Zooplankton oxygen consumption and nutrient release in relation to species composition, animals size and enviromental conditions in the Baltic Sea during May and August

[EN] Zooplankton metabolism in terms of oxygen consumption and ñutrient reléase (ammonia, phosphate) were measiu'ed in the Baltic Sea, a températe área with high envirormiental changes both in space and in time. Plankton of the surface layer were analysed with balance measurements in 4 size classes between 50 and 1000 nm during spring in 1988, 1990 and 1991, in summer 19^8 and 1990 as well. The use of electrón transport system (ETS), and the Glutamate Dehydrogenase (GDH) activity as indicators for respiration and ammonia reléase respectively, enlarged the data density and made a three dimensional resolution available (May 1990, 1991). Data are in the range of the latitudinal dependend magnitude. They reflect slight interannual, more seasonal and regional aspects. Animáis size, temperature, food concentration, and species composition influence the specific rates

Coupling between upper ocean layer variability and size-fractionated phytoplankton in a non-nutrient-limited environment

[EN] We describe the coupling between upper ocean layer variability and size-fractionated phytoplankton distribution in the non-nutrient-limited Bransfield Strait region (BS) of Antarctica. For this purpose we use hydrographic and size-fractionated chlorophyll a data from a transect that crossed 2 fronts and an eddy, together with data from 3 stations located in a deeply mixed region, the Antarctic Sound (AS). In the BS transect, small phytoplankton (<20 μm equivalent spherical diameter [ESD]) accounted for 80% of total chl a and their distribution appeared to be linked to cross-frontal variability. On the deepening upper mixed layer (UML) sides of both fronts we observed a deep subducting column-like structure of small phytoplankton biomass. On the shoaling UML sides of both fronts, where there were signs of restratification, we observed a local shallow maximum of small phytoplankton biomass. We propose that this observed phytoplankton distribution may be a response to the development of frontal vertical circulation cells. In the deep, turbulent environment of the AS, larger phytoplankton (>20 μm ESD) accounted for 80% of total chl a. The proportion of large phytoplankton increases as the depth of the upper mixed layer (ZUML), and the corresponding rate of vertical mixing, increases. We hypothesize that this change in phytoplankton composition with varying ZUML is related to the competition for light, and results from modification of the light regime caused by vertical mixing.

Physiological and metabolic effects of nutrient enrichment on adult Artemia franciscana

[EN] Brine shrimp nauplii (Artemia sp.) are used in aquaculture as the major food source for many cultured marine larvae, and also used in the adult phase for many juvenile and adult fish. One artemia species, Artemia franciscana is most commonly preferred, due to the availability of its cysts and to its ease in hatching and biomass production. The problem with A. franciscana is that its nutritional quality is relatively poor in essential fatty acids, so that it is common practice to enrich it with emulsions like SELCO and ORIGO. This “bioencapsulation”, enrichment method permits the incorporation of different kinds of products into the artemia. This brine-shrimp’s non-selective particle-feeding habits, makes it particularly suitable for this enrichment process. The bioencapsulation is done just prior to feeding the artemia to a predator organism. This allows the delivery of different substances, not only for nutrient enrichment, but also for changing pigmentation and administering medicine. This is especially useful in culturing ornamental seahorses and tropical fish in marine aquaria In this study the objectives were to determine, the relative nutrient value of ORIGO and SELCO as well as the optimal exposure to these supplements prior to their use as food-organisms.

Carbon flux, nutrient retention efficiency and the curvature of respiration depth-profiles in the ocean water column

Trabajo realizado por: Packard, T. T., Osma, N., Fernández Urruzola, I., Gómez, M

Assimilation of Meteosat Second Generation (MSG) satellite data in a regional numerical weather prediction model using a one-dimensional variational approach

The quality of temperature and humidity retrievals from the infrared SEVIRI sensors on the geostationary Meteosat Second Generation (MSG) satellites is assessed by means of a one dimensional variational algorithm. The study is performed with the aim of improving the spatial and temporal resolution of available observations to feed analysis systems designed for high resolution regional scale numerical weather prediction (NWP) models. The non-hydrostatic forecast model COSMO (COnsortium for Small scale MOdelling) in the ARPA-SIM operational configuration is used to provide background fields. Only clear sky observations over sea are processed. An optimised 1D–VAR set-up comprising of the two water vapour and the three window channels is selected. It maximises the reduction of errors in the model backgrounds while ensuring ease of operational implementation through accurate bias correction procedures and correct radiative transfer simulations. The 1D–VAR retrieval quality is firstly quantified in relative terms employing statistics to estimate the reduction in the background model errors. Additionally the absolute retrieval accuracy is assessed comparing the analysis with independent radiosonde and satellite observations. The inclusion of satellite data brings a substantial reduction in the warm and dry biases present in the forecast model. Moreover it is shown that the retrieval profiles generated by the 1D–VAR are well correlated with the radiosonde measurements. Subsequently the 1D–VAR technique is applied to two three–dimensional case–studies: a false alarm case–study occurred in Friuli–Venezia–Giulia on the 8th of July 2004 and a heavy precipitation case occurred in Emilia–Romagna region between 9th and 12th of April 2005. The impact of satellite data for these two events is evaluated in terms of increments in the integrated water vapour and saturation water vapour over the column, in the 2 meters temperature and specific humidity and in the surface temperature. To improve the 1D–VAR technique a method to calculate flow–dependent model error covariance matrices is also assessed. The approach employs members from an ensemble forecast system generated by perturbing physical parameterisation schemes inside the model. The improved set–up applied to the case of 8th of July 2004 shows a substantial neutral impact.

A dynamical system approach to data assimilation in chaotic models

The Assimilation in the Unstable Subspace (AUS) was introduced by Trevisan and Uboldi in 2004, and developed by Trevisan, Uboldi and Carrassi, to minimize the analysis and forecast errors by exploiting the flow-dependent instabilities of the forecast-analysis cycle system, which may be thought of as a system forced by observations. In the AUS scheme the assimilation is obtained by confining the analysis increment in the unstable subspace of the forecast-analysis cycle system so that it will have the same structure of the dominant instabilities of the system. The unstable subspace is estimated by Breeding on the Data Assimilation System (BDAS). AUS- BDAS has already been tested in realistic models and observational configurations, including a Quasi-Geostrophicmodel and a high dimensional, primitive equation ocean model; the experiments include both fixed and“adaptive”observations. In these contexts, the AUS-BDAS approach greatly reduces the analysis error, with reasonable computational costs for data assimilation with respect, for example, to a prohibitive full Extended Kalman Filter. This is a follow-up study in which we revisit the AUS-BDAS approach in the more basic, highly nonlinear Lorenz 1963 convective model. We run observation system simulation experiments in a perfect model setting, and with two types of model error as well: random and systematic. In the different configurations examined, and in a perfect model setting, AUS once again shows better efficiency than other advanced data assimilation schemes. In the present study, we develop an iterative scheme that leads to a significant improvement of the overall assimilation performance with respect also to standard AUS. In particular, it boosts the efficiency of regime’s changes tracking, with a low computational cost. Other data assimilation schemes need estimates of ad hoc parameters, which have to be tuned for the specific model at hand. In Numerical Weather Prediction models, tuning of parameters — and in particular an estimate of the model error covariance matrix — may turn out to be quite difficult. Our proposed approach, instead, may be easier to implement in operational models.

Algal wastewater treatment and biomass producing potential: nutrient removal efficiency and cell physiological responses

Microalgae are sun - light cell factories that convert carbon dioxide to biofuels, foods, feeds, and other bioproducts. The concept of microalgae cultivation as an integrated system in wastewater treatment has optimized the potential of the microalgae - based biofuel production. These microorganisms contains lipids, polysaccharides, proteins, pigments and other cell compounds, and their biomass can provide different kinds of biofuels such as biodiesel, biomethane and ethanol. The algal biomass application strongly depends on the cell composition and the production of biofuels appears to be economically convenient only in conjunction with wastewater treatment. The aim of this research thesis was to investigate a biological wastewater system on a laboratory scale growing a newly isolated freshwater microalgae, Desmodesmus communis, in effluents generated by a local wastewater reclamation facility in Cesena (Emilia Romagna, Italy) in batch and semi - continuous cultures. This work showed the potential utilization of this microorganism in an algae - based wastewater treatment; Desmodesmus communis had a great capacity to grow in the wastewater, competing with other microorganisms naturally present and adapting to various environmental conditions such as different irradiance levels and nutrient concentrations. The nutrient removal efficiency was characterized at different hydraulic retention times as well as the algal growth rate and biomass composition in terms of proteins, polysaccharides, total lipids and total fatty acids (TFAs) which are considered the substrate for biodiesel production. The biochemical analyses were coupled with the biomass elemental analysis which specified the amount of carbon and nitrogen in the algal biomass. Furthermore photosynthetic investigations were carried out to better correlate the environmental conditions with the physiology responses of the cells and consequently get more information to optimize the growth rate and the increase of TFAs and C/N ratio, cellular compounds and biomass parameter which are fundamental in the biomass energy recovery.