Linking process rates with modelling data and ecosystem characteristics

This report is related to the BONUS project “Nutrient Cocktails in COAstal zones of the Baltic Sea” alias COCOA. The aim of BONUS COCOA is to investigate physical, biogeochemical and biological processes in a combined and coordinated fashion to improve the understanding of the interaction of these processes on the removal of nutrients along the land-sea interface. The report is especially related to BONUS COCOA WP 6 in which the main objective is extrapolation of results from the BONUS COCOA learning sites to coastal sites around the Baltic Sea in general. Specific objectives of this deliverable (D6.4) were to connect observed process rates with modelling data and ecosystem characteristics. In the report we made statistical analyses of observations from BONUS COCOA study sites together with results from the Swedish Coastal zone Model (SCM). Eight structural variables (water depth, temperature, salinity, bottom water concentrations of oxygen, ammonium, nitrate and phosphate, as well as nitrogen content in sediment) were found common to both the experimentally determined and the model data sets. The observed process rate evaluated in this report was denitrification. In addition regressions were tested between observed denitrification rates and several structural variables (latitude, longitude, depth, light, temperature, salinity, grain class, porosity, loss of ignition, sediment organic carbon, total nitrogen content in the sediment,  sediment carbon/nitrogen-ratio, sediment chlorphyll-a as well as bottom water concentrations of oxygen, ammonium, nitrate, and dissolved inorganic  phosphorus and silicate) for pooled data from all learning sites. The statistical results showed that experimentally determined multivariate data set from the shallow, illuminated stations was mainly found to be similar to the multivariate data set produced by the SCM model. Generally, no strong correlations of simple relations between observed denitrification and available structural variables were found for data collected from all the learning sites. We found some non-significant correlation between denitrification rates and bottom water dissolved inorganic phosphorous and dissolved silica but the reason behind the correlations is not clear. We also developed and evaluated a theory to relate process rates to monitoring data and nutrient retention. The theoretical analysis included nutrient retention due to denitrification as well as burial of phosphorus and nitrogen. The theory of nutrient retention showed good correlations with model results. It was found that area-specific nitrogen and phosphorus retention capacity in a sub-basin depend much on mean water depth, water residence time, basin area and the mean nutrient concentrations in the active sediment layer and in the water column

Adenosine triphosphate in the marine boundary layer in the southern Baltic Sea

Changes in adenosine triphosphate (ATP) concentration weremeasured in the offshore and coastal waters of the Gdansk Basinin spring. As regards the vertical distribution, it was found that highATP concentrations occurred mainly in the euphotic layer (abovethe thermocline) and near the bottom (below the halocline).The high concentrations of ATP in the euphotic layer resultedfrom primary and secondary production, while the other maximum wasdue to the presence of bacteria actively degrading organic matter.Changes in ATP concentration in the euphotic layerwere closely correlated with the phase of the day. An increase inATP concentrations in the surface microlayer was observed inthe evening and at night, probably as a result of heterotroph proliferation.During daylight, ATP production was inhibited by increasing radiation,hence its concentrations in the sea surface microlayer were considerably lower.Strong winds exerted a significant influence on ATP concentrations in thesurface microlayer and in the subsurface water. Windstress depressed ATPconcentrations. The biomass of living microorganismsin the microlayer was comparable with the microbiomass beneath the halocline

Temporal variability in the chemical composition of bottom sediments in the Pomeranian Bay (southern Baltic)* Pomeranian Bay Sediments Organic carbon Organic nitrogen C/N ratio Total phosphorus Organic phosphorus

Abstract Seasonal changes in the chemical composition of sediments from four stations located in the Pomeranian Bay were analysed. The investigations were carried out in four period

Diurnal variations in nitrogen, phosphorus and iron compounds in the southern Baltic Sea

In order to assess their short-term variability, nutrient concentrations were measured at standard depths at 2 h intervals in the deepest region of the Gdańsk Deep during the first ten days of June 2001. The mean concentrations of nutrients in the euphotic zone were: N_N (NO₂^-, NO₃^-, NH₄⁺) - 1.93 µmol dm^-3, PO₄^3- - 0.12 µmol dm^-3 and Fe_tot - 0.11 µmol dm^-3. During daylight hours, when the rate of assimilation was fastest, concentrations of nitrogen, phosphorus and iron compounds were very low. The phosphate concentration fell to a minimum (0.03 µmol dm^-3) between 04:00 and 10:00 hrs, while total iron dropped to 0.01 µmol dm^-3 between 10:00 and 16:00 hrs. Both levels were below the limiting values for phosphorus and iron. At night, concentrations of NO₃^- and PO₄^3- rose by 25%, those of NH₄⁺ and Fe_tot by 35%. The mean molar ratios of N_N:PO₄^3- and Fe_tot:PO₄^3- in the surface layer were subject to significant daily fluctuations. The molar N_N:PO₄^3- ratio was higher than the optimum value established for the Baltic Sea. Below the halocline, the concentrations of dissolved iron and phosphorus rose as a result of diffusion from sediments in response to changing redox conditions

New simple statistical formulas for estimating surface concentrations of suspended particulate matter (SPM) and particulate organic carbon (POC) from remote-sensing reflectance in the southern Baltic Sea

In a step taken towards improving the new system for the satellite monitoring of the Baltic Sea environment, officially started in Poland recently (SatBałtyk System, see http://www.satbaltyk.pl), a new set of simple statistical formulas was derived. These combine the empirically determined spectral values of remote-sensing reflectance Rrs(λ) with the mass concentrations of suspended particulate matter (SPM) and particulate organic carbon (POC) in southern Baltic surface waters. The new formulas are based on 73 empirical data sets gathered during 4 research cruises on board r/v Oceania during spring and late summer in the open waters of the southern Baltic and coastal regions of the Gulf of Gdańsk. Correlations of SPM and POC concentrations with reflectance or reflectance ratios in various spectral bands were tested. Several variants of candidate statistical relationships, which can be used later in the construction of simple local remote sensing algorithms for the waters in question, are introduced here. These relationships utilise either absolute values of Rrs at a selected waveband, mostly from the yellow, red or near infrared part of the light spectrum, or Rrs ratios for two different wavebands, mostly ratios of blue to yellow, blue to red and blue to infrared or green to yellow and green to red spectral band. From the numerous simple approximate relationships established, the following two, characterised by large correlation coefficients r2 and small standard error factors X, may serve as examples: SPM [g m−3] = 1480(Rrs(710))0.902 (with the factors r2 = 0.86; X = 1.26) (the unit of Rrs(λ) is [sr−1]) and POC [g m−3] = 0.814(Rrs(555)/Rrs(589))−4.42 (r2 = 0.75; X = 1.37). From the practical standpoint, taking into consideration light wavelengths that are close to or concurrent with the currently available spectral bands used in satellite observations of the Baltic Sea, another two formulas (using the same spectral ratio) are worth pointing out: SPM [g m−3] = 2.6(Rrs(490)/Rrs(625))−1.29 (r2 = 0.86; X = 1.25) and POC [g m−3] = 0.774(Rrs(490)/Rrs(625))−1.18 (r2 = 0.66; X = 1.44). The paper also presents a number of intermediate statistical relationships between SPM and POC concentrations, Rrs spectra and light backscattering coefficients in order to illustrate the simplified physical justification for some of the observed direct statistical relationships, presented as the main content of this work