Hierarchical modelling of species sensitivity distribution: Development and application to the case of diatoms exposed to several herbicides
Hierarchical modelling of species sensitivity distribution: Development and application to the case of diatoms exposed to several herbicides
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DOI：
10.1016/j.ecoenv.2015.01.022
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发表时间：
2015-04-01
影响因子：
6.8
通讯作者：
Delignette-Muller, Marie Laure
中科院分区：
文献类型：
--
作者：
King, Guillaume Kon Kam;Larras, Floriane;Delignette-Muller, Marie Laure
物种敏感性分布（SSD）是评估污染物对生物多样性的生态毒理学威胁的关键工具。对于污染物，它可以预测哪个浓度对于物种群落是安全的。这种方法被广泛使用，但有几个缺点：（i）用单个值总结每个物种的敏感性会丢失有关表征浓度效应曲线的其他参数的有价值的信息； (ii) 它不会将估计灵敏度的不确定性传播到 SSD 中； (iii) SSD 估计的危险浓度仅表明对生物多样性的威胁，而没有了解与测量终点相关的社区的全球反应。为了弥补这些缺点，我们建立了一个全局层次模型，包括浓度效应模型和 SSD 的分布规律。我们重新审视了当前的 SSD 方法，以考虑比传统分析更多的可变性和不确定性来源，并评估社区的全球响应。在贝叶斯框架内工作，我们能够计算出 SSD，同时考虑到原始数据的不确定性。我们还制定了社区对污染物的全球反应的定量指标。我们应用这种方法根据生物量终点研究六种除草剂对日内瓦湖底栖硅藻的毒性和风险。我们的方法强调了硅藻物种集合中浓度效应模型所有参数的广泛变异性以及它们之间的潜在相关性。值得注意的是，之前没有考虑模型形状参数的可变性和相关性。 SSD 与社区的全球响应之间的比较表明，保护 95% 的物种可能只能保留 80-86% 的全球响应。最后，传播估计灵敏度的不确定性表明，在低水平效应（例如 EC10）上构建 SSD 可能是不合理的，因为它会给结果带来很大的不确定性。 (C) 2015 Elsevier Inc. 保留所有权利。
The species sensitivity distribution (SSD) is a key tool to assess the ecotoxicological threat of contaminants to biodiversity. For a contaminant, it predicts which concentration is safe for a community of species. Widely used, this approach suffers from several drawbacks: (i) summarizing the sensitivity of each species by a single value entails a loss of valuable information about the other parameters characterizing the concentration-effect curves; (ii) it does not propagate the uncertainty on estimated sensitivities into the SSD; (iii) the hazardous concentration estimated with SSD only indicates the threat to biodiversity, without any insight about a global response of the community related to the measured endpoint. To remedy these drawbacks, we built a global hierarchical model including the concentration-effect model together with the distribution law of the SSD. We revisited the current SSD approach to account for more sources of variability and uncertainty into the prediction than the traditional analysis and to assess a global response for the community. Working within a Bayesian framework, we were able to compute an SSD taking into account the uncertainty from the original raw data. We also developed a quantitative indicator of a global response of the community to the contaminant. We applied this methodology to study the toxicity and the risk of six herbicides to benthic diatoms from Lake Geneva, based on the biomass endpoint. Our approach highlighted a wide variability within the set of diatom species for all the parameters of the concentration-effect model and a potential correlation between them. Remarkably, variability of the shape parameter of the model and correlation had not been considered before. Comparison between the SSD and the global response of the community revealed that protecting 95% of the species might preserve only 80-86% of the global response. Finally, propagating the uncertainty on the estimated sensitivity showed that building an SSD on a low level of effect, such as EC10, might be unreasonable as it induces a large uncertainty on the result. (C) 2015 Elsevier Inc. All rights reserved.