were within 10%, five exceeded this only slightly, and five were 20-40% of the total extraneous variance. The 

 latter group requires additional evaluation to determine if error variability can be reduced by nnodification of 

 the scoring approach, alteration of the fish species in a particular group, or possibly altering the index period 

 itself. Also, these estimates are based on only two years and a relatively small number of sites; more precise 

 estimates will be possible with additional years of repeat sampling. Some of these metrics represent the most 

 widely-used attributes for characterizing aquatic communities; deleting any of them for purely statistical reasons 

 might diminish the utility of the indicator (Karr and Chu 1977). 



For trend detection capability, the coherent variability across years component should not be large relative to 

 the total extraneous variance. This cannot be completely evaluated at the present time because the coherent 

 variation component is estimated from only two years of data, and thus probably underestimates the true 

 coherent variation of all sites across years. Several years of data from repeat sampling are required to 

 rigorously estimate this component. Trend detection capability is further evaluated as part of Guideline 13 

 (Data Quality Objectives). 



Summary 



Important components of variability, particularly within-year variability, were estimated for the indicator and 

 candidate metric score variables. The indicator and most individual metrics achieved or nearly achieved the 

 performance objective (contributing < 10% to the total extraneous variance). Five metrics were well above 

 this and should be further evaluated. Performance of the indicator and candidate metrics with respect to 

 trend detection cannot be evaluated at this time, as several years of data are required to provide rigorous 

 estimates of coherent annual variability. 



Guideline 11: Spatial Variability 



Indicator responses to various environmental conditions must be consistent across the monitoring region 

 if that region is treated as a single reporting unit. Locations within the reporting unit that are known to be 

 in similar ecological condition should exhibit similar indicator results. If spatial variability occurs due to 

 regional differences in physiography or habitat, it may be necessary to normalize the indicator across the 

 region, or to divide the reporting area into more homogeneous units. 



Performance Objective 



1. Demonstrate that indicator response will be consistent across the monitoring region of interest. 



The geographic scale of the proposed monitoring framework is such that differences might be expected in 

 species composition and potential richness, general structure of stream fish assemblages, and general 

 abiotic characteristics of stream ecosystems. Aquatic ecoregions (Omernik 1 987), along with consideration 

 of zoogeographic factors affecting fish distribution patterns, can serve as a basis for determining if normalizing 

 the indicator across the region of interest is necessary (Table 4-16). If major differences in the response 

 variables associated with individual candidate metrics (e.g., potential species richness, percent of carnivorous 

 individuals) are observed among ecoregions (or aggregates of similar ecoregions), the indicator will require 

 some type of normalization. Normalization can be attained by adjusting expectations (addressed under 

 Guideline 14) for individual metrics within ecoregions as necessary. For example, the expectation for the 

 percent of tolerant individuals may be 10% or less in one ecoregion, but be 20% or less in another because 

 of the natural occurrence of more tolerant species. The final indicator value remains consistent with this 

 approach, but its derivation is altered {i.e., an indicator value of 60 means the same across the entire region 

 of interest). 



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