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) are well‐established theoretical frameworks that describe sublethal 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. 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 us 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 modeling 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 modeling techniques can increase the ecological realism in risk assessment. Environ Toxicol Chem 2021;40:513–527. © 2020 SETAC

中文翻译：

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基于个体的动态能量收支模型中混合毒性实施的开发和验证：铜和锌对大型水蚤种群的影响

机械种群模型在生态风险评估中越来越受到关注。毒性动态能量平衡法 (DEBtox) 和通用统一生存阈值模型 (GUTS) 是完善的理论框架，分别描述了化学应激源的亚致死和致死效应。然而，这些模型在化学品混合物方面的应用有限，特别是在预测对人群的长期影响方面。我们在基于个体的模型 (IBM) 框架中使用 DEBtox 和 GUTS 来预测铜和锌对大溞的单一和组合影响人口。该模型基于单一物质的标准慢性毒性测试结果进行校准。开发了基于混合物的一般独立作用模型的混合物毒性实施，并使用来自铜和锌混合物的群体实验数据进行验证。DEB-IBM 准确预测了暴露于个体金属的人群水平影响。DEB-IBM 框架还使我们能够确定这些观察背后的潜在机制。在独立行动下，DEB-IBM 能够预测在暴露于单一金属及其混合物的人群中观察到的人群动态 ( R ² 在所有处理中 > 65%）。我们的模型表明，可以从个体水平的单一物质效应外推到群体水平的混合物毒性效应，而无需从标准混合物毒性测试中获得个体水平的混合物毒性数据。这种建模技术的应用可以增加风险评估中的生态真实性。环境毒理学化学2021；40：513-527。© 2020 SETAC