We investigated the relations among 83 Hydrologic Condition Metrics (HCM) and changes in algal, invertebrate, and fish communities in 5 metropolitan areas across the continental United States.  We used a statistical approach that employed spearman correlation analysis, regression tree analysis, and multiple linear-regression modeling to identify 5 HCM that were strongly associated with observed ecological changes.  Average flow magnitude, high-flow magnitude, high-flow event frequency, high-flow duration and rate of change were the HCMs most consistently associated with changes in aquatic communities. Although our investigation used an urban gradient design with short hydrologic periods of records (<= 1year) of hourly cross-sectional area time series, these 5 HCM were consistent with previous investigations using long-term daily flow records.  The ecological sample day was often included within the hydrologic period. Regression models explained up to 67%, 85%, and 81% of variance for specific algae, invertebrate, and fish community metrics, respectively. National models were generally not as statistically significant as models for individual metropolitan areas.  High-flow event frequency, a hydrologic index found to be transferable across stream type and useful for classifying habitat by previous research, was also found to be the most ecologically-relevant HCM; transformation by precipitation increased national scale applicability.