dimensions.
A new article published in Ecology and Society discusses the role that modelling has played and can play when conducting resilience-based social-ecological systems (SES) research. It is authored by centre researcher Maja Schlüter who collaborated with researchers from the Helmholtz Centre for Environmental Research and from the University of Osnabrück in Germany.
The authors start by providing a helpful review of various model types and purposes as they have been used across different disciplines that contribute to SES research such as ecology, resource economics, land system sciences, social simulation, and participatory natural resource management. They then offer SES researchers an easy-to-use guide to understanding existing model types and their suitability to meeting different research aims.
By creating a reference scheme called “modeling for SES research" (ModSES) that places approaches along two dimensions – one, a model’s ability to incorporate different knowledge types (degree of integration) and two, its ability to represent the specifics of studied contexts (realism) – the authors demonstrate how modelling can play a more significant role in resilience-based research.
We believe that a deeper engagement of the SESs research community with dynamic modeling, and of the modeling community with recent developments in SESs research, can help advance the field and enhance the understanding and governance of SESs as complex adaptive systems.
Maja Schlüter, lead author
In their review of 52 resilience modeling studies published between 1998 and 2011, the authors found that most past models were developed to understand and manage the persistence of ecological or natural resource systems in the face of disturbance or change.
Few modeling studies addressed adaptation or transformation. A majority of early resilience models aimed at understanding were generic which limits their ability to account for the on-ground reality of sustainability issues. Models for decision support or policy analysis often aimed at finding optimal management strategies or explore impacts and tradoffs between alternative management strategies.
Many models have also lacked the ability to incorporate social-ecological feedbacks e.g. when studying the impacts of anthropogenic drivers on ecological resilience, models have failed to account for the ways in which humans respond (or not) to emerging ecosystem change. This thus reduces the potential of models to help understand the realities as they unfold in contexts where such feedback loops are inevitable.
Taking a step forward from the past, Schlüter and her colleagues have identified five SES research aims that they feel can benefit from a greater involvement of modelling.
Essentially, models are tools that serve the objectives researchers set. Hence, knowing the objective is crucial when determining the most suitable model type. Models can serve a variety of purposes ranging from acting as analytical tools that help in theory generation to being tools that help to explore possible future sustainable pathways and support social learning.
The authors offer a list of the different model types such as dynamical system models, bioeconomic models and structurally realistic models (also called agent-based models) that have their origins in different disciplines, but that can be leveraged in a variety of SES research applications and processes of engagement.
The reference scheme ModSES delineates a space to map different research aims and align them with suitable modelling approaches.
“ModSES is intended as a tool to help modellers, non-modellers, students, policy makers, and other stakeholders interested in using models or modelling for SESs research to navigate the diversity of model types as well as model building and application processes used in SESs research and related fields,” says Schlüter.
The authors emphasise that models are “simplified representations of reality” and results “should always be interpreted” keeping in mind the assumptions and system understandings that researchers initially started with. What is apparent from the article is that models can provide much-needed assistance to researchers addressing the increasingly complex and uncertain realities of our times.
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.
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