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See detailEstimating marine biogeochemical rates of the carbonate pH system—A Kalman filter tested
Soetaert; Grégoire, Marilaure ULg

in Ecological Modelling (2011), 222

Oxygen (O2), nitrate (NO3), dissolved inorganic carbon (DIC) or pCO2, and pH or total alkalinity (TA), are useful indices of marine chemical, physical and biological processes operating on varying ... [more ▼]

Oxygen (O2), nitrate (NO3), dissolved inorganic carbon (DIC) or pCO2, and pH or total alkalinity (TA), are useful indices of marine chemical, physical and biological processes operating on varying timescales. Although these properties are increasingly being monitored at high frequency, they have not been extensively used for studying ecosystem dynamics. We test whether we can estimate time-evolving biogeochemical rates (e.g. primary production, respiration, calcification and carbonate dissolution, and nitrification) from synthetic high frequency time-series of O2, NO3, DIC, pCO2, TA or pH. More specifically, a Kalman filter has been implemented in a very simplified biogeochemical model describing the dynamics of O2, NO3, DIC and TA and linking the concentration data to biogeochemical fluxes. Different sets of concentration data are assimilated and biogeochemical rates are estimated. The frequency of assimilation required to get acceptable results is investigated and is compared with the frequency of sampling in the field or in controlled experimental settings. Smoothing of the data to remove data noise before assimilation improves the estimation of the biogeochemical rates. The best estimated rates are obtained when assimilating O2, NO3 and TA although the assimilation of DIC instead of TA also gives satisfactory results. In case pH or pCO2 is assimilated rather than DIC or TA, the linearization of the (now nonlinear) observation equation introduces perturbations and the Kalman filter behaves suboptimal. We conclude that, given the resolution of data required, the tool has potential to estimate biogeochemical rates of the carbonate system under controlled settings. [less ▲]

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See detailCarbon, nitrogen, oxygen and sulfide budgets in the Black Sea: A biogeochemical model of the whole water column coupling the oxic and anoxic parts
Grégoire, Marilaure ULg; Soetaert, Karline

in Ecological Modelling (2010)

Carbon, nitrogen, oxygen and sulfide budgets are derived for the Black Sea water column from a coupled physical-biogeochemical model. The model is applied in the deep part of the sea and simulates ... [more ▼]

Carbon, nitrogen, oxygen and sulfide budgets are derived for the Black Sea water column from a coupled physical-biogeochemical model. The model is applied in the deep part of the sea and simulates processes over the whole water column including the anoxic layer that extends from ~ 115 m to the bottom (~ 2000 m). The biogeochemical model involves a refined representation of the Black Sea foodweb from bacteria to gelatinous carnivores. It includes notably a series of biogeochemical processes typical for oxygen deficient conditions with, for instance, bacterial respiration using different types of oxidants (i.e denitrification, sulfate reduction), the lower efficiency of detritus degradation, the ANAMMOX (ANaerobic AMMonium OXidation) process and the occurrence of particular redox reactions. The model has been calibrated and validated against all available data gathered in the Black Sea TU Ocean Base and this exercise is described in Gregoire et al., (2008). In the present paper, we focus on the biogeochemical flows produced by the model and we compare model estimations with the measurements performed during the R.V. KNORR expedition conducted in the Black Sea from April to July 1988 (Murray and the Black Sea Knorr Expedition, 1991). Model estimations of hydrogen sulfide oxidation, metal sulfide precipitation, hydrogen sulfide formation in the sediments and water column, export flux to the anoxic layer and to the sediments, denitrification, primary and bacterial production are in the range of field observations. With a simulated Gross Primary Production (GPP) of 7.9 molC m-2 yr-1 and a Community Respiration (CR) of 6.3 molC m-2 yr-1, the system is net autotrophic with a Net Community Production (NCP) of 1.6 molC m-2 yr-1. This NCP corresponds to 20 % of the GPP and is exported to the anoxic layer. In order to model Particulate Organic Matter (POM) fluxes to the bottom and hydrogen sulfide profiles in agreement with in-situ observations, we have to consider that the degradation of POM in anoxic conditions is less efficient that in oxygenated waters as it has often been observed (see discussion in Hedges et al., 1999). The vertical POM profile produced by the model can be fitted to the classic power function describing the oceanic carbon rate (CR=Z-) using an attenuation coefficient  of 0.36 which is the value proposed for another anoxic environment (i.e. the Mexico Margin) by Devol and Hartnett, (2001). Due to the lower efficiency of detritus degradation in anoxic conditions and to the aggregation of particles that enhanced the sinking, an important part of the export to the anoxic layer (i.e. 33 %, 0.52 molC m-2 yr-1) escapes remineralization in the water column and reaches the sediments. Therefore, sediments are active sites of sulfide production contributing to 26 % of the total sulfide production. In the upper layer, the oxygen dynamics is mainly governed by photosynthesis and respiration processes as well as by air-sea exchanges. ~ 71 % of the oxygen produced by phytoplankton (photosynthesis + nitrate reduction) is lost through respiration, ~ 21 % by outgasing to the atmosphere, ~ 5 % through nitrification and only ~ 2 % in the oxidation of reduced components (e.g. Mn2+, Fe2+, H2S). The model estimates the amount of nitrogen lost through denitrification at 307 mmolN m-2 yr-1 that can be partitioned into a loss of ~ 55 % through the use of nitrate for the oxidation of detritus in low oxygen conditions, ~ 40 % in the ANAMMOX process and the remaining ~ 5% in the oxidation of reduced substances by nitrate. In agreement with data analysis performed on long time series collected since the 1960's (Konovalov and Murray, 2001), the sulfide and nitrogen budgets established for the anoxic layer are not balanced in response to the enhanced particle fluxes induced by eutrophication: the NH4 and H2S concentrations increase. [less ▲]

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See detailIndividual distance-independent girth increment model for Douglas-fir in southern Belgium
Monty, Arnaud ULg; Lejeune, Philippe ULg; Rondeux, Jacques ULg

in Ecological Modelling (2008), 212(3-4), 472-479

An individual distance-independent girth increment model for pure stands of Douglas-fir (Pseudotsuga menziesii (MIRB.) FRANCO), comprising two equations, is presented. The data used to fit the model were ... [more ▼]

An individual distance-independent girth increment model for pure stands of Douglas-fir (Pseudotsuga menziesii (MIRB.) FRANCO), comprising two equations, is presented. The data used to fit the model were collected from 1007 trees in 42 plots installed in regularly stocked and even-aged stands located in Wallonia (southern Belgium). Both equations predict girth increment from individual girth, dominant height, basal area per hectare, stand mean girth and variables linked to site fertility. These last variables are the site index H50 in the first equation, and a combination of mean annual rainfall and altitude in the second. The coefficient of determination ranges from 0.434 to 0.481 and the root mean square error ranges from 0.7857 to 0.8194 cm year(-1). Estimated increments of 224 Douglas-fir trees in 12 different and independent stands were used to validate the model, which is expected to provide reliable predictions for most of the pure Douglas-fir stands located in the study area. (c) 2007 Elsevier B.V. All rights reserved [less ▲]

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See detailStudy of the nutrient and plankton dynamics in Lake Tanganyika using a reduced-gravity model
Naithani, Jaya; Darchambeau, François ULg; Deleersnijder, Eric et al

in Ecological Modelling (2007), 200(1-2), 225-233

An eco-hydrodynamic (ECOH) model is proposed for Lake Tanganyika to study the plankton productivity. The hydrodynamic sub-model solves the non-linear, reduced-gravity equations in which wind is the ... [more ▼]

An eco-hydrodynamic (ECOH) model is proposed for Lake Tanganyika to study the plankton productivity. The hydrodynamic sub-model solves the non-linear, reduced-gravity equations in which wind is the dominant forcing. The ecological sub-model for the epilimnion comprises nutrients, primary production, phytoplankton biomass and zooplankton biomass. In the absence of significant terrestrial input of nutrients, the nutrient loss is compensated for by seasonal, wind-driven, turbulent entrainment of nutrient-rich hypolimnion water into the epilimnion, which gives rise to high plankton productivity twice in the year, during the transition between two seasons. Model simulations predict well the seasonal contrasts of the measured physical and ecological parameters. Numerical tests indicate that the half saturation constant for grazing by zooplankton and the fish predation rate on zooplankton affect the zooplankton biomass measurably more than that of phytoplankton biomass. This work has implications for the application of this model to predict the climatological biological productivity of Lake Tanganyika. (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 detailA model of the seasonal dynamics of biomass and production of the seagrass Posidonia oceanica in the Bay of Calvi (Northwestern Mediterranean)
Elkalay, Khalid; Frangoulis, Constantin; Skliris, Nikolaos ULg et al

in Ecological Modelling (2003), 167(1-2), 1-18

Modelling of seagrasses can be an effective tool to assess factors regulating their growth. Growth and production model of Posidonia oceanica, the dominant submerged aquatic macrophyte occurring in the ... [more ▼]

Modelling of seagrasses can be an effective tool to assess factors regulating their growth. Growth and production model of Posidonia oceanica, the dominant submerged aquatic macrophyte occurring in the Bay of Calvi (Corsica, Ligurian Sea, Northwestern (NW) Mediterranean) was developed. The state variables are the above- and below-ground biomass of P oceanica, the epiphyte biomass, and the internal nitrogen concentration of the whole plant. Light intensity and water temperature are the forcing variables. The model reproduces successfully seasonal growth and production for each variable at various depths (10, 20 and 30 m). The model can simulate also a number of consecutive years. Sensitivity analysis of model's parameters showed that the maximum nitrogen quota n(max) rate is the most sensitive parameter in this model. The results simulations imply that light intensity is one of the most important abiotic factors, the diminution of which can cause an important reduction in seagrass density. (C) 2003 Elsevier B.V. All rights reserved. [less ▲]

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See detailModelling short-term CO2 fluxes and long-term tree growth in temperate forests with ASPECTS
Rasse, Daniel P.; François, Louis ULg; Aubinet, Marc ULg et al

in Ecological Modelling (2001), 141(1-3), 35-52

The net ecosystem exchange (NEE) Of CO2 between temperate forests and the atmosphere governs both carbon removal from the atmosphere and forest growth. In recent years, many experiments have been ... [more ▼]

The net ecosystem exchange (NEE) Of CO2 between temperate forests and the atmosphere governs both carbon removal from the atmosphere and forest growth. In recent years, many experiments have been conducted to determine temperate forest NEE. These data have been used by forest modellers to better understand the processes that govern CO, fluxes, and estimate the evolution of these fluxes under changing environmental conditions. Nevertheless, it is not clear whether models capable of handling short-term processes, which are mostly source-driven, can provide an accurate estimate of long-term forest growth, which is potentially more influenced by sink- and phenology-related processes. To analyse the interactions between short- and long-term processes, we developed the ASPECTS model, which predicts long-term forest growth by integrating, over time, hourly NEE estimates. Validation data consisting of measurements of NEE by eddy-covariance and forest carbon reservoir estimates were obtained from mixed deciduous and evergreen experimental forests located in Belgium. ASPECTS accurately estimated both: (1) the NEE fluxes for several years of data; and (2) the amount of carbon contained in stems, branches, leaves, fine and coarse roots. Our simulations demonstrated that: (1) NEE measurements in Belgian forests are compatible with forest growth over the course of the 20th century, and (2) that forest history and long-term processes need to be considered for accurate simulation of short-term CO2 fluxes. [less ▲]

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See detailInverse vegetation modelling : a tool to reconstruct palaeoclimates under changed CO2 conditions
Guiot, J.; Torre, F.; Jolly, D. et al

in Ecological Modelling (2000), 127

Atmospheric CO2 concentration has greatly fluctuated during the Quaternary. These variations have influenced the vegetation changes. The assumption that the relationship vegetation–climate sensu stricto ... [more ▼]

Atmospheric CO2 concentration has greatly fluctuated during the Quaternary. These variations have influenced the vegetation changes. The assumption that the relationship vegetation–climate sensu stricto was constant through time should be reconsidered taking into account the impact of the atmospheric CO2 content on the plants. Here we propose to use a process-based vegetation model (BIOME3) in an inverse mode to reconstruct from pollen data the most probable climate under precipitation seasonality change and under lowered CO2 concentration in the biosphere. Appropriate tools to match the model outputs with the pollen data are developed to generate a probability distribution associated with the reconstruction (Monte Carlo sampling and neural network techniques). The method is validated with modern pollen samples from Greece and Italy: it proves to be able to reconstruct modern climate with a more or less large error bar from pollen data. The error bar depends in fact on the tolerance of the vegetation to the corresponding climatic variable. The application to six pollen assemblages from Greece and Italy, representing the last glacial maximum (LGM: 18 000 14C-year B.P.), is done into three experiments: (1) modern CO2 concentration; (2) LGM CO2 concentration; (3) LGM CO2 concentration and high winter precipitation. The latter experiment is motivated by evidence of high lake-levels in Greece during the LGM which has been attributed to winter rainfall. These experiments show that winter was ca. 15–20°C colder than the present, in agreement with previous climate reconstruction. The apparent discrepancy between the high lake-levels and the steppe vegetation during the LGM, can be explained by an increase of the winter precipitation (which leads to high lake level) while the summer season is mild and dry (which affects the vegetation). The summer temperature has three stable states (−16°C, −10°C, −2°C), but the warmest one is the most probable if we take into account the lowered CO2 and the high lake-levels. [less ▲]

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