In an analysis of the 200‐year history of flood management in Hungary, I use the advocacy coalition framework and the focusing event literature to examine what policy change occurs and what is learned as a result of experiencing extreme and damaging flood events. By analyzing the policy response to a series of extreme floods (1998–2001) in this newly democratizing nation, I attempt to identify the factors that influenced the occurrence of policy change and policy‐oriented learning. In 2003, Hungary enacted a comprehensive flood management program that included economic development and environmental protection goals, a distinct departure from Hungary's historical structural approach to flood management. However, it is less clear that long‐lasting changes in belief systems about how floods should be managed have occurred. In this analysis, I argue that processes external to the flood policy subsystem (e.g., process of democratization and Hungary's accession to the European Union), along with the occurrence of the extreme flood events, enabled a coalition of individuals and organizations to press for policy change.

Organizations managing forest land often make fire management decisions that seem overly risk-averse in relation to their stated goals for ecosystem restoration, protection of sensitive species and habitats, and protection of water and timber resources. Research in behavioral decision theory has shown that people faced with difficult decisions under uncertainty and decisions with multiple and conflicting objectives adopt mental shortcuts that systematically bias decision-making. Fire management decisions exhibit exactly the characteristics that are likely to trigger such mental shortcuts. Cumulative and unwitting use of mental shortcuts can lead to fire management decisions that are excessively risk-averse, to the point of jeopardizing stated management goals. It can also cause retrospective analyses of fire decisions to focus inappropriately on placing blame for bad outcomes and fail to scrutinize the quality of the decision itself. Excessive risk aversion is evident in the behavior of individual land managers, land management organizations, regulatory agencies that review land management decisions, and the general public and its agents in the media, courts and legislature. Remedies to excessive risk aversion include: (1) wider use of structured decision processes designed to counteract the mental shortcuts that plague human decision-making, (2) structural and educational changes within and between organizations to change perverse incentives that reward risk aversion and discourage adaptive management, and (3) locally focused collaborations among land management agencies, regulatory agencies, and citizens to build trust and to enhance understanding of forest management goals and practices. #

Natural disasters may be windows of opportunity for policy change and learning by local governments, which are the entities primarily responsible for the recovery and rebuilding process after a disaster strikes in the United States. During disaster recovery, local governments are faced with myriad policy challenges, from technical issues concerning the repair and replacement of infrastructure to broader substantive questions of reducing vulnerability to future hazards. Their actions are constrained by federal and state policies related to disaster recovery, and yet they must make their own decisions regarding disaster recovery finance within those constraints. These decisions may then influence a local government's long‐term fiscal planning, such as their target level of budget reserves, borrowing, categories of spending, and mechanisms to generate revenue. To assess how local governments respond to and learn from fiscal constraints during disaster recovery, we analyze flood recovery in seven Colorado communities in the three counties most impacted by extreme flooding in 2013. Data from in‐depth interviews with local finance personnel and other administrators, budgets, and public documents are used to analyze recovery decisions and postdisaster fiscal policy learning. While most local governments drew instrumental lessons from the disaster experience, such as how to better manage grant reimbursement processes, some also drew broader lessons that may contribute to achieving longer term community resilience, fiscal stability, and disaster preparedness.

Current and future climate-related coastal impacts such as catastrophic and repetitive flooding, hurricane intensity, and sea level rise necessitate a new approach to developing and managing coastal infrastructure. Traditional “hard” or “grey” engineering solutions are proving both expensive and inflexible in the face of a rapidly changing coastal environment. Hybrid solutions that incorporate natural, nature-based, structural, and non-structural features may better achieve a broad set of goals such as ecological enhancement, long-term adaptation, and social benefits, but broad consideration and uptake of these approaches has been slow. One barrier to the widespread implementation of hybrid solutions is the lack of a relatively quick but holistic evaluation framework that places these broader environmental and societal goals on equal footing with the more traditional goal of exposure reduction. To respond to this need, the Adaptive Gradients Framework was developed and pilot-tested as a qualitative, flexible, and collaborative process guide for organizations to understand, evaluate, and potentially select more diverse kinds of infrastructural responses. These responses would ideally include natural, nature-based, and regulatory/cultural approaches, as well as hybrid designs combining multiple approaches. It enables rapid expert review of project designs based on eight metrics called “gradients”, which include exposure reduction, cost efficiency, institutional capacity, ecological enhancement, adaptation over time, greenhouse gas reduction, participatory process, and social benefits. The framework was conceptualized and developed in three phases: relevant factors and barriers were collected from practitioners and experts by survey; these factors were ranked by importance and used to develop the initial framework; several case studies were iteratively evaluated using this technique; and the framework was finalized for implementation. The article presents the framework and a pilot test of its application, along with resources that would enable wider application of the framework by practitioners and theorists.

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