Abstract:Global climate change poses significant risks to the security and livelihoods of people around the world, and people are adapting to address these risks, but some people--some individuals, households, communities, organizations, and nations--are able to adapt more quickly and easily than others. Adaptation scientists call this ability adaptive capacity, and building adaptive capacity may be key to reducing global vulnerability to long-term change. This dissertation contributes to a growing body of research on adaptive capacity, and to the field of adaptation science more broadly, by proposing new approaches to define, assess, and apply adaptive capacity. I use computational text mining, natural language processing, and network analysis techniques drawn from the digital humanities to build a conceptual model of how various factors interact to build adaptive capacity. Using this model, I argue that the core elements of adaptive capacity are a set of five abilities, rather than capital assets, and that these abilities apply across scales and global contexts. I propose a capacity-based framework centered on these five abilities as a means to assess adaptive capacity and apply it to a case of urban adaptation planning in London, UK, to illustrate the utility of multi-scale assessment. Results of the dissertation reconcile a theoretical divide within the field, raise new questions about theoretical limits of adaptability and the rate of social adaptation, and suggest an alternative approach to allocating adaptation resources.