ALBERT

Description: Highlights: • Elemental C:N:P variations of organic matter are simulated at monitoring site BY15. • No N2 fixation needed to explain observed PO4PO4 and pCO2pCO2 levels after spring bloom. • Model features relevance of DOP production and remineralization for N2 fixation. • Model estimates of annual N2 fixation are View the MathML source297±24mmolNm-2a-1. • Model estimates of annual total production are View the MathML source14.16±0.71molCm-2a-1. Abstract: For most marine ecosystems the growth of diazotrophic cyanobacteria and the associated amount of nitrogen fixation are regulated by the availability of phosphorus. The intensity of summer blooms of nitrogen (N2) fixing algae in the Baltic Sea is assumed to be determinable from a surplus of dissolved inorganic phosphorus (DIP) that remains after the spring bloom has ended. But this surplus DIP concentration is observed to continuously decrease at times when no appreciable nitrogen fixation is measured. This peculiarity is currently discussed and has afforded different model interpretations for the Baltic Sea. In our study we propose a dynamical model solution that explains these observations with variations of the elemental carbon-to-nitrogen-to-phosphorus (C:N:P) ratio during distinct periods of organic matter production and remineralization. The biogeochemical model resolves seasonal C, N and P fluxes with depth at the Baltic Sea monitoring site BY15, based on three assumptions: (1) DIP is utilized by algae though not needed for immediate growth, (2) the uptake of dissolved inorganic nitrogen (DIN) is hampered when the algae׳s phosphorus (P) quota is low, and (3) carbon assimilation continues at times of nutrient depletion. Model results describe observed temporal variations of DIN, DIP and chlorophyll-a concentrations along with partial pressure of carbon dioxide (pCO2)(pCO2). In contrast to other model studies, our solution does not require N2 fixation to occur shortly after the spring bloom to explain DIP drawdown and pCO2pCO2 levels. Model estimates of annual N2 fixation are View the MathML source297±24mmolNm-2a-1. Estimates of total production are View the MathML source14200±700mmolCm-2a-1, View the MathML source1400±70mmolNm-2a-1, and View the MathML source114±5mmolPm-2a-1 for the upper 50 m. The models C, N and P fluxes disclose preferential remineralization of P and of organic N that was introduced via N2 fixation. Our results are in support of the idea that P uptake by phytoplankton during the spring bloom contributes to the consecutive availability of labile dissolved organic phosphorus (LDOP). The LDOP is retained within upper layers and its remineralization affects algal growth in summer, during periods of noticeable N2 fixation.

Description: Highlights: • Sensitivities of annual carbon (C), nitrogen (N) and phosphorus (P) flux estimates to parameter variations are determined. • Model parameters that specify annual inventories are compared with those that determine timing and magnitude of bloom events. • Seven model parameters are of primary importance, affecting C, N and P budgets simultaneously. • Nine parameters have negligible effects on annual budget estimates and on seasonal trajectories. • Parameter categorization provides important prior information for parameter optimization in the central Baltic Sea. Abstract: This study describes a sensitivity analysis that allows the parameters of a one-dimensional ecosystem model to be ranked according to their specificity in determining biochemical key fluxes. Key fluxes of interest are annual (a) total production (TP), (b) remineralization above the halocline (RM), and (c) export at 50 m (EX) at the Baltic Sea monitoring site BY15 located in the Gotland Deep basin. The model resolves mass flux of carbon (C), nitrogen (N), and phosphorous (P), while considering nitrogen fixation explicitly. Our first null hypothesis is that the variation of the value of every single model parameter affects each annual C, N, and P budget simultaneously. Our second null hypothesis states that the variation of every parameter value induces changes at least in either of the annual C, N or P budgets. Our analyses falsify both null hypotheses and reveal that 8 out of 36 parameters must be regarded redundant, as their variation neither alter annual key fluxes nor produce considerable time-shifts in model trajectories at the respective site. Seven parameters were found to induce substantial changes in annual C, N, and P flux estimates simultaneously. The assimilation efficiency of zooplankton turned out to be of vital importance. This parameter discriminates between the assimilation and destruction of algal prey during grazing. The fraction of unassimilated dead algal cells is critical for the amount of organic matter exported out of the euphotic zone. The maximum cellular N:C quota of diazotrophs and the degradation/hydrolysis rate of detrital carbon are two parameters that will likely remain unconstrained by time series data, but both affect the annual C budget considerably. Overall, our detailed specification of model sensitivities to parameter variations will facilitate the formulation of a well-posed inverse problem for the estimation of C, N and P fluxes from stock observations at the Gotland Deep.

Description: A central aspect of coastal biogeochemistry is to determine how nutrients, lithogenic- and organic matter are distributed and transformed within coastal and estuarine environments. Analyses of the spatio-temporal changes of total suspended matter (TSM) concentration indicate strong and variable linkages between intertidal fringes and pelagic regions. In particular, knowledge about the organic fraction of TSM provides insight to how biogenic and lithogenic particulate matter are distributed in suspension. In our study we take advantage of a set of over 3000 in situ Loss on Ignition (LoI) data from the Southern North Sea that represent fractions of particulate organic matter (POM) relative to TSM (LoI $\equiv$ POM:TSM). We introduce a parameterization (POM-TSM model) that distinguishes between two POM fractions incorporated in TSM. One fraction is described in association with mineral particles. The other represents a seasonally varying fresh pool of POM. The performance of the POM-TSM model is tested against data derived from MERIS/ENVISAT-TSM products of the German Bight. Our analysis of remote sensing data exhibits specific qualitative features of TSM that can be attributed to distinct coastal zones. Most interestingly, a transition zone between the Wadden Sea and seasonally stratified regions of the Southern North Sea is identified where mineral associated POM appears in concentrations comparable to those of freshly produced POM. We will discuss how this transition is indicative for a zone of effective particle interaction and sedimentation.The dimension of this transition zone varies between seasons and with location. Our proposed POM-TSM model is generic and can be calibrated against in situ data of other coastal regions.

Description: Marine phytoplankton can regulate their stoichiometric composition in response to variations in the availability of nutrients, light and the pH of seawater. Varying elemental composition of photoautotrophs affects several important ecological and biogeochemical processes, e.g., primary and export production, nutrient cycling, calcification, and grazing. Here we compare two plankton ecosystem models that consider regulatory mechanisms of cellular carbon and nitrogen, driving the physiological acclimation of photoautotrophs. The Carbon:Nitrogen Regulated Ecosystem Model (CN-REcoM) and the optimality-based model (OBM) differ in their representation of phytoplankton dynamics, i.e. nutrient acquisition, synthesis of chlorophyll a, and growth. All other model compartments (zooplankton, detritus, dissolved inorganic and organic matter) and processes (grazing, aggregation, remineralisation) remain identical in both models. We assess the skills of the two models against data from an ocean acidification mesocosm experiment with three CO2 treatments. Neither model accounts for any carbon dioxide (CO2) effects explicitly. Instead, we assimilate data of the different CO2 treatments separately into the models. Thereby we aim at identifying optimal model parameter values that might correlate with differences in CO2 conditions. For the OBM, optimal parameter estimates of Qmin (subsistence N:C ratio) and V (maximum potential photosynthesis rate of photoautotrophs) turned out to be higher for mesocosms exposed to high CO2 compared to those with low CO2 concentrations. By contrast, a similar correlation is not observed for the CN-REcoM. A possible physiological interpretation of higher estimates of Qmin and V according to the OBM is that phytoplankton may experience environmental stress under more acidic conditions, and hence must invest more energy/resources for maintaining basic cellular functions. Our data assimilation reveals that the parameters of the OBM are better constrained by the data than those of the CN-REcoM. Furthermore, the OBM is better able than CN-REcoM to reproduce data that were not used for parameter optimization.