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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 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 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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