What can ecosystem models tell us about the risk of eutrophication in the North Sea?
Saux Picart, S.; Allen, J. I.; Butenschön, M.; Artioli, Y.; de Mora, L.; Wakelin, S. ORCID: https://orcid.org/0000-0002-2081-2693; Holt, J. ORCID: https://orcid.org/0000-0002-3298-8477. 2015 What can ecosystem models tell us about the risk of eutrophication in the North Sea? Climatic Change, 132 (1). 111-125. https://doi.org/10.1007/s10584-014-1071-x
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Abstract/Summary
Eutrophication is a process resulting from an increase in anthropogenic nutrient inputs from rivers and other sources, the consequences of which can include enhanced algal biomass, changes in plankton community composition and oxygen depletion near the seabed. Within the context of the Marine Strategy Framework Directive, indicators (and associated threshold) have been identified to assess the eutrophication status of an ecosystem. Large databases of observations (in situ) are required to properly assess the eutrophication status. Marine hydrodynamic/ecosystem models provide continuous fields of a wide range of ecosystem characteristics. Using such models in this context could help to overcome the lack of in situ data, and provide a powerful tool for ecosystem-based management and policy makers. Here we demonstrate a methodology that uses a combination of model outputs and in situ data to assess the risk of eutrophication in the coastal domain of the North Sea. The risk of eutrophication is computed for the past and present time as well as for different future scenarios. This allows us to assess both the current risk and its sensitivity to anthropogenic pressure and climate change. Model sensitivity studies suggest that the coastal waters of the North Sea may be more sensitive to anthropogenic rivers loads than climate change in the near future (to 2040).
Item Type: | Publication - Article |
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Digital Object Identifier (DOI): | https://doi.org/10.1007/s10584-014-1071-x |
ISSN: | 0165-0009 |
NORA Subject Terms: | Marine Sciences |
Date made live: | 08 Oct 2015 13:30 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/511981 |
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