This paper is an output of an ongoing EU Horizon 2020 project (MAGIC) that aims to better understand how EU water, food, energy, waste and biodiversity policies link with each other and with EU climate and sustainability goals, framed in terms of the nexus concept. The project conducts transdisciplinary research with policy makers using an approach termed Quantitative Story Telling (QST), as an interface between science and policy domains. QST combines semantic (qualitative) and formal (quantitative) approaches to assess the plausibility, normative fairness and analytical coherence of narratives being used by stakeholders to justify either the status quo or alternative policy positions for the EU. The paper focuses on those aspects of the MAGIC analysis highlighted by external reviewers of the project as being most insightful and having the most potential value to a wider community of practice concerned with supporting or evaluating sustainability related policies. The paper outlines the process of QST used and the quantitative method used, multi-scale societal metabolism analyses (SMA) assessing the funds of land and human time needed to create the flows of materials, energy and money that reproduce and maintain the identity of the system of interest. As one of the five MAGIC policy studies, the authors focused on a key EU Common Agricultural Policy (CAP) narrative. CAP is a policy which is now expected to deliver multiple objectives across policy domains, but as implemented, potentially contributes to a tension between supporting competitiveness and delivering public goods. High-level findings that quantify aspects of this tension are presented, followed by specific technical issues found when conducting the analysis. The paper then reflects on the authors' use of these data to discuss with policy-makers issues where the tension between competitiveness and public goods are most stark; a more interpretive, qualitative phase of analysis that builds on the quantitative analysis. The outputs of the analysis used within the CAP QST imply the need for policy makers to consider alternative issue framings, otherwise they risk appearing to make only a rhetorical commitment to defining and delivering EU sustainability goals. The societal metabolic framing used in MAGIC highlights the biophysical underpinnings of EU farming systems; their dependence on non-renewable resources and the pressures generated by them that degrade ecosystem functions or services. A societal metabolic framing also means considering multiple scales, since otherwise EU policy is blind to the effects it has on sustainability beyond the borders of the EU. If research impact is defined in terms of acknowledged change in stakeholders' concepts or behaviours (an expected impact for the project by funders) then to date, there has been limited 'success'. While the rhetoric of 'evidence-based policy' remains prominent, it remains extremely challenging to engage with policy makers in deliberation on evidence that challenges conventional narratives. This was the case even for staff with extensive experience of inter- A nd transdisciplinary working at the science-policy interface. In conclusion, science for sustainability policy could benefit from adopting the approaches like QST, which can integrate and balance the semantic and formal parts of science for policy research. For the wider science-policy community of practice, the key insight is that for processes like QST the key decisions are made at the interfaces between the sematic and formal phases of analysis (what is modelled and why) and the formal and semantic phases of analysis (what the outputs mean and why they shouldn't be ignored).
CITATION STYLE
Matthews, K. B., Waylen, K. A., Blackstock, K. L., Juarez-Bourke, A., Miller, D. G., Wardell-Johnson, D. H., & Giampietro, M. R. M. (2019). Science for sustainability: Using societal metabolism analysis to check the robustness of european union policy narratives in the water, energy and food nexus. In 23rd International Congress on Modelling and Simulation - Supporting Evidence-Based Decision Making: The Role of Modelling and Simulation, MODSIM 2019 (pp. 877–883). Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ). https://doi.org/10.36334/modsim.2019.j5.matthews
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