Publication Date:
2019-08-09
Description:
One particular task of marine ecosystem models is to simulate the biogenic transformation of dissolved inorganic carbon (DIC) into organic matter and hence to quantify the export of particulate organic carbon (POC) to deep oceanic layers. To date, environmental changes, such as increasing carbon dioxide concentrations (pCO_2) and temperature, are perceived to have an impact on the formation of organic carbon. However, well established nitrogen or phosphorus based ecosystem models are insensitive to variations in the carbonate system. In order to investigate biological responses to pCO_2 variations, ecosystem models need to distinguish between carbon, nitrogen, and/or phosphorus cycles. We present a simple biological model which decouples carbon from nitrogen fluxes such that carbon found in transparent exopolymer particles (TEP) is additionally accounted for. The model regards phytoplankton acclimation to varying environmental conditions, having included parameterizations for phytoplankton growth as proposed by Geider et al.~(1998, L&O). By means of data assimilation, an optimal parameter set is determined, which brings model results into agreement with experimental data. From the optimised model results it is infered that about 50% of dissolved organic carbon (DOC) exuded by phytoplankton is subsequently transformed into TEP, eventually influencing the amount of POC available
for the export flux. Model sensitivity studies are performed at local sites and along a latitudinal transect (30^oN-60^oN at 19^oW) in the North Atlantic. As soon as CO_2 limitation for phytoplankton growth is explicitely considered in the model, the formation of POC shows great sensitivity to pCO_2 variations. Temperature variations alter remineralisation rates and growth efficiencies. With the current model version dependencies between biomass accumulation, the date of nutrient depletion to occur, and the exudation of organic compounds are acquired.
Type:
Conference or Workshop Item
,
NonPeerReviewed
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