Uncertainty and Sensitivity of Ecosystem Restoration Decisions: A Case Study from Coastal Louisiana
ARMY CORPS OF ENGINEERS VICKSBURG MS ENGINEER RESEARCH AND DEVELOPMENT CENTER
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OVERVIEW Effective ecosystem restoration decision making requires analysis of the costs and benefits of alternative actions. The outcomes of restoration actions are often uncertain--and the models used to assess the outcomes are equally uncertain--due to incomplete ecological knowledge and other factors, such as limited data. These uncertainties can impose some risk. This technical note provides an overview of two quantitative methods for assessing risk associated with restoration decisions, sensitivity, and uncertainty analysis. An example of these methods is provided for a Louisiana coastal wetland restoration study. RISK ASSESSMENT A risk is a potential adverse consequence that may or may not be realized in the future and is typically defined by the product of the likelihood of an outcome i.e., probability and the consequence of that outcome Suedel et al. 2012. Forecasting the outcome of a restoration project often includes considerable uncertainty due to incomplete knowledge, imperfect models, stochastic environmental conditions, and many other factors. Risk-informed decision making requires explicit acknowledgement of key sources of uncertainty and seeks to minimize adverse outcomes related to those uncertainties. Risk assessment is a field of study that applies an array of qualitative and quantitative tools to define likelihoods and outcomes of a given decision Suedel et al. 2012. Assessment of project risk and uncertainty has been required of US Army Corps of Engineers USACE planners since the establishment of Principles and Standards in 1973. Qualitative risk assessment methods include listing sources of risk and uncertainty, relative rankings of risks, and multi-objective comparison of risks. Although qualitative methods have been used in restoration decision making, few quantitative risk assessments have been undertaken Suedel et al. 2012.
- Physical and Dynamic Oceanography