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首页> 外文期刊>Ecological indicators >Quantifying uncertainties in biologically-based water quality assessment: A pan-European analysis of lake phytoplankton community metrics
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Quantifying uncertainties in biologically-based water quality assessment: A pan-European analysis of lake phytoplankton community metrics

机译:量化基于生物的水质评估中的不确定性:泛欧湖泊浮游植物群落指标的分析

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摘要

Lake phytoplankton are adopted world-wide as a sensitive indicator of water quality. European environmental legislation, the EU Water Framework Directive (WFD), formalises this, requiring the use of phytoplankton to assess the ecological status of lakes and coastal waters. Here we provide a rigorous assessment of a number of proposed phytoplankton metrics for assessing the ecological quality of European lakes, specifically in response to nutrient enrichment, or eutrophication, the most widespread pressure affecting lakes. To be useful indicators, metrics must have a small measurement error relative to the eutrophication signal we want them to represent among lakes of different nutrient status. An understanding of variability in metric scores among different locations around a lake, or due to sampling and analytical variability can also identify how best this measurement error is minimised. To quantify metric variability, we analyse data from a multi-scale field campaign of 32 European lakes, resolving the extent to which seven phytoplankton metrics (including chlorophyll a, the most widely used metric of lake quality) vary among lakes, among sampling locations within a lake and through sample replication and processing. We also relate these metrics to environmental variables, including total phosphorus concentration as an indicator of eutrophication. For all seven metrics, 65-96% of the variance in metric scores was among lakes, much higher than variability occurring due to sampling/sample processing. Using multi-model inference, there was strong support for relationships between among-lake variation in three metrics and differences in total phosphorus concentrations. Three of the metrics were also related to mean lake depth. Variability among locations within a lake was minimal (<4%), with sub-samples and analysts accounting for much of the within-lake metric variance. This indicates that a single sampling location is representative and suggests that sub-sample replication and standardisation of analyst procedures should result in increased precision of ecological assessments based upon these metrics. For three phytoplankton metrics being used in the WFD: chlorophyll a concentration, the Phytoplankton Trophic Index (FTI) and cyanobacterial biovolume, >85% of the variance in metric scores was among-lakes and total phosphorus concentration was well supported as a predictor of this variation. Based upon this study, we can recommend that these three proposed metrics can be considered sufficiently robust for the ecological status assessment of European lakes in WFD monitoring schemes.
机译:浮游植物在世界范围内被用作水质的敏感指标。欧洲环境立法(欧盟水框架指令(WFD))对此进行了形式化,要求使用浮游植物来评估湖泊和沿海水域的生态状况。在这里,我们对许多拟议的浮游植物指标进行了严格的评估,以评估欧洲湖泊的生态质量,特别是对营养物富集或富营养化(影响湖泊的最普遍压力)的响应。要用作有用的指标,相对于我们希望它们在不同养分状态的湖泊之间表示的富营养化信号,指标必须具有较小的测量误差。了解湖泊周围不同位置之间的度量标准得分的可变性,或者由于采样和分析可变性,也可以确定如何最大程度地减小此测量误差。为了量化度量标准的可变性,我们分析了来自32个欧洲湖泊的多尺度野外活动的数据,确定了湖泊之间,采样点之间的七个浮游植物度量标准(包括叶绿素a,湖泊质量最广泛使用的度量标准)之间变化的程度。一个湖泊,并通过样品复制和处理。我们还将这些指标与环境变量相关联,包括总磷浓度作为富营养化的指标。对于所有七个指标,指标得分差异的65-96%位于湖泊之间,远高于由于采样/样本处理而发生的差异。使用多模型推论,强烈支持三个指标的湖间变化与总磷浓度差异之间的关系。其中三个指标还与平均湖泊深度有关。湖泊内各位置之间的差异极小(<4%),其中子样本和分析人员占了湖内度量标准偏差的大部分。这表明单个采样点具有代表性,并暗示子样本的复制和分析员程序的标准化应导致基于这些指标的生态评估的准确性提高。对于WFD中使用的三种浮游植物度量标准:叶绿素a浓度,浮游植物营养指数(FTI)和蓝细菌生物量,度量标准得分的变异中> 85%位于湖泊之间,总磷浓度得到了很好的支持变异。根据这项研究,我们可以建议在WFD监测方案中,可以将这三个建议的指标视为对欧洲湖泊的生态状况评估足够有力的指标。

著录项

  • 来源
    《Ecological indicators》 |2013年第6期|34-47|共14页
  • 作者单位

    Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster LA1 4AP, UK;

    Centre for Limnology, Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, 61117 Rannu, Tartumaa, Estonia;

    Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire 0X10 8BB, UK;

    Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian EH26 OOB. UK;

    Norsk Instituttfor Vannforskning, Gaustadalleen 21, NO-0349 Oslo, Norway;

    CNR Institute for Ecosystems Study. Largo V. Tonolli 50,28922 Verbania Pallanza, Italy;

    Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian EH26 OOB. UK;

    Environment Agency, Kings Meadow House, Kings Meadow Road, Reading RG1 8DQ, UK;

    Leibniz Institute of Freshwater Ecology and Inland Fisheries, Justus-von-Liebig-Strabie 7, 12489 Berlin, Germany;

    Center for Advanced Studies of Blanes (CEAB-CSIC), Acces Cala St. Francesc 14, Blanes 17300, Spain;

    Centro de Estudios Hidrograficos del CEDEX, PO Bajo de la Virgen del Puerto 3,28005 Madrid, Spain;

    Research Institute for Agricultural and Environmental Engineering, CEMAGREF, av de Verdun 50,33612 Cestas-Gazinet, France;

    CNR Institute for Ecosystems Study. Largo V. Tonolli 50,28922 Verbania Pallanza, Italy;

    University of Sassari, Department of Sciences for Nature and Territory, Localita Piandanna, 07100 Sassari, Italy;

    Centre for Limnology, Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, 61117 Rannu, Tartumaa, Estonia;

    Institute of Environmental Protection-National Research Institute, 01-692 Warszawa, Kolektorska 4, Poland;

    Finnish Environment Institute (SYKE). Thejyvaeskylae Office, Survontie 9, FI-40500 Jyvaskyla, Finland;

    Norsk Instituttfor Vannforskning, Gaustadalleen 21, NO-0349 Oslo, Norway;

    Conservation Ecology and Environmental Sciences (CEES), School of Applied Sciences, Bournemouth University, Talbot Campus, Fern Barrow, Poole, Dorset BH12 5BB, UK;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    cyanobacteria; ecological quality assessment; eutrophication; linear mixed effects models; multi-model inference; water framework directive;

    机译:蓝细菌生态质量评估;富营养化线性混合效应模型;多模型推理;水框架指令;

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