Department of Applied Environmental Science (ITM), Stockholm University, SE 106 91 Stockholm, Sweden.
Sci Total Environ. 2011 Nov 15;409(24):5416-22. doi: 10.1016/j.scitotenv.2011.08.070. Epub 2011 Oct 1.
A dynamic combined fate and food web model was developed to estimate the food web transfer of chemicals in small aquatic ecosystems (i.e. ponds). A novel feature of the modeling approach is that aquatic macrophytes (submerged aquatic vegetation) were included in the fate model and were also a food item in the food web model. The paper aims to investigate whether macrophytes are effective at mitigating chemical exposure and to compare the modeling approach developed here with previous modeling approaches recommended in the European Union (EU) guideline for risk assessment of pesticides. The model was used to estimate bioaccumulation of three hypothetical chemicals of varying hydrophobicity in a pond food web comprising 11 species. Three different macrophyte biomass densities were simulated in the model experiments to determine the influence of macrophytes on fate and bioaccumulation. Macrophytes were shown to have a significant effect on the fate and food web transfer of highly hydrophobic compounds with log KOW>=5. Modeled peak concentrations in biota were highest for the scenarios with the lowest macrophyte biomass density. The distribution and food web transfer of the hypothetical compound with the lowest hydrophobicity (log KOW=3) was not affected by the inclusion of aquatic macrophytes in the pond environment. For the three different hypothetical chemicals and at all macrophyte biomass densities, the maximum predicted concentrations in the top predator in the food web model were at least one order of magnitude lower than the values estimated using methods suggested in EU guidelines. The EU guideline thus provides a highly conservative estimate of risk. In our opinion, and subject to further model evaluation, a realistic assessment of dynamic food web transfer and risk can be obtained using the model presented here.
开发了一种动态综合命运和食物网模型，用于估计小型水生生态系统（即池塘）中化学物质的食物网传递。该建模方法的一个新颖特点是将水生植物（沉水植被）纳入命运模型中，并且也是食物网模型中的一种食物。本文旨在研究水生植物是否能有效减轻化学物质的暴露，并将这里开发的建模方法与欧盟（EU）农药风险评估指南中推荐的先前建模方法进行比较。该模型用于估计三种具有不同疏水性的假设化学物质在包含 11 个物种的池塘食物网中的生物蓄积。在模型实验中模拟了三种不同的大型植物生物量密度，以确定大型植物对命运和生物蓄积的影响。研究表明，大型植物对疏水性大于等于 5 的高度疏水性化合物的命运和食物网传递有显著影响。在模型情景中，生物体内的最高峰值浓度出现在大型植物生物量密度最低的情况下。在池塘环境中包含水生植物不会影响疏水性最低的假设化合物（log KOW=3）的分布和食物网传递。对于三种不同的假设化学物质和所有大型植物生物量密度，在食物网模型中，顶级捕食者的最大预测浓度至少比欧盟指南中建议的方法估计的浓度低一个数量级。因此，欧盟指南提供了一个高度保守的风险估计。在我们看来，并且需要进一步的模型评估，使用这里提出的模型可以对动态食物网传递和风险进行现实的评估。
