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dc.contributor.authorHolt, Jason
dc.contributor.authorWakelin, Sarah
dc.contributor.authorButenschon, Momme
dc.contributor.authorAllen, Icarus
dc.contributor.authorSkogen, Morten D.
dc.contributor.authorMathisen, L. R.
dc.contributor.authorSchrum, Corinna
dc.date.accessioned2010-11-18T14:10:30Z
dc.date.available2010-11-18T14:10:30Z
dc.date.issued2010-02
dc.identifier.urihttp://hdl.handle.net/11250/109515
dc.descriptionECOOP WP10, Deliverable no: D10.1.2.1en_US
dc.description.abstractThis report describes three studies using multi-decadal simulations of regional coupled hydrodynamics ecosystem models. These models are used to investigate the relationship between lower trophic level marine ecosystems and biogeochemistry, and the physical environment. The models considered here:  POLCOMS-ERSEM Atlantic Margin Model run from 1960 to 2003 (NERC and PML) NORWECOM North Sea Model run from 1985-2006 (IMR) ECOSMO (UiB-GFI) North sea and Baltic Sea run 1980-2004 (UiB-GFI) The POLCOMS-ERSEM model is validated using in-situ data from the world ocean data centre and analysed to investigate the potential long term changes in primary production across the period 1960-2004, in the context of model open boundary conditions and drift. The model experiments demonstrate a strong sensitivity of the on-shelf primary production to the oceanic nutrient boundary conditions, suggesting cross-shelf edge nutrient fluxes provide a significant source of variability. The relationship between the model results and the North Atlantic Oscillation are also considered, demonstrating a r~0.65 correlation with on-shelf nutrients and the NAO The NORWECOM model is validated here using time series data from the Dutch coast. Correlations between model variables in a selection of ICES boxes are compared with a number of driving factors. River loads are shown to dominate coastal boxes. The relationships in open-shelf boxes are more ambiguous, although the southerly inflow is demonstrated to have an important role. The validation of the POLCOMS-ERSEM and NORWECOM models both conclude that the simulations have better skill for nutrients than chlorophyll and in open-shelf seas away from the coast. The validation of ECOSMO presented here focuses on zooplankton and comparison with data from the continuous plankton recorder, investigating six different approaches to matching CPR records with model data. Across the North Sea the mean annual cycle shows good agreement between model and CPR. There is also good correlation with along-track variability. EOF and correlation analysis is used to relate the primary production in the North Sea to atmospheric forcing parameters. The EOF patterns tend to match the distribution of summer time stratification, while the wind speed is shows the highest correlation, particularly during the onset and breakdown of stratification. This indicates the strength of cross-thermocline mixing is an important control on primary production variability. The ECOSMO model has been further developed for use in the Baltic by inclusion of nitrogen fixing cyanobacteria. These studies each demonstrate significant control of the inter-annual variability of shelf sea ecosystems through a range of external forcing vectors: oceanic through cross-shelf edge nutrient flux, terrestrial through variations in river nutrient loading, and atmospheric via the wind control of vertical mixing. Each of these vectors potentially mediates climatic variability and climate change.en_US
dc.language.isoengen_US
dc.publisherDanish Meteorological Instituteen_US
dc.subjecthydrographyen_US
dc.subjecthydrografien_US
dc.subjectecosystem modelsen_US
dc.subjectøkosystemmodelleren_US
dc.subjecttrophic interactionsen_US
dc.subjecttrofiske interaksjoneren_US
dc.titleQuantify the monthly to decadal variability of climate effects on the lower trophic levelse of shelf sea ecosystemsen_US
dc.typeResearch reporten_US
dc.subject.nsiVDP::Mathematics and natural science: 400::Zoology and botany: 480::Ecology: 488en_US
dc.subject.nsiVDP::Mathematics and natural science: 400::Geosciences: 450::Oceanography: 452en_US
dc.subject.nsiVDP::Mathematics and natural science: 400::Geosciences: 450::Hydrology: 454en_US
dc.source.pagenumber43 s.en_US


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