Spatially explicit bioaccumulation modeling in aquatic environments: Results from 2 demonstration sites. (11th May 2017)

• Record Type: Journal Article
• Authors: von Stackelberg, Katherine; Williams, Marc A; Clough, Jonathan; Johnson, Mark S
• Is Part Of: Integrated environmental assessment and management. Volume 13:Number 6(2017)
• Page Start: 1023
• Page End: 1037
• Publication Date: 2017-05-11
• Subjects: Aquatic -- Bioaccumulation -- Probabilistic -- Risk assessment -- Spatially explicit; Environmental management -- Periodicals; Pollution -- Periodicals; Environmental toxicology -- Periodicals; Environmental risk assessment -- Periodicals; Environmental impact analysis -- Periodicals; 628
• DOI: 10.1002/ieam.1927
• Languages: English
• ISSNs: 1551-3777

Abstract

ABSTRACT: Bioaccumulation models quantify the relationship between sediment and water exposure concentrations and resulting tissue levels of chemicals in aquatic organisms and represent a key link in the suite of tools used to support decision making at contaminated sediment sites. Predicted concentrations in the aquatic food web provide exposure estimates for human health and ecological risk assessments, which, in turn, provide risk‐based frameworks for evaluating potential remedial activities and other management alternatives based on the fish consumption pathway. Despite the widespread use of bioaccumulation models to support remedial decision making, concerns remain about the predictive power of these models. A review of the available literature finds the increased mathematical complexity of typical bioaccumulation model applications is not matched by the deterministic exposure concentrations used to drive the models. We tested a spatially explicit exposure model (FishRand) at 2 nominally contaminated sites and compared results to estimates of bioaccumulation based on conventional, nonspatial techniques, and monitoring data. Differences in predicted fish tissue concentrations across applications were evident, although these demonstration sites were only mildly contaminated and would not warrant management actions on the basis of fish consumption. Nonetheless, predicted tissue concentrations based on the spatially explicit exposure characterization consistently outperformed conventional, nonspatial techniques across a variety of model performance metrics. These results demonstrate the improved predictive power as well as greater flexibility in evaluating the impacts of food web exposure and fish foraging behavior in a heterogeneous exposure environment. Integr Environ Assess Manag 2017;13:1023–1037. © 2017 SETAC Key Points: We demonstrate the advantages of a probabilistic, spatially explicit bioaccumulation modeling framework. We identify how fish foraging behavior intersects with heterogeneity in exposure concentrations in aquatic environments. Spatially explicit methods take advantage of GIS. Probabilistic methods combined with GIS better inform decision making.