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.

Description: The Baltic Sea is prone to oxygen deficiency due to the restricted water exchange with the North Sea in coincidence with a high biological oxygen demand. The partitioning of organic carbon between respiration, accumulation and export is co-determined by phytoplankton primary production and its subsequent bacterial remineralization. Here, we investigated net phytoplankton primary production, heterotrophic bacterial biomass production and dark CO2 fixation by on-board incubations with radiolabeled tracers in the Baltic Proper and in the Gulf of Riga after the main spring bloom. Results show that low phytoplankton standing stocks of ≤1.6 μg chlorophyll a L–1 sustained net primary production of 161–724 mg C m–2 d–1 under nitrogen limitation. Estimates of bacterial carbon remineralization suggest that freshly produced organic carbon was supplied to the aphotic zone at all stations. In the southern Baltic Proper, net primary production exceeded the bacterial carbon demand in the surface mixed layer, suggesting that organic matter derived from nutrient-limited primary production was available for export to bacterial communities below the oxycline. On average, 46% of heterotrophic bacterial production was mediated in oxygen minimum zones, revealing the high importance of organic matter recycling under hypoxic and anoxic conditions for the carbon budget. Dark CO2 fixation of up to 4.33 μg C L–1 d–1 in sulfide-free waters equaled 9–54% of the co-inciding heterotrophic bacterial carbon demand and may have provided another organic carbon source for heterotrophic activity. Substantially higher dark CO2 fixation up to 25.46 μg C L–1 d–1 was determined in sulfidic waters. Since our study was conducted 5 months after the major Baltic inflow event in winter 2014/2015, potential effects of deep water ventilation could be investigated. In the Gotland Basin, heterotrophic bacterial production in renewed oxygen-rich bottom water was similar to that in the uplifted oxygen-deficient former bottom water, while it was significantly reduced in sulfidic waters. Hence, our results suggest that the removal of hydrogen sulfide by inflow events has a high potential to increase bacterial carbon remineralization.

Description: Mesocosm experiments on phytoplankton dynamics under high CO2 concentrations mimic the response of marine primary producers to future ocean acidification. However, potential acidification effects can be hindered by the high standard deviation typically found in the replicates of the same CO2 treatment level. In experiments with multiple unresolved factors and a sub-optimal number of replicates, post-processing statistical inference tools might fail to detect an effect that is present. We propose that in such cases, data-based model analyses might be suitable tools to unearth potential responses to the treatment and identify the uncertainties that could produce the observed variability. As test cases, we used data from two independent mesocosm experiments. Both experiments showed high standard deviations and, according to statistical inference tools, biomass appeared insensitive to changing CO2 conditions. Conversely, our simulations showed earlier and more intense phytoplankton blooms in modeled replicates at high CO2 concentrations and suggested that uncertainties in average cell size, phytoplankton biomass losses, and initial nutrient concentration potentially outweigh acidification effects by triggering strong variability during the bloom phase. We also estimated the thresholds below which uncertainties do not escalate to high variability. This information might help in designing future mesocosm experiments and interpreting controversial results on the effect of acidification or other pressures on ecosystem functions

Description: Phytoplankton species composition and the associated community size structure are expected to change with a warming and freshening of the Arctic Ocean. Cell size controls many physiological (bottom-up) processes, such as nutrient uptake, photosynthesis and growth, thereby affecting the functioning of the planktonic ecosystem as a whole. Furthermore, predator-prey interaction (top-down control) is highly size dependent. The size structure of the phytoplankton community in the Fram Strait has been analysed, based on observations of cell abundance and size. Non- parametric size spectra are obtained from microscopic observations, using a statistical approach that also provides respective confidence intervals. A bootstrap approach is applied, with cell counts and size measurements being resampled respectively. Kernel density estimates (KDE) are derived for all resampled data sets. The collection of KDEs yield robust continuous descriptions of cell density versus cell size together with their confidence limits. With this approach we resolve detailed changes in community size structure that shall be used to improve and constrain results of a size-based plankton ecosystem model. Size dependencies of bottom-up and top-down effects on biogeochemical mass flux will be investigated. The calibrated model can then be applied for deriving reliable projections of how the planktonic ecosystem in the Arctic may be affected by climate change.