De Laender F, De Schamphelaere K A C, Janssen C R, Vanrolleghem P A
Laboratory of Environmental Toxicology and Aquatic Ecology, Ghent University, J. Plateaustraat 22, B-9000 Gent, Belgium.
Water Sci Technol. 2007;56(6):19-27. doi: 10.2166/wst.2007.582.
Ecological effects of chemicals on ecosystems are the result of direct effects of the chemical, determined in single-species toxicity testing, and indirect effects due to ecological interactions between species. Current experimental methods to account for such interactions are expensive. Hence, mathematical models of ecosystems have been proposed as an alternative. The use of these models often requires extensive calibration, which hampers their use as a general tool in ecological effect assessments. Here we present a novel ecosystem modelling approach which assesses effects of chemicals on ecosystems by integrating single-species toxicity test results and ecological interactions, without the need for calibration on case-specific data. The methodology is validated by comparing predicted ecological effects of copper in a freshwater planktonic ecosystem with an experimental ecosystem data set. Two main effects reflected by this data set (a decrease of cladocerans and an increase of small phytoplankton) which were unpredictable from single-species toxicity test results alone, were predicted accurately by the developed model. Effects on populations which don't interact directly with other populations, were predicted equally well by single-species toxicity test results as by the ecosystem model. The small amount of required data and the high predictive capacity can make this ecosystem modelling approach an efficient tool in water quality criteria derivation for chemicals.
化学物质对生态系统的生态效应是由化学物质的直接效应（通过单物种毒性测试确定）以及物种间生态相互作用产生的间接效应共同导致的。目前考虑此类相互作用的实验方法成本高昂。因此，有人提出将生态系统数学模型作为一种替代方法。使用这些模型通常需要进行大量校准，这阻碍了它们作为生态效应评估通用工具的应用。在此，我们提出一种新颖的生态系统建模方法，该方法通过整合单物种毒性测试结果和生态相互作用来评估化学物质对生态系统的影响，而无需针对特定案例数据进行校准。通过将淡水浮游生态系统中铜的预测生态效应与一个实验生态系统数据集进行比较，对该方法进行了验证。该数据集反映的两个主要效应（枝角类动物数量减少和小型浮游植物数量增加），仅从单物种毒性测试结果来看是无法预测的，但所开发的模型却能准确预测。对于那些不与其他种群直接相互作用的种群的影响，单物种毒性测试结果与生态系统模型的预测效果相当。所需数据量少且预测能力强，使得这种生态系统建模方法成为推导化学物质水质标准的有效工具。
