An evaluation of logistic regression models for predicting amphipod toxicity from sediment chemistry

An empirical screening level approach was developed to assess the probability of toxicity to benthic organisms associated with contaminated sediment exposure. The study was based on simple logistic regression models (LRMs) of matching sediment chemistry and toxicity data retrieved from a large database of field-collected sediment samples contaminated with multiple chemicals. Three decisions were made to simplify the application of LRMs to sediment samples contaminated with multiple chemicals. First, percent mortality information associated with each sediment sample was condensed into a dichotomous response (i.e., toxic or nontoxic). Second, each LRM assumed that toxicity was attributable to a single contaminant. Third, individual contaminants present at low concentrations were excluded from toxic sediment samples. Based on an analysis of the National Sediment Inventory database, the LRM approach classified 55% of nontoxic sediments as toxic (i.e., false-positives). Because this approach has been used to assess the probability of benthic toxicity as reported by the U.S. Environmental Protection Agency (U.S. EPA), the resultant estimates of potential toxicity convey a misleading impression of the increased hazard that sediments pose to the health of aquatic organisms at many sites in the United States. This could result in important resources needlessly being diverted from truly contaminated sites to evaluate and possibly remediate sediments at uncontaminated sites.