MetaData

The NewSTHEPS MetaData catalogue gives an overview of all persons and institutes involved and lists all created datasets and publications coming out of the project.

 

Persons Institutes Publications Datasets

 

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Salinity predicts the distribution of chlorophyll a spring peak in the southern North Sea continental waters
Desmit, X.; Ruddick, K.; Lacroix, G. (2015). Salinity predicts the distribution of chlorophyll a spring peak in the southern North Sea continental waters. J. Sea Res. 103: 59-74. http://dx.doi.org/10.1016/j.seares.2015.02.007
In: Journal of Sea Research. Elsevier/Netherlands Institute for Sea Research: Amsterdam; Den Burg. ISSN 1385-1101; e-ISSN 1873-1414
Peer reviewed article  
Beschikbaar in  Auteurs 
Trefwoorden
    ANE, North Sea
    Eutrophication
    Phaeocystis Lagerheim, 1893 [WoRMS]
    Noordzee [Marine Regions]
    Marien/Kust
Author keywords
    DIN:DIP Ratio; Nutrient Limitation; Nutrient Requirement
Auteurs  Top 
  • Desmit, X.
  • Ruddick, K.
  • Lacroix, G.
Abstract
    In the North Sea, the coastal waters of Belgium and The Netherlands regularly exhibit intense spring phytoplankton blooms where species such as Phaeocystis recurrently form a potential ecological nuisance. In the Belgian and Dutch continental shelves (BCS and DCS), we observe a direct correlation between the chlorophyll a spring maximum (Chlmax) and the nutrients (DIN and DIP) available for the bloom. As the nutrients are themselves strongly correlated with salinity, a rationale is developed to predict Chlmax from winter salinity. The proposed rationale is first tested in a theoretical case with a 3D-biogeochemical model (3D-MIRO&CO). The method is then applied to independent sets of in situ observations over 20 years in the BCS and the DCS, and to continuous FerryBox data in April 2008. Linear regressions explain the relationships between winter nutrients and winter salinity (R2 = 0.88 to 0.97 with model results, and R2 = 0.83 to 0.96 with in situ data). The relationship between Chlmax and the available nutrients across the salinity gradient is also explained by yearly linear regressions (R2 = 0.82 to 0.94 with model results, and R2 = 0.46 to 0.98 with in situ data). Empirical ‘DIP requirement’ and ‘DIN requirement’ for the spring biomass bloom formation are derived from the latter relationships. They depend i.a. on the losses from phytoplankton during the spring bloom formation, and therefore show some interannual variability (8–12% for DIP and 13–20% for DIN). The ratio between nutrient requirements allows predicting in winter which nutrient will eventually limit the spring biomass bloom along the salinity gradient. DIP will generally be limiting in the coastal zone, whereas DIN will generally be limiting offshore, the switch occurring typically at salinity 33.5 in the BCS and 33.6 in the DCS.
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