Ecology and Society (Jun 2018)

Combining participatory scenario planning and systems modeling to identify drivers of future sustainability on the Mongolian Plateau

  • Ginger R. H. Allington,
  • Maria E. Fernandez-Gimenez,
  • Jiquan Chen,
  • Daniel G. Brown

DOI
https://doi.org/10.5751/ES-10034-230209
Journal volume & issue
Vol. 23, no. 2
p. 9

Abstract

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The study of social-ecological systems (SES) is an inherently interdisciplinary endeavor that necessitates collaboration among multiple researchers and stakeholders. These collaborations often result in novel insights into the dynamics and feedbacks that occur within these systems. Achieving these insights requires methods and tools that integrate diverse knowledge from multiple disciplines and sectors of society to inform actionable research on complex systems. Past research has demonstrated the contributions that stakeholders can make to defining scenarios that are subsequently applied to quantitative modeling. Here, we focus on the feedback from quantitative modeling to refinement and interpretation of scenarios, and demonstrate how quantitative modeling can reveal aspects of system dynamics that were not considered during scenario development. We present a case study in which we use qualitative scenario planning as a tool to engender systems thinking by a diverse set of stakeholders in a complex transboundary SES: the Mongolian Plateau. This exercise demonstrated the value of participatory scenario planning as a tool for facilitating interdisciplinary and cross-sectoral dialog and knowledge generation. It also ensured the integration of place-based knowledge into scenario development for subsequent quantitative modeling. In addition to incorporating stakeholder knowledge in simulation of complex human-environment dynamics, the quantitative modeling revealed how the dynamics of rural out-migration contribute to the decoupling of rural herder populations and livestock numbers. The emergent knowledge gained from this process underscores the utility of pairing the qualitative scenarios with quantitative simulations to reveal unanticipated system behavior and key drivers not identified or overlooked by stakeholders.

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