ALBERT

Description: Recent modeling results suggest that oceanic oxygen levels will decrease significantly over the next decades to centuries in response to climate change and altered ocean circulation. Hence the future ocean may experience major shifts in nutrient cycling triggered by the expansion and intensification of tropical oxygen minimum zones (OMZs). There are numerous feedbacks between oxygen concentrations, nutrient cycling and biological productivity; however, existing knowledge is insufficient to understand physical, chemical and biological interactions in order to adequately assess past and potential future changes. We investigated the pelagic biogeochemistry of OMZs in the eastern tropical North Atlantic and eastern tropical South Pacific during a series of cruise expeditions and mesocosm studies. The following summarizes the current state of research on the influence of low environmental oxygen conditions on marine biota, viruses, organic matter formation and remineralization with a particular focus on the nitrogen cycle in OMZ regions. The impact of sulfidic events on water column biogeochemistry, originating from a specific microbial community capable of highly efficient carbon fixation, nitrogen turnover and N2O production is further discussed. Based on our findings, an important role of sinking particulate organic matter in controlling the nutrient stochiometry of the water column is suggested. These particles can enhance degradation processes in OMZ waters by acting as microniches, with sharp gradients enabling different processes to happen in close vicinity, thus altering the interpretation of oxic and anoxic environments.

Description: Both atmospheric deposition and benthic remineralisation influence the marine nitrogen cycle, and hence ultimately also marine primary production. The biological and biogeochemical relations in the eastern tropical South Pacific (ETSP) among nitrogen deposition, benthic denitrification and phosphorus regeneration are analysed in a prognostic box model of the oxygen, nitrogen and phosphorus cycles in the ETSP. Atmospheric nitrogen deposition ( ≈ 1.5 Tg N yr−1 for the years 2000–2009) is offset by half in the model by reduced N2 fixation, with the other half transported out of the model domain. Model- and data-based benthic denitrification in our model domain are responsible for losses of 0.19 and 1.0 Tg Tg N yr−1, respectively, and both trigger nitrogen fixation, partly compensating for the NO3− loss. Model- and data-based estimates of enhanced phosphate release via sedimentary phosphorus regeneration under suboxic conditions are 0.062 and 0.11 Tg N yr−1, respectively. Since phosphate is the ultimate limiting nutrient in the model, even very small additional phosphate inputs stimulate primary production and subsequent export production and NO3− loss in the oxygen minimum zone (OMZ). A sensitivity analysis of the local response to both atmospheric deposition and benthic remineralisation indicates dominant stabilising feedbacks in the ETSP, which tend to keep a balanced nitrogen inventory; i.e. nitrogen input by atmospheric deposition is counteracted by decreasing nitrogen fixation; NO3− loss via benthic denitrification is partly compensated for by increased nitrogen fixation; enhanced nitrogen fixation stimulated by phosphate regeneration is partly counteracted by stronger water-column denitrification. Even though the water column in our model domain acts as a NO3− source, the ETSP including benthic denitrification might be a NO3− sink.

Description: Marine ecosystem models used to investigate how global change affects ocean ecosystems and their functioning typically omit pelagic plankton diversity. Diversity, however, may affect functions such as primary production and their sensitivity to environmental changes. Here we use a global ocean ecosystem model that explicitly resolves phytoplankton diversity by defining subtypes within four phytoplankton functional types (PFTs). We investigate the model's ability to capture diversity effects on primary production under environmental change. An idealized scenario with a sudden reduction in vertical mixing causes diversity and primary-production changes that turn out to be largely independent of the number of coexisting phytoplankton subtypes. The way diversity is represented in the model provides a small number of niches with respect to nutrient use in accordance with the PFTs defined in the model. Increasing the number of phytoplankton subtypes increases the resolution within the niches. Diversity effects such as niche complementarity operate between, but not within PFTs, and are constrained by the variety of traits and trade-offs resolved in the model. The number and nature of the niches formulated in the model, for example via trade-offs or different PFTs, thus determines the diversity effects on ecosystem functioning captured in ocean ecosystem models.

Description: Local coupling between nitrogen fixation and denitrification in current biogeochemical models could result in runaway feedback in open-ocean oxygen minimum zones (OMZs), eventually stripping OMZ waters of all fixed nitrogen. This feedback does not seem to operate at full strength in the ocean, as nitrate does not generally become depleted in open-ocean OMZs. To explore in detail the possible mechanisms that prevent nitrogen depletion in the OMZ of the eastern tropical South Pacific (ETSP), we develop a box model with fully prognostic cycles of carbon, nutrients and oxygen in the upwelling region and its adjacent open ocean. Ocean circulation is calibrated with Δ14C data of the ETSP. The sensitivity of the simulated nitrogen cycle to nutrient and oxygen exchange and ventilation from outside the model domain and to remineralization scales inside an OMZ is analysed. For the entire range of model configurations explored, we find that the fixed-N inventory can be stabilized at non-zero levels in the ETSP OMZ only if the remineralization rate via denitrification is slower than that via aerobic respiration. In our optimum model configuration, lateral oxygen supply into the model domain is required at rates sufficient to oxidize at least about one fifth of the export production in the model domain to prevent anoxia in the deep ocean. Under these conditions, our model is in line with the view of phosphate as the ultimate limiting nutrient for phytoplankton, and implies that for the current notion of nitrogen fixation being favoured in N-deficit waters, the water column of the ETSP could even be a small net source of nitrate.

Description: We analyse 400 perturbed-parameter simulations for two configurations of an optimality-based plankton-ecosystem model (OPEM), implemented in the University of Victoria Earth-System Climate Model (UVic-ESCM), using a Latin-Hypercube sampling method for setting up the parameter ensemble. A likelihood-based metric is introduced for model assessment and selection of the model solutions closest to observed distributions of NO3−, PO43−, O2, and surface chlorophyll a concentrations. According to our metric the optimal model solutions comprise low rates of global N2 fixation and denitrification. These two rate estimates turned out to be poorly constrained by the data. For identifying the “best” model solutions we therefore also consider the model’s ability to represent current estimates of water-column denitrification. We employ our ensemble of model solutions in a sensitivity analysis to gain insights into the importance and role of individual model parameters as well as correlations between various biogeochemical processes and tracers, such as POC export and the NO3− inventory. Global O2 varies by a factor of two and NO3− by more than a factor of six among all simulations. Remineralisation rate is the most important parameter for O2, which is also affected by the subsistence N quota of ordinary phytoplankton (QN0,phy) and zooplankton maximum specific ingestion rate. QN0,phy is revealed as a major determinant of the oceanic NO3− pool. This indicates that unraveling the driving forces of variations in phytoplankton physiology and elemental stoichiometry, which are tightly linked via QN0,phy, is a prerequisite for understanding the marine nitrogen inventory.

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.

Description: The acclimative response of phytoplankton, which adjusts their nutrient and pigment content in response to changes in ambient light, nutrient levels, and temperature, is an important determinant of observed chlorophyll distributions and biogeochemistry. Acclimative models typically capture this response and its impact on the C : nutrient : Chl ratios of phytoplankton by explicitly resolving the dynamics of these constituents of phytoplankton biomass. The instantaneous acclimation (IA) approach only requires resolving the dynamics of a single tracer and calculates the elemental composition assuming instantaneous local equilibrium. IA can capture the acclimative response without substantial loss of accuracy in both 0D box models and spatially explicit 1D models. A major drawback of IA so far has been its inability to maintain mass balance for the elements with unresolved dynamics. Here we extend the IA model to capture both C and N cycles in a 0D setup, which requires analytical derivation of additional flux terms to account for the temporal changes in cellular N quota, Q. We present extensive tests of this model, with regard to the conservation of total C an N and its behavior in comparison to an otherwise equivalent, fully explicit dynamic acclimation (DA) variant under idealized conditions with variable light and temperature. We also demonstrate a modular implementation of this model in the Framework for Aquatic Biogeochemical Modelling (FABM), which facilitates modeling competition between an arbitrary number of different acclimative phytoplankton types. In a 0D setup, we did not find evidence for computational advantages of the IA approach over the DA variant. In a spatially explicit setup, performance gains may be possible but would require modifying the physical-flux calculations to account for spatial differences in Q between model grid cells.

Description: Nitrogen (N) is a crucial limiting nutrient for phytoplankton growth in the ocean. The main source of bioavailable N in the ocean is delivered by N2-fixing diazotrophs in the surface layer. Since field observation of N2 fixation are spatially and temporally sparse, the fundamental processes and mechanisms controlling N2 fixation are not well understood and constrained. Here, we implement benthic denitrification in an Earth System Model of intermediate complexity (UVic-ESCM 2.9) coupled to an optimality-based plankton ecosystem model (OPEM v1.1). Benthic denitrification occurs mostly in coastal upwelling regions and on shallow continental shelves, and is the largest N-loss process in the global ocean. We calibrate our model against three different combinations of observed Chl, NO3-, PO43-, O2 and N* = NO3- −16PO43- +2.9. The inclusion of N* provides a powerful constraint on biogeochemical model behavior. Our new model version including benthic denitrification simulates higher global rates of N2 fixation with a more realistic distribution extending to higher latitudes that are supported by independent estimates based on geochemical data. Oxygen deficient zone volume and water column denitrification rates are reduced in the new version, indicating that including benthic denitrification may improve global biogeochemical models that commonly overestimate anoxic zones. With the improved representation of the ocean N cycle, our new model configuration also yields better global net primary production (NPP) when compared to the independent datasets not included in the calibration. Benthic denitrification plays an important role shaping N2 fixation and NPP throughout the global ocean in our model, and should be considered when evaluating and predicting their response to environmental change.