Browsing by Author "Albright, EA"

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Open Access
Can behavioral decision theory explain risk-averse fire management decisions?
(Forest Ecology and Management, 2005-06-06) Maguire, LA; Albright, EA
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. © 2005 Elsevier B.V. All rights reserved.
Open Access
Pathways to coastal resiliency: The Adaptive Gradients Framework
(Sustainability (Switzerland), 2018-07-26) Hamin, EM; Abunnasr, Y; Dilthey, MR; Judge, PK; Kenney, MA; Kirshen, P; Sheahan, TC; DeGroot, DJ; Ryan, RL; McAdoo, BG; Nurse, L; Buxton, JA; Sutton-Grier, AE; Albright, EA; Marin, MA; Fricke, R
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.