A review of systems modelling for local sustainability

Moallemi, E.A., Bertone, E., Eker, S. ORCID: https://orcid.org/0000-0003-2264-132X, Gao, L., Szetey, K., Taylor, N., & Bryan, B.A. (2021). A review of systems modelling for local sustainability. Environmental Research Letters 16 e113004. 10.1088/1748-9326/ac2f62.

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Abstract

The 17 Sustainable Development Goals (SDGs) represent a holistic and ambitious agenda for transforming the world towards societal well-being, economic prosperity, and environmental protection. Achieving the SDGs is, however, challenged by the performance of interconnected sectors and the complexity of their interactions which drive non-linear system responses, tipping points, and spillover effects. Systems modelling, as an integrated way of thinking about and modelling multisectoral dynamics, can help explain how feedback interactions within and among different sectors can lead to broader system transformation and progress towards the SDGs. Here, we review how system dynamics, as a prominent systems modelling approach, can inform and contribute to sustainability research and implementation, framed by the SDGs. We systematically analyse 357 system dynamics studies undertaken at the local scale where the most important SDG impacts and their initiators are often located, published between 2015 (i.e., SDGs' inception) and 2020. We analyse the studies to illuminate strengths and limitations in four key areas: diversity of scope; interdisciplinarity of the approaches; the role of stakeholder participation; and the analysis of SDG interactions. Our review highlights opportunities for a better consideration of societal aspects of sustainable development (e.g., poverty, inequality) in modelling efforts; integrating with new interdisciplinary methods to leverage system dynamics modelling capabilities; improving genuine stakeholder engagement for credibility and impacts on the ground; and a more in-depth analysis of SDG interactions (i.e., synergies and trade-offs) with the feedback-rich structure of system dynamics models.

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