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that cannot be directly measured in test systems. Extrapolation was not explicitly considered in the paper by Anderson (Appendix E). Other published literature attempts to relate spotted owl abundance to regional patterns of old-growth forest harvesting (Salwasser et al., 1986; Lande, 1988). Bartell et al. (1992) have recently discussed the problem of estimating population and ecosystem-level effects of toxic contaminants from laboratory toxicity tests. A variety of approaches are now being developed for extrapolating local-scale disturbances (e.g., fires or insect outbreaks) to regional-scale changes in landscape patterns (Costanza et al., 1990; Turner and Gardner, 1991; Graham et al., 1991). Extrapolations from spatial and temporal scales suitable for rigorous experiments and observations to scales relevant to environmental management appear to be essential for adequate characterization of ecological risks.

QUANTIFICATION OF UNCERTAINTY

Formal analysis of uncertainty is another major subject for improvement in ecological risk assessments of all types. The ''uncertainties" discussion group at the workshop identified three general categories of uncertainty that affect all types of risk assessments:

  • Measurement uncertainties, e.g., low statistical power due to insufficient observations, difficulties in making physical measurements, inappropriateness of measurements, and natural variability in organic responses to stress.

  • Conditions of observation, e.g., spatiotemporal variability in climate and ecosystem structure, differences between natural and laboratory conditions, and differences between tested or observed species and species of interest for risk assessment.

  • Inadequacies of models, e.g., lack of or knowledge concerning underlying mechanisms, failure to consider multiple stresses and responses, extrapolation beyond the range of observations, and instability of parameter estimates.

Measurement uncertainties can be reduced by making more and better measurements. Uncertainties related to conditions of observation cannot



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