To understand the full benefits of EMODnet, users are kindly asked to describe how EMODnet supports them in their daily work and activities.
If you have developed an application using EMODnet products that you would like to share with us or if you use EMODnet data for other purposes, submit your use case by contacting email@example.com.
Outcomes: Authors were able to map and assess the ecosystem services provided by habitats in the European North Atlantic Ocean, providing a point for further research and discussion on ecosystem services contribution of benthic habitats in Europe.
How EMODnet Seabed Habitats helped the user:EUSeaMap provided a basis of EUNIS classified benthic habitats to fill in the gaps for where seabed habitats in the study area were previously unclassified.
The Joint Research Centre (JRC) is responsible for creating, managing and making sense of knowledge to support European policies with independent evidence. This includes developing innovative tools and making them available to policy makers, anticipating emerging issues that will need addressed at EU level, understanding policy environments and sharing knowledge with EU countries, the scientific community and international partners.
SIMCelt was a two-year cross-border project involving partners from the UK, Ireland and France. It's objectives were to support co-operation between EU Member States on the implementation of the Maritime Spatial Planning (MSP) Directive in the Celtic Seas.
Outcomes: Successfully quantifying the overall condition of European seas, authors were able to conceptualise indicator-based spatial tools to apply ecosystem-based approaches to human activities and provide practical solutions to marine governance. The report is considered a contribution to the MSFD Article 20.3 reporting and provides material which can be used to the 8th Environment Action Plan.
How EMODnet Seabed Habitats helped the user: Contained habitat data at the resolution and coverage required.
EMODnet Seabed Habitats data enabled the mapping of potential disturbance to benthic habitats due to fishing in the north-east Atlantic. The assessment was part of the wider OSPAR Intermediate Assessment 2017, which evaluates the status of the marine environment of the North-East Atlantic.
Orsted Power (UK) Ltd are responsible for the development, construction and operation of offshore windfarms across Europe. Hornsea Project Three has been proposed in the North Sea, off the North Norfolk Coast, with the potential to be generating up to 2,400 MW of electricity, the average daily needs of approximately 2 million UK homes.
The pan-European map presenting the distribution of modelled broad scale seabed habitats (EUSeaMap v2016) made available through the EMODnet Seabed Habitats project, was crucial in the assessment recently performed by ISPRA in collaboration with the European Environment Agency to compile information on the distribution of all marine broad-scale habitats for the whole Western Mediterranean basin.
NIVA Denmarkis a regional office under the Norwegian Institute for Water Research (NIVA), an institution with over 50 years experience in applied aquatic science. NIVA Denmark is focussed on applied research in aquatic ecosystems and evidence-based consultancy. Their key areas of research include eutrophication, hazardous substances, biodiversity and ecosystem health, as well as the implications of multiple human activities in aquatic environments.
The digital topographic map layers produced by EMODnet do not only show the depth of water, they also indicate where surveys are sparse and confidence in data is low. Extending this analysis for more distant waters requires collaboration with countries outside the EU who have similar programmes.
JNCC produced a ‘Combined Map’ integrating data from field survey maps (mostly from the EUNIS habitat datasets collection) and the most recent version of the EMODnet Seabed Habitats broad-scale predictive habitat map available at that time. The Combined Map is a single flat layer without overlaps between habitats or component datasets, making it suitable and efficient for area calculations.