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See detailA mathematical modelling of bloom of the coccolithophore Emiliania huxleyi in a mesocosm experiment
Joassin, Pascal ULg; Delille, Bruno ULg; Soetaert, Karline et al

Poster (2008, July 23)

A dynamic model has been developed to represent biogeochemical variables and processes observed during a bloom of Emiliania huxleyi coccolithophore. This bloom was induced in a mesocosm experiment during ... [more ▼]

A dynamic model has been developed to represent biogeochemical variables and processes observed during a bloom of Emiliania huxleyi coccolithophore. This bloom was induced in a mesocosm experiment during which the ecosystem development was followed over a period of 23-days through changes in various biogeochemical parameters such as inorganic nutrients (nitrate, ammonium and phosphate), total alkalinity (TA), dissolved inorganic carbon (DIC), partial pressure of carbon dioxide (pCO2), dissolved oxygen (O2), photosynthetic pigments, particulate organic carbon (POC), dissolved organic carbon (DOC), Transparent Exopolymer Particles (TEP), primary production, and calcification. This dynamic model is based on unbalanced algal growth and balanced bacterial growth. In order to adequately reproduce the observations, the model includes an explicit description of phosphorus cycling, calcification, TEP production and an enhanced mortality due to viral lysis. The model represented carbon, nitrogen and phosphorus fluxes observed in the mesocosms. Modelled profiles of algal biomass and final concentrations of DIC and nutrients are in agreement with the experimental observations. [less ▲]

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See detailA mathematical modelling of bloom of the coccolithophore Emiliania huxleyi in a mesocosm experiment
Joassin, Pascal ULg; Delille, Bruno ULg; Soetaert, K. et al

in Biogeosciences Discussions (2008), 5

A dynamic model has been developed to represent biogeochemical variables and processes observed during a bloom of Emiliania huxleyi coccolithophore. This bloom was induced in a mesocosm experiment during ... [more ▼]

A dynamic model has been developed to represent biogeochemical variables and processes observed during a bloom of Emiliania huxleyi coccolithophore. This bloom was induced in a mesocosm experiment during which the ecosystem development was followed over a period of 23-days through changes in various biogeochemical parameters such as inorganic nutrients (nitrate, ammonium and phosphate), total alkalinity (TA), dissolved inorganic carbon (DIC), partial pressure of CO[SUB]2[/SUB] (pCO[SUB]2[/SUB]), dissolved oxygen (O[SUB]2[/SUB]), photosynthetic pigments, particulate organic carbon (POC), dissolved organic carbon (DOC), Transparent Exopolymer Particles (TEP), primary production, and calcification. This dynamic model is based on unbalanced algal growth and balanced bacterial growth. In order to adequately reproduce the observations, the model includes an explicit description of phosphorus cycling, calcification, TEP production and an enhanced mortality due to viral lysis. The model represented carbon, nitrogen and phosphorus fluxes observed in the mesocosms. Modelled profiles of algal biomass and final concentrations of DIC and nutrients are in agreement with the experimental observations. [less ▲]

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See detailApplication of a data-interpolating variational analysis (DIVA) tool to physical and biogeochemical measurements covering the Black Sea
Joassin; Beckers, Jean-Marie ULg; Boicenco, L. et al

in Climate change in the Black Sea, hypthesis, observations, trends scenarios and mitigation strategy for the ecosystem (2008)

The European project SESAME (Southern European Seas: Assessing and Modelling Ecosystem changes) is dedicated to the assessment of ecological changes in the Mediterranean and Black seas during these last ... [more ▼]

The European project SESAME (Southern European Seas: Assessing and Modelling Ecosystem changes) is dedicated to the assessment of ecological changes in the Mediterranean and Black seas during these last decades. This assessment will be done by combining statistical analysis of available data and the development of a 3D hydrodynamical-biogeochemical model. Data available since 1960 for the Black Sea from the databases MEDAR and NATO have been completed with data provided by SESAME partners. These data sets have been analyzed using DIVA, a geostatistical analysis tool developed by the GHER laboratory of the University of Liège. The DIVA analysis relies on a finite element resolution, taking into account coastlines, sub-basins, and advection by ocean currents. DIVA analysis generates spatially interpolated fields for biogeochemical and physical variables. Outputs consist in sets of analysis as well as error fields, and colorimetric scaled maps related to several depth layers. Biogeochemical variables considered consist in measures of chlorophyll, inorganic nutrients concentration, and phytoplankton abundances; physical variables consist in temperature and salinity. These treatments of the Black sea data sets offer an overview of the global pattern of the Black sea biogeochemical structure, and its evolution through the time periods concerned by the project. The interpolated fields generated by the DIVA tool will be used to validate the outputs of the 3D hydrodynamical-biogeochemical model developed for the north-western shelf of the Black sea in the framework of SESAME. [less ▲]

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See detailUnderstanding the Black Sea ecosystem functioning during the eutrophication phase using mathematical modelling
Grégoire, Marilaure ULg; Capet, Arthur ULg; Barth, Alexander ULg et al

in Moncheva, Snejana (Ed.) Climate change in the Black Sea, hypthesis, observations, trends scenarios and mitigation strategy for the ecosystem (2008)

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See detailNumerical modeling of the deep Black Sea ecosystem functioning during the late 80’s (eutrophication phase)
Grégoire, Marilaure ULg; Raick, Caroline ULg; Soetaert, Karline

in Progress in Oceanography (2008), 76(9), 286-333

A one-dimensional coupled physical–biogeochemical model has been developed to simulate the ecosystem of the central Black Sea at the end of the 1980s when eutrophication and invasion by gelatinous ... [more ▼]

A one-dimensional coupled physical–biogeochemical model has been developed to simulate the ecosystem of the central Black Sea at the end of the 1980s when eutrophication and invasion by gelatinous organisms seriously affected the stability and dynamics of the system. The physical model is the General Ocean Turbulence Model (GOTM) and the biogeochemical model describes the foodweb from bacteria to gelatinous carnivores through 24 state variables including three groups of phytoplankton: diatoms, small phototrophic flagellates and dinoflagellates, two zooplankton groups: micro- and mesozooplankton, two groups of gelatinous zooplankton: the omnivorous and carnivorous forms, an explicit representation of the bacterial loop: bacteria, labile and semi-labile dissolved organic matter, particulate organic matter. The model simulates oxygen, nitrogen, silicate and carbon cycling. In addition, an innovation of this model is that it explicitly represents processes in the anoxic layer. Biogeochemical processes in anaerobic conditions have been represented using an approach similar to that used in the modeling of diagenetic processes in the sediments lumping together all the reduced substances in one state variable [Soetaert, K., Herman, P., 1996. A model of early diagenetic processes from the shelf to abyssal depths. Geochimica et Cosmochimica Acta 60 (6) 1019–1040]. In this way, processes in the upper oxygenated layer are fully coupled with anaerobic processes in the deep waters, allowing to perform longterm simulations. The mathematical modeling of phytoplankton and zooplankton dynamics, detritus and the microbial loop is based on the model developed by Van den Meersche et al. [Van den Meersche, K., Middelburg, J., Soetaert, K., van Rijswijk P.H.B., Heip, C., 2004. Carbon–nitrogen coupling and algal–bacterial interactions during an experimental bloom: Modeling a 13c tracer experiment. Limnology and Oceanography 49 (3), 862–878] and tested in the modeling of mesocosm experiments and of the Ligurian sea ecosystem [Raick, C., Delhez, E., Soetaert, K., Gregoire, M., 2005. Study of the seasonal cycle of the biogeochemical processes in the Ligurian sea using an 1D interdisciplinary model. Journal of Marine Systems 55 (3–4) 177–203]. This model has been extended to simulate the development of top predators, the aggregation of detritus as well as the degradation and chemical processes in suboxic/anoxic conditions (e.g. denitrification, anoxic remineralization, redox reactions). The coupled model extends down to the sediments (’2000 m depth) and is forced at the air–sea interface by the 6 hourly ERA-40 reanalysis of ECMWF data. The model has been calibrated and validated using a large set of data available in the Black Sea TU Ocean Base. The biogeochemical model involves some hundred parameters which are first calibrated by hand using published values. Then, an identifiability analysis has been performed in order to determine a subset of identifiable parameters (i.e. ensemble of parameters that can be together estimated from the amount of data we have at our disposal, see later in the text). Also a subset of 10 identifiable parameters was isolated and an automatic calibration subroutine (Levenberg Marquart) has been used to fine tune these parameters. Additionally, in order to assess the sensitivity of model results to the parameterization of the two gelatinous groups, Monte Carlo simulations were performed perturbing all the parameters governing their dynamics. In order to calibrate the particle dynamics and export, the chemical model was run off-line with the particle and microbial loop model in order to check its capacity of simulating anoxic waters. After a 104 year run, the model simulated NH4 and H2S profiles similar to observations but steady state was not reached suggesting that the Black Sea deep waters are not at steady state. The fully coupled model was then used to simulate the period 1988–1992 of the Black Sea ecosystem. The model solution exhibits a complex dynamics with several years of transient adjustment. This complexity is imparted by the explicit modeling of top predators. The integrated chlorophyll and phytoplankton biomasses, the maximum concentration and depth of maximum, mesozooplankton biomass, depth of oxycline, primary production, bacterial production, surface concentrations of nutrients and plankton simulated by the model and obtained from available data analysis were compared and showed a satisfactory agreement. Also, as in the data, the model shows a continuous development of phytoplankton throughout the year, with an intense spring bloom dominated by diatoms and a fall bloom dominated by dinoflagellates. Dinoflagellates dominate from summer until late fall while small phototrophic flagellates are never dominant in terms of biomass, but are present almost throughout the year except in winter. The model simulates an intense silicate removal associated to increased diatoms blooms which were promoted by increased nutrient conditions, and by the presence of gelatinous zooplankton. This silicate pumping leads to silicate limitation of diatoms development in summer allowing the development of dinoflagellates. [less ▲]

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See detailA dynamic model of an experimental bloom of coccolithophores Emiliania huxleyi
Joassin, Pascal ULg; Borges, Alberto ULg; Chou, Lei et al

Conference (2007, November 27)

A dynamic model has been developed to represent biogeochemical events observed during an experimentally induced bloom of coccolithophores Emiliania huxleyi. This bloom occurred in a mesocosm experiment ... [more ▼]

A dynamic model has been developed to represent biogeochemical events observed during an experimentally induced bloom of coccolithophores Emiliania huxleyi. This bloom occurred in a mesocosm experiment (Bergen 2001 experiment) during which ecosystem development was followed over a 23-days period through changes of the stocks of inorganic nutrients (nitrate, ammonium and phosphate), dissolved inorganic carbon and pCO2, O2 concentration, pigments, particulate organic carbon and nitrogen, dissolved organic carbon, the production of Transparent Exopolymeric Particles (TEP), primary production, alkalinity, calcification and particulate inorganic carbon. The dynamic model is based on unbalanced algal growth and balanced growth for bacteria as described in Van den Meersche et al. (2004). In addition, in order to adequately reproduce the observations, the model has been extended by including an explicit description of calcification, T.E.P production and an enhanced mortality due to viruses. This last process, based on a critical promiscuity between cellular hosts and viral agents, successfully contributed to reproduce the bloom extinction as observed in the mesocosm experiment. This model will be implemented in a coupled physical-biogeochemical model of the Black Sea ecosystem in the framework of the EU Sesame project and in the Gulf of Biscay in the frame of the Belgian PEACE project. [less ▲]

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See detailApplication of a SEEK filter to a 1D biogeochemical model of the Ligurian Sea: Twin experiments and real in-situ data assimilation
Raick, Caroline ULg; Alvera Azcarate, Aïda ULg; Barth, Alexander ULg et al

in Journal of Marine Systems (2007), 65(1-4), 561-583

The Singular Evolutive Extended Kalman (SEEK) filter has been implemented to assimilate in-situ data in a 1D coupled physical-ecosystem model of the Ligurian Sea. The biogeochemical model describes the ... [more ▼]

The Singular Evolutive Extended Kalman (SEEK) filter has been implemented to assimilate in-situ data in a 1D coupled physical-ecosystem model of the Ligurian Sea. The biogeochemical model describes the partly decoupled nitrogen and carbon cycles of the pelagic food web. The GHER hydrodynamic model (1D version) is used to represent the physical forcings. The data assimilation scheme (SEEK filter) parameterizes the error statistics by means of a set of empirical orthogonal functions (EOFs). Twin experiments are first performed with the aim to choose the suitable experimental protocol (observation and estimation vectors, number of EOFs, frequency of the assimilation,...) and to assess the SEEK filter performances. This protocol is then applied to perform real data assimilation experiments using the DYFAMED data base. By assimilating phytoplankton observations, the method has allowed to improve not only the representation of the phytoplankton community, but also of other variables such as zooplankton and bacteria that evolve with model dynamics and that are not corrected by the data assimilation scheme. The validation of the assimilation method and the improvement of model results are studied by means of suitable error measurements. (c) 2006 Elsevier B.V. All rights reserved. [less ▲]

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See detailCan principal component analysis be used to predict the dynamics of a strongly non-linear marine biogeochemical model?
Raick, Caroline ULg; Beckers, Jean-Marie ULg; Soetaert, Karline et al

in Ecological Modelling (2006), 196(3-4), 345-364

In the framework of model complexity reduction, we investigate the ability of the principal component analysis technique to represent in a compact form the dynamics of a coupled physical-ecosystem model ... [more ▼]

In the framework of model complexity reduction, we investigate the ability of the principal component analysis technique to represent in a compact form the dynamics of a coupled physical-ecosystem model. The biogeochemical model describes the evolution in time and depth of the partly decoupled nitrogen and carbon cycles of the pelagic food web in the Ligurian Sea (North Western Mediterranean Sea) through 19 biogeochemical state variables. The GHER hydrodynamic model (1D version) is used to represent the physical forcings. The coupled model presents a high variability in time and space that can be decomposed in modes by principal component analysis. To investigate the possibility of being represented in a compact form, the model is constrained to evolve in a reduced space spanned by its most dominant modes of variability that are the empirical orthogonal functions (EOFs). Different orthogonal bases (formed by 1D and OD EOFs) are used to investigate the performance and realism of the method. 1D vertical EOFs show a tendency to impose a spatial structure to model results according to the most dominant EOFs. In the case of OD EOFs, results of the reduced model can be very close to the original one, but it requires a large number of modes. (c) 2006 Elsevier B.V. All rights reserved. [less ▲]

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See detailModel complexity and performance: How far can we simplify?
Raick, Caroline ULg; Soetaert, Karline; Grégoire, Marilaure ULg

in Progress in Oceanography (2006), 70(1), 27-57

Handling model complexity and reliability is a key area of research today. While complex models containing sufficient detail have become possible due to increased computing power, they often lead to too ... [more ▼]

Handling model complexity and reliability is a key area of research today. While complex models containing sufficient detail have become possible due to increased computing power, they often lead to too much uncertainty. On the other hand, very simple models often crudely oversimplify the real ecosystem and can not be used for management purposes. Starting from a complex and validated 1D pelagic ecosystem model of the Ligurian Sea (NW Mediterranean Sea), we derived simplified aggregated models in which either the unbalanced algal growth, the functional group diversity or the explicit description of the microbial loop was sacrificed. To overcome the problem of data availability with adequate spatial and temporal resolution, the outputs of the complex model are used as the baseline of perfect knowledge to calibrate the simplified models. Objective criteria of model performance were used to compare the simplified models' results to the complex model output and to the available data at the DYFAMED station in the central Ligurian Sea. We show that even the simplest (NPZD) model is able to represent the global ecosystem features described by the complex model (e.g. primary and secondary productions, particulate organic matter export flux, etc.). However, a certain degree of sophistication in the formulation of some biogeochemical processes is required to produce realistic behaviors (e.g. the phytoplankton competition, the potential carbon or nitrogen limitation of the zooplankton ingestion, the model trophic closure, etc.). In general, a 9 state-variable model that has the functional group diversity removed, but which retains the bacterial loop and the unbalanced algal growth, performs best. (C) 2006 Elsevier Ltd. All rights reserved. [less ▲]

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See detailMarine research at the Liège University: a long tradition of oceanography far away from the sea
Grégoire, Marilaure ULg; MARE interfacultry research centre, .

Conference (2005, February 25)

MARE gathers 24 laboratories of the Faculties of Science, Applied Science, Law and Veterinary Medicine. It integrates complementary disciplines of Oceanology through both pluridisciplinary field works and ... [more ▼]

MARE gathers 24 laboratories of the Faculties of Science, Applied Science, Law and Veterinary Medicine. It integrates complementary disciplines of Oceanology through both pluridisciplinary field works and modeling. Major research themes of MARE are: 1) The detection and prediction of changes in coastal ecosystems integrating data collection, the development of statistical tools and 3D interdisciplinary models used conjointly with specific diagnostic tools tailored to management purposes; 2) The study of the CO2 dynamics in order to budget fluxes in major coastal areas and the Southern Ocean, through data collection, satellite imagery and modeling studies; 3) The dynamic and diversity of the Ocean Pelagic Ecosystem; 4) Biodiversity and taxonomic studies in different coastal and deep-sea areas; 5) Study of marine trophic webs using stable carbon and nitrogen isotopes; 6) Ecotoxicology and Ecophysiology: study of the effects of pollutants on marine organisms including marine mammals and investigations on genetic diversity, pathology and causes of death of marine mammals and seabirds; 7) Ecology of macrophytes systems and of benthic algae; 8) Sediments studies (e.g. sediment transport, sediment structure analysis, benthic habitats characterization and diversity); 9) Reconstruction of paleocirculations using isotope analysis (Nd, Pb); 10) Study of coastal evolution and management. This includes the study of coastal geomorphology using remote sensing data and coastal engineering. Moreover, MARE researchers have access to the research station STARESO in Corsica (http://www.stareso.com/), and to the Belgian R.V. Belgica, which operates in the North Sea and adjacent areas (http://www.mumm.ac.be/EN/Monitoring/Belgica/). Finally, the MARE centre supports the extant set of second and third cycle Teachings (master in Oceanography; http://www.ulg.ac/oceanbio/, DEA in Oceanology, European DEA in Marine Environment Modeling) - unique in the French-speaking Community of Belgium -, of a Doctoral School, and of international Conferences and Colloquia (The International Liège Colloquium on Ocean Dynamics and associated Symposia). [less ▲]

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See detailModelling the Ligurian Sea ecosystem by means of a 1D couled physical-biogeochemical model. Improvement of model results using sequential data assimilation
Raick, C.; Soetaert, K.; Grégoire, Marilaure ULg

in Geophysical Research Abstracts (2005), 7

A 1D coupled physical-biogeochemical model has been built to study the pelagic food web of the Ligurian Sea (NW Mediterranean Sea). The physical model is the turbulent closure model (version 1D) developed ... [more ▼]

A 1D coupled physical-biogeochemical model has been built to study the pelagic food web of the Ligurian Sea (NW Mediterranean Sea). The physical model is the turbulent closure model (version 1D) developed at the GHER (University of Liège, Belgium). The ecosystem model contains nineteen state variables describing the carbon and nitrogen cycles of the pelagic food web. Silicate is considered as a potential limiting nutrient of diatoms’ growth. The aggregation model described in Kriest and Evans (2000) is used to evaluate the sinking rate of particulate detritus. The model is forced at the air-sea interface by the METEO France meteorological data. The DYFAMED time series data of year 2000 are used to calibrate and validate the biological model (Raick et al., 2005). By combining the numerical model and the available observations, data assimilation techniques are useful to improve the state estimation of the ocean. A Singular Fixed Extended Kalman filter (Pham et al., 1998) has been implemented in this way. Twin experiments are first performed to choose the suitable experimental protocol, which is then applied to perform real data assimilation experiments using DYFAMED data (Raick et al., submitted). To be coupled in a 3D environment, the ecosystem model is too complex. Our ongoing work is to perform a simplification, by studying simplified structures in comparison with the original ecosystem model. The advantage of deriving a simplified model from the complex one, is that we would be able to identify the most important processes of the Ligurian Sea ecosystem. [less ▲]

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See detailApplication of a sequential data assimilation technique to improve the results of a 1D couled physical-biogeochemical model of the Ligurian Sea
Raick, C.; Soetaert, K.; Grégoire, Marilaure ULg

in VLIZ Young Scientists' Day, Brugge, Belgium 25th February 2005: book of abstracts (2005)

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See detailStudy of the seasonal cycle of the biogeochemical processes in the Ligurian Sea using a ID interdisciplinary model
Raick, Caroline ULg; Delhez, Eric ULg; Soetaert, Karline et al

in Journal of Marine Systems (2005), 55(3-4), 177-203

A one-dimensional coupled physical-biogeochemical model has been built to study the pelagic food web of the Ligurian Sea (NW Mediterranean Sea). The physical model is the turbulent closure model (version ... [more ▼]

A one-dimensional coupled physical-biogeochemical model has been built to study the pelagic food web of the Ligurian Sea (NW Mediterranean Sea). The physical model is the turbulent closure model (version I D) developed at the GeoHydrodynamics and Environmental Laboratory (GHER) of the University of Liege. The ecosystem model contains 19 state variables describing the carbon and nitrogen cycles of the pelagic food web. Phytoplankton and zooplankton are both divided in three size-based compartments and the model includes an explicit representation of the microbial loop including bacteria, dissolved organic matter, nano-, and microzooplankton. The internal carbon/nitrogen ratio is assumed variable for phytoplankton and detritus, and constant for zooplankton and bacteria. Silicate is considered as a potential limiting nutrient of phytoplankton's growth. The aggregation model described by Kriest and Evans in (Proc. Ind. Acad. Sci., Earth Planet. Sci. 109 (4) (2000) 453) is used to evaluate the sinking rate of particulate detritus. The model is forced at the air-sea interface by meteorological data coming from the "Cote d'Azur" Meteorological Buoy. The dynamics of atmospheric fluxes in the Mediterranean Sea (DYFAMED) time-series data obtained during the year 2000 are used to calibrate and validate the biological model. The comparison of model results within in situ DYFAMED data shows that although some processes are not represented by the model, such as horizontal and vertical advections, model results are overall in agreement with observations and differences observed can be explained with environmental conditions. (c) 2004 Elsevier B.V. All rights reserved. [less ▲]

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See detailModeling Biogeochemical Processes in Marine Ecosystems
Grégoire, Marilaure ULg; Oguz, Temel

in Nihoul, Jacques; Chen, Arthur (Eds.) the Unesco Encyclopedia of Life Support Systems (2005)

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See detailInfluence of the Aral Sea negative water balance on its seasonal circulation patterns: use of a 3D hydrodynamic model
Sirjacobs, Damien ULg; Grégoire, Marilaure ULg; Delhez, Eric ULg et al

in Journal of Marine Systems (2004), 47(1-4), 51-66

A 3D hydrodynamic model of the Aral Sea was successfully implemented to address the complex hydrodynamic changes induced by the combined effect of hydrologic and climatic change in the Aral region. The ... [more ▼]

A 3D hydrodynamic model of the Aral Sea was successfully implemented to address the complex hydrodynamic changes induced by the combined effect of hydrologic and climatic change in the Aral region. The first barotropic numerical experiments allowed us to produce a comparative description of the mean general seasonal circulation patterns corresponding to the original situation (1956-1960) and of the average situation for the period from 1981 to 1985, a very low river flow period. The dominant anticyclonic circulation suggested by our seasonal simulation is in good agreement with previous investigations. In addition. this main anticyclonic gyre was shown to be stable and clearly established from February to September, while winter winds led to another circulation scenario. In winter, the main anticyclonic gyre was considerably limited, and cyclonic circulations appeared in the deep western basin and in the northeast of the shallow basin. In contrast, stronger anticyclonic circulation was observed in the Small Aral Sea during winter. As a consequence of the 10-m sea level drop observed between the two periods considered, the 1981-1985 simulation suggests an intensification of seasonal variability. Total water transport of the main gyre was reduced with sea level drop by a minimum of 30% in May and up to 54% in September. Before 1960, the study of the net flows through Berg and Kokaral Straits allowed us to evaluate the component of water exchange between the Small and the Large Seas linked with the general anticyclonic circulation around Kokaral Island. This exchange was lowest in summer (with a mean anticyclonic exchange of 222 m(3)/s for July and August), highest in fall and winter (with a mean value of 1356 m(3)/s from September to February) and briefly reversed in the spring (mean cyclonic circulation of 316 m(3)/s for April and May). In summer, the water exchange due to local circulation at the scale of each strait was comparatively more important because net flows through the straits were low. After about 20 years of negative water balance, the western Kokaral Strait was dried up and the depth of Berg Strait was reduced from 15 to 5 m. Simulation indicated a quasi-null net transport, except during the seasonal modification of the circulation pattern, in February and October. A limited, but stable, water exchange of about 100 m(3)/s remained throughout the year, as a result of the permanent superposition of opposite currents. (C) 2004 Elsevier B.V. All rights reserved. [less ▲]

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See detailModeling the nitrogen cycling and plankton productivity in the Black Sea using a three-dimensional interdisciplinary model
Grégoire, Marilaure ULg; Soetaert, Karline; Nezlin, Nikolay Pavlovich et al

in Journal of Geophysical Research. Oceans (2004), 109(C5),

[1] A six-compartment ecosystem model defined by a simple nitrogen cycle is coupled with a general circulation model in the Black Sea so as to examine the seasonal variability of the ecohydrodynamics ... [more ▼]

[1] A six-compartment ecosystem model defined by a simple nitrogen cycle is coupled with a general circulation model in the Black Sea so as to examine the seasonal variability of the ecohydrodynamics. Model results show that the annual cycle of the biological productivity of the whole basin is characterized by the presence of a winter-early spring bloom. In all the regions this bloom precedes the onset of the seasonal thermocline and occurs as soon as the vertical winter mixing decreases. Phytoplankton development starts in winter in the central basin, while in coastal areas ( except in the river discharge area) it begins in early spring. In the Danube's discharge area and along the western coast, where surface waters are almost continuously enriched in nutrient by river inputs, the phytoplankton development is sustained during the whole year at the surface. The seasonal variability of the northwestern shelf circulation induced by the seasonal variations in the Danube discharge and the wind stress intensity has been found to have a major impact on the primary production repartition of the area. In the central basin the primary production in the surface layer relies essentially on nutrients being entrained in the upper layer from below. Simulated phytoplankton concentrations are compared with satellite and field data. It has been found that the model is able to reproduce the main characteristics of the space-time evolution of the Black Sea's biological productivity but underestimates the phytoplankton biomass especially in regions extremely rich in nutrients such as the Danube discharge area. [less ▲]

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