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Improving risk assessment by predicting the survival of field gammarids exposed to dynamic pesticide mixtures.
Environmental Science & Technology ( IF 10.8 ) Pub Date : 2020-09-08 , DOI: 10.1021/acs.est.0c03939 Maricor J Arlos 1, 2, 3 , Andreas Focks 4 , Juliane Hollender 2, 3 , Christian Stamm 2
Environmental Science & Technology ( IF 10.8 ) Pub Date : 2020-09-08 , DOI: 10.1021/acs.est.0c03939 Maricor J Arlos 1, 2, 3 , Andreas Focks 4 , Juliane Hollender 2, 3 , Christian Stamm 2
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Exposure assessment of pesticides has substantially improved over time, with methods that now include a combination of advanced analytical techniques and fate/transport models to evaluate their spatiotemporal distribution. However, the current regulatory environmental risk assessment considers thresholds from laboratory studies completed under standardized conditions that do not reflect environmental dynamics. Using the General Unified Threshold model for Survival (GUTS) model framework, we predicted the impact of time-varying pesticide exposures on the survival of gammarids in a small agricultural stream. The LP50 values were used as an additional metric for assessing risks (defined in GUTS as a multiplication factor applied to the concentration time series to induce 50% mortality by the end of exposure). Although real-case exposures to individual pesticides were predicted to produce little to no impact on survival, the LP50 values indicate acute (LP50 ≤ 100) and/or chronic (LP50 ≤ 10) toxicities for azoxystrobin, chlorpyrifos, diazinon, and imidacloprid, while risk to propiconazole exposure was considered very low (LP50 ≫ 100). Finally, the model was extended to reflect mixture toxicity via concentration addition. It predicted risks under acute and chronic exposures to organophosphates and neonicotinoids. Given that gammarids are simultaneously exposed to multiple chemicals and other stressors throughout their lifetime, a decline in survival probabilities due to chemical stress can likely influence their overall fitness. We recognize that some assumptions require validation, but our work included a level of realism that can assist risk managers when evaluating the cumulative consequences of chemical exposure.
中文翻译：
通过预测暴露于动态农药混合物中的田间γ-甲酰胺的存活来改善风险评估。
随着时间的推移，农药的暴露评估已大大改善，现在的方法包括结合先进的分析技术和命运/运输模型来评估其时空分布。但是，当前的监管环境风险评估考虑了在不反映环境动态的标准化条件下完成的实验室研究的阈值。使用通用的生存统一阈值模型（GUTS）模型框架，我们预测了随时间变化的农药暴露量对一小股农业生产流中γ-芽孢杆菌存活的影响。LP 50值用作评估风险的附加指标（在GUTS中定义为应用于浓度时间序列的乘法因子，以在暴露结束前诱发50％的死亡率）。虽然实际的情况下暴露于单独的农药进行了预测，以产生小到对存活率没有影响，LP 50值表明急性（LP 50 ≤100）和/或慢性（LP 50 ≤10）的毒性为嘧菌酯，毒死蜱，二嗪磷，和吡虫啉，而丙环唑暴露的风险被认为很低（LP 50≫ 100）。最后，扩展了模型以通过添加浓度反映混合物毒性。它预测了在急性和慢性接触有机磷酸盐和新烟碱类药物下的风险。考虑到伽马龙在其一生中同时暴露于多种化学物质和其他应激源，由于化学应激而导致的生存概率下降可能会影响它们的整体适应性。我们认识到某些假设需要验证，但是我们的工作包括一定程度的现实性，可以帮助风险管理人员评估化学品暴露的累积后果。
更新日期：2020-10-06
中文翻译：
通过预测暴露于动态农药混合物中的田间γ-甲酰胺的存活来改善风险评估。
随着时间的推移，农药的暴露评估已大大改善，现在的方法包括结合先进的分析技术和命运/运输模型来评估其时空分布。但是，当前的监管环境风险评估考虑了在不反映环境动态的标准化条件下完成的实验室研究的阈值。使用通用的生存统一阈值模型（GUTS）模型框架，我们预测了随时间变化的农药暴露量对一小股农业生产流中γ-芽孢杆菌存活的影响。LP 50值用作评估风险的附加指标（在GUTS中定义为应用于浓度时间序列的乘法因子，以在暴露结束前诱发50％的死亡率）。虽然实际的情况下暴露于单独的农药进行了预测，以产生小到对存活率没有影响，LP 50值表明急性（LP 50 ≤100）和/或慢性（LP 50 ≤10）的毒性为嘧菌酯，毒死蜱，二嗪磷，和吡虫啉，而丙环唑暴露的风险被认为很低（LP 50≫ 100）。最后，扩展了模型以通过添加浓度反映混合物毒性。它预测了在急性和慢性接触有机磷酸盐和新烟碱类药物下的风险。考虑到伽马龙在其一生中同时暴露于多种化学物质和其他应激源，由于化学应激而导致的生存概率下降可能会影响它们的整体适应性。我们认识到某些假设需要验证，但是我们的工作包括一定程度的现实性，可以帮助风险管理人员评估化学品暴露的累积后果。
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