The species composition of benthic diatoms was related to environmental conditions in streams throughout the western US to develop diatom traits, indicators for assessment of biological condition and indicators for diagnosing stressors. We hypothesized that indicators based on species traits determined for subsets of streams with similar natural landscape features would be more precisely related to environmental conditions than would be indicators calculated based on species traits for all streams in the data set. The ranges of many environmental conditions were wide among western streams, and these conditions covaried greatly along a major environmental gradient characterized by positive correlations among % watershed disturbed by agricultural and urban land uses (% WD), conductivity, total N, total P, and % fine sediments. Species traits were calculated for 242 diatom taxa. Weighted average (WA) methods were used to define species environmental optima, and regression approaches were used to determine whether species were sensitive or tolerant to environmental conditions indicated by % WD, total P, total N, a nutrient multivariate index, pH, conductivity, % fine sediments, % embeddedness, and a watershed disturbance multivariate index. Indicators based on WA optima and sensitive/tolerant traits were highly correlated with these environmental conditions. Natural and anthropogenic conditions varied greatly among classes of streams grouped by climate regions, but indicators developed for the entire western US were consistently more accurate than were regional indicators. Indicators for individual stressors, such as total P, conductivity, and % embeddedness, were highly correlated with values of respective stressors, but covariation among all indicators and stressors indicated that only 1 environmental gradient was reliably reflected by the indicators. Thus, robust indicators of the biological condition of diatom assemblages were developed for streams of the western US, but development of stressor-specific indicators will require application of additional analytical approaches.
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