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Lake Lunz Supersite, Austria

The Host Laboratory for the Lake Lunz Supersite will be WasserCluster Lunz (WCL), a joint research centre of the University of Vienna, the University of Natural Resources and Life Science Vienna and the Danube University Krems.

Lake Lunz comprises three lakes and a river network in a pre-alpine catchment draining into the Upper Danube. The catchment is mostly unimpacted by agriculture and other point sources. This part of the Upper Danube catchment comprises pre-alpine systems including running water systems, wetlands and lake ecosystems along a gradient of altitude, intensity of land use and a varying extent of hydromorphological alterations. The river network ranges from first order streams to large Danube tributaries and the Upper Danube itself. A sound data base on pressures, land use and conditions of water bodies compiled in a national data base provide an excellent information base.

The Supersite, with its laboratory and outdoor experimental facilities, is well positioned for studies on the effects of climate change and other pressures on aquatic ecosystems applying a combined approach of targeted long term field observations, experimental setups and integrated modelling systems to analyse the complex interactions within aquatic ecosystems and beyond system boundaries. Experimental infrastructures and expertise are available in terms of experimental flumes and mesocosm systems. The available systems allow testing of global change-related stressors such as changes in DOC, temperature and CO2 levels. The catchment is part of a LTSER site and the lake is part of the worldwide GLEON network. Seebach and Lake Lunz have been regularly monitored for many years, hence time series data are available for various parameters and organisms.

The Supersite will support the overall aims of DANUBIUS-RI by elucidating the multiple interactions between current and emerging pressures, which will affect aquatic ecosystems, their structure, functions and provision of services.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 739562.