Belden Jason B, Gilliom Robert J, Martin Jeffrey D, Lydy Michael J
Fisheries and Illinois Aquaculture Center and Department of Zoology, Southern Illinois University, Carbondale, Illinois 62901, USA.
Integr Environ Assess Manag. 2007 Jan;3(1):90-100.
To evaluate the relative toxicity and the occurrence patterns of pesticide mixtures in streams draining agricultural watersheds, a 3-step approach was used. First, a landscape of interest was identified, defined, and isolated. Second, the relative toxicity of mixtures, on the basis of pesticide toxicity index scores, was compared with the relative toxicity of the highest individual pesticide, on the basis of highest toxicity quotient values. Third, occurrence patterns of pesticide mixtures were identified for use in follow-up mechanistic studies. The landscape of interest was identified as the corn and soybeans crop setting and concentrations of pesticides in streams within this crop setting were determined from US Geological Survey data. Pesticide toxicity index scores for individual samples were highest for the primary producers, Pseudokirchneriella subcapitata and Lemna gibba; with 95th percentile pesticide toxicity index scores of 4.7 and 1.9, respectively. The 95th percentile pesticide toxicity index score for Daphnia magna was 0.40 when a chronic sublethal endpoint was used. Pesticide toxicity index values were above the highest toxicity quotient values, indicating that consideration of mixtures does increase the estimated risk, but pesticide toxicity index scores were generally within a factor of 2 of highest toxicity quotient values, indicating that the increased risk is not large for most samples. Pesticide toxicity index scores tended to be dominated by individual pesticides and simple mixtures. Two different prioritization strategies were used to identify important mixtures for further study on the basis of potential effects on P. subcapitata. Both techniques decreased the complexity of the pesticide mixtures to consider by reducing the number of components within the identified mixtures as well as identifying a few specific combinations that constitute the majority of mixtures within the sample. Nearly all important pesticides for P. subcapitata were herbicides from 2 chemical classes: acetanilide and triazine herbicides.
为评估农业流域排水溪流中农药混合物的相对毒性及出现模式,采用了一种三步法。首先,确定、界定并隔离感兴趣的区域。其次,根据农药毒性指数得分,将混合物的相对毒性与基于最高毒性商值的单一毒性最高的农药的相对毒性进行比较。第三,确定农药混合物的出现模式,以供后续的机理研究使用。感兴趣的区域被确定为玉米和大豆种植区,并根据美国地质调查局的数据确定了该种植区内溪流中农药的浓度。单个样本的农药毒性指数得分,对于初级生产者斜生栅藻和浮萍来说最高,第95百分位数的农药毒性指数得分分别为4.7和1.9。当使用慢性亚致死终点时,大型溞的第95百分位数农药毒性指数得分为0.40。农药毒性指数值高于最高毒性商值,表明考虑混合物确实会增加估计风险,但农药毒性指数得分通常在最高毒性商值的2倍以内,这表明大多数样本的风险增加幅度不大。农药毒性指数得分往往由单一农药和简单混合物主导。基于对斜生栅藻的潜在影响,使用了两种不同的优先排序策略来确定重要混合物以供进一步研究。这两种技术都通过减少已识别混合物中的成分数量以及识别构成样本中大多数混合物的一些特定组合,降低了要考虑的农药混合物的复杂性。对斜生栅藻几乎所有重要的农药都是来自两类化学物质的除草剂:乙酰苯胺类和三嗪类除草剂。