Institute for Water and Wetland Research, Department of Environmental Science , Radboud University , P.O. Box 9010, Heyendaalseweg 135 , 6525 AJ Nijmegen , The Netherlands.
Environ Sci Technol. 2018 Mar 20;52(6):3716-3726. doi: 10.1021/acs.est.7b05904. Epub 2018 Mar 9.
Ecological risks (ERs) of pollutants are typically assessed using species sensitivity distributions (SSDs), based on effect concentrations obtained from bioassays with unknown representativeness for field conditions. Alternatively, monitoring data relating breeding success in bird populations to egg concentrations may be used. In this study, we developed a procedure to derive SSDs for birds based on field data of egg concentrations and reproductive success. As an example, we derived field-based SSDs for p, p'-DDE and polychlorinated biphenyls (PCBs) exposure to birds. These SSDs were used to calculate ERs for these two chemicals in the American Great Lakes and the Arctic. First, we obtained field data of p, p'-DDE and PCBs egg concentrations and reproductive success from the literature. Second, these field data were used to fit exposure-response curves along the upper boundary (right margin) of the response's distribution (95th quantile), also called quantile regression analysis. The upper boundary is used to account for heterogeneity in reproductive success induced by other external factors. Third, the species-specific ECs obtained from the field-based exposure-response curves were used to derive SSDs per chemical. Finally, the SSDs were combined with specific exposure data for both compounds in the two areas to calculate the ER. We found that the ERs of combined exposure to these two chemicals were a factor of 5-35 higher in the Great Lakes compared to Arctic regions. Uncertainty in the species-specific exposure-response curves and related SSDs was mainly caused by the limited number of field exposure-response data for bird species. With sufficient monitoring data, our method can be used to quantify field-based ecological risks for other chemicals, species groups, and regions of interest.
污染物的生态风险 (ERs) 通常采用物种敏感度分布 (SSD) 进行评估，其依据是生物测定中获得的、对野外条件代表性未知的效应浓度。或者，可以使用与鸟类种群繁殖成功率相关的监测数据。在这项研究中，我们开发了一种基于卵浓度和繁殖成功率的野外数据来推导鸟类 SSD 的方法。作为一个示例，我们推导了鸟类暴露于 p,p'-DDE 和多氯联苯 (PCBs) 的基于野外的 SSD。这些 SSD 用于计算这两种化学物质在大湖地区和北极地区的 ER。首先，我们从文献中获得了 p,p'-DDE 和 PCB 的卵浓度和繁殖成功率的野外数据。其次，这些野外数据用于拟合暴露-反应曲线，沿着反应分布的上边界（右边界）（第 95 分位数），也称为分位数回归分析。上边界用于解释由其他外部因素引起的繁殖成功率的异质性。第三，从基于野外的暴露-反应曲线中获得的物种特异性 EC 用于为每种化学物质推导 SSD。最后，将 SSD 与这两种化合物在两个区域的特定暴露数据相结合，以计算 ER。我们发现，与北极地区相比，这两种化学物质联合暴露的 ER 在大湖地区高出 5-35 倍。物种特异性暴露-反应曲线和相关 SSD 的不确定性主要是由于鸟类物种的野外暴露-反应数据有限。有了足够的监测数据，我们的方法可以用于量化其他化学物质、物种群体和感兴趣地区的基于野外的生态风险。
