Karline Soetaert

Bio: Karline Soetaert is an academic researcher from Utrecht University. The author has contributed to research in topics: Benthic zone & Total organic carbon. The author has an hindex of 66, co-authored 342 publications receiving 15161 citations. Previous affiliations of Karline Soetaert include Ghent University & Free University of Brussels.

Solving Differential Equations in R: Package deSolve

Abstract: In this paper we present the R package deSolve to solve initial value problems (IVP) written as ordinary differential equations (ODE), differential algebraic equations (DAE) of index 0 or 1 and partial differential equations (PDE), the latter solved using the method of lines approach. The differential equations can be represented in R code or as compiled code. In the latter case, R is used as a tool to trigger the integration and post-process the results, which facilitates model development and application, whilst the compiled code significantly increases simulation speed. The methods implemented are efficient, robust, and well documented public-domain Fortran routines. They include four integrators from the ODEPACK package (LSODE, LSODES, LSODA, LSODAR), DVODE and DASPK2.0. In addition, a suite of Runge-Kutta integrators and special-purpose solvers to efficiently integrate 1-, 2- and 3-dimensional partial differential equations are available. The routines solve both stiff and non-stiff systems, and include many options, e.g., to deal in an efficient way with the sparsity of the Jacobian matrix, or finding the root of equations. In this article, our objectives are threefold: (1) to demonstrate the potential of using R for dynamic modeling, (2) to highlight typical uses of the different methods implemented and (3) to compare the performance of models specified in R code and in compiled code for a number of test cases. These comparisons demonstrate that, if the use of loops is avoided, R code can efficiently integrate problems comprising several thousands of state variables. Nevertheless, the same problem may be solved from 2 to more than 50 times faster by using compiled code compared to an implementation using only R code. Still, amongst the benefits of R are a more flexible and interactive implementation, better readability of the code, and access to R’s high-level procedures. deSolve is the successor of package odesolve which will be deprecated in the future; it is free software and distributed under the GNU General Public License, as part of the R software project.

Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME

Abstract: Mathematical simulation models are commonly applied to analyze experimental or environmental data and eventually to acquire predictive capabilities. Typically these models depend on poorly defined, unmeasurable parameters that need to be given a value. Fitting a model to data, so-called inverse modelling, is often the sole way of finding reasonable values for these parameters. There are many challenges involved in inverse model applications, e.g., the existence of non-identifiable parameters, the estimation of parameter uncertainties and the quantification of the implications of these uncertainties on model predictions. The R package FME is a modeling package designed to confront a mathematical model with data. It includes algorithms for sensitivity and Monte Carlo analysis, parameter identifiability, model fitting and provides a Markov-chain based method to estimate parameter confidence intervals. Although its main focus is on mathematical systems that consist of differential equations, FME can deal with other types of models. In this paper, FME is applied to a model describing the dynamics of the HIV virus.

Production and consumption of biological particles in temperate tidal estuaries

Abstract: The question is reviewed whether a balance exists between production and consumption of biological particles in temperate tidal estuaries and what the relationships are between the magnitude of production and consumption processes and system carbon metabolism. The production terms considered are primary production by phytoplankton, microphytobenthos, macroalgae and vascular plants and the chemoautotrophic production, mainly by nitrifying bacteria. The consumption terms are generalized by considering pelagic and benthic mineralization, but major consumer compartments, heterotrophic bacteria, zooplankton, meiobenthos, and macrobenthos are considered in detail. The proposition that estuaries are heterotrophic systems, and become more so when nutrient inputs are higher, is confirmed, and a general equation relating respiration to production is proposed as log R = 0.081 + 1.02 log P (R and P in gC m(-2) yr(-1)). This equation suggests that the amount of heterotrophy is a constant fraction of production. Annual pelagic primary production values lower than 160 gC m(-2) yr(-1) in nutrient- rich or heterotrophic systems are the result of light limitation. The overall recycling efficiency is constant, between 0.7 and 0.8, and is thus independent of system characteristics. Organic loading, rather than inorganic nitrogen loading, ultimately appears to control the primary production in estuarine systems. It is difficult to predict and compare phytoplankton primary production in different estuaries because it is not always clear whether gross or net primary production has been measured. Annual production in some estuaries is probably nitrogen-limited. When phytoplankton is light-limited, annual gross primary production can reasonably be predicted from biomass, incident irradiance and light availability in the water column (photic depth). It appears that interannual variations in annual production are mainly due to (the timing of) different climatological conditions, such as the amount of rainfall and sunshine. Phytoplankton biomass is lower in macrotidal estuaries than in microtidal estuaries. Despite the fact that phytoplankton primary production is controlled by nutrients or light, phytoplankton biomass seems to be determined by the biomass of suspension feeders. Primary production by nitrifying bacteria can be important in estuaries with a heavy organic load. The main suspension feeders in macrotidal estuaries belong to the macrobenthos. The feeding relations between macrobenthos and the production and sedimentation of organic matter in the water are therefore emphasized. For macrobenthic suspension feeders, it is argued that the system-wide biomass and secondary production are limited by the planktonic primary production of the system, whereas the local biomass is highly dependent on hydrodynamic conditions. Macrobenthic deposit feeders take a share of the sedimenting organic matter that depends on the quality and quantity of the organic carbon arriving at the sediment/water interface. Surface deposit feeders directly take up a considerable fraction of the freshly deposited organic matter. Deep deposit feeding is limited by adverse chemical conditions al high organic loading; microbiota take the largest share under these conditions. At low and intermediate loading levels, deep-deposit feeding animals are responsible for a relatively large share of the macrobenthos. [KEYWORDS: Copepod eurytemora-affinis; long-island sound; particulate organic-matter; mesohaline chesapeake bay; coastal marine-sediments; eelgrass zostera-marina; st-lawrence-estuary; mytilus-edulis-l; macrobenthic community structure; bacterial sulfate reduction]

Denitrification in marine sediments: A model study

Abstract: The rate and factors controlling denitrification in marine sediments have been investigated using a prognostic diagenetic model. The model is forced with observed carbon fluxes, bioturbation and sedimentation rates, and bottom water conditions. It can reproduce rates of aerobic mineralization, denitrification, and fluxes of oxygen, nitrate, and ammonium. The globally integrated rate of denitrification is estimated by this model to be about 230-285 Tg N yr(-1), with about 100 Tg N yr(-1) occurring in shelf sediments. This estimate is significantly higher than literature estimates (12-89 Tg N yr(- 1)), mainly because of a proposed upward revision of denitrification rates in slope and deep-sea sediments. Higher sedimentary denitrification estimates require a revision of the marine nitrogen budget and lowering of the oceanic residence time of nitrogen down to about 2 x 10(3) years and are consistent with reported low N/P remineralization ratios between 1000 and 3000 m. Rates of benthic denitrification are most sensitive to the flux of labile organic carbon arriving at the sediment-water interface and bottom water concentrations of nitrate and oxygen. Denitrification always increases when bottom water nitrate increases but may increase or decrease if oxygen in the bottom water increases. Nitrification is by far the most important source of nitrate for denitrification, except for organic-rich sediments underlying oxygen-poor and nitrate-rich water. [KEYWORDS: Organic-matter; biogeochemical cycles; early diagenesis; atmospheric co2; benthic fluxes; sea-floor; ocean; carbon;nitrogen; nutrient]

Influence of Diet On the Distribtion of Nitrogen Isotopes in Animals

Abstract: The influence of diet on the distribution of nitrogen isotopes in animals was investigated by analyzing animals grown in the laboratory on diets of constant nitrogen isotopic composition. The isotopic composition of the nitrogen in an animal reflects the nitrogen isotopic composition of its diet. The δ^(15)N values of the whole bodies of animals are usually more positive than those of their diets. Different individuals of a species raised on the same diet can have significantly different δ^(15)N values. The variability of the relationship between the δ^(15)N values of animals and their diets is greater for different species raised on the same diet than for the same species raised on different diets. Different tissues of mice are also enriched in ^(15)N relative to the diet, with the difference between the δ^(15)N values of a tissue and the diet depending on both the kind of tissue and the diet involved. The δ^(15)N values of collagen and chitin, biochemical components that are often preserved in fossil animal remains, are also related to the δ^(15)N value of the diet. The dependence of the δ^(15)N values of whole animals and their tissues and biochemical components on the δ^(15)N value of diet indicates that the isotopic composition of animal nitrogen can be used to obtain information about an animal's diet if its potential food sources had different δ^(15)N values. The nitrogen isotopic method of dietary analysis probably can be used to estimate the relative use of legumes vs non-legumes or of aquatic vs terrestrial organisms as food sources for extant and fossil animals. However, the method probably will not be applicable in those modern ecosystems in which the use of chemical fertilizers has influenced the distribution of nitrogen isotopes in food sources. The isotopic method of dietary analysis was used to reconstruct changes in the diet of the human population that occupied the Tehuacan Valley of Mexico over a 7000 yr span. Variations in the δ^(15)C and δ^(15)N values of bone collagen suggest that C_4 and/or CAM plants (presumably mostly corn) and legumes (presumably mostly beans) were introduced into the diet much earlier than suggested by conventional archaeological analysis.

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Nitrogen cycles: past, present, and future

Abstract: This paper contrasts the natural and anthropogenic controls on the conversion of unreactive N2 to more reactive forms of nitrogen (Nr). A variety of data sets are used to construct global N budgets for 1860 and the early 1990s and to make projections for the global N budget in 2050. Regional N budgets for Asia, North America, and other major regions for the early 1990s, as well as the marine N budget, are presented to highlight the dominant fluxes of nitrogen in each region. Important findings are that human activities increasingly dominate the N budget at the global and at most regional scales, the terrestrial and open ocean N budgets are essentially dis- connected, and the fixed forms of N are accumulating in most environmental reservoirs. The largest uncertainties in our understanding of the N budget at most scales are the rates of natural biological nitrogen fixation, the amount of Nr storage in most environmental reservoirs, and the production rates of N2 by denitrification.

Places: A 10 Million Image Database for Scene Recognition

Abstract: The rise of multi-million-item dataset initiatives has enabled data-hungry machine learning algorithms to reach near-human semantic classification performance at tasks such as visual object and scene recognition. Here we describe the Places Database, a repository of 10 million scene photographs, labeled with scene semantic categories, comprising a large and diverse list of the types of environments encountered in the world. Using the state-of-the-art Convolutional Neural Networks (CNNs), we provide scene classification CNNs (Places-CNNs) as baselines, that significantly outperform the previous approaches. Visualization of the CNNs trained on Places shows that object detectors emerge as an intermediate representation of scene classification. With its high-coverage and high-diversity of exemplars, the Places Database along with the Places-CNNs offer a novel resource to guide future progress on scene recognition problems.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

Abstract: The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.