combination included pH, alkalinity, conductivity, hardness, and total residual chlorine (TRC). First, 7-day means for each water-quality factor were computed. PCA then was used to identify two orthogonal water-quality axes (axis I, associated primarily with hardness, conductivity, and pH; and axis II, strongly associated with TRC). The two axes accounted for 60.5 and 17.6 percent, respectively, of the total variance in the chemical data. Multiple regression analysis was then used to test relationships between the results of the ambient toxicity tests and the two principal component factors. This analysis showed that the fathead minnow survival and growth did not correspond well to any combination of the measured chemical variables and that the Ceriodaphnia test results related strongly to axes I and II. Mean survival of Ceriodaphnia was related strongly to axis II (p < 0.001) and secondarily to axis I (p = 0.101), whereas mean reproduction of Ceriodaphnia had strong relationships to both axes (axis I, p = 0.011; axis II, p = 0.019). The results of the PCA-multiple regression analyses suggested that TRC was a biologically significant contaminant whose presence strongly influenced Ceriodaphnia test outcomes.
We were able to draw two more conclusions from the study using other supporting analyses. First, for ambient assessments of water quality in these streams, Ceriodaphnia tests detected toxic conditions better than fathead minnow tests. This conclusion was supported by examination of R2 changes in ANOVAs of the Ceriodaphnia and fathead minnow tests in response to data pruning by date, as described above. Second, we were able to show that ambient toxicity dynamics in the Oak Ridge National Laboratory streams were dominated by episodic events that sometimes caused acutely toxic conditions at "poor quality" sites. Together, the three conclusions focused subsequent remediation activities and shaped the strategy for more cost-effective monitoring at the Oak Ridge National Laboratory. We began frequent testing to assess episodic events, but using Ceriodaphnia only for reasons of sensitivity and cost; we documented long-term improvements in water quality by monitoring biological and chemical conditions at the poor quality sites; to reduce costs, we halted testing at nonreference sites that have shown no evidence of toxicity; and we continue to conduct special studies and use diagnostic testing to better understand the fate and ecological effects of low concentrations of TRC.
Logistic regression analysis was used to relate chemical conditions to Ceriodaphnia mortality patterns in water samples from East Fork Poplar Creek. When using 7-day static-renewal toxicity test methods to assess ambient water quality, the water in the test chambers is replaced daily with freshly collected water. This procedure generates both an interesting challenge and a strong potential bias. The challenge is this: How should one best relate a time-varying exposure regime (e.g., daily changes in conductivity, pH, TRC) to a single, biologically integrated measure of "response" (e.g., Ceriodaphnia reproduction, expressed as a 7-day mean)? The potential bias also relates to the problem of time. The physicochemical characteristics of a sample of stream water may not