Simulating microbial degradation of organic matter in a simple porous system using the 3-D diffusion-based model MOSAIC

This paper deals with the simulation of microbial degradation of organic matter in soil within the pore space at a microscopic scale. Pore space was analysed with micro-computed tomography and described using a sphere network coming from a geometrical modelling algorithm. The biological model was improved regarding previous work in order to include the transformation of dissolved organic compounds and diffusion processes. We tested our model using experimental results of a simple substrate decomposition experiment (fructose) within a simple medium (sand) in the presence of different bacterial strains. Separate incubations were carried out in microcosms using five different bacterial communities at two different water potentials of −10 and −100 cm of water. We calibrated the biological parameters by means of experimental data obtained at high water content, and we tested the model without changing any parameters at low water content. Same as for the experimental data, our simulation results showed that the decrease in water content caused a decrease of mineralization rate. The model was able to simulate the decrease of connectivity between substrate and microorganism due the decrease of water content

Interactions between Kluyveromyces marxianus from cheese origin and the intestinal symbiont Bacteroides thetaiotaomicron: Impressive antioxidative effects

The effects of yeast Kluyveromyces marxianus S-2-05, of cheese origin, were assessed on the intestine anaerobe symbiont Bacteroides thetaiotaomicron ATCC 29741 to unveil any changes in its antioxidant properties. To this end, these microorganisms were grown and incubated either separately, or co-incubated, under anaerobic atmosphere. Afterwards, the microbial cells were recovered and washed, and extracts were prepared using a sterile detergent solution to mimic the intestine detergent content. The extracts prepared from K. marxianus S-2-05 and reference strain K. marxianus MUCL 29917, grown under different conditions, were assessed for their antioxidant properties against superoxide anion and hydrogen peroxide. Extracts from both yeasts showed antioxidative effects, which were particularly important for K. marxianus S-02-5 after anaerobic incubation. Moreover, K. marxianus S-02-5 displayed a high level of activity against the aforementioned reactive oxygen species, enhancing that of B. thetaiotaomicron ATCC 29741, after the co-incubation process. Two-dimensional polyacrylamide gel electrophoresis was used to separate the proteins extracted. Superoxide dismutase, thiol peroxidase, rubrerythrin -intensively produced by B. thetaiotaomicron induced by the yeast-were identified by mass spectrometry. The antioxidative potential evidenced for K. marxianus S-02-5 is another advantage which could justify the utilization of this strain as a probiotic for countering intestinal inflammatory processes. © 2017 Elsevier Lt

A framework for modelling soil structure dynamics induced by biological activity

Acknowledgments: This work was funded by the Swedish Research Council for Sustainable Development (FORMAS) in the project “Soil structure and soil degradation: improved model tools to meet sustainable development goals under climate and land use change” (grant no. 2018-02319). We would also like to thank Mikael Sasha Dooha for carrying out the measurements for the water retention curves shown in figure 4.Peer reviewedPublisher PD

Quantitative metabolomics based on gas chromatography mass spectrometry: status and perspectives

Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites relevant to a specific phenotypic characteristic can be identified. However, the reliability of the analytical data is a prerequisite for correct biological interpretation in metabolomics analysis. In this review the challenges in quantitative metabolomics analysis with regards to analytical as well as data preprocessing steps are discussed. Recommendations are given on how to optimize and validate comprehensive silylation-based methods from sample extraction and derivatization up to data preprocessing and how to perform quality control during metabolomics studies. The current state of method validation and data preprocessing methods used in published literature are discussed and a perspective on the future research necessary to obtain accurate quantitative data from comprehensive GC-MS data is provided

Learning in games with continuous action spaces and unknown payoff functions

International audienc

Spatial aggregation for crop modelling at regional scales: the effects of soil variability

Modelling agriculture production and adaptation to the environment at regional or global scale receives much interest in the context of climate change (CC). One concern is to take into account the spatial variability of the environmental conditions (e.g. climate, soils, management practices) used as model input because the impacts of CC on cropping systems depend strongly on the site conditions [1]. For example CC effects on yield can be either negative or positive depending on the soil type [2]. Additionally, the use of different methods of upscaling and downscaling adds new sources of modelling uncertainties [3].In the present study, the effect of aggregating soil data by area majority of soil mapping units was explored for regional simulations with the soil-vegetation model CoupModel for a region inGermany (North Rhine-Westphalia). Data aggregation effects (DAE) were analysed for wheat yield, water drainage, soil carbon mineralisation and nitrogen leaching below the root zone. DAE were higher for soil C and N variables than for yield and drainage and were strongly related to the presence of specific soils within the study region. These 'key soils' were identified by a model sensitivity analysis to soils present in the region. The spatial aggregation of the key soils additionally influenced the DAE. A spatial analysis of the pattern of these key soils (i.e. presence/ absence, coverage and aggregation) can help in defining the appropriate grid-resolution that would minimize the error caused by aggregated soil input data in regional model simulations. In a second step the method will be applied and evaluated with respect to another European region(Tuscany) which is characterised by a warmer and drier climate.[1] Kersebaum, K.C., Nendel, C., 2014. Site-specific impacts of climate change on wheat production across regions ofGermany using different CO2 response functions. Eur. J. Agron. 52, 22–32. doi:10.1016/j.eja.2013.04.005[2] Folberth, C. et al, 2016. Uncertainty in soil data can outweigh climate impact signals in global crop yield simulations. Nat. Commun. 7, 11872. doi:10.1038/ncomms11872[3] Ewert et al., 2011. Scale changes and model linking methods for integrated assessment of agri-environmental systems. Agric. Ecosyst. Environ. 142, 6–17. doi:10.1016/j.agee.2011.05.01

Neutral and Non-Neutral Countries in a Global Internet: What Does it Imply?

International audienceNetwork neutrality is being discussed worldwide, with different countries applying different policies, some imposing it, others acting against regulation or even repealing it as recently in the USA. The goal of this paper is to model and analyze the interactions of users, content providers, and Internet service providers (ISPs) located in countries with different rules. To do so, we build a simple two-regions game-theoretic model and focus on two scenarios of net neutrality relaxation in one region while it remains enforced in the other one. In a first scenario, from an initial situationwhere both regions offer the same basic quality, one region allows ISPs to offer fast lanes for a premium while still guaranteeing the basic service; in a second scenario the ISPs in both regions play a game on quality, with only one possible quality in the neutral region, and two in the non-neutralone but with a regulated quality ratio between those. Our numerical experiments lead to very different outcomes, with the first scenario benefiting to all actors (especially the ones in the relaxed-neutrality region) and the second one mainly benefiting mostly to ISPs while Content Providers are worse off, suggesting that regulation should be carefully designed

Non Neutrality With Users Deciding Differentiation: A Satisfying Option?

International audienceThe network neutrality debate has been raging worldwide for around fifteen years now. Our goal in this paper is to model and discuss a quite recent option which could be seen as a trade-off between neutrality and differentiation operated by Internet service providers (ISPs), and satisfy both ends of the world: differentiation potentially chosen by end users. By using a model from the literature, we compare the outcomes of three scenarios: neutrality, non-neutrality with differentiation decided by ISPs, and non-neutrality decided by users. We illustrate that, depending on network parameters, letting end users decide may end up as a fair and viable solution, and that non-neutrality imposed by ISPs is not necessarily bad for all actors

Evolution of the STICS crop model to tackle new environmental issues: New formalisms and integration in the modelling and simulation platform RECORD

International audienceTo address new environmental and social issues, crop models need to widen their scope and be linked to other tools. The crop model STICS was encapsulated in the modelling platform RECORD and new process-based developments were added to address environmental issues. We present plant and soil processes developed recently in STICS and describe three projects using STICS within RECORD: MICMAC-Design aims to design innovative cropping systems at field scale, integrating economic and epidemiological analysis and using a database to represent agricultural management; CRASH aims to develop and evaluate crop-allocation strategies at farm scale that meet water-shortage regulations, using links with databases, optimisation processes and farmers' representation; AICHA aims to analyse impacts of irrigation on the water table at catchment scale using links to a hydrological model, cluster computation, integrated economic and agronomic optimisation. Automated encapsulation procedures allow STICS and RECORD communities to work independently but to benefit from mutual exchanges