Comparison of the capacity of two biotic ligand models to predict chronic copper toxicity to twoDaphnia magnaclones and formulation of a generalized bioavailability model

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Abstract

Although it is increasingly recognized that biotic ligand models (BLMs) are valuable in the risk assessment of metals in aquatic systems, the use of 2 differently structured and parameterized BLMs (1 in the United States and another in the European Union) to obtain bioavailability-based chronic water quality criteria for copper is worthy of further investigation. In the present study, the authors evaluated the predictive capacity of these 2 BLMs for a large dataset of chronic copper toxicity data with 2 Daphnia magna clones, termed K6 and ARO. One BLM performed best with clone K6 data, whereas the other performed best with clone ARO data. In addition, there was an important difference between the 2 BLMs in how they predicted the bioavailability of copper as a function of pH. These modeling results suggested that the effect of pH on chronic copper toxicity is different between the 2 clones considered, which was confirmed with additional chronic toxicity experiments. Finally, because fundamental differences in model structure between the 2 BLMs made it impossible to create an average BLM, a generalized bioavailability model (gBAM) was developed. Of the 3 gBAMs developed, the authors recommend the use of model gBAM-C(uni), which combines a log-linear relation between the 21-d median effective concentration (expressed as free Cu(2+) ion activity) and pH, with more conventional BLM-type competition constants for sodium, calcium, and magnesium. This model can be considered a first step in further improving the accuracy of chronic toxicity predictions of copper as a function of water chemistry (for a variety of Daphnia magna clones), even beyond the robustness of the current BLMs used in regulatory applications.

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