Risk Assessment to Support Decision Making
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1 Risk Assessment to Support Decision Making
2 RISK ASSESSMENT TO SUPPORT DECISION MAKING Katherine von Stackelberg, ScD Center for Climate, Health and the Global Environment Harvard Center for Risk Analysis NEK Associates LTD
3 Risk = p(adverse Effect Exposure, Effects) Environmental source of stressors Fate, transport, transformation movement in the environment Laboratory studies Field studies Exposure Effects (hazard) Probability of adverse ecological effect Risk
4 Probabilistic Approaches in Risk Assessment Frequency Most are at this value: highest frequency Source: Using Probabilistic Methods to Enhance the Role of Risk Analysis in Decision Making - Managers' Summary, 2009 Range of Values Prepared by the EPA Risk Assessment Forum Working Group Concentration- Response Function
5 Probabilistic Ecological Risk Assessment 1.0 Probability of exceedance of a threshold Probability of exceeding an increasing magnitude of effect % of population % reduction in fecundity
6 Conceptual Model of Bt Exposure Source: Carstens et al Transgenic Research 21:
7 Example: Invasive Species Source: Kolar et al Science 298(8):1233
8 Example of an Invasive Species Model Output: visualization of probability of invasion Source: ve/invasivespread/model.html
9 Need to Understand Conditions Under Which Impacts Occur Can be downloaded from Examples of outcomes Offtarget effects Resistance over time Efficacy target effects
10 Some Examples of Risk from the Literature The Biosafety Clearing-House (BCH) is a mechanism set up by the Cartagena Protocol on Biosafety to facilitate the exchange of information on Living Modified Organisms (LMOs) and assist the Parties to better comply with their obligations under the Protocol. Global access to a variety of scientific, technical, environmental, legal and capacity building information is provided in the six official languages of the UN. An Ad Hoc Technical Expert Group (AHTEG) on Risk Assessment and Risk Management has a mandate to develop risk assessment guidelines Review Article: What Risk Assessments of Genetically Modified Organisms Can Learn from Institutional Analyses of Public Health Risks S. Ravi Rajan and Deborah K. Letourneau, Journal of Biomedicine and Biotechnology, Vol 2012, Article ID ,
11 Ecosystem Services: Context for Ecological Risk Source: Munns et al Integrated Environmental Assessment and Management, DOI: /ieam.1707
12 Decision Analytic Approaches for Evaluating Alternatives Risk is not just an academic exercise. There must be a decision context. Possible alternatives Criteria against which to compare alternatives
13 Example Metrics for Forest Ecosystem Health Metric Measurable Outcome Primary productivity Nutrient acquisition Mortality Nutrient retention Water use/evapotranspiration Resilience to moderate stress (pest, disease) Physical structure, age structure, and plant species composition Food web structure Soil quality Biodiversity Demand (products, recreation) Wood growth + litterfall or eddy covariance CO 2 flux Foliar chemistry Mortality rate or standing dead trees Leaching rate (Precip. streamflow) or eddy covariance H 2 O flux Mortality after stress event Forest inventory / canopy assessment Monitoring animal populations Soil chemistry Abundance Market or nonmarket value Adapted from Gary Lovett s presentation Updated.pdf
14 Take Away 1 All non-trivial decisions involve the potential for both good and bad outcomes Risk applies to more than just bad outcomes Decisions are informed by risk as a probability and as a perception Risk as a probability If we make a decision today, what are the probabilities of detrimental and beneficial outcomes in the future, and how confident are we in our estimates of these probabilities?
15 Risk as perception Take Away 2 Heuristics; Individual; Voluntary; Familiar (Known) Safe Your audience is regulatory decision and policy makers, their constituencies, and associated stakeholders Their acceptance of risk will likely be driven more by perception ( safe ) than by any scientific determination (i.e., calculated probabilities) Risk of bad outcomes to humans will almost always out-weigh those to ecological resources
16 Take Away 3 New ecological assessment tools are available: Bayesian belief networks Weight-of-evidence analysis Ecosystem services Decision analytics But: what constitutes a gene drive hazard/adverse effect? Things could go easier if you show that: Your technology is self-limiting (can t escape ) Indirect consequences won t happen e.g., loss of the target population won t affect non-target populations or communities, etc.
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