| Summary: | We live in a complex, interconnected and constantly changing world. Human driven global climate change is now a local reality that reinforces the inherent need for adaptability in human systems. Adaptability, the capacity to adapt to disturbance and change and navigate system transformation, can be understood as a function of socio-political interactions. The capacity of governing systems to deal with novel challenges through novel forms of interaction is a key issue in the governance literature, but which is only beginning to be explored. We therefore know little of how global change will impact the local level and how institutions and governing systems will respond. The need for adaptability is likely to be more pronounced for tightly coupled human-environmental systems. Indigenous and natural resource dependent communities in general, and in the Northern hemisphere in particular, are among the most exposed to ongoing and projected climate change. In Sweden, reindeer husbandry is an Indigenous Sami livelihood and extensive land-use practice highly exposed to weather conditions and increasing competition over land and resources. Whereas herders struggle to deal with the challenges that now confront them, the practice is also known as resilient and sustainable, having withstood large-scale social, ecological and economic change before. The aim with this thesis is to explore adaptability from a governancetheoretical perspective in the case of Sami reindeer husbandry in Sweden. The thesis thereby contributes to the emerging literatures on governance and adaptability and addresses empirically identified needs. Theoretically, the thesis draws on Kooiman’s interactive governance framework, which offers a multidimensional approach to governance analysis where structural aspects are addressed through modes (self-, coand hierarchical governing) and intentional aspects through governing elements (images, instruments and action). While conceptually encompassing, the framework has rarely been employed in empirical ...
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