Development and Validation of a Mixture Toxicity Implementation in DED‐IBM: Effects of Copper and Zinc on Daphnia Magna Populations

Mechanistic population models are gaining considerable interest in ecological risk assessment. The dynamic energy budget approach for toxicity (debtox) and the general unified threshold model for survival (guts) is a well‐established theoretical framework that describes sub‐lethal and lethal effects of a chemical stressor, respectively. However, there have been limited applications of these models for mixtures of chemicals, especially to predict long‐term effects on populations.

 

 

Scientific abstract

Mechanistic population models are gaining considerable interest in ecological risk assessment. The dynamic energy budget approach for toxicity (debtox) and the general unified threshold model for survival (guts) is a well‐established theoretical framework that describes sub‐lethal and lethal effects of a chemical stressor, respectively. However, there have been limited applications of these models for mixtures of chemicals, especially to predict long‐term effects on populations.

Here, we used DEBtox and GUTS in an Individual‐Based Model (IBM) framework to predict both single and combined effects of copper and zinc on Daphnia magna populations. The model was calibrated based on standard chronic toxicity test results with the single substances. A mixture toxicity implementation based on the general independent action model for mixtures was developed and validated with data from a population experiment with copper and zinc mixtures.

Population‐level effects of exposure to individual metals were accurately predicted by DEB‐IBM. The DEB‐IBM framework also allowed to identify the potential mechanisms underlying these observations. Under independent action the DEB‐IBM was able to predict the population dynamics observed in populations exposed to the single metals and their mixtures (R2 > 65% in all treatments).

Our modelling shows that it is possible to extrapolate from single‐substance effects at the individual level to mixture toxicity effects at the population level, without the need for mixture toxicity data at the individual level from standard mixture toxicity tests. The application of such modelling techniques can increase the ecological realism in risk assessment.

Full reference (link):

Vlaeminck, K., Viaene, K. P. J., Van Sprang, P., & De Schamphelaere, K. A. C. (2020). Development and Validation of a Mixture Toxicity Implementation in DED‐IBM: Effects of Copper and Zinc on Daphnia Magna Populations. Environmental Toxicology and Chemistry. https://doi.org/10.1002/etc.4946

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