Abstract
Ecological risk assessment (ERA) of metals typically starts from standardized toxicity tests, the data from which are then extrapolated to derive safe concentrations for the envisioned protection goals. Because such extrapolation in conventional ERA lacks ecological realism, ecological modeling is considered as a promising new approach for extrapolation. Many published population models are complex, that is, they include many processes and parameters, and thus require an extensive dataset to calibrate. In the present study, we investigated how individual-based models based on a reduced version of the Dynamic Energy Budget theory (DEBkiss IBM) could be applied for metal effects on the rotifer Brachionus calyciflorus. Data on survival over time and reproduction at different temperatures and food conditions were used to calibrate and evaluate the model for copper effects. While population growth and decline were well predicted, the underprediction of population density and the mismatch in the onset of copper effects were attributed to the simplicity of the approach. The DEBkiss IBM was applied to toxicity datasets for copper, nickel, and zinc. Predicted effect concentrations for these metals based on the maximum population growth rate were between 0.7 and 3 times higher in all but one case (10 times higher) than effect concentrations based on the toxicity data. The size of the difference depended on certain characteristics of the toxicity data: both the steepness of the concentration-effect curve and the relative sensitivity of lethal and sublethal effects played a role. Overall, the present study is an example of how a population model with reduced complexity can be useful for metal ERA. Environ Toxicol Chem 2024;43:324-337. © 2023 SETAC.
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