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首页> 外文期刊>Ecological Modelling >Use of sensitivity analysis to identify influential and non-influential parameters within an aquatic ecosystem model
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Use of sensitivity analysis to identify influential and non-influential parameters within an aquatic ecosystem model

机译：敏感性分析的使用来确定水生生态系统模型中的有影响力和非影响力参数

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Food-web models can be powerful tools to assess effects of chemicals on ecosystem structure and functioning. Indeed, they do not only account for direct ecotoxicological effects on aquatic species, but also consider the interactions between these species and the resulting indirect effects of chemicals. However, such models often contain a large number of parameters and are therefore difficult to calibrate on experimental data. Following this rationale, sensitivity analyses (SA) are essential tools that enable us to simplify the calibration process by identifying the non-influential input parameters which can be further fixed at a nominal value. In this study, the screening SA Morris method and the variance-based SA method EFAST were compared on two ecological food-web models (of 20 and 34 parameters). These sub-models represent two prey-predator chains, the first containing two outputs (periphyton and grazers) and the second one three outputs (green algae, rotifers and invertebrate predators). Both SA methods ranked the models' parameters according to their influence on the outputs. Nevertheless, the Morris approach can a priori be sensitive to sampling design parameters that are (generally arbitrarily) chosen by the modeller. Therefore, we then tested different settings of this method, in particular the 'level' and 'sampling' numbers of the design, as well as its aleatory component, and gave recommendations about the most accurate Morris sampling design. To test the accuracy of the Morris results, median ranks derived from this latter approach were compared to those obtained with EFAST. It was observed that Morris and EFAST approaches actually identified the same 8 and 15 non-influential parameters for the two sub-models. These parameters were mainly related to the mortality, respiration and excretion processes. None of the non-influential parameters were involved in the growth functions, expected to be the driving processes of the system.
机译：食品网型号可以是强大的工具，以评估化学品对生态系统结构和功能的影响。实际上，它们不仅考虑了对水生物种的直接生态毒理学作用，还考虑了这些物种之间的相互作用和由此产生的化学物质的间接影响。然而，这种模型通常包含大量参数，因此难以在实验数据上进行校准。在这个理由之后，灵敏度分析（SA）是必不可少的工具，使我们能够通过识别不受影响的输入参数来简化校准过程，该参数可以进一步固定在标称值。在该研究中，在两种生态食品网模拟（20和34个参数）上比较了筛选SA Morris方法和基于方差的SA方法。这些子模型代表了两个猎物捕食者链，第一个包含两个输出（Periphyton和Grazers）和第二个输出（绿藻，轮虫和无脊椎动物捕食者）。两个SA方法根据它们对输出的影响等了模型的参数。尽管如此，莫里斯方法可以先验敏感于由莫德勒选择的（通常是任意）的采样设计参数敏感。因此，我们然后测试了这种方法的不同设置，特别是“级别”和“采样”编号的设计，以及其aleatory组件，并提供了关于最准确的Morris采样设计的建议。为了测试莫里斯结果的准确性，将从这种后一种方法衍生的中位数与用EfST获得的那些进行比较。观察到莫里斯和EFST方法实际上鉴定了两个子模型的相同的8和15个非影响力参数。这些参数主要与死亡率，呼吸和排泄过程有关。没有任何非影响力参数参与增长职能，预计将成为系统的驾驶过程。

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