Cyanobacteria net community production in the Baltic Sea as inferred from profiling pCO(2) measurements

Organic matter production by cyanobacteria blooms is a major environmental concern for the Baltic Sea, as it promotes the spread of anoxic zones. Partial pressure of carbon dioxide (pCO(2)) measurements carried out on Ships of Opportunity (SOOP) since 2003 have proven to be a powerful tool to resolve the carbon dynamics of the blooms in space and time. However, SOOP measurements lack the possibility to directly constrain depth-integrated net community production (NCP) in moles of carbon per surface area due to their restriction to the sea surface. This study tackles the knowledge gap through (1) providing an NCP best guess for an individual cyanobacteria bloom based on repeated profiling measurements of pCO(2) and (2) establishing an algorithm to accurately reconstruct depth-integrated NCP from surface pCO(2) observations in combination with modelled temperature profiles.Goal (1) was achieved by deploying state-of-the-art sensor technology from a small-scale sailing vessel. The low-cost and flexible platform enabled observations covering an entire bloom event that occurred in July-August 2018 in the Eastern Gotland Sea. For the biogeochemical interpretation, recorded pCO(2) profiles were converted to C-T*, which is the dissolved inorganic carbon concentration normalised to alkalinity. We found that the investigated bloom event was dominated by Nodularia and had many biogeochemical characteristics in common with blooms in previous years. In particular, it lasted for about 3 weeks, caused a C-T* drawdown of 90 mu mol kg(-1), and was accompanied by a sea surface temperature increase of 10 degrees C. The novel finding of this study is the vertical extension of the C-T* drawdown up to the compensation depth located at around 12 m. Integration of the C-T* drawdown across this depth and correction for vertical fluxes leads to an NCP best guess of similar to 1:2 mol m(-2) over the productive period.Addressing goal (2), we combined modelled hydrographical profiles with surface pCO(2) observations recorded by SOOP Finnmaid within the study area. Introducing the temperature penetration depth (TPD) as a new parameter to integrate SOOP observations across depth, we achieve an NCP reconstruction that agrees to the best guess within 10 %, which is considerably better than the reconstruction based on a classical mixed-layer depth constraint.Applying the TPD approach to almost 2 decades of surface pCO(2) observations available for the Baltic Sea bears the potential to provide new insights into the control and long-term trends of cyanobacteria NCP. This understanding is key for an effective design and monitoring of conservation measures aiming at a Good Environmental Status of the Baltic Sea

The Role of Turbulence in Fueling the Subsurface Chlorophyll Maximum in Tidally Dominated Shelf Seas

Glider observations show a subsurface chlorophyll maximum (SCM) at the base of the seasonal pycnocline in the North Sea during stable summer conditions. A colocated peak in the dissipation rate of turbulent kinetic energy suggests the presence of active turbulence that potentially generates a nutrient flux to fuel the SCM. A one‐dimensional turbulence closure model is used to investigate the dynamics behind this local maximum in turbulent dissipation at the base of the pycnocline (PCB) as well as its associated nutrient fluxes. Based on a number of increasingly idealized forcing setups of the model, we are able to draw the following conclusions: (a) only turbulence generated inside the stratified PCB is able to entrain a tracer (e.g., nutrients) from the bottom mixed layer into the SCM region; (b) surface wind forcing only plays a secondary role during stable summer conditions; (c) interfacial shear from the tide accounts for the majority of turbulence production at the PCB; (d) in stable summer conditions, the strength of the turbulent diapycnal fluxes at the PCB is set by the strength of the anticyclonic component of the tidal currents.Plain Language Summary: Many midlatitude shelf seas are vertically stratified in summer, where a warm surface layer sits on top of a cold, dense bottom layer. Both of these layers are unproductive environments for phytoplankton—the bottom layer is light limited, and the surface layer is nutrient‐limited. However, abundant phytoplankton is observed directly at the interface between surface and bottom layers. In order to sustain this phytoplankton, nutrient‐rich bottom water needs to be mixed with interface water. While both wind and tides are major causes for mixing in the coastal ocean, we find that the tides alone provide sufficient stirring at the right place to potentially act as an effective fuel pump for the phytoplankton. Interestingly, it is not the strength of the tides alone that counts, rather the sense of rotation of the tidal currents; rotation opposite to the Earth's spin causes more stirring than rotation along with it.Key Points: Turbulence and chlorophyll both peak at the base of the pycnocline on a mid‐latitude shelf. Locally generated turbulence at the pycnocline base is a fuel pump for the subsurface chlorophyll maximum. Amplitude and polarity of the M2 tide govern the local generation of turbulence at the pycnocline base.Helmholtz Associationhttps://doi.org/10.5281/zenodo.3525787https://oceancolor.gsfc.nasa.gov/l3/https://www.cen.uni-hamburg.de/icdc/data/ocean/nsbc.htm

Cryptic or simply neglected diversity?

The southern North Sea constitutes one of the best studied and data rich, but also most exploited marine areas globally. However, still we lack sufficient knowledge of core ecological features and processes, e.g., species distribution dynamics, environmental drivers, and their links. Although meaningful management requires knowledge of the spatial structure and variability of the systems, the traditional approach sees species handled together according to the concept of ecological communities. Consequently, the scientific “handling” of the linkage between environmental drivers and biota does neither consider nor test whether the targeted communities actually exist or are just artificial artifacts created by the classification process. Crisp classifications are used to identify and define “communities” adding the further limitation of correctly setting a community border that possibly does not exist. But how valid is this approach? This is the question we tackle here. We analyse a large data set of about 1150 grab samples of benthic macrofauna collected in the German Bight. We applied fuzzy logic to provide an unsupervised classification of any degree of species association. Random Forest aided in mapping all degrees of species association and to shed light on their potential environmental drivers. Our approach overcomes the problem of crisp borders between communities. It classifies faunal associations in a continuous range from areas where one community can be well defined to areas where no community is distinguishable. One endpoint of this range is characterized by associations with highly structured interactions and dependency between species. The other endpoint is characterized by associations assembled by random processes. The German Bight benthos displays the full range of association types. Regions where random association of species occurs show higher small-scale spatial variability, which indicates higher turnover rates than areas characterized by communities. These findings raise important questions for conservation strategies. Are these dynamic areas of higher “value”? How can conservation management account for a more complex spatial pattern as well as for the different turnover rates

A numerical model for the entire Wadden Sea: skill assessment and analysis of hydrodynamics

A baroclinic three-dimensional numerical model for the entire Wadden Sea of the German Bight in the southern North Sea is first assessed by comparison to field data for surface elevation, current velocity, temperature, and salinity at selected stations and then used to calculate fluxes of volume and salt inside the Wadden Sea and the exchange between the Wadden Sea and the adjacent North Sea through the major tidal inlets. The model is simulating the reference years 2009–2011. An overview of tidal prisms and residual volume fluxes of the main inlets and their variability is given. In addition, data from an intensive observational campaign in a tidal channel south of the island of Spiekeroog as well as satellite images and observations of sea surface properties from a ship of opportunity are used for the skill assessment. Finally, the intensity of estuarine overturning circulation and its variability in the tidal gullies are quantified and analyzed as function of gravitational and wind straining using various estimates including Total Exchange Flow (TEF). Regional differences between the gullies are assessed and drivers of the estuarine circulation are identified. For some inlets, the longitudinal buoyancy gradient dominates the exchange flow, for some others wind straining is more important. Also the intensity of tidal straining (scaled covariance of eddy viscosity and vertical shear) depends on buoyancy gradient and wind forcing in different ways, depending on local topography, orientation toward the main wind direction, and influence by freshwater run off inside or outside the tidal basin

The Baltic Sea Model Intercomparison Project (BMIP) - a platform for model development, evaluation, and uncertainty assessment

While advanced computational capabilities have enabled the development of complex ocean general circulation models (OGCMs) for marginal seas, systematic comparisons of regional ocean models and their setups are still rare. The Baltic Sea Model Intercomparison Project (BMIP), introduced herein, was therefore established as a platform for the scientific analysis and systematic comparison of Baltic Sea models. The inclusion of a physically consistent regional reanalysis data set for the period 1961–2018 allows for standardized meteorological forcing and river runoff. Protocols to harmonize model outputs and analyses are provided as well. An analysis of six simulations performed with four regional OGCMs differing in their resolution, grid coordinates, and numerical methods was carried out to explore intermodel differences despite harmonized forcing. Uncertainties in the modeled surface temperatures were shown to be larger at extreme than at moderate temperatures. In addition, a roughly linear increase in the temperature spread with increasing water depth was determined and indicated larger uncertainties in the near-bottom layer. On the seasonal scale, the model spread was larger in summer than in winter, likely due to differences in the models' thermocline dynamics. In winter, stronger air–sea heat fluxes and vigorous convective and wind mixing reduced the intermodel spread. Uncertainties were likewise reduced near the coasts, where the impact of meteorological forcing was stronger. The uncertainties were highest in the Bothnian Sea and Bothnian Bay, attributable to the differences between the models in the seasonal cycles of sea ice triggered by the ice–albedo feedback. However, despite the large spreads in the mean climatologies, high interannual correlations between the sea surface temperatures (SSTs) of all models and data derived from a satellite product were determined. The exceptions were the Bothnian Sea and Bothnian Bay, where the correlation dropped significantly, likely related to the effect of sea ice on air–sea heat exchange. The spread of water salinity across the models is generally larger compared to water temperature, which is most obvious in the long-term time series of deepwater salinity. The inflow dynamics of saline water from the North Sea is covered well by most models, but the magnitude, as inferred from salinity, differs as much as the simulated mean salinity of deepwater. Marine heat waves (MHWs), coastal upwelling, and stratification were also assessed. In all models, MHWs were more frequent in shallow areas and in regions with seasonal ice cover. An increase in the frequency (regionally varying between ∼50 % and 250 %) and duration (50 %–150 %) of MHWs during the last 3 decades in all models was found as well. The uncertainties were highest in the Bothnian Bay, likely due to the different trends in sea ice presence. All but one of the analyzed models overestimated upwelling frequencies along the Swedish coast, the Gulf of Finland, and around Gotland, while they underestimated upwelling in the Gulf of Riga. The onset and seasonal cycle of thermal stratification likewise differed among the models. Compared to observation-based estimates, in all models the thermocline in early spring was too deep, whereas a good match was obtained in June when the thermocline intensifies