HIERARCHICAL MONTE-CARLO MODELING WITH S-DISTRIBUTIONS - CONCEPTS ANDILLUSTRATIVE ANALYSIS OF MERCURY CONTAMINATION IN KING MACKEREL

The quantitative assessment of environmental contaminants is a complex process. It involves nonlinear models and the characterization of var iables, factors, and parameters that are distributed and dependent on each other. Assessments based on point estimates are easy to perform, but since they are unreliable, Monte Carlo simulations have become a s tandard procedure. Simulations pose two challenges: They require the n umerical characterization of parameter distributions and they do not a ccount for dependencies between parameters. This paper offers strategi es for dealing with both challenges. The first part discusses the char acterization of data with the S-distribution. This distribution offers several advantages, which include simplicity of numerical analysis, f lexibility in shape, and easy computation of quantiles. The second par t outlines how the S-distribution can be used for hierarchical Monte C arlo simulations. In these simulations the selection of parameter valu es occurs sequentially, and each choice depends on the parameter value s selected before. The method is illustrated with preliminary simulati on analyses that are concerned with mercury contamination in king mack erel (Scomberomorus cavalla). It is demonstrated that the results of s uch hierarchical simulations are generally different from those of tra ditional Monte Carlo simulations.