The primary goal of the present study is to provide a broad view of best practices for evaluating bioavailability models for metals for use in the protection of aquatic life. We describe the state of the science regarding 1) the evaluation and selection of ecotoxicity data, 2) the selection of bioavailability models for use in normalization, and 3) subsequent application of bioavailability models. Although many examples of normalization steps exist worldwide, a scheme is proposed to evaluate and select a model that takes account of its representativeness (water chemistry and taxonomic coverage of the ecotoxicity data set) and validation performance. Important considerations for a suitable model are the quantity of inputs needed, accuracy, and ease of use, all of which are needed to set protective values for aquatic life and to use these values to evaluate potential risks to organisms in receiving waters. Although the end results of different model application approaches may be broadly similar, the differences in these application frameworks ultimately come down to a series of trade-offs between who needs to collect the data and use the bioavailability model, the different requirements of spatial scales involved (e.g., regional vs site-specific values), and model predictiveness and protectiveness. Ultimately, understanding the limits and consequences of these trade-offs allows for selection of the most appropriate model and application framework to best provide the intended levels of aquatic life protection. Environ Toxicol Chem 2019;39:118-130. © 2019 SETAC.

中文翻译：

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使用基于生物利用度的方法推导和应用金属阈值的最佳实践。

本研究的主要目标是为评估用于保护水生生物的金属的生物利用度模型的最佳实践提供广泛的视角。我们描述了以下方面的科学状况：1) 生态毒性数据的评估和选择，2) 用于标准化的生物利用度模型的选择，以及 3) 生物利用度模型的后续应用。尽管世界范围内存在许多标准化步骤的示例，但提出了一种方案来评估和选择一个考虑其代表性（水化学和生态毒性数据集的分类覆盖）和验证性能的模型。合适模型的重要考虑因素是所需输入的数量、准确性和易用性，所有这些都是为水生生物设定保护值并使用这些值来评估对受纳水域生物体的潜在风险所必需的。尽管不同模型应用方法的最终结果可能大体相似，但这些应用框架的差异最终归结为谁需要收集数据和使用生物利用度模型之间的一系列权衡，所涉及的空间尺度的不同要求（例如，区域与特定地点的值），以及模型的预测性和保护性。最终，了解这些权衡的限制和后果允许选择最合适的模型和应用框架，以最好地提供预期水平的水生生物保护。环境毒物化学 2019；39:118-130。© 2019 SETAC。