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Biogeochemical 1D ERSEM ecosystem model applied to recent carbon dioxide and nutrient data in the North Sea Elkalay, K.; Khalil, K.; Thomas, H.; Bozec, Y.; Ruardij, P.; de Baar, H. (2012). Biogeochemical 1D ERSEM ecosystem model applied to recent carbon dioxide and nutrient data in the North Sea, in: Jordán, F. et al. Models of the ecological hierarchy: from molecules to the ecosphere. Developments in environmental modelling, 25: pp. 275-294. https://dx.doi.org/10.1016/b978-0-444-59396-2.00017-1 In: Jordán, F.; Jørgensen, S.E. (Ed.) (2012). Models of the ecological hierarchy: from molecules to the ecosphere. Developments in environmental modelling, 25. Elsevier: Amsterdam. ISBN 978-0-444-59396-2. xxxi-562 pp., meer In: Developments in environmental modelling. ISSN 0167-8892, meer

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Beschikbaar in	Auteurs
VLIZ: Non-open access 386558 [ aanvragen ]

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Trefwoorden

Chemical compounds > Carbon compounds > Atmospheric gases > Carbon dioxide Continental shelf North Sea [Marine Regions] Marien/Kust

Author keywords

ERSEM; Biogeochemical cycles modeling; climate feed-backs

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Auteurs		Top
Elkalay, K. Khalil, K. Thomas, H., meer	Bozec, Y. Ruardij, P. de Baar, H.

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Abstract

The European Regional Seas Ecosystem Model (ERSEM) coupled to the Princeton Ocean Model (POM) one-dimensional physical model was applied to the first results of the pluridisciplinary biogeochemical data set acquired in the North Sea during four cruises carried out from 2000 to 2001. We introduced a CO2 submodel in ERSEM and we focused on simulations at two stations, one in the southern part and one in the northern part of the North Sea. A basic validation of the simulations is presented which indicates that results are in a good agreement with the field measurements. The model reproduces the vertical structure and the temporal variations of biogeochemical variables, both qualitatively and quantitatively. An inorganic carbon limitation function of phytoplankton growth was also implemented in the model to investigate potential changes of ecosystem structure with predicted future increases of atmospheric CO2 levels. A sensitivity analysis suggests that diatoms and large phytoplankton are more sensitive than flagellates and picophytoplankton to predicted future increases of atmospheric CO2 levels.

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