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Exploring the robustness of macrophyte-based classification methods to assess the ecological status of coastal and transitional ecosystems under the Water Framework Directive

机译:探索基于水生植物的分类方法的稳健性,以根据《水框架指令》评估沿海和过渡生态系统的生态状况

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Identifying and quantifying the factors that contribute to the potential misclassification of the ecological status of water bodies is a major challenge of the Water Framework Directive (WFD). The present study compiles extensive biomonitoring data from a range of macrophyte-based classification methods developed by several European countries. The data reflect spatial and temporal variation as well as inter-observer variation. Uncertainty analysis identified that factors related to the spatial scale of sampling generally contributed most to the uncertainty in classifying water bodies to their ecological status, reflecting the high horizontal and depth-related heterogeneity displayed by macrophyte communities. In contrast, the uncertainty associated with temporal variation was low. In addition, inter-observer variation, where assessed, did not contribute much to overall uncertainty, indicating that these methods are easily transferable and insensitive to observer error. The study, therefore, suggests that macrophyte-based sampling schemes should prioritize large spatial replication over temporal replication to maximize the effectiveness and reliability of water body classification within the WFD. We encourage conducting similar uncertainty analyses for new/additional ecological indicators to optimize sampling schemes and improve the reliability of classification of ecological status.
机译:识别和量化导致水体生态状况潜在错误分类的因素是水框架指令(WFD)的主要挑战。本研究从几个欧洲国家开发的一系列基于大型植物的分类方法中收集了广泛的生物监测数据。数据反映了空间和时间变化以及观察者之间的变化。不确定性分析表明,与采样空间规模有关的因素通常是造成水体生态状态分类不确定性的最大原因,这反映了大型植物群落所表现出的高度的水平和深度相关异质性。相反,与时间变化相关的不确定性较低。此外,观察者之间的差异在评估时对整体不确定性的贡献不大,这表明这些方法易于转移且对观察者错误不敏感。因此,该研究表明,基于大型植物的采样方案应优先考虑大空间复制而不是时间复制,以最大程度地在WFD中实现水体分类的有效性和可靠性。我们鼓励对新的/其他生态指标进行类似的不确定性分析,以优化采样方案并提高生态状态分类的可靠性。

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