ALBERT

Description: Over the last ten years, satellite and geographically constrained in situ observations largely focused on the northern hemisphere have suggested that annual phytoplankton biomass cycles cannot be fully understood from environmental properties controlling phytoplankton division rates (e.g., nutrients and light), as they omit the role of ecological and environmental loss processes (e.g., grazing, viruses, sinking). Here, we use multi-year observations from a very large array of robotic drifting floats in the Southern Ocean to determine key factors governing phytoplankton biomass dynamics over the annual cycle. Our analysis reveals seasonal phytoplankton accumulation (‘blooming’) events occurring during periods of declining modeled division rates, an observation that highlights the importance of loss processes in dictating the evolution of the seasonal cycle in biomass. In the open Southern Ocean, the spring bloom magnitude is found to be greatest in areas with high dissolved iron concentrations, consistent with iron being a well-established primary limiting nutrient in this region. Under ice observations show that biomass starts increasing in early winter, well before sea ice begins to retreat. The average theoretical sensitivity of the Southern Ocean to potential changes in seasonal nutrient and light availability suggests that a 10% change in phytoplankton division rate may be associated with a 50% reduction in mean bloom magnitude and annual primary productivity, assuming simple changes in the seasonal magnitude of phytoplankton division rates. Overall, our results highlight the importance of quantifying and accounting for both division and loss processes when modeling future changes in phytoplankton biomass cycles.

Description: Uncertainties in projections of marine biogeochemistry from Earth system models (ESMs) are associated to a large degree with the imperfect representation of the marine plankton ecosystem, in particular the physiology of primary and secondary producers. Here, we describe the implementation of an optimality-based plankton–ecosystem model (OPEM) version 1.1 with variable carbon : nitrogen : phosphorus (C:N:P) stoichiometry in the University of Victoria ESM (UVic; Eby et al., 2009; Weaver et al., 2001) and the behaviour of two calibrated reference configurations, which differ in the assumed temperature dependence of diazotrophs. Predicted tracer distributions of oxygen and dissolved inorganic nutrients are similar to those of an earlier fixed-stoichiometry formulation in UVic (Nickelsen et al., 2015). Compared to the classic fixed-stoichiometry UVic model, OPEM is closer to recent satellite-based estimates of net community production (NCP), despite overestimating net primary production (NPP), can better reproduce deep-ocean gradients in the NO3-:PO43- ratio and partially explains observed patterns of particulate C:N:P in the surface ocean. Allowing diazotrophs to grow (but not necessarily fix N2) at similar temperatures as other phytoplankton results in a better representation of surface Chl and NPP in the Arctic and Antarctic oceans. Deficiencies of our calibrated OPEM configurations may serve as a magnifying glass for shortcomings in global biogeochemical models and hence guide future model development. The overestimation of NPP at low latitudes indicates the need for improved representations of temperature effects on biotic processes, as well as phytoplankton community composition, which may be represented by locally varying parameters based on suitable trade-offs. The similarity in the overestimation of NPP and surface autotrophic particulate organic carbon (POC) could indicate deficiencies in the representation of top-down control or nutrient supply to the surface ocean. Discrepancies between observed and predicted vertical gradients in particulate C:N:P ratios suggest the need to include preferential P remineralisation, which could also benefit the representation of N2 fixation. While OPEM yields a much improved distribution of surface N* (NO3--16⋅PO43-+2.9 mmol m−3), it still fails to reproduce observed N* in the Arctic, possibly related to a misrepresentation of the phytoplankton community there and the lack of benthic denitrification in the model. Coexisting ordinary and diazotrophic phytoplankton can exert strong control on N* in our simulations, which questions the interpretation of N* as reflecting the balance of N2 fixation and denitrification.

Description: Uncertainties in projections from Earth system models (ESMs) are associated to a large degree with the imperfect representation of the marine plankton ecosystem, in particular the physiology of primary and secondary producers. Here we describe the implementation of an optimality-based plankton-ecosystem model (OPEM) with variable C:N:P stoichiometry in the University of Victoria ESM (UVic) and the behaviour of two calibrated reference configurations, which differ in the assumed temperature dependence of diazotrophs. Predicted tracer distributions of oxygen and dissolved inorganic nutrients are similar to those of an earlier fixed-stoichiometry model (Keller et al., 2012). Compared to the classic fixed-stoichiometry model, OPEM is closer to recent satellite-based estimates of net community production (NCP), despite overestimating net primary production (NPP), can better reproduce deep-ocean gradients in the NO3:PO43− ratio, and partially explains observed patterns of particulate C:N:P in the surface ocean. Allowing diazotrophs to grow (but not necessarily fix N2) at similar temperatures as other phytoplankton results in a better representation of surface Chl and NPP in the Arctic and Antarctic Oceans. Deficiencies of our calibrated OPEM configurations may serve as a magnifying glass for shortcomings in global biogeochemical models and hence guide future model development. The overestimation of NPP at low latitudes indicates the need for improved representations of temperature effects on biotic processes, as well as phytoplankton community composition, which may be represented by locally-varying parameters based on suitable trade-offs. Discrepancies between observed and predicted vertical gradients in particulate C:N:P ratios suggest the need to include preferential P remineralisation, which could also benefit the representation of N2 fixation. While OPEM yields a much improved distribution of surface N* (NO3− 16·PO43− + 2.9 mmol m−3), it still fails to reproduce observed N* in the Arctic, possibly related to a mis-representation of the phytoplankton community there and the lack of benthic denitrification in the model. Coexisting ordinary and diazotrophic phytoplankton can exert strong control on N* in our simulations, which questions the interpretation of N* as reflecting the balance of N2 fixation and denitrification.