Monitoring to detect changes in water quality to meet policy objectives.

Detecting change in water quality is key to providing evidence of progress towards meeting water quality objectives. A key measure for detecting change is statistical power. Here we calculate statistical power for all regularly (monthly) monitored streams in New Zealand to test the effectiveness of monitoring for policy that aims to decrease contaminant (phosphorus and nitrogen species, E. coli and visual clarity) concentrations to threshold levels in 5 or 20 years. While > 95% of all monitored sites had sufficient power and samples to detect change in nutrients and clarity over 20 years, on average, sampling frequency would have to double to detect changes in E. coli. Furthermore, to detect changes in 5 years, sampling for clarity, dissolved reactive phosphorus and E. coli would have to increase up to fivefold. The cost of sampling was predicted to increase 5.3 and 4.1 times for 5 and 20 years, respectively. A national model of statistical power was used to demonstrate that a similar number of samples (and cost) would be required for any new monitoring sites. Our work suggests that demonstrating the outcomes of implementing policy for water quality improvement may not occur without a step change in investment into monitoring systems. Emerging sampling technologies have potential to reduce the cost, but existing monitoring networks may also have to be rationalised to provide evidence that water quality is meeting objectives. Our study has important implications for investment decisions involving balancing the need for intensively sampled sites where changes in water quality occur rapidly versus other sites which provide long-term time series.

Biomarker responses in juvenile rainbow trout (Oncorhynchus mykiss) after single and combined exposure to low doses of cadmium, zinc, PCB77 and 17beta-oestradiol.

The objective of this study was to examine (i) the biochemical responses of rainbow trout exposed to sublethal water concentrations of the metals cadmium (Cd) (1.5 microg l(-1)) and zinc (Zn) (150 microg l(-1)); and (ii) the potential combined effects when applied in mixture (Cd/Zn) with and without co-exposure to model organic chemicals 3,3',4,4'-tetrachlorobiphenyl (PCB77) (1 mg kg (-1)) and 17beta-oestradiol (E2) (0.5 mg kg(-1)). After 21 days of exposure, several biomarkers were assessed in the liver (enzymatic and nonenzymatic antioxidants, heat shock proteins [HSP70 and HSP60], ethoxyresorufin-O-deethylase [EROD]) and in the plasma (vitellogenin [Vtg], aminotransferases). Plasma aminotransferases were not affected, whereas the other biomarkers showed different patterns of response depending on the treatment. For example, Cd, and Zn to a lesser extent, induced an adaptive response in the liver shown by an increase in antioxidant defences (total glutathione [GSH], superoxide dismutase, Trolox equivalent antioxidant capacity [TEAC]), without any impairment of GSH redox status or induction of heat shock proteins. Antagonistic effects were observed in GSH-related biomarkers after Cd/Zn exposure. PCB77 strongly induced EROD activity, HSP70 and TEAC. Co-exposure with metals did not modulate significantly the effects of PCB77. E2 induced Vtg and inhibited liver antioxidants and basal EROD activity. These inhibitory effects were suppressed in fishes exposed to E2 + Cd/Zn, suggesting additive effects of E2 and metals. In addition, E2-induced Vtg was not altered by metals. Multivariate analyses confirmed some correlation between the biomarkers. The use of complementary biomarkers is necessary to discriminate different treatments and to highlight interactive effects.