Manganese(iv) oxide amendments reduce methylmercury concentrations in sediment by poising redox to inhibit sulfate reduction.

Risk assessments and risk management decisions concerning risks to wild fish populations resulting from exposures to polychlorinated biphenyls (PCBs) and related chemicals have been based primarily on observations of effects of chemicals on individual organisms. Although the development and application of population-level ecological risk-assessment methods is proceeding at a rapid pace, the organism-level approach is still being justified by arguments that population-level ecological risk assessment is in an early stage of development and has not been shown to be reliable. This article highlights the importance of including population-level effects in risk-management decision-making, by examining the effects of exposures to PCBs on fish populations inhabiting the Hudson River, New York, USA, a system in which data have been collected for approximately 30 y concerning both concentrations of PCBs in sediment and fish tissue and the abundance and reproduction of exposed fish populations. We previously tested hypotheses concerning the effects of PCBs on the striped bass population of the Hudson River, and found that the available data conflicted with all of these hypotheses. Here, we report results of similar analyses of effects of historic PCB exposures on the Hudson River white perch population, using an extended data set that recently became available. As with striped bass, we found no correlation between maternal PCB tissue concentrations and any measure of reproductive success in Hudson River white perch during the 30-y period covered by the data set. Together with results of studies performed on fish populations exposed to PCBs at other sites, our results clearly demonstrate that physiological and genetic adaptation, biological compensation, and other ecological processes influence responses of fish populations to PCB exposures and should be considered in risk management decision-making.

No abstract

The purpose of this paper is to discuss the effective use of quantitative modeling in environmental decision making, with a particular focus on problems of contaminated sediment and surface water. The intended audience includes both model developers and model users. Our goal is to facilitate more effective communication among model developers and those using the information produced by models to aid decision making. We provide a series of observations or conclusions we have reached in our experience that are as follows. A model is a tool for evaluating alternate hypotheses; a model itself is not a hypothesis. All decisions are actually based upon models, either explicitly or implicitly. Models are used to address diagnostic and prognostic questions. Models can provide value added when applied throughout the lifetime of a project. Uncertainty, and therefore the need for models, is greater in systems near background. Models can provide useful information even when based on relatively small data sets. The utility of a model depends on the strength of the constraints placed upon it. The calibration process can be only partially specified a priori. Model calibration and evaluation require multiple lines of evidence. Uncertainty analysis is both qualitative and quantitative. Validation is provided by the application of the model under a wide range of conditions. Communication of the strength of model constraints is critical to model acceptance. We conclude that while models are often used in the evaluation of contaminated sediment problems, distrust in the use of models remains strong. The assessment of uncertainty is the factor most limiting acceptability.