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For example, one approach in current vogue is to assemble groups of professional hydrologists, biologists, engineers, silviculturists and foresters to assess or "audit" forest practices ( BMPs) as they relate to observed, but not empirically quantified, impacts on water quality. Specific sites are visited and each person simply provides his/her qualitative judgment as to whether the logging activity has had any impact on the streams draining the area. Again audit values are apportioned among BMPs on an areal basis and summed up to allow inferences about levels of disturbance to be drawn (Ehinger and Potts 1990). In the Rocky Mountains and Pacific Northwest, including the Flathead, another popular approach for assessing the impacts of forestry on water and sediment yield is to assemble a series of impact or "risk" values and recovery rates for various land disturbance activities (e.g., roads, skid trails, site preparation, logging method). These values are then apportioned on an areal basis for the catchment and summed to provide a measure of cumulative effects (Klock 1984, U.S. Forest Service 1988, Cobourn 1989). This approach can be greatly improved when formalized as a true risk analysis (Cairns and Orvos 1990) or Markovian simulation in which the impact values are based on catchment-specific experiments and the results are expressed in terms of specific forest dynamics such as materials mass transfer of water, sediment or nutrients (Pastor and Johnston this volume). Unfortunately, subjective methods or model results are often never verified in terms of actual impact measured in situ (e.g, increase in fine sediments, decrease in fish production) and inferences and recommendations can be misleading to those seriously interested in minimizing negative instream effects associated with anthropogenic land disturbances. Clearly, these methods will identify pervasive effects, such as severe sedimentation resulting from roads collapsed into streams or skid crossings that are not bridged. But, it is virtually impossible to detect chronic effects (e.g., accelerated water yield and bank erosion, slow reduction in woody debris accumulation, changes in water chemistry and bioproduction, fish habitat alteration) via non-emperical audits. Value of the judgment is lost in formalization of the approach unless the audit result can be verified by temporal and spatial ecological measures obtained within appropriate experimental designs. Too often standardized techniques or mathematical models are used to evaluate impacts when in fact they have little or no predictive power at all in terms of ecosystem connectivity. This amounts to an "illusion of technique" (R. Behnke, Colorado State University, unpublished). 21