Description: Arctic coastal ecosystems are rapidly changing due to climate warming. This makes modeling their produc- tivity crucially important to better understand future changes. System primary production in these systems is highest dur- ing the pronounced spring bloom, typically dominated by di- atoms. Eventually the spring blooms terminate due to sili- con or nitrogen limitation. Bacteria can play an important role for extending bloom duration and total CO2 fixation through ammonium regeneration. Current ecosystem mod- els often simplify the effects of nutrient co-limitations on al- gal physiology and cellular ratios and simplify nutrient re- generation. These simplifications may lead to underestimations of primary production. Detailed biochemistry- and cell- based models can represent these dynamics but are difficult to tune in the environment. We performed a cultivation experiment that showed typical spring bloom dynamics, such as extended algal growth via bacterial ammonium remineralization, reduced algal growth and inhibited chlorophyll synthesis under silicate limitation, and gradually reduced nitrogen assimilation and chlorophyll synthesis under nitrogen limitation. We developed a simplified dynamic model to represent these processes. Overall, model complexity in terms of the number of parameters is comparable to the phytoplankton growth and nutrient biogeochemistry formulations in common ecosystem models used in the Arctic while improv- ing the representation of nutrient-co-limitation-related processes. Such model enhancements that now incorporate in- creased nutrient inputs and higher mineralization rates in a warmer climate will improve future predictions in this vulnerable system.

Description: Phytoplankton functional‐type (PFT) data are assimilated into the global coupled ocean‐ecosystem model MITgcm‐REcoM2 for two years using a local ensemble Kalman filter. The ecosystem model has two PFTs: small phytoplankton (SP) and diatoms. Three different sets of satellite PFT data are assimilated: Ocean‐Color‐Phytoplankton Functional Type (OC‐PFT), Phytoplankton Differential Optical Absorption Spectroscopy (PhytoDOAS), and SYNergistic exploitation of hyper‐ and multi‐spectral precursor SENtinel measurements to determine Phytoplankton Functional Types (SynSenPFT), which is a synergistic product combining the independent PFT products OC‐PFT and PhytoDOAS. The effect of assimilating PFT data is compared with the assimilation of total chlorophyll data (TChla), which constrains both PFTs through multivariate assimilation. While the assimilation of TChla already improves both PFTs, the assimilation of PFT data further improves the representation of the phytoplankton community. The effect is particularly large for diatoms where, compared to the assimilation of TChla, the SynSenPFT assimilation results in 57% and 67% reduction of root‐mean‐square error and bias, respectively, while the correlation is increased from 0.45 to 0.54. For SP the assimilation of SynSenPFT data reduces the root‐mean‐square error and bias by 14% each and increases the correlation by 30%. The separate assimilation of the PFT data products OC‐PFT, SynSenPFT, and joint assimilation of OC‐PFT and PhytoDOAS data leads to similar results while the assimilation of PhytoDOAS data alone leads to deteriorated SP but improved diatoms. When both OC‐PFT and PhytoDOAS data are jointly assimilated, the representation of diatoms is improved compared to the assimilation of only OC‐PFT. The results show slightly lower errors than when the synergistic SynSenPFT data are assimilated, which shows that the assimilation successfully combines the separate data sources.

Description: Primary production by phytoplankton represents a major pathway whereby atmospheric CO2 is sequestered in the ocean, but this requires iron, which is in scarce supply. As over 99% of iron is complexed to organic ligands, which increase iron solubility and microbial availability, understanding the processes governing ligand dynamics is of fundamental importance. Ligands within humic-like substances have long been considered important for iron complexation, but their role has never been explained in an oceanographically consistent manner. Here we show iron co-varying with electroactive humic substances at multiple open ocean sites, with the ratio of iron to humics increasing with depth. Our results agree with humic ligands composing a large fraction of the iron-binding ligand pool throughout the water column. We demonstrate how maximum dissolved iron concentrations could be limited by the concentration and binding capacity of humic ligands, and provide a summary of the key processes that could influence these parameters. If this relationship is globally representative, humics could impose a concentration threshold that buffers the deep ocean iron inventory. This study highlights the dearth of humic data, and the immediate need to measure electroactive humics, dissolved iron and iron-binding ligands simultaneously from surface to depth, across different ocean basins.

Description: In this study, a three-dimensional, coupled ocean ecosystem model (FESOM- REcoM2) is used to investigate the effect of krill on the biogeochemistry of the Southern Ocean. The implementation of Antarctic krill in the model was done in three steps. 1) A second zooplankton group was implemented, which grazes on diatoms, mesozooplankton and nanophytoplankton (in order of descending preference). 2) A new detritus group was added to the model, which represents faster-sinking krill fecal pellets. 3) The grazing impact of both zooplankton groups on detritus was described. Afterward, four different simulations (control and three krill simulations for previously described steps) were conducted to evaluate, how the implementation of the new zooplankton group and additional features affected biogeochemical processes in the Southern Ocean. In our krill simulation, the spatial distribution of krill biomass in the Southern Ocean was reasonably reproduced. Preliminary results showed that the proportion of living compartments (phytoplankton and zooplankton groups) in the model changed, which led to different POC (particulate organic carbon) flux pathways to the deep ocean. Zooplankton biomass contribution to total carbon biomass increased from 2.4% to 10% in our model in the Southern Ocean. The contribution of zooplankton to POC production doubled. The implementation of krill in the ecosystem model enhanced nutrient recycling in the upper ocean layer. Therefore, our novel krill implementation improved the bias between model and observations in surface spatial distributions of the macronutrients silicic acid and nitrate.

Description: Macrozooplankton and its grazing pressure shape ecosystem structures and carbon pathways in the Southern Ocean. Here, we present the implementation of “polar macrozooplankton” as a plankton functional type and a related fast-sinking detritus class (fecal pellets) into the biogeochemical model REcoM-2. We use the model to assess major carbon pathways and ecosystem structure in the Southern Ocean south of 50°S. The model represents zooplankton biomass and its spatial distribution in the Southern Ocean reasonably well in comparison to available biomass data. A distinct difference of our model from previous versions is the seasonal pattern of particle formation processes and ecosystem structures in the Southern Ocean. REcoM-2 now captures high zooplankton biomass and a typical shift from a dominance of phytodetrital aggregates in spring to zooplankton fecal pellets later in the year. At sites with high biomass of macrozooplankton, the transfer efficiency of particulate organic carbon can be as high as 50%, and the carbon content of the exported material increases. In our simulations, macrozooplankton is an important component of the Southern Ocean plankton community, contributing up to 0.12 Pg C per year (14%) to total modeled carbon export across 100 m depth. Macrozooplankton changes the phytoplankton composition and supports the recycling of macronutrients. These results support the important role of macrozooplankton such as krill in the Southern Ocean and have implications for the representation of Southern Ocean biogeochemical cycles in models.

Description: Globally, mesoscale processes create a rich and filamented pattern in biological productivity. Despite of remoteness and a harsh environment, observations likewise show an impact of mesoscale processes on phytoplankton growth in the Arctic. Observations of sufficiently high resolution are, however, difficult to carry out. Large-scale models are another way to gain knowledge about the system. In the current study, we use a global sea ice-ocean biogeochemical model, which is eddy resolving in Fram Strait, to show that the mesoscale dynamics has a strong effect on shaping phytoplankton growth. For the year 2009, we demonstrate that the growth season in the West Spitzbergen Current can be divided into two regimes; during Regime I, which takes place in May and June before and during the spring bloom, high chlorophyll concentrations are associated with areas of positive vorticity and a shallow mixed layer, pointing toward light limitation controlling growth. During Regime II, which occurs after the bloom from mid-July to late August, the highest chlorophyll concentration is found in areas of negative vorticity. Here, upwelling of nutrient-rich water occurs, through doming isopycnals, acting to raise the nutricline, may also play a role in alleviating nutrient limitation in the surface water. The study suggests that the mesoscale eddy environment locally modulates the seasonal cycle of light and nutrient limitation. Knowledge of the eddy field should be taken into consideration for making conclusions from point-wise measurements in Fram Strait.