The disaster chronotope : Spatial and temporal learning in governance of extreme events

How does the type of disaster affect the learning among key stakeholder groups? This chapter provides a framework of disaster governance through examination of local and global response strategies based on the spatial and temporal attributes (or chronotope) of disaster events and related discourse. A series of case studies builds on the concept of “panarchy” in resilience and adaptation sciences to reveal the interaction between disasters and the capacity of various stakeholder groups to adjust the rules and assumptions that underlie disaster governance. With particular focus on patterns of learning, we map our findings in a matrix to reveal disasters as complex social-ecological processes at three levels: (1) the small fast-moving local system, (2) the nation-state as the intermediate level in speed and size, and (3) the global community of nation-states as the largest, slowest moving social system

The disaster chronotope : Spatial and temporal learning in governance of extreme events

How does the type of disaster affect the learning among key stakeholder groups? This chapter provides a framework of disaster governance through examination of local and global response strategies based on the spatial and temporal attributes (or chronotope) of disaster events and related discourse. A series of case studies builds on the concept of “panarchy” in resilience and adaptation sciences to reveal the interaction between disasters and the capacity of various stakeholder groups to adjust the rules and assumptions that underlie disaster governance. With particular focus on patterns of learning, we map our findings in a matrix to reveal disasters as complex social-ecological processes at three levels: (1) the small fast-moving local system, (2) the nation-state as the intermediate level in speed and size, and (3) the global community of nation-states as the largest, slowest moving social system

Scenarios thinking for the Bering-Chukchi-Beaufort Region

A number of biophysical and socio-economic drivers will have a significant influence on future vulnerability, risk, resilience, and adaptation planning in the Bering-Chuckchi-Beaufort (BCB) region ( Chapters 4-7). The trajectories of some of those drivers are amenable to modeling, forecasting, or projection. However, the future is inherently uncertain, particularly over long time horizons. Scenarios have been used for over 50 years as a tool for exploring such uncertainty in order to identify key driving forces and critical unknowns, as well as to generate shared understanding among stakeholders regarding the potential for, and implications of, alternative futures (van Notten et al., 2003; Bishop et al., 2007; Avango et al., 2013). This chapter provides a general overview of scenarios and their value for understanding the implications of a changing climate within the broader context of global change. The chapter includes a review of how scenarios have been used previously to understand climate change vulnerability, risk, and resilience, with a particular emphasis on the Arctic. It also introduces a new series of qualitative regional and subregional socio­economic scenarios for the BCB region, peering into the future to 2050, and discusses their implications for climate change impacts as well as adaptation planning and implementation