Please use this identifier to cite or link to this item:
|Title:||Site-Specific Chlorophyll Reference Conditions for European Lakes|
|Authors:||CARVALHO Laurence; SOLIMINI Angelo; PHILLIPS3 Geoff; PIETILÄINEN O-P.; MOE J.; CARDOSO Ana; LYCHE A.; OTT I.; SONDERGAARD M.; TARTARI G.; REKOLAINEN S.|
|Citation:||HYDROBIOLOGIA vol. 633 no. 1 p. 59-66|
|JRC Publication N°:||JRC51335|
|Type:||Articles in Journals|
|Abstract:||Recent European water legislation, the Water Framework Directive (WFD), requires European Member States to assess the ¿ecological status¿ of surface waters. As part of this, many European countries are choosing to develop a quality classification scheme for chlorophyll concentrations as a measure of phytoplankton abundance. The assessment of ecological quality and its component parts, such as chlorophyll, must be based on the degree of divergence of a water body from an appropriate baseline, or ¿reference condition¿. It is, therefore, necessary to determine chlorophyll reference conditions for all European lake types, or alternatively, models for predicting reference chlorophyll concentrations on a site-specific basis. For this purpose, a large dataset of European lakes considered to be in reference condition has been assembled; 466 lakes in total. Data were included from 12 European countries, but lakes from Norway and Finland dominated and made up 82% of all reference lakes. Data have been collated on chlorophyll concentration, altitude, mean depth, alkalinity, humic type, surface area, and geographical region. Regression models were developed for estimating site-specific reference chlorophyll concentrations from significant predictor ¿typology¿ variables. Reference chlorophyll concentrations were found to vary along a number of environmental gradients. Concentrations increased with colour and alkalinity, and decreased with lake depth and altitude. Forward selection was used to identify independent explanatory variables in regression models for predicting site-specific reference chlorophyll concentrations. Due to data limitations, colour was only included in the model for very humic lakes. Depth was selected as an explanatory variable in all models. Alkalinity was included in models for low colour and humic lakes and altitude was included in models for low colour and very humic lakes. Uncertainty in the models was quite high and arises from errors in the data used to develop the models (including natural temporal and spatial variability in data) and also from additional explanatory variables not considered in the models, particularly nutrient concentrations, flushing rate and grazing. Despite these uncertainties, site-specific reference conditions are still recommended in preference to type-specific reference conditions, as they should result in reduced error in ecological status classifications, particularly for lakes close to typology boundaries. Because of the bias in the dataset towards Northern European low and medium alkalinity lakes, the models are not currently recommended for application to lakes in Central and Mediterranean regions of Europe where drivers of background productivity could be different.|
|JRC Institute:||Institute for Environment and Sustainability|
Files in This Item:
There are no files associated with this item.
Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.