Masaryk University, Faculty of Science, RECETOX, Kamenice 5, 62500 Brno, Czech Republic.
UFZ - Helmholtz Centre for Environmental Research, Dept. System Ecotoxicology, Permoser Strasse 15, 04318 Leipzig, Germany.
Environ Pollut. 2014 Jun;189:126-33. doi: 10.1016/j.envpol.2014.03.002. Epub 2014 Mar 21.
Species Sensitivity Distribution (SSD) is a statistical model that can be used to predict effects of contaminants on biological communities, but only few comparisons of this model with field studies have been conducted so far. In the present study we used measured pesticides concentrations from streams in Germany, France, and Finland, and we used SSD to calculate msPAF (multiple substance potentially affected fraction) values based on maximum toxic stress at localities. We compared these SSD-based predictions with the actual effects on stream invertebrates quantified by the SPEARpesticides bioindicator. The results show that the msPAFs correlated well with the bioindicator, however, the generally accepted SSD threshold msPAF of 0.05 (5% of species are predicted to be affected) severely underestimated the observed effects (msPAF values causing significant effects are 2-1000-times lower). These results demonstrate that validation with field data is required to define the appropriate thresholds for SSD predictions.
物种敏感性分布 (SSD) 是一种可以用来预测污染物对生物群落影响的统计模型，但到目前为止，这种模型与现场研究的比较还很少。在本研究中，我们使用了来自德国、法国和芬兰溪流的实测农药浓度，并利用 SSD 计算了基于局部最大毒性胁迫的多物质潜在影响分数 (msPAF) 值。我们将这些基于 SSD 的预测与 SPEARpesticides 生物指标量化的溪流无脊椎动物的实际影响进行了比较。结果表明，msPAFs 与生物指标相关性良好，但普遍接受的 SSD 阈值 msPAF 为 0.05（预计 5%的物种受到影响）严重低估了实际影响（导致显著影响的 msPAF 值低 2-1000 倍）。这些结果表明，需要使用现场数据进行验证来定义 SSD 预测的适当阈值。
