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Titel The stoichiometry of inorganic carbon and nutrient removal in the Mississippi River plume and adjacent continental shelf
VerfasserIn W.-J. Huang, W.-J. Cai, R. T. Powell, S. E. Lohrenz, Y. Wang, L.-Q. Jiang, C. S. Hopkinson
Medientyp Artikel
Sprache Englisch
ISSN 1726-4170
Digitales Dokument URL
Erschienen In: Biogeosciences ; 9, no. 7 ; Nr. 9, no. 7 (2012-07-30), S.2781-2792
Datensatznummer 250007200
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/bg-9-2781-2012.pdf
 
Zusammenfassung
The stoichiometry of dissolved inorganic carbon (DIC) and nutrients during biological uptake is widely assumed to follow the Redfield ratios (especially the C / N ratio) in large river plume ecosystems. However, this assumption has not been systematically examined and documented, because DIC and nutrients are rarely studied simultaneously in river plume areas and interpretation of ratios can be confounded by strong river–ocean mixing as well as intense biological activity. We examined stoichiometric ratios of DIC and nutrients (NO3-, PO43- and Si[OH]4) in the Mississippi River plume and adjacent continental shelf in June 2003 and August 2004 and calculated biological removal as the difference between observed concentrations and those predicted from conservative mixing, as determined from a multi-end-member mixing model and observed salinity and total alkalinity. Despite complex physical and biogeochemical influences, relationships between DIC and nutrients were strongly dependent on salinity range and geographic location, and influenced by biological removal. Lower C / Si and N / Si ratios in one nearshore area were likely due to localized input of high Si and low NO3- water from adjacent wetlands or preferential removal of nitrogen in the area. When net biological uptake was separated from river–ocean mixing and corrected for preferential N removal, the stoichiometric ratio of C / N / Si was similar to the Redfield ratio, thus supporting the applicability of the Redfield-type C / N / Si ratios in river-plume biogeochemical models.
 
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