Corinne G. Severn

Bio: Corinne G. Severn is an academic researcher from Mercer University. The author has contributed to research in topics: Acute toxicity & Hyalella azteca. The author has an hindex of 6, co-authored 6 publications receiving 728 citations.

Classifying probabilities of acute toxicity in marine sediments with empirically derived sediment quality guidelines

Abstract: Matching, marine sediment chemistry, and toxicity data (n = 1,513), compiled from three studies conducted in the United States, were analyzed to determine both the frequency of acute toxicity to amphipods and average percentage survival in laboratory bioassays within ranges in toxicant concentrations. We determined that the probability of observing acute toxicity was relatively low (<10%) and that average control-adjusted survival equaled or exceeded 92% in samples in which sediment quality guidelines were not exceeded. Both the incidence of toxicity increased and average survival decreased as chemical concentrations increased relative to the guidelines. In sediments with highest contaminant concentrations, 73 to 83% of the samples were highly toxic, and average control-adjusted amphipod survival was 37 to 46%. Results of this study confirm that the relationships between sediment chemical concentrations and toxicity reported in a previous study were robust. Further, they indicate that numerical guidelines for saltwater sediments can be used to estimate the probability of observing toxic effects in acute amphipod tests.

Predictions of Sediment Toxicity Using Consensus-Based Freshwater Sediment Quality Guidelines

Abstract: The objectives of this study were to compare approaches for evaluating the combined effects of chemical mixtures on the toxicity in field-collected sediments and to evaluate the ability of consensus-based probable effect concentrations (PECs) to predict toxicity in a freshwater database on both a national and regional geographic basis. A database was developed from 92 published reports, which included a total of 1,657 samples with high-quality matching sediment toxicity and chemistry data from across North America. The database was comprised primarily of 10- to 14-day or 28- to 42-day toxicity tests with the amphipod Hyalella azteca (designated as the HA10 or HA28 tests) and 10- to 14-day toxicity tests with the midges Chironomus tentans or C. riparius (designated as the CS10 test). Mean PEC quotients were calculated to provide an overall measure of chemical contamination and to support an evaluation of the combined effects of multiple contaminants in sediments. There was an overall increase in the incidence of toxicity with an increase in the mean quotients in all three tests. A consistent increase in the toxicity in all three tests occurred at a mean quotient > 0.5, however, the overall incidence of toxicity was greater in the HA28 test compared to the short-term tests. The longer-term tests, in which survival and growth are measured, tend to be more sensitive than the shorter-term tests, with acute to chronic ratios on the order of six indicated for H. azteca. Different patterns were observed among the various procedures used to calculate mean quotients. For example, in the HA28 test, a relatively abrupt increase in toxicity was associated with elevated polychlorinated biphenyls (PCBs) alone or with elevated polycyclic aromatic hydrocarbons (PAHs) alone, compared to the pattern of a gradual increase in toxicity observed with quotients calculated using a combination of metals, PAHs, and PCBs. These analyses indicate that the different patterns in toxicity may be the result of unique chemical signals associated with individual contaminants in samples. Though mean quotients can be used to classify samples as toxic or nontoxic, individual quotients might be useful in helping identify substances that may be causing or substantially contributing to the observed toxicity. An increase in the incidence of toxicity was observed with increasing mean quotients within most of the regions, basins, and areas in North America for all three toxicity tests. The results of these analyses indicate that the consensus-based PECs can be used to reliably predict toxicity of sediments on both a regional and national basis.

Predicting amphipod toxicity from sediment chemistry using logistic regression models.

Abstract: Individual chemical logistic regression models were developed for 37 chemicals of potential concern in contaminated sediments to predict the probability of toxicity, based on the standard 10-d survival test for the marine amphipods Ampelisca abdita and Rhepoxynius abronius. These models were derived from a large database of matching sediment chemistry and toxicity data, which includes contaminant gradients from a variety of habitats in coastal North America. Chemical concentrations corresponding to a 20, 50, and 80% probability of observing sediment toxicity (T20, T50, and T80 values) were calculated to illustrate the potential for deriving application-specific sediment effect concentrations and to provide probability ranges for evaluating the reliability of the models. The individual chemical regression models were combined into a single model, using either the maximum (P(Max) model) or average (P(Avg) model) probability predicted from the chemicals analyzed in a sample, to estimate the probability of toxicity for a sample. The average predicted probability of toxicity (from the P(Max) model) within probability quartiles closely matched the incidence of toxicity within the same ranges, demonstrating the overall reliability of the P(Max) model for the database that was used to derive the model. The magnitude of the toxic effect (decreased survival) in the amphipod test increased as the predicted probability of toxicity increased. Users have a number of options for applying the logistic models, including estimating the probability of observing acute toxicity to estuarine and marine amphipods in 10-d toxicity tests at any given chemical concentration or estimating the chemical concentrations that correspond to specific probabilities of observing sediment toxicity.

Relationships between acute sediment toxicity in laboratory tests and abundance and diversity of benthic infauna in marine sediments: a review.

Abstract: Acute sediment toxicity tests have become important in regulatory, monitoring, and scientific programs, partly because it has been assumed that they are indicative of ecological damage to benthic infaunal resources. Data from tests of sediment toxicity and measures of benthic community structure were examined from > 1,400 saltwater samples to determine the relationships between acute toxicity and changes in the abundance and diversity of infauna resources. Data were compiled from studies conducted along portions of the Atlantic, Gulf of Mexico, and Pacific coasts of the United States. There was considerable variability among the data sets in the relationships between laboratory results and benthic measures. However, in 92% of the samples classified as toxic, at least one measure of benthic diversity or abundance was < 50% of the average reference value. In 67% of these samples, at least one measure of benthic infauna abundance or diversity was < 10% of average reference conditions. No amphipods were found in 39% of samples that were classified as toxic, whereas amphipods were absent from 28% of the nontoxic samples. In many survey areas, the abundance of crustaceans (notably the amphipods) decreased in the infauna as amphipod survival decreased in the laboratory tests. There appeared to be a break point in the data indicating that, generally, amphipod abundance in the field was lowest when survival in the laboratory tests dropped below 50% of controls. Based on the weight of evidence from all the data analyses, we conclude that ecologically relevant losses in the abundance and diversity of the benthic infauna frequently corresponded with reduced amphipod survival in the laboratory tests.

Evaluating sediment chemistry and toxicity data using logistic regression modeling

Abstract: This paper describes the use of logistic-regression modeling for evaluating matching sediment chemistry and toxicity data. Contaminant-specific logistic models were used to estimate the percentage of samples expected to be toxic at a given concentration. These models enable users to select the probability of effects of concern corresponding to their specific assessment or management objective or to estimate the probability of observing specific biological effects at any contaminant concentration. The models were developed using a large database (n = 2,524) of matching saltwater sediment chemistry and toxicity data for field-collected samples compiled from a number of different sources and geographic areas. The models for seven chemicals selected as examples showed a wide range in goodness of fit, reflecting high variability in toxicity at low concentrations and limited data on toxicity at higher concentrations for some chemicals. The models for individual test endpoints (e.g., amphipod mortality) provided a better fit to the data than the models based on all endpoints combined. A comparison of the relative sensitivity of two amphipod species to specific contaminants illustrated an important application of the logistic model approach.

Sediment quality criteria in use around the world

Abstract: There have been numerous sediment quality guidelines (SQGs) developed during the past 20 years to assist regulators in dealing with contaminated sediments. Unfortunately, most of these have been developed in North America. Traditionally, sediment contamination was determined by assessing the bulk chemical concentrations of individual compounds and often comparing them with background or reference values. Since the 1980s, SQGs have attempted to incorporate biological effects in their derivation approach. These approaches can be categorized as empirical, frequency-based approaches to establish the relationship between sediment contamination and toxic response, and theoretically based approaches that attempt to account for differences in bioavailability through equilibrium partitioning (EqP) (i.e., using organic carbon or acid volatile sulfides). Some of these guidelines have been adopted by various regulatory agencies in several countries and are being used as cleanup goals in remediation activities and to identify priority polluted sites. The original SQGs, which compared bulk chemical concentrations to a reference or to background, provided little insight into the ecosystem impact of sediment contaminants. Therefore, SQGs for individual chemicals were developed that relied on field sediment chemistry paired with field or laboratory-based biological effects data. Although some SQGs have been found to be relatively good predictors of significant site contamination, they also have several limitations. False positive and false negative predictions are frequently in the 20% to 30% range for many chemicals and higher for others. The guidelines are chemical specific and do not establish causality where chemical mixtures occur. Equilibrium-based guidelines do not consider sediment ingestion as an exposure route. The guidelines do not consider spatial and temporal variability, and they may not apply in dynamic or larger-grained sediments. Finally, sediment chemistry and bioavailability are easily altered by sampling and subsequent manipulation processes, and therefore, measured SQGs may not reflect in situ conditions. All the assessment tools provide useful information, but some (such as SQGs, laboratory toxicity and bioaccumulation, and benthic indices) are prone to misinterpretation without the availability of specific in situ exposure and effects data. SQGs should be used only in a “screening” manner or in a “weight-of-evidence” approach. Aquatic ecosystems (including sediments) must be assessed in a “holistic” manner in which multiple components are assessed (e.g., habitat, hydrodynamics, resident biota, toxicity, and physicochemistry, including SQGs) by using integrated approaches.

Calculation and Uses of Mean Sediment Quality Guideline Quotients: A Critical Review

Abstract: Fine-grained sediments contaminated with complex mixtures of organic and inorganic chemical contaminants can be toxic in laboratory tests and/or cause adverse impacts to resident benthic communities. Effects-based, sediment quality guidelines (SQGs) have been developed over the past 20 years to aid in the interpretation of the relationships between chemical contamination and measures of adverse biological effects. Mean sediment quality guideline quotients (mSQGQ) can be calculated by dividing the concentrations of chemicals in sediments by their respective SQGs and calculating the mean of the quotients for the individual chemicals. The resulting index provides a method of accounting for both the presence and the concentrations of multiple chemicals in sediments relative to their effects-based guidelines. Analyses of considerable amounts of data demonstrated that both the incidence and magnitude of toxicity in laboratory tests and the incidence of impairment to benthic communities increases incrementally with increasing mSQGQs. Such concentration/response relationships provide a basis for estimating toxicological risks to sediment-dwelling organisms associated with exposure to contaminated sediments with a known degree of accuracy. This sediment quality assessment tool has been used in numerous surveys and studies since 1994. Nevertheless, mean SQGQs have some important limitations and underlying assumptions that should be understood by sediment quality assessors. This paper provides an overview of the derivation methods and some of the principal advantages, assumptions, and limitations in the use of this sediment assessmenttool. Ideally, mean SQGQs should be included with other measures including results of toxicity tests and benthic community surveys to provide a weight of evidence when assessing the relative quality of contaminated sediments.