Ben Nagel

• Over the last few decades, environmental governance research has embraced a complex adaptive systems (CAS) framing: solving sustainability challenges requires an understanding of the social-ecological systems (SES) they are embedded in, consisting of interlinked components and relationships which form dynamic and emergent patterns. Many frameworks have been developed to help conceptually understand SES, however less focus has been given to advancing methods for SES research. I identify a particular need to advance quantitative SES methods, as despite a growing range of available approaches, much quantitative SES research heavily relies on classic statistical methods which by design ignore interactive effects and focus on reducing systems to individual variables. This creates tensions when applied to systems shaped by highly interactive and context-sensitive processes. Further, despite an emphasis on standardizability, quantitative research has not led to widespread synthesis of SES knowledge. There is a need to advance quantitative SES methods in ways which 1) incorporate complex system properties into case studies and 2) synthesize generalizable findings across cases without overly abstracting case complexity. In this thesis I explore these methodological challenges within the literature on Elinor Ostrom’s social-ecological systems framework (SESF). I then apply recent advances in methods for complexity through the case study of small-scale aquaculture governance in Indonesia: a participatory modeling method called fuzzy cognitive mapping to analyze “mental models” of aquaculture complexity, and archetypes analysis to synthesize generalizable patterns in complexity across a large set of heterogeneous aquaculture cases. I conclude that advancing SES methods to inform sustainable outcomes requires more critical engagement with “complex systems thinking” in not only conceptualizing environmental governance problems but also in empirical research design.