Description: In this paper, we review the state of the art and major challenges in current efforts to incorporate biogeochemical functional groups into models that can be applied on basin-wide and global scales, with an emphasis on models that might ultimately be used to predict how biogeochemical cycles in the ocean will respond to global warming. We define the term “biogeochemical functional group” to refer to groups of organisms that mediate specific chemical reactions in the ocean. Thus, according to this definition, “functional groups” have no phylogenetic meaning—these are composed of many different species with common biogeochemical functions. Substantial progress has been made in the last decade toward quantifying the rates of these various functions and understanding the factors that control them. For some of these groups, we have developed fairly sophisticated models that incorporate this understanding, e.g. for diazotrophs (e.g. Trichodesmium), silica producers (diatoms) and calcifiers (e.g. coccolithophorids and specifically Emiliania huxleyi). However, current representations of nitrogen fixation and calcification are incomplete, i.e., based primarily upon models of Trichodesmium and E. huxleyi, respectively, and many important functional groups have not yet been considered in open-ocean biogeochemical models. Progress has been made over the last decade in efforts to simulate dimethylsulfide (DMS) production and cycling (i.e., by dinoflagellates and prymnesiophytes) and denitrification, but these efforts are still in their infancy, and many significant problems remain. One obvious gap is that virtually all functional group modeling efforts have focused on autotrophic microbes, while higher trophic levels have been completely ignored. It appears that in some cases (e.g., calcification), incorporating higher trophic levels may be essential not only for representing a particular biogeochemical reaction, but also for modeling export. Another serious problem is our tendency to model the organisms for which we have the most validation data (e.g., E. huxleyi and Trichodesmium) even when they may represent only a fraction of the biogeochemical functional group we are trying to represent. When we step back and look at the paleo-oceanographic record, it suggests that oxygen concentrations have played a central role in the evolution and emergence of many of the key functional groups that influence biogeochemical cycles in the present-day ocean. However, more subtle effects are likely to be important over the next century like changes in silicate supply or turbulence that can influence the relative success of diatoms versus dinoflagellates, coccolithophorids and diazotrophs. In general, inferences drawn from the paleo-oceanographic record and theoretical work suggest that global warming will tend to favor the latter because it will give rise to increased stratification. However, decreases in pH and Fe supply could adversely impact coccolithophorids and diazotrophs in the future. It may be necessary to include explicit dynamic representations of nitrogen fixation, denitrification, silicification and calcification in our models if our goal is predicting the oceanic carbon cycle in the future, because these processes appear to play a very significant role in the carbon cycle of the present-day ocean and they are sensitive to climate change. Observations and models suggest that it may also be necessary to include the DMS cycle to predict future climate, though the effects are still highly uncertain. We have learned a tremendous amount about the distributions and biogeochemical impact of bacteria in the ocean in recent years, yet this improved understanding has not yet been incorporated into many of our models. All of these considerations lead us toward the development of increasingly complex models. However, recent quantitative model intercomparison studies suggest that continuing to add complexity and more functional groups to our ecosystem models may lead to decreases in predictive ability if the models are not properly constrained with available data. We also caution that capturing the present-day variability tells us little about how well a particular model can predict the future. If our goal is to develop models that can be used to predict how the oceans will respond to global warming, then we need to make more rigorous assessments of predictive skill using the available data.

Description: Highlights • We objectively identify and remove unconstrained parameters from a marine ecosystem model. • Optimal model complexity is identified using three model selection metrics. • As many as 14 of the model’s 30 parameters can be removed, with no significant reduction in model-data misfit. • Optimal model structures and parameters are different at two different North Atlantic locations. • The specialised structures and parameters at each site may be unsuitable for new environments The degree of structural complexity that should be incorporated in marine biogeochemical models is unclear. We know that the marine ecosystem is complex, and that its observed behaviour is attributable to the interaction of a large number of separate processes, but observations are scarce and often insufficient to constrain more than a small number of model parameters. This issue is addressed using a novel algorithm that systematically removes model processes that are not constrained by observations. The algorithm is applied to a one-dimensional, eight component ecosystem-biogeochemistry model at two North Atlantic time-series sites. Between 11 and 14 of the 30 model parameters can be removed at each site with no significant reduction in the model’s ability to fit upper ocean (0–200 m) biogeochemical tracer and productivity data. The statistically optimal model structures and parameters provide estimates of the most likely state variables and fluxes at each site. Differences in these estimates between the two sites indicate that the optimal models are specialised to both the physical environment and the assimilated observations. At each site the heavily reduced models may thus be suitable for diagnostic purposes but may not be sufficiently complex for more general applications, such as in global ocean general circulation models, or for predicting the response of marine systems to environmental change.

Description: Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.

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: Protecting the ocean has become a major goal of international policy as human activities increasingly endanger the integrity of the ocean ecosystem, often summarized as “ocean health.” By and large, efforts to protect the ocean have failed because, among other things, (1) the underlying socio-ecological pathways have not been properly considered, and (2) the concept of ocean health has been ill defined. Collectively, this prevents an adequate societal response as to how ocean ecosystems and their vital functions for human societies can be protected and restored. We review the confusion surrounding the term “ocean health” and suggest an operational ocean-health framework in line with the concept of strong sustainability. Given the accelerating degeneration of marine ecosystems, the restoration of regional ocean health will be of increasing importance. Our advocated transdisciplinary and multi-actor framework can help to advance the implementation of more active measures to restore ocean health and safeguard human health and well-being.

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: Highlights • SPM concentration and organic fractions are analyzed in coastal-offshore gradients • Diagnostic model of SPM allows separating fresh, labile from less reactive PON • Analysis of PON fractions reveals a characteristic area, the transition zone • There, particle settling is enhanced, fostering their transport back to the coast, which controls the fate of organic matter • The transition zone is generally confined to water depths below 20 m Abstract Identifying the mechanisms that contribute to the variability of suspended particulate matter concentrations in coastal areas is important but difficult, especially due to the complexity of physical and biogeochemical interactions involved. Our study addresses this complexity and investigates changes in the horizontal spread and composition of particles, focusing on cross-coastal gradients in the southern North Sea and the English Channel. A semi-empirical model is applied on in situ data of SPM and its organic fraction to resolve the relationship between organic and inorganic suspended particles. The derived equations are applied onto remote sensing products of SPM concentration, which provide monthly synoptic maps of particulate organic matter concentrations (here, particulate organic nitrogen) at the surface together with their labile and less reactive fractions. Comparing these fractions of particulate organic matter reveals their characteristic features along the coastal-offshore gradient, with an area of increased settling rate for particles generally observed between 5 and 30 km from the coast. We identify this area as the transition zone between coastal and offshore waters with respect to particle dynamics. Presumably, in that area, the turbulence range and particle composition favor particle settling, while hydrodynamic processes tend to transport particles of the seabed back towards the coast. Bathymetry plays an important role in controlling the range of turbulent dissipation energy values in the water column, and we observe that the transition zone in the southern North Sea is generally confined to water depths below 20 m. Seasonal variations in suspended particle dynamics are linked to biological processes enhancing particle flocculation, which do not affect the location of the transition zone. We identify the criteria that allow a transition zone and discuss the cases where it is not observed in the domain. The impact of these particle dynamics on coastal carbon storage and export is discussed.