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(T/FF231) Application of Second Order Monte Carlo Analysis and Probability Bounds Analysis to Estimate Risk to Birds Exposed to Chlorpyrifos in Apple Orchards. Moore, Dwayne1, Hart, Andy2, Hicks, William3, Pawlisz, Andrew1, Teed, Scott1, 1 2 3 ABSTRACT- Although simple probabilistic techniques (e.g. interval analysis, moment propagation, first-order Monte Carlo analysis) are applicable to most risk assessments, other techniques might be better suited to specific risk assessment problems. For example, higher-order techniques such as second-order Monte Carlo analysis and probability bounds analysis can be used to determine the relative importance of two sources of uncertainty: variability and incertitude. In second-order Monte Carlo analysis, every replication is itself a result of a separate Monte Carlo analysis. This type of nested simulation has been used to explore the effect of uncertainty about the parameters used to define the input distributions in risk analyses. Probability bounds analysis represents an uncertain input distribution with an entire class of probability distributions that conform with the available empirical information about the variable. These techniques were used in a case study on blue tits exposed to chlorpyrifos in apple orchards. The case study application of second-order Monte Carlo analysis and probability bounds analysis indicated that the major strengths of both techniques are their ability to: identify the most important and reducible sources of uncertainty and to express analyst confidence about risk predictions. Second-order Monte Carlo analysis is somewhat cumbersome and with both techniques risk communication can be a challenge. Key words: Second Order Monte Carlo, Uncertainty, Probabilistic Risk Assessment, Probability Bounds Analysis |
