The current state of ecological risk assessment (ERA) considers the assessment of effects in standardized toxicity tests for single substances on individual organisms. However, in the environment, chemicals are rarely found alone, and not individual organisms are exposed but populations within communities in the ecosystem. The current ERA approach disregards potential mixture toxicity of chemicals and effects at higher levels of organization, such as the population level.

With our work, we present a holistic, state-of-the-art approach to tackle an issue in current risk assessment of chemicals. Based on standardized, toxicity data, we are able to predict mixture toxicity effects of copper (Cu) and zinc (Zn) at the population-level for Daphnia magna. Mechanistic models, such as the DEB-IBM framework presented here, integrate effects on different endpoints (both lethal and sub-lethal) and different compounds, and produces a mechanistic extrapolation predicting mixture toxicity effects at the population level.

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