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Application of ecosystem-scale fate and bioaccumulation models to predict fish mercury response times to changes in atmospheric deposition

Authors

  • Christopher D. Knightes,

    Corresponding author
    1. U.S. Environmental Protection Agency, Office of Research and Development, Ecosystem Research Division, 960 College Station Road, Athens, Georgia 30605
    • U.S. Environmental Protection Agency, Office of Research and Development, Ecosystem Research Division, 960 College Station Road, Athens, Georgia 30605
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  • Elsie M. Sunderland,

    1. Harvard School of Engineering and Applied Sciences, 29 Oxford Street, Cambridge, Massachusetts 02138, USA
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  • M. Craig Barber,

    1. U.S. Environmental Protection Agency, Office of Research and Development, Ecosystem Research Division, 960 College Station Road, Athens, Georgia 30605
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  • John M. Johnston,

    1. U.S. Environmental Protection Agency, Office of Research and Development, Ecosystem Research Division, 960 College Station Road, Athens, Georgia 30605
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  • Robert B. Ambrose Jr.

    1. U.S. Environmental Protection Agency, Office of Research and Development, Ecosystem Research Division, 960 College Station Road, Athens, Georgia 30605
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Abstract

Management strategies for controlling anthropogenic mercury emissions require understanding how ecosystems will respond to changes in atmospheric mercury deposition. Process-based mathematical models are valuable tools for informing such decisions, because measurement data often are sparse and cannot be extrapolated to investigate the environmental impacts of different policy options. Here, we bring together previously developed and evaluated modeling frameworks for watersheds, water bodies, and food web bioaccumulation of mercury. We use these models to investigate the timescales required for mercury levels in predatory fish to change in response to altered mercury inputs. We model declines in water, sediment, and fish mercury concentrations across five ecosystems spanning a range of physical and biological conditions, including a farm pond, a seepage lake, a stratified lake, a drainage lake, and a coastal plain river. Results illustrate that temporal lags are longest for watershed-dominated systems (like the coastal plain river) and shortest for shallow water bodies (like the seepage lake) that receive most of their mercury from deposition directly to the water surface. All ecosystems showed responses in two phases: A relatively rapid initial decline in mercury concentrations (20–60% of steady-state values) over one to three decades, followed by a slower descent lasting for decades to centuries. Response times are variable across ecosystem types and are highly affected by sediment burial rates and active layer depths in systems not dominated by watershed inputs. Additional research concerning watershed processes driving mercury dynamics and empirical data regarding sediment dynamics in freshwater bodies are critical for improving the predictive capability of process-based mercury models used to inform regulatory decisions.

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