CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia.
Integr Environ Assess Manag. 2020 Nov;16(6):813-830. doi: 10.1002/ieam.4321. Epub 2020 Sep 15.
The risk assessment for the environmental impact of oil spills in Australia is often conducted in part using a combination of spill mapping and toxicological thresholds derived from laboratory studies. While this process is useful in planning operational responses, such as where to position equipment stockpiles and whether to disperse oil, and can be used to identify areas near the spill site where impacts are likely to occur, it cannot accurately predict the environmental consequences of an oil spill or the ecosystem recovery times. Evidence of this disconnect between model predictions and observed impacts is the lack of a profound effect of the Deepwater Horizon wellhead blowout on recruitment to fisheries in the northern Gulf of Mexico, contrary to the predictions made in the Natural Resources Damage Assessment and despite the occurrence of impacts of the spill on marine mammals, marshes, and deep water ecosystems. The incongruity between predictions made with the current approach using threshold monitoring and impacts measured in the field results from some of the assumptions included in the oil spill models. The incorrect assumptions include that toxicity is acute, results from dissolved phase exposure, and would be readily reversible. The toxicity tests from which threshold models are derived use members of the ecosystem that are easily studied in the lab but may not represent the ecosystem as a whole. The test species are typically highly abundant plankton or planktonic life stages, and they have life histories that account for rapid changes in environmental conditions. As a consequence, these organisms recover quickly from an oil spill. The interdependence of ecosystem components, including the reliance of organisms on their microbiomes, is often overlooked. Additional research to assess these data gaps conducted using economically and ecologically relevant species, especially in Australia and other understudied areas of the world, and the use of population dynamic models, will improve the accuracy of environmental risk assessment for oil spills. Integr Environ Assess Manag 2020;16:813-830. © 2020 SETAC.
澳大利亚溢油环境影响风险评估通常部分采用溢油图和毒理学阈值的组合进行，这些阈值源自实验室研究。虽然该过程有助于规划操作响应，例如在何处定位设备储备以及是否分散溢油，并且可用于识别溢油地点附近可能发生影响的区域，但它无法准确预测溢油的环境后果或生态系统恢复时间。模型预测与观察到的影响之间缺乏关联的证据是，墨西哥湾北部深水区井喷对渔业资源补充没有产生深远影响，这与自然资源损害评估中的预测相反，尽管溢油对海洋哺乳动物、湿地和深海生态系统产生了影响。使用阈值监测进行的当前方法和在现场测量的影响之间的不一致性源于溢油模型中包含的一些假设。错误的假设包括毒性是急性的，来自溶解相暴露，并且容易逆转。用于推导阈值模型的毒性测试使用的是在实验室中易于研究的生态系统成员，但可能无法代表整个生态系统。测试物种通常是大量丰富的浮游生物或浮游生物阶段，并且它们的生活史能够应对环境条件的快速变化。因此，这些生物能够迅速从溢油中恢复。生态系统组成部分的相互依存关系，包括生物体对其微生物组的依赖，通常被忽视。使用具有经济和生态相关性的物种，特别是在澳大利亚和世界其他研究不足的地区进行这些数据空白的评估研究，以及使用种群动态模型，将提高溢油环境风险评估的准确性。综合环境评估与管理 2020；16：813-830。© 2020 SETAC。
