PH22 Large-Scale Investigations of Contaminated Sediments
Exhibit Hall
8:00 AM - Thursday
(PH253) Predicting Toxicity to Amphipods from Sediment Chemistry.
Field, L1, Norton, S2, MacDonald, D3, Severn, C3, Ingersoll, C4, 1 National Oceanic and Atmospheric Administration, Seattle, WA, USA2 U.S. Environmental Protection Agency, Washington, DC, USA3 MacDonald Environmental Sciences Ltd., Nanaimo, BC, Canada4 Premier Environmental Services, Las Vegas, NV, USA
ABSTRACT- This poster describes the development of logistic regression models that quantify relationships between the concentrations of sediment-associated contaminants and toxicity in two species of marine amphipods. The models provide a nationwide framework that can be used to evaluate site-specific data, guide data collection efforts, and compare ecological risks across sites and regions. Logistic regression models for 37 chemicals were developed using a large database of matching whole-sediment chemistry and toxicity data that encompass many different contaminant gradients from a wide variety of habitats in coastal North America. We used the single-chemical models to evaluate two approaches for designating samples as toxic: (1) less than 90% survival that was significantly different from negative control samples and (2) control-normalized survival less than 80% that was significantly different from negative control samples. We also evaluated two approaches for normalizing sediment chemistry: dry weight and organic carbon. Because the individual chemical models were derived from field-collected sediments that included mixtures of contaminants, to some extent each individual chemical model represents the overall toxicity of the mixtures. The results of the individual models were combined into a single explanatory variable to better estimate the probability that a sediment sample would be toxic, based on the mixture of chemicals present in the sample. The multiple-chemical model was used to evaluate several additional issues, including the relationship between the probability of observing a toxic effect and the magnitude of toxicity, the performance of the models in predicting toxicity observed in regional data sets or in individual studies, and the application to other marine and freshwater toxicity test endpoints.
Key words: sediment guidelines, sediment toxicity, logistic regression models