Mathematical modeling of biogeochemical processes associated to a coccolithophorid (Emiliania huxleyi) bloom - Study of the seasonal and long-term variability of biogeochemical properties in the Black Sea using a Data Interpolating Variational Analysis (DIVA)

A OD biogeochemical model has been developed to represent coccolithophorid physiological features concerned by carbon export (primary production, active DOC excretion, TEP formation, and calcification) and susceptible to be sensitive to varying pCO2. The model is initially calibrated and validated using a large set of biogeochemical data monitored during Emiliania huxleyi blooms induced in a mesocosm experiment, under present-day pCO2 conditions. Afterwards, impacts of varying pCO2 conditions on Emiliania huxleyi physiology are investigated using biogeochemical variables monitored in mesocosms under low and high pCO2 conditions. The methodology promotes a double approach: the recalibration model parameters’ that optimizes the representation of observations from low and high pCO2 treatments, and the utilization of a RM ANOVA procedure to indicate significant differences between biogeochemical variables monitored during blooms induced in low and high pCO2 treatments.

Since the early 1970’s, the Black Sea ecosystem has suffered significant ecological alterations, essentially caused by anthropogenic impacts. Dam constructions on the Danube River in combination with heavy nutrients discharge via the riverine run-off lead to strong modifications of its physical and biogeochemical properties, with final consequences consisting in an enhancement of the typical anoxic state of the deep waters. The long-term evolution of key biogeochemical variables (oxygen, hydrogen sulfide, and chlorophyll) has been studied through the reconstruction of horizontal fields, using long time data series and the DIVA interpolating tool. In addition, the examination during the best sampled period (1986-1993) of these biogeochemical variables’ fields, completed with nitrates and phosphates fields, highlighted seasonal and horizontal variability within typical sections of their profiles.