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水生生态系统的生态-流行病学:将化学品与多种胁迫因素分开。

Eco-epidemiology of aquatic ecosystems: Separating chemicals from multiple stressors.

机构信息

RIVM, Centre for Sustainability, Environment and Health, P.O. Box 1, 3720 BA Bilthoven, The Netherlands; Department of Environmental Science, Institute for Water and Wetland Research, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands.

The Procter & Gamble Company, Cincinnati, OH, USA.

出版信息

Sci Total Environ. 2016 Dec 15;573:1303-1319. doi: 10.1016/j.scitotenv.2016.06.242. Epub 2016 Aug 9.

Abstract

A non-toxic environment and a good ecological status are policy goals guiding research and management of chemicals and surface water systems in Europe and elsewhere. Research and policies on chemicals and water are however still disparate and unable to evaluate the relative ecological impacts of chemical mixtures and other stressors. This paper defines and explores the use of eco-epidemiological analysis of surveillance monitoring data sets via a proxy to quantify mixture impacts on ecosystems. Case studies show examples of different, progressive steps that are possible. Case study data were obtained for various regions in Europe and the United States. Data types relate to potential stressors at various scales, concerning landscape, land-use, in-stream physico-chemical and pollutant data, and data on fish and invertebrates. The proxy-values for mixture impacts were quantified as predicted (multi-substance) Potentially Affected Fractions of species (msPAF), using Species Sensitivity Distribution (SSD) models in conjunction with bioavailability and mixture models. The case studies summarize the monitoring data sets and the subsequent diagnostic bioassessments. Variation in mixture toxic pressures amongst sites appeared to covary with abundance changes in large (50-86%) percentages of taxa for the various study regions. This shows that an increased mixture toxic pressure (msPAF) relates to increased ecological impacts. Subsequent multi-stressor evaluations resulted in statistically significant, site-specific diagnosis of the magnitudes of ecological impacts and the relative contributions of different stress factors to those impacts. This included both mixtures and individual chemicals. These results allow for ranking stressors, sites and impacted species groups. That is relevant information for water management. The case studies are discussed in relation to policy and management strategies that support reaching a non-toxic environment and good ecological status. Reaching these goals requires not only focused sectoral policies, such as on chemical- or water management, but also an overarching and solution-focused view.

摘要

无毒环境和良好的生态状况是指导欧洲和其他地区化学物质和地表水系统研究和管理的政策目标。然而,关于化学物质和水的研究和政策仍然存在差异,无法评估化学混合物和其他胁迫因素的相对生态影响。本文定义并探讨了通过代理来量化混合物对生态系统的影响的监测监测数据集的生态流行病学分析的使用。案例研究展示了不同的、渐进的步骤的例子。案例研究数据是从欧洲和美国的各个地区获得的。数据类型涉及不同尺度的潜在胁迫因素,包括景观、土地利用、溪流理化和污染物数据,以及鱼类和无脊椎动物的数据。使用物种敏感性分布(SSD)模型结合生物利用度和混合物模型,将混合物影响的代理值量化为预测的(多物质)潜在受影响物种分数(msPAF)。案例研究总结了监测数据集和随后的诊断生物评估。各个研究区域中,大多数(50-86%)分类单元的丰度变化与各站点之间混合物毒性压力的变化似乎存在相关性。这表明增加的混合物毒性压力(msPAF)与增加的生态影响有关。随后的多胁迫评估导致了对生态影响的大小和不同胁迫因素对这些影响的相对贡献的具有统计学意义的、特定于站点的诊断。这包括混合物和个别化学品。这些结果允许对压力源、站点和受影响的物种群体进行排序。这是水管理的相关信息。案例研究讨论了支持实现无毒环境和良好生态状况的政策和管理策略。实现这些目标不仅需要有针对性的部门政策,如化学品或水管理政策,还需要有一个全面的、以解决方案为重点的观点。

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