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Measuring and predicting the effects of time variable exposure of pesticides on populations of green algae : combination of flow through studies and ecological modelling as an innovative tool for refined risk assessments

机译:测量和预测农药的时变暴露量对绿藻种群的影响:通过研究与生态建模相结合的流量分析,作为完善风险评估的创新工具

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摘要

The EU risk assessment of pesticides for aquatic organisms relates measured effect data to exposure values obtained from model predictions. The FOCUS exposure models provide Predicted Environmental Concentrations in surface waters. Calculations use realistic worst-case scenarios, based on representative agricultural conditions. Pesticide input via spray drift, runoff or drain flow results in exposure patterns in a time-variable scale. Standard toxicity tests and effect data are based on the assumption of a single exposure event into a static water body. Relating the results of these standard tests to FOCUS time-variable exposure patterns is only possible by gross simplifications and the use of overly conservative worst-case assumptions. The topic on how to relate pulsed exposure patterns to simple exposure assumptions is discussed since the inclusion of the FOCUS scenarios in the EU risk assessment of pesticides. Population-level effects and time-to-recovery after time-variable exposure need to be considered for more realistic, but still conservative risk assessments. One way forward is the use of population models within the higher-tier risk assessment, in close combination with ecotoxicological experiments. Out of the multitude of interactions of pesticides and aquatic non-target organisms, the example of herbicides and algae was chosen for this work. This work aimed to develop and test a new approach to assess the effects of time-variable exposure on algae. This approach comprised the close combination of ecotoxicological experiments and population modelling. It involved the development of an algae model including all necessary steps for verification and validation as well the performance of laboratory experiments. A mechanistic compartment model, SAM-X (Simple Algae Model EXtended), was developed. This model describes population dynamics of the four different algae species under static as well as under continuous culture conditions. The experimental approach of this work was the development and application of a flow-through system for the continuous culture of algae. Thereby, the exposure of algae populations to a pesticide could be investigated in a time-variable scale. This setup was based on the Chemostat principle, which allowed a continuous operation in a stable manner without the need of external influence. The results of this work confirm the proposals available in literature to use flow-through systems as appropriate higher-tier tools to assess effects of complex toxicant exposure to algae. The algae model proved its capability to simulate effects on population growth and times to recovery after time-variable exposure of toxicants. Moreover, the results support the use of the algae model as a predictive tool to assess effects of pesticides on population level. Thus, an implementation of the model as an inherent part of the pesticide risk assessment would be an asset. The usefulness of the combined approach was confirmed by the results, as not only the experiments offered detailed information on population-level effects after pesticide exposure, also the model application showed practical advantages: It can be applied for designing and improving the flow-through study as a first step, to describe the results as a second step, and thirdly, to extrapolate to different exposure scenarios to predict effects on the algae populations. In summary, this work demonstrated an excellent option to represent pulsed exposure of a pesticide and corresponding effects on algae a bit closer to reality. The conclusive results of the combined approach confirm the beneficial use of population models as supporting tools in higher-tier risk assessment of aquatic toxicants.
机译:欧盟对水生生物农药的风险评估将测得的效果数据与从模型预测中获得的暴露值联系起来。 FOCUS暴露模型提供了地表水中的预测环境浓度。基于代表性的农业条件,计算使用了现实的最坏情况。通过喷雾漂移,径流或排水流输入的农药会导致时间变化的暴露模式。标准毒性测试和效果数据是基于对静态水体的单次暴露事件的假设得出的。只有通过总体简化和使用过于保守的最坏情况假设,才能将这些标准测试的结果与FOCUS随时间变化的曝光模式联系起来。自从将FOCUS情景纳入欧盟农药风险评估以来,讨论了如何将脉冲暴露方式与简单暴露假设联系起来的主题。为了更现实,但仍是保守的风险评估,需要考虑人口水平的影响和时间可变暴露后的恢复时间。前进的一种方法是在更高级别的风险评估中使用人口模型,并与生态毒理学实验紧密结合。从农药和水生非目标生物的多种相互作用中,选择了除草剂和藻类作为这项工作的例子。这项工作旨在开发和测试一种新方法,以评估随时间变化的暴露对藻类的影响。这种方法包括生态毒理学实验和种群建模的紧密结合。它涉及藻类模型的开发,其中包括用于验证和确认以及实验室实验性能的所有必要步骤。开发了机械隔室模型SAM-X(扩展的简单藻类模型)。该模型描述了静态和连续培养条件下四种不同藻类的种群动态。这项工作的实验方法是开发和应用藻类连续培养流通系统。因此,可以以时变尺度研究藻类种群对农药的暴露。该设置基于Chemostat原理,无需外部影响即可稳定地连续运行。这项工作的结果证实了文献中提出的建议,即使用流通系统作为适当的较高层工具来评估藻类对复杂毒物的影响。藻类模型证明了其有能力模拟有毒的时间可变暴露后对种群增长和恢复时间的影响。此外,结果支持将藻类模型用作评估农药对种群水平影响的预测工具。因此,将模型作为农药风险评估的固有部分实施将是一项资产。结果证实了该组合方法的有效性,因为该实验不仅提供了接触农药后种群水平效应的详细信息,而且该模型的应用还显示出实际的优势:它可用于设计和改进流通研究。第一步,将结果描述为第二步,第三步,推断出不同的暴露情景以预测对藻类种群的影响。总而言之,这项工作证明了代表农药的脉冲暴露以及对藻类的相应影响的一种极佳选择,这一点更加接近现实。组合方法的最终结果证实了人口模型作为水生毒性物质较高级风险评估的支持工具的有益用途。

著录项

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    Weber Dennis;

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  • 年度 2012
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  • 原文格式 PDF
  • 正文语种 eng
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