Quantifying uncertainties in biologically-based water quality assessment: A pan-European analysis of lake phytoplankton community metrics |
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| Affiliation: | 1. Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster LA1 4AP, UK;2. Centre for Limnology, Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, 61117 Rannu, Tartumaa, Estonia;3. Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire OX10 8BB, UK;4. Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian EH26 0QB, UK;5. Norsk Institutt for Vannforskning, Gaustadalléen 21, NO-0349 Oslo, Norway;6. CNR Institute for Ecosystems Study, Largo V. Tonolli 50, 28922 Verbania Pallanza, Italy;7. Environment Agency, Kings Meadow House, Kings Meadow Road, Reading RG1 8DQ, UK;8. Leibniz Institute of Freshwater Ecology and Inland Fisheries, Justus-von-Liebig-Straße 7, 12489 Berlin, Germany;9. Center for Advanced Studies of Blanes (CEAB-CSIC), Accés Cala St. Francesc 14, Blanes 17300, Spain;10. Centro de Estudios Hidrográficos del CEDEX, PO Bajo de la Virgen del Puerto 3, 28005 Madrid, Spain;11. Research Institute for Agricultural and Environmental Engineering, CEMAGREF, av de Verdun 50, 33612 Cestas-Gazinet, France;12. University of Sassari, Department of Sciences for Nature and Territory, Località Piandanna, 07100 Sassari, Italy;13. Institute of Environmental Protection-National Research Institute, 01-692 Warszawa, Kolektorska 4, Poland;14. Finnish Environment Institute (SYKE), The Jyväskylä Office, Survontie 9, FI-40500 Jyväskylä, Finland;15. Conservation Ecology and Environmental Sciences (CEES), School of Applied Sciences, Bournemouth University, Talbot Campus, Fern Barrow, Poole, Dorset BH12 5BB, UK;1. Chair of Hydrobiology and Fishery, Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Rannu, Tartu County, 61117, Estonia;2. Department of Biological & Environmental Science, University of Jyväskylä, PL35, FI-40014, Finland;1. Department of Hydrobiology, University of Kazimierz Wielki in Bydgoszcz, 30 Chodkiewicz Str., 85-064 Bydgoszcz, Poland;2. Department of Land Reclamation and Environmental Management, University of Warmia and Mazury in Olsztyn, 2 Łódzki Sq., 10-719 Olsztyn-Kortowo, Poland;3. Pomeranian University in Słupsk, Faculty of Mathematic and Natural Sciences, Institute of Biology and Environmental Protection, Department of Environmental Chemistry, 22b Arciszewskiego Str., 76-200 Słupsk, Poland;1. MTA Centre for Ecological Research, Department of Tisza Research, 18/c, Bem Square, H-4026 Debrecen, Hungary;2. University of Debrecen, Department of Hydrobiology, Egyetem Tér 1, H-4032 Debrecen, Hungary;3. Environmental Protection, Nature Conservation and Water Authority, Lower-Tisza Region, Felső Tisza-part 17, H-6721 Szeged, Hungary;4. MTA-DE Biodiversity and Ecosystem Services Research Group, Egyetem tér 1, H-4032 Debrecen, Hungary;5. Environmental Protection, Nature Conservation and Water Authority, Trans-Tisza Region, Hatvan u. 16, H-4025 Debrecen, Hungary |
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| Abstract: | 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 (PTI) 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. |
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