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Stormwater runoff in a coastal urban area (San Diego County, CA) produced significant toxicity to early life stages of medaka (Oryzias latipes) and Menidia (M. beryllina). Exposure of embryos to lower concentrations (5 to 25%) increased the incidence of abnormal swim bladder inflation and other teratogenic responses, whereas higher concentrations resulted in mortality or failure to hatch. Comparisons of EC50s for mortality and failure to hatch with concentrations of individual chemical pollutants (including Cd, Cr, Cu, Pb, Ni, and Zn) revealed low correlations; however, the correlation with total metals was high (-0.84) and corresponded with sample exceedences of Water Quality Criteria (WQC) for Cd, Cu, Pb, and Zn. This strong association between developmental toxicity and toxic metal content of storm water compared favorably with developmental anomalies reported in other studies. Analytical chemistry data for pesticides that may have been in these samples were limited to selected pesticides found usually below detection limits. Greater toxicity of the watershed effluents sampled was generally associated with more developed land surface and less open space. Both medaka and Menidia were found to be useful for studying effects of stormwater on embryonic and early larval development. http://link.springer-ny. com/link/service/journals/00244/bibs/37n2p227.html

Values below a specified detection limit are a common occurrence in environmental measurement which complicates statistical analysis. This paper addresses the problem of how these data may be included in hypothesis testing and demonstrates a solution that uses a regression model in the SAS statistical package with the ability to accommodate left-censored data. To illustrate, the LIFER-EG procedure is applied to data for an analyte (tin) found in fish tissue during a multifactorial bioaccumulation study involving two experimental sites, three experiments at each site, and sampling on multiple days. The results of this analysis are presented, indicating evidence of bioaccumulation but no significant differences between sites or experiments. While regression methods to accommodate left-censored data are not new, their use in environmental studies does not appear to be widely practiced. The strengths and limitations of this approach are discussed.