Source: OHIO STATE UNIVERSITY submitted to
DECISION MAKING PROCESSES FOR ADAPTIVE ENVIRONMENTAL RISK MANAGEMENT
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
TERMINATED
Funding Source
Reporting Frequency
Annual
Accession No.
0201055
Grant No.
(N/A)
Project No.
OHO01104
Proposal No.
(N/A)
Multistate No.
(N/A)
Program Code
(N/A)
Project Start Date
Jul 1, 2004
Project End Date
Dec 31, 2005
Grant Year
(N/A)
Project Director
Arvai, J. L.
Recipient Organization
OHIO STATE UNIVERSITY
1680 MADISON AVENUE
WOOSTER,OH 44691
Performing Department
SCHOOL OF NATURAL RESOURCES
Non Technical Summary
The concept of adaptive management was born out of the need to address this objective of learning about managed environmental systems over time. But, despite a rich academic literature and the "common-sense" appeal of this approach, there are few real-world examples of successful adaptive management efforts. This project explores the feasibility of incorporating adaptive management processes as part of stakeholder-based environmental management recommendations using the tools of the decision sciences as a means of improving our understanding of how adaptive management may be implemented.
Animal Health Component
34%
Research Effort Categories
Basic
33%
Applied
34%
Developmental
33%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
12260503100100%
Goals / Objectives
IAdaptive environmental management, informed by principles from the decision sciences, must be sensitive to the concerns and interests of a wide range of stakeholders, particularly in terms of how difficult tradeoffs are framed. As such, the fundamental objective for the intended research is to develop and test analytical and deliberative techniques that encourage the integration of cognitive and affective considerations to facilitate learning through adaptive management efforts; this, in turn, will have the benefit of improving individual decision making and group consultation processes for choices about wildfire management, species recovery, and other environmental risks with the goal of reducing long-range ecological and economic risks on public and private lands. In order to meet these objectives, I propose to undertake a series of exploratory experimental investigations that address the following research questions: 1. How can values-based decision aiding techniques be developed and used to help stakeholders frame tradeoffs across the multiple values and objectives relating to adaptive management efforts? In particular, how can the approach help diverse stakeholders to address tradeoffs between a variety of short and long-term objectives? 2. How can affective considerations be integrated alongside other types of decision aids that emphasize more conventional cognitive considerations to encourage higher quality judgments involving objectives such as learning over time in the context of adaptive management?
Project Methods
Part 1 of the proposed research focuses on developing a decision aiding model for adaptive management, based on the insights of decision analysis and behavioral decision research. I propose to design and test a new type of group decision making process that addresses the requirements of adaptive management based on principles of constructive decision. Several groups of expert and community stakeholders (working in defined groups representing specific and varied interests such as federal, state/provincial, and regional experts, property owners, recreationists, First Nations, etc.) will be led by a trained facilitator through the following steps in a structured group consultation process; (1) identifying stakeholders short and long-range objectives in the context of impending adaptive environmental management decisions; (2) creating a series of appealing and purposeful management treatments that address both technical (e.g., reinstating natural disturbance regimes in the form of periodic prescribed fires) and stakeholders (e.g., maintaining human heath and safety, protecting property, etc.) objectives; (3) employing available technical information (from previous and ongoing field studies as well as expert stakeholders judgments) to characterize the consequences of each treatment; (4) designing an overall treatment regime above as well as a plan for their spatial and temporal arrangement), which entails carrying out an in-depth evaluation of each of the individual treatments by addressing tradeoffs; and (5) establishing thresholds for outcomes that constitute success and failure as well as a protocol that governs switching between treatments in the overall management regime. I also will carry out controlled experiments to assess the effectiveness of decision structuring in an adaptive management context. These experiments will allow for additional control of potential biases, in part stemming from an imbalance between the art of conducting a deliberative decision-making process like the one outlined above (which in part reflects the personality and training of the analysts) and the science of decision making. Carrying out experiments also allows for involvement of a broader array of stakeholders to determine if the elicited objectives and proposed management options are satisfactory from the point of view of a more general population. The third aspect of the proposed research builds upon results obtained from a pilot study conducted in 2001. From my previous findings, I anticipate that non-expert decision makers will find it affectively more difficult to balance deliberative and affective modes of judgment when decision problems are framed solely in terms of meeting technical objectives, leading to lower overall evaluations of the proposed management alternatives. I also expect that incorporating learning over time through adaptive management will introduce additional affective and cognitive difficulties. Finally, I speculate that both the decision context (lower vs. higher affect) and ones level of expertise are also likely to influence individuals ability to balance affective and deliberative components of a choice.

Progress 07/01/04 to 12/31/05

Outputs
Over the course of this project, we established the first of two planned case studies. Beyond working with participants aligned with the case study to determine if adaptive management is an appropriate strategy, we have been developing decision support tools to help managers of the Snohomish River to determine (1) if passive or adaptive management ought to be implemented, (2) areas of uncertainty/knowledge gaps that need to be addressed with the highest priority, (3) how adaptive management plans can be appropriately scaled to maximize earning and reduce uncertainty (with respect to the goals and objectives of the management plan), (4) appropriate quasi-experimental probes to test hypotheses that link what is learned via AM to specific recovery activities, and (5) their tolerance for inter-temporal tradeoffs that involve learning less over a short time period and learning more but over a longer time. A second case study -- this one in the context of developing fire risk reduction strategies in the Upper Peninsula of Michigan -- is currently in development. Two experiments were also conducted over the course of this project. The first experiment merged themes from past work on the evaluability hypothesis (Hsee et al.) with those from studies of affect and affective heuristics to address the following question: If enhanced evaluability is explained by making the attributes of an option more or less meaningful in the context of choice, can the affective characteristics of the context of the evaluation counteract any gains achieved through presenting alternatives in side-by-side comparisons? Two studies were conducted in an attempt to answer this question. Subjects in both studies received quantitative information about the nature of risks associated with two problems -- one whose context was affect-poor combined with relatively high risks and another whose context was affect-rich combined with relatively low risks in order to determine the relative weight placed by decision makers on the technical and affective aspects of a given management problem. The second experiment focused on evaluating the effectiveness of various decision aiding tools (related mainly to clarifying objectives and addressing tradeoffs) in a risk management context. It was hypothesized that a decision aiding approach would lead participants to make more thoughtful and better informed decisions which accurately reflect their objectives with these outcomes determined through both self-reports by decision makers and internally consistent decision making behavior. A two-treatment experiment was designed to test this hypothesis; the main finding was that self-reported evaluations of decision quality in an adaptive management context tended to diverge substantially from actual (measured via internal consistency checks) decision quality. Two (at minimum) additional experiments are planned for the future.

Impacts
Improved decision making processes for adaptive management are expected to both ease implementation and improve the quality of resource and environmental management processes.

Publications

  • Arvai, J. L., R. Gregory, and M. Zaksek. 2006 (In Press). Improving wildfire risk management decisions. in W. Martin, I. Martin, and C. Raish, editors. Wildfire and Fuels Management: Risk and Human Reaction. RFF Press, Washington, DC.
  • Wilson, R. S., and J. L. Arvai. 2006. When less is more: How affect influences preferences when comparing low and high-risk options. Journal of Risk Research 9:165-178.
  • Wilson, R. S., and J. L. Arvai. 2006. Evaluating the quality of structured risk management decisions. In review.
  • Gregory, R., D. Ohlson, and J. L. Arvai. 2006. Deconstructing adaptive management: Criteria for applications to resource and environmental management. In review.
  • Froschauer, A., and J. L. Arvai. 2006. Good decisions, bad decisions: The interaction of process and outcome in lay evaluations of risk management decisions. In review.
  • Arvai, J. L., R. Gregory, D. Ohlson, B. A. Blackwell, and R. W. Gray. 2006. Letdowns, wake-up calls, and constructed preferences: People's responses to fuel and wildfire risks. Journal of Forestry 104(4): 173-181.
  • Arvai, J. L., G. Bridge, N. Dolsak, R. Franzese, T. Koontz, A. Luginbuhl, P. Robbins, K. Richards, K. Smith Korfmacher, B. Sohngen, J. Tansey, and A. Thompson. 2006. Adaptive management of the global climate problem: Bridging the gap between climate research and climate policy. Climatic Change In press.


Progress 01/01/04 to 12/31/04

Outputs
Work on this research is ongoing. I am in the process of developing or conducting several lines of research aimed at addressing project objectives. Case study analysis is either being developed (e.g., in the case of forest management issues in Michigan and California) or conducted (e.g., in the case of fisheries management in Washington state). In all of these cases, improving decision making for adaptive management is the primary objective. Experimental work is also proceeding; two experiments are in the development/testing stages. These include an experiment to test the effectiveness of decision aiding tools for helping people to learn over time from both their successes and their failures. A second experiment involves looking at the affective (emotional) impact of failure -- a common feature of adaptive management efforts -- on people's judgments about (a) decision quality and (b) the effectiveness of adaptive management efforts.

Impacts
Improved decision making processes for adaptive management are expected to both ease implementation and improve the quality of resource and environmental management processes.

Publications

  • Arvai, J.L., V.E.A. Campbell, A. Baird, and L. Rivers. 2004. Teaching students to make better decisions about the environment: Lessons from the decision sciences. Journal of Environmental Education, 36: 33-44.
  • Williams, L.R., M.L. Warren, C.M. Taylor, and J.L Arvai. 2004. Design and interpretation of basin visual estimation technique (BVET) surveys: Methodological limitations and future directions. Fisheries, 29: 10-20.
  • Zaksek, M. and J. L. Arvai. 2004. Communicating the risks of wildland fire: Using mental models research to identify risk communication needs for natural resource management. Risk Analysis, 24: 1503-1514.