Population models can provide valuable tools for ecological risk assessment (ERA). A growing amount of work on model development and documentation is now available to guide modelers and risk assessors to address different ERA questions. However, there remain misconceptions about population models for ERA, and communication between regulators and modelers can still be hindered by a lack of clarity in the underlying formalism, implementation, and complexity of different model types. In particular, there is confusion about differences among types of models and the implications of including or ignoring interactions of organisms with each other and their environment. In this review, we provide an overview of the key features represented in population models of relevance for ERA, which include density dependence, spatial heterogeneity, external drivers, stochasticity, life‐history traits, behavior, energetics, and how exposure and effects are integrated in the models. We differentiate 3 broadly defined population model types (unstructured, structured, and agent‐based) and explain how they can represent these key features. Depending on the ERA context, some model features will be more important than others, and this can inform model type choice, how features are implemented, and possibly the collection of additional data. We show that nearly all features can be included irrespective of formalization, but some features are more or less easily incorporated in certain model types. We also analyze how the key features have been used in published population models implemented as unstructured, structured, and agent‐based models. The overall aim of this review is to increase confidence and understanding by model users and evaluators when considering the potential and adequacy of population models for use in ERA. Integr Environ Assess Manag 2021;17:521–540. © 2020 SETAC

中文翻译：

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生态风险评估的非结构化、结构化和基于主体的种群模型的主要特征及其实施回顾

人口模型可以为生态风险评估（ERA）提供有价值的工具。现在，越来越多的模型开发和文档工作可用于指导建模者和风险评估者解决不同的 ERA 问题。然而，对于 ERA 的人口模型仍然存在误解，监管机构和建模者之间的沟通仍可能因不同模型类型的基本形式、实施和复杂性缺乏明确性而受到阻碍。特别是，对于模型类型之间的差异以及包括或忽略生物体之间的相互作用及其环境的影响存在混淆。在这篇综述中，我们概述了与 ERA 相关的人口模型中表示的关键特征，包括密度依赖性、空间异质性、外部驱动因素、随机性、生活史特征、行为、能量学以及暴露和影响如何整合到模型中。我们区分了 3 种广泛定义的人口模型类型（非结构化、结构化和基于代理），并解释了它们如何表示这些关键特征。根据 ERA 上下文，某些模型特征将比其他模型特征更重要，这可以告知模型类型选择、特征如何实现以及可能的附加数据收集。我们表明，无论形式化如何，几乎所有特征都可以包含在内，但某些特征或多或少容易合并到某些模型类型中。我们还分析了如何在已发布的人口模型中使用关键特征，这些模型实现为非结构化、结构化和基于代理的模型。2021 年整合环境评估管理；17：521–540。© 2020 SETAC