A food web bioaccumulation model for organic chemicals in aquatic ecosystems

Authors

  • Jon A. Arnot,

    1. School of Resource and Environmental Management, Simon Fraser University, 8888 University Drive, Barnaby, BC V5A 1S6, Canada
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  • Frank A. P. C. Gobas

    Corresponding author
    1. School of Resource and Environmental Management, Simon Fraser University, 8888 University Drive, Barnaby, BC V5A 1S6, Canada
    • School of Resource and Environmental Management, Simon Fraser University, 8888 University Drive, Barnaby, BC V5A 1S6, Canada
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Abstract

The present study examines a new bioaccumulation model for hydrophobic organic chemicals in aquatic food webs. The purpose of the model is to provide site-specific estimates of chemical concentrations and associated bioconcentration factors, bioaccumulation factors, and biota-sediment accumulation factors in organisms of aquatic food webs using a limited number of chemical, organism, and site-specific data inputs. The model is a modification of a previous model and incorporates new insights regarding the mechanism of bioaccumulation derived from laboratory experiments and field studies as well as improvements in model parameterization. The new elements of the model include: A model for the partitioning of chemicals into organisms; kinetic models for predicting chemical concentrations in algae, phytoplankton, and zooplankton; new allometric relationships for predicting gill ventilation rates in a wide range of aquatic species; and a mechanistic model for predicting gastrointestinal magnification of organic chemicals in a range of species. Model performance is evaluated using empirical data from three different freshwater ecosystems involving 1,019 observations for 35 species and 64 chemicals. The effects of each modification on the model's performance are illustrated. The new model is able to provide better estimates of bioaccumulation factors in comparison to the previous food web bioaccumulation model while the model input requirements remain largely unchanged.

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