Risk Assessment to Support Decision Making RISK ASSESSMENT TO - - PowerPoint PPT Presentation

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 kvon@hsph.harvard.edu 1.617.998.1037

RISK ASSESSMENT TO SUPPORT DECISION MAKING

Risk = p(Adverse Effect|Exposure, Effects)

Exposure Effects (hazard) Probability of adverse ecological effect  Risk Fate, transport, transformation movement in the environment Laboratory studies Environmental source of stressors Field studies

Probabilistic Approaches in Risk Assessment

Range of Values 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 Prepared by the EPA Risk Assessment Forum Working Group

Concentration- Response Function

Probabilistic Ecological Risk Assessment

% reduction in fecundity

50 100

% of population

1.0 0.5

Probability of exceedance of a threshold Probability of exceeding an increasing magnitude

• f effect

Conceptual Model of Bt Exposure

Source: Carstens et al. 2012 Transgenic Research 21:813-842

Example: Invasive Species

Source: Kolar et al. 2002 Science 298(8):1233

Example of an Invasive Species Model

Source: http://www.indiana.edu/~preser ve/InvasiveSpread/model.html Output: visualization of probability of invasion

Need to Understand Conditions Under Which Impacts Occur

Can be downloaded from www.biorxiv.org Examples of outcomes Offtarget effects Resistance over time Efficacy – target effects

• The Biosafety Clearing-House (BCH) is a mechanism set up by the

Cartagena Protocol on Biosafety to facilitate the exchange of information

• n 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.

• https://bch.cbd.int/onlineconferences/ahteg_ra.shtml
• 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 203093, http://dx.doi.org/10.1155/2012/203093

Some Examples of Risk from the Literature

Ecosystem Services: Context for Ecological Risk

Source: Munns et al. 2015 Integrated Environmental Assessment and Management, DOI: 10.1002/ieam.1707

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

Example Metrics for Forest Ecosystem Health

Metric Measurable Outcome Primary productivity Wood growth + litterfall or eddy covariance CO2 flux Nutrient acquisition Foliar chemistry Mortality Mortality rate or standing dead trees Nutrient retention Leaching rate Water use/evapotranspiration (Precip. – streamflow) or eddy covariance H2O flux Resilience to moderate stress (pest, disease) Mortality after stress event Physical structure, age structure, and plant species composition Forest inventory / canopy assessment Food web structure Monitoring animal populations Soil quality Soil chemistry Biodiversity Abundance Demand (products, recreation) Market or nonmarket value

Adapted from Gary Lovett’s presentation http://nas-sites.org/dels/files/2018/01/Gary-Lovett-Presentation- Updated.pdf

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

• utcomes in the future, and how confident are we

in our estimates of these probabilities?

Take Away 2

• Risk as perception

– 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

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
• r communities, etc.