Ecological risk assessment (ERA) is charged with assessing the likelihood a chemical will have adverse environmental or ecological effects. When assessing the risk of a potential contaminant to biological organisms, ecologists are most concerned with the sustainability of populations of organisms, rather than protecting every individual. However, ERA most commonly relies on data on the effect of a potential contaminant on individuals because these experiments are more feasible than costly population-level exposures. In this work, we address the challenge of extrapolating these individual-level results to predict population-level effects. Previous per-capita population growth rate estimates calculated from individual-level exposures of Daphnia pulicaria to silver nanoparticles (AgNPs) at different food rations predict a critical daily food requirement for daphnid populations exposed to 200 μg/L AgNPs to avoid extinction. To test this, we exposed daphnid populations to the same AgNP concentration at three different food inputs, with the lowest ration close to the extinction threshold predicted from data on individuals. The two populations with the higher food inputs persisted, and the population with the lowest food input went extinct after 50 days but did persist through two generations. We demonstrate that we can extrapolate between these levels of biological organization by parameterizing an individual-level biomass model with data on individuals’ response to AgNPs and using these parameters to predict the outcome for control and AgNP-exposed populations. Key to successful extrapolation is careful modeling of temporal changes in resource density, driven by both the experimental protocols and feedback from the consumer. The implication for ecotoxicology is that estimates of extinction thresholds based on studies of individuals may be reliable predictors of population outcomes, but only with careful treatment of resource dynamics.

生态风险评估 (ERA) 负责评估化学品对环境或生态产生不利影响的可能性。在评估生物有机体潜在污染物的风险时，生态学家最关心的是有机体种群的可持续性，而不是保护每个个体。然而，ERA 最常依赖于潜在污染物对个体影响的数据，因为这些实验比昂贵的人群水平暴露更可行。在这项工作中，我们解决了推断这些个体水平结果以预测人口水平效应的挑战。以前的人均人口增长率估计值是根据水蚤的个体水平暴露计算的以不同食物配给的银纳米粒子 (AgNPs) 预测暴露于 200 μg/L AgNPs 的水蚤种群的关键每日食物需求以避免灭绝。为了测试这一点，我们在三种不同的食物输入中将水蚤种群暴露在相同的 AgNP 浓度下，最低的日粮接近个体数据预测的灭绝阈值。食物投入较高的两个种群持续存在，食物投入最低的种群在 50 天后灭绝，但确实持续了两代。我们证明，我们可以通过使用个人对 AgNPs 反应的数据参数化个体水平的生物量模型并使用这些参数来预测控制和暴露于 AgNP 的群体的结果，从而在这些生物组织水平之间进行推断。成功推断的关键是对资源密度的时间变化进行仔细建模，由实验协议和消费者反馈驱动。对生态毒理学的影响是，基于研究的灭绝阈值估计个人可能是人口结果的可靠预测者，但只有在仔细处理资源动态的情况下。