ALBERT

Description: The effect of ocean acidification on growth and calcification of the marine algae Emiliania huxleyi was investigated in a series of mesocosm experiments where enclosed water volumes that comprised a natural plankton community were exposed to different carbon dioxide (CO2) concentrations. Calcification rates observed during those experiments were found to be highly variable, even among replicate mesocosms that were subject to similar CO2 perturbations. Here, data from an ocean acidification mesocosm experiment are reanalysed with an optimality-based dynamical plankton model. According to our model approach, cellular calcite formation is sensitive to variations in CO2 at the organism level. We investigate the temporal changes and variability in observations, with a focus on resolving observed differences in total alkalinity and particulate inorganic carbon (PIC). We explore how much of the variability in the data can be explained by variations of the initial conditions and by the level of CO2 perturbation. Nine mesocosms of one experiment were sorted into three groups of high, medium, and low calcification rates and analysed separately. The spread of the three optimised ensemble model solutions captures most of the observed variability. Our results show that small variations in initial abundance of coccolithophores and the prevailing physiological acclimation states generate differences in calcification that are larger than those induced by ocean acidification. Accordingly, large deviations between optimal mass flux estimates of carbon and of nitrogen are identified even between mesocosms that were subject to similar ocean acidification conditions. With our model-based data analysis we document how an ocean acidification response signal in calcification can be disentangled from the observed variability in PIC.

Description: A considerable amount of primary production by marine phytoplankton is released to seawater as dissolved organic matter (DOM) via exudation and leakage processes. The labile fraction of DOM can either directly serve as a source of energy and nutrients or is transformed to particulate matter by abiotic gel particle formation. Principally, both pathways induce diverse effects on higher trophic levels, as they: (i) affect the growth of bacteria and photo-autotrophic nanoplankton, which directly affects the microbial foodweb, and (ii) enhance the formation of aggregates, which provide pelagic microhabitats but also accelerate the export of organic matter to the benthos. Reliable biogeochemical flux estimates of these distinct pathways will crucially depend on our understanding of small-scale processes. Here, we show examples that address the microbial turnover of organic matter and how it is related to primary and secondary production in the North Atlantic and at sites in shelf regions. Recent findings on the sensitivity of microbial processes to changes in temperature and pH will be incorporated. Ecosystems in coastal and shelf regions are most sensitive to anthropogenic impacts, as they are susceptible not only to global changes but also to regional changes. We will therefore give an outlook on how to improve monitoring, experimental, and modelling strategies to better account for microbial foodweb dynamics when assessing climate change effects on ecosystems in coastal and shelf regions.

Description: During phytoplankton growth a fraction of dissolved inorganic carbon (DIC) assimilated by phytoplankton is exuded in the form of dissolved organic carbon (DOC), which can be transformed into extracellular particulate organic carbon (POC). A major fraction of extracellular POC is associated with carbon of transparent exopolymer particles (TEP; carbon content = TEPC) that form from dissolved polysaccharides (PCHO). The exudation of PCHO is linked to an excessive uptake of DIC that is not directly quantifiable from utilisation of dissolved inorganic nitrogen (DIN), called carbon overconsumption. Given these conditions, the concept of assuming a constant stoichiometric carbon-to-nitrogen (C:N) ratio for estimating new production of POC from DIN uptake becomes inappropriate. Here, a model of carbon overconsumption is analysed, combining phytoplankton growth with TEPC formation. The model describes two modes of carbon overconsumption. The first mode is associated with DOC exudation during phytoplankton biomass accumulation. The second mode is decoupled from algal growth, but leads to a continuous rise in POC while particulate organic nitrogen (PON) remains constant. While including PCHO coagulation, the model goes beyond a purely physiological explanation of building up carbon rich particulate organic matter (POM). The model is validated against observations from a mesocosm study. Maximum likelihood estimates of model parameters, such as nitrogen- and carbon loss rates of phytoplankton, are determined. The optimisation yields results with higher rates for carbon exudation than for the loss of organic nitrogen. It also suggests that the PCHO fraction of exuded DOC was 63±20% during the mesocosm experiment. Optimal estimates are obtained for coagulation kernels for PCHO transformation into TEPC. Model state estimates are consistent with observations, where 30% of the POC increase was attributed to TEPC formation. The proposed model is of low complexity and is applicable for large-scale biogeochemical simulations.

Description: Estuary-type circulation is a residual circulation in coastal systems with horizontal density gradients. It drives the accumulation of suspended particulate matter in coastal embayments where density gradients are sustained by some freshwater inflow from rivers. Ebenhöh et al. (Ecol Model 174(3):241–252, 2004) found that shallow water depth can explain nutrient gradients becoming established towards the coast even in the absence of river inflow. The present study follows their concept and investigates the characteristic transport of organic matter towards the coast based on idealised scenarios whereby an estuary-type circulation is maintained by surface freshwater fluxes and pronounced shoaling towards the coast. A coupled hydrodynamical and biogeochemical model is used to simulate the dynamics of nutrient gradients and to derive budgets of organic matter flux for a coastal transect. Horizontal nutrient gradients are considered only in terms of tidal asymmetries of suspended matter transport. The results show that the accumulation of organic matter near the coast is not only highly sensitive to variations in the sinking velocity of suspended matter but is also noticeably enhanced by an increase in precipitation. This scenario is comparable with North Sea conditions. By contrast, horizontal nutrient gradients would be reversed in the case of evaporation-dominated inverse estuaries (cf. reverse gradients of nutrient and organic matter concentrations). Credible coastal nutrient budget calculations are required for resolving trends in eutrophication. For tidal systems, the present results suggest that these calculations require an explicit consideration of freshwater flux and asymmetries in tidal mixing. In the present case, the nutrient budget for the vertically mixed zone also indicates carbon pumping from the shelf sea towards the coast from as far offshore as 25 km.

Description: To describe the underlying processes involved in oceanic plankton dynamics is crucial for the determination of energy and mass flux through an ecosystem and for the estimation of biogeochemical element cycling. Many planktonic ecosystem models were developed to resolve major processes so that flux estimates can be derived from numerical simulations. These results depend on the type and number of parameterizations incorporated as model equations. Furthermore, the values assigned to respective parameters specify a model's solution. Representative model results are those that can explain data; therefore, data assimilation methods are utilized to yield optimal estimates of parameter values while fitting model results to match data. Central difficulties are (1) planktonic ecosystem models are imperfect and (2) data are often too sparse to constrain all model parameters. In this review we explore how problems in parameter identification are approached in marine planktonic ecosystem modelling. We provide background information about model uncertainties and estimation methods, and how these are considered for assessing misfits between observations and model results. We explain differences in evaluating uncertainties in parameter estimation, thereby also discussing issues of parameter identifiability. Aspects of model complexity are addressed and we describe how results from cross-validation studies provide much insight in this respect. Moreover, approaches are discussed that consider time- and space-dependent parameter values. We further discuss the use of dynamical/statistical emulator approaches, and we elucidate issues of parameter identification in global biogeochemical models. Our review discloses many facets of parameter identification, as we found many commonalities between the objectives of different approaches, but scientific insight differed between studies. To learn more from results of planktonic ecosystem models we recommend finding a good balance in the level of sophistication between mechanistic modelling and statistical data assimilation treatment for parameter estimation

Description: The influence of seawater carbon dioxide (CO2) concentration on the size distribution of suspended particles (2–60 μm) and on phytoplankton abundance was investigated during a mesocosm experiment at the large scale facility (LFS) in Bergen, Norway, in the frame of the Pelagic Ecosystem CO2 Enrichment study (PeECE II). In nine outdoor enclosures the partial pressure of CO2 in seawater was modified by an aeration system to simulate past (~190 μatm CO2), present (~370 μatm CO2) and future (~700 μatm CO2) CO2 conditions in triplicates. Due to the initial addition of inorganic nutrients, phytoplankton blooms developed in all mesocosms and were monitored over a period of 19 days. Seawater samples were collected daily for analysing the abundance of suspended particles and phytoplankton with the Coulter Counter and with Flow Cytometry, respectively. During the bloom period, the abundance of small particles (〈4 μm) significantly increased at past, and decreased at future CO2 levels. At that time, a direct relationship between the total-surface-to-total-volume ratio of suspended particles and DIC concentration was determined for all mesocosms. Significant changes with respect to the CO2 treatment were also observed in the phytoplankton community structure. While some populations such as diatoms seemed to be insensitive to the CO2 treatment, others like Micromonas spp. increased with CO2, or showed maximum abundance at present day CO2 (i.e. Emiliania huxleyi). The strongest response to CO2 was observed in the abundance of small autotrophic nano-plankton that strongly increased during the bloom in the past CO2 mesocosms. Together, changes in particle size distribution and phytoplankton community indicate a complex interplay between the ability of the cells to physiologically respond to changes in CO2 and size selection. Size of cells is of general importance for a variety of processes in marine systems such as diffusion-limited uptake of substrates, resource allocation, predator-prey interaction, and gravitational settling. The observed changes in particle size distribution are therefore discussed with respect to biogeochemical cycling and ecosystem functioning.

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: Controlled manipulation of environmental conditions within large enclosures in the ocean, so-called pelagic mesocosms, has become a standard method to explore potential responses of marine plankton communities to anthropogenic change. Among the challenges of interpreting mesocosm data is the often uncertain role of vertical mixing, which usually is not observed directly. To account for mixing nonetheless, two pragmatic assumptions are common: either that the water column is homogeneously mixed or that it is divided into two water bodies with a horizontal barrier inhibiting turbulent exchange. In this study, we present a model-based reanalysis of vertical turbulent diffusion in the mesocosm experiments PeECE III and KOSMOS 2013. Our diffusivity estimates indicate intermittent mixing events along with stagnating periods and yield simulated temperature and salinity profiles that are consistent with the observations. Here, we provide the respective diffusivities as a comprehensive data product in the Network Common Data Format (NetCDF). This data product will help to guide forthcoming model studies that aim at deepening our understanding of biogeochemical processes in the PeECE III and KOSMOS 2013 mesocosms, such as the CO2-related changes in marine carbon export. In addition, we make our model code available, providing an adjustable tool to simulate vertical mixing in any other pelagic mesocosm. The data product and the model code are available at https://doi.org/10.1594/PANGAEA.905311 (Mathesius et al., 2019).

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.