Extrapolation of Metal Toxicity Data for the Rotifer Brachionus calyciflorus Using an Individual‐Based Population Model

Abstract

Ecological risk assessment (ERA) of metals typically starts from standardized toxicity tests, the data of which is then extrapolated to derive safe concentrations for the envisioned protection goals. As such extrapolation in conventional ERA is lacking ecological realism, ecological modelling is considered as a promising new approach for extrapolation. Many published population models are complex, i.e. include many processes and parameters, and thus require an extensive dataset to calibrate. In this 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 to the rotifer Brachionus calyciflorus. Data on survival over time and reproduction at different temperatures and food conditions was 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 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, this study is an example of how a population model with reduced complexity can be useful for metal ERA.