| Text | 281532 2013 10.1016/j.ecolind.2012.12.010 ISI Web of Science WOS 000316580700005 Cyanobacteria Ecological quality assessment Eutrophication Linear mixed effects models Multi model inference Water Framework Directive Quantifying uncertainties in biologically based water quality assessment A pan European analysis of lake phytoplankton community metrics Stephen J. Thackeray; Peeter Noges; Michael J. Dunbar; Bernard J. Dudley; Birger Skjelbred; Giuseppe Morabito; Laurence Carvalho; Geoff Phillips; Ute Mischke; Jordi Catalan; Caridad de Hoyos; Christophe Laplace; Martina Austoni; Bachisio M. Padedda; Kairi Maileht; Agnieszka Pasztaleniec; Marko Jarvinen; Anne L. Solheim; Ralph T. Clarke Thackeray, Stephen J. Centre for Ecology Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster LA1 4AP, UK Noges, Peeter Centre for Limnology, Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, 61117 Rannu, Tartumaa, Estonia Dunbar, Michael J. Centre for Ecology Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire OX10 8BB, UK Dudley, Bernard J. Centre for Ecology Hydrology, Bush Estate, Penicuik, Midlothian EH26 0QB, UK Skjelbred, Birger Norsk Institutt for Vannforskning, Gaustadalleen 21, NO 0349 Oslo, Norway Morabito, Giuseppe CNR ISE, Pallanza Verbania Carvalho, Laurence Centre for Ecology Hydrology, Bush Estate, Penicuik, Midlothian EH26 0QB, UK Phillips, Geoff Environment Agency, Kings Meadow House, Kings Meadow Road, Reading RG1 8DQ, UK Mischke, Ute Leibniz Institute of Freshwater Ecology and Inland Fisheries, Justus von Liebig Straße 7, 12489 Berlin, Germany Catalan, Jordi Center for Advanced Studies of Blanes CEAB CSIC , Acces Cala St. Francesc 14, Blanes 17300, Spain De Hoyos, Caridad Centro de Estudios Hidrograficos del CEDEX, PO Bajo de la Virgen del Puerto 3, 28005 Madrid, Spain Laplace, Christophe Research Institute for Agricultural and Environmental Engineering, CEMAGREF, av de Verdun 50, 33612 Cestas Gazinet, France Austoni, Martina CNR ISE, Pallanza Verbania Padedda, Bachisio M. University of Sassari, Department of Sciences for Nature and Territory, Localita Piandanna, 07100 Sassari, Italy Maileht, Kairi Centre for Limnology, Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, 61117 Rannu, Tartumaa, Estonia Pasztaleniec, Agnieszka Institute of Environmental Protection National Research Institute, 01 692 Warszawa, Kolektorska 4, Poland Jarvinen, Marko Finnish Environment Institute SYKE , The Jyvaskyla Office, Survontie 9, FI 40500 Jyvaskyla, Finland Solheim, Anne Lyche Norsk Institutt for Vannforskning, Gaustadalleen 21, NO 0349 Oslo, Norway Clarke, Ralph T. Conservation Ecology and Environmental Sciences CEES , School of Applied Sciences, Bournemouth University, Talbot Campus, Fern Barrow, Poole, Dorset BH12 5BB, UK 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. 29 Published version Articolo 2013_Ecological_Indicators_29_34_47.pdf Articolo in rivista Elsevier Science Ireland. 1470 160X Ecological indicators Ecological indicators Ecological indicators. martina.austoni AUSTONI MARTINA giuseppe.morabito MORABITO GIUSEPPE TA.P04.016.004 Ecologia teorica e applicata degli ecosistemi acquatici |
