Agricultural Production and Externalities Simulator (APES) prototype to be used in Prototype 1 of SEAMLESS-IF

Production Economics,

Library of model components for process simulation relevant to production activities, Prototype 1 versions

Production Economics,

Maintaining (locus of) control? : Assessing the impact of locus of control on education decisions and wages

This paper establishes that individuals with an internal locus of control, i.e., who believe that reinforcement in life comes from their own actions instead of being determined by luck or destiny, earn higher wages. However, this positive effect only translates into labor income via the channel of education. Factor structure models are implemented on an augmented data set coming from two different samples. By so doing, we are able to correct for potential biases that arise due to reverse causality and spurious correlation, and to investigate the impact of premarket locus of control on later outcomes

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales

While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by similar to 17 +/- 11 days, and lagged air and soil temperature by median values of 8 +/- 16 and 5 +/- 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4. At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.Peer reviewe

Altered energy partitioning across terrestrial ecosystems in the European drought year 2018

Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO(2)exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004-2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO(2)uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'

Gap-filling eddy covariance methane fluxes : Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting halfhourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).Peer reviewe

Modelling soil organic carbon dynamics under land use and climate change

Soil organic matter (SOM) models simplify the complex turnover dynamics of organic matter in soils. Stabilization mechanisms are currently thought to play a dominant role in SOM turnover but they are not explicitly accounted for in most SOM models. One study addresses the implementation of an approach to account for the stabilization mechanism of physical protection in the SOC model RothC using 13C abundance measurements in conjunction with soil size fractionation data. SOM models are increasingly used to support policy decisions on carbon (C) mitigation and credibility of model predictions move into the focus of research. A site scale, Monte Carlo based model uncertainty analysis of a SOM model was carried out. One of the major results was that uncertainty and factor importance depend on the combination of external drivers. A different approach was used with the SOM ECOSSE model to estimate uncertainties in soil organic carbon (SOC) stock changes of mineral and organic soils in Scotland. The average statistical model error from site scale evaluation was transferred to regional scale uncertainty to give an indication of the uncertainty in national scale predictions. National scale simulations were carried out subsequently to quantify SOC stock changes differentiating between organic and mineral soils and land use change types. Organic soils turned out to be most vulnerable to SOC losses in the last decades. The final study of this thesis emplyed the RothC model to simulate possible futures of global SOC stock changes under land use change and ten different climate scenarios. Land use change turned out to be of minor importance. The regionally balance between soil C inputs and decomposition leads to a diverse map of regional C gains and losses with different degrees of certainty.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Caractérisation de microparticules de matières grasses contenant de l’huile essentielle et leur stabilisation en vue de leur application

La thèse porte sur le développement et la caractérisation d’un additive pour l’alimentation du bétail contenant de l’huile essentielle. Dans cette formulation, un mélange d’huiles essentielles avec des effets anti-inflammatoires et antioxydants est encapsulaté dans une matrice d’huile de tournesol hydrogéné par spray cooling. Ces premières particules sont enrobées par une couche d’huiles essentielles dans un lit fluidisé. Du spray cooling conduit à la formation d’une poudre fluide avec une fluidité des microparticules qui décroit avec la concentration en huiles essentielles. A haute concentration en huiles essentielles, les particules maintiennent leur fluidité durant le stockage alors que sans ou avec de faibles concentrations en huiles essentielles, elles ont tendance à s’agglomérer.Cet effet dépend des conditions de stockage. Les études de la structure de la surface des microparticules révèlent qu’un effet d’efflorescence des matières grasses à la surface des particules est la cause de l’agglomération. L’analyse thermique différentielle et la spectrométrie aux rayons X démontrent une accélération de la transformation polymorphique des triglycérides de la matrice grasse en présence d’huile essentielle. L'utilisation d’un 'agent de fluidisation dans l'huile essentielle a permis l’application d’un enrobage contenant une huile essentielle et accroissant la palatabilité des particules.The thesis aimed at the development and the characterization of an essential oil containing feed additive formulation. In this formulation one essential oil mixture with anti-inflammatory and antioxidative properties shall be imbedded into a hydrogenated sunflower oil-based matrix via spray cooling and the resulting microparticles shall be furnished with a coating comprising a second essential oil in a fluidized bed process. Spray cooling resulted in the formation of freeflowing powders with the flowability of the microparticles decreasing with increasing essential oil concentration. High-concentrated microparticles maintained their flowability during storage whilst those without and with less essential oil tended to agglomerate. This effect also depended on the storage conditions. Surface structure investigations revealed that fatblooming on the microparticles surface causes agglomeration. Differential scanning calorimetry and X-ray scattering powder diffraction proved the accelerating effect of essential oil on the polymorphic transformation of the triacylglycerides of the fat matrix. The use of an essential oil loaded flow agent allowed the successful application of a coating containing a second palatability increasing essential oil mixture

Simulation of soil organic carbon in different soil size fractions using 13Carbon measurement data

We simulate the soil organic carbon (SOC) dynamics at a chronoseqeunce site in France, using the Rothamsted Carbon model. The site exhibits a transition from C3 plants, dominated by pine forest, to a conventional C4 maize rotation. The different 13C signatures of the forest plants and maize are used to distinguish between the woodland derived carbon (C) and the maize derived C. The model is evaluated against total SOC and C derived from forest and maize, respectively. The SOC dynamics of the five SOC pools of the model, decomposable plant material (DPM), resistant plant material (RPM), biomass, humus and inert C, are also compared to the SOC dynamics measured in different soil size fractions. These fractions are > 50 mum (particulate organic matter), 2-50 mum (silt associated SOC) and 50 mum and the sum of the other pools corresponds well to the SOC measured in the soil size fraction < 50 mum. Default model applications show that the model underestimates the fast drop in forest C stocks in the first 20 years after land-use change and overestimates the C accumulation of maize C. Several hypotheses were tested to evaluate the simulations. Input data and internal model parameter uncertainties had minor effects on the simulations results. Accounting for erosion and implementing a simple tillage routine did not improve the simulation fit to the data. We therefore hypothesize that a generic process that is not yet explicitly accounted for in the ROTHC model could explain the loss in soil C after land use change. Such a process could be the loss of the physical protection of soil organic matter as would be observed following cultivation of a previously uncultivated soil. Under native conditions a fraction of organic matter is protected in stable soil aggregates. These aggregates are physically disrupted by continuous and repeated cultivation of the soil. The underestimation of SOC loss by the model can be mainly attributed to the slow turnover of the humus pool. This pool was shown to represent mainly the SOC associated with the silt and clay soil fraction. Here, the clay associated SOC shows as similar turnover time as the humus pool in the model. We split the humus pool into a clay and a silt associated pool. The clay pool now corresponds to the clay associated SOC with the turnover time of the humus pool. The silt pool now corresponds to the silt associated SOC. From the measurements, the latter has a turnover time similar to the turnover time of the particulate organic matter. We therefore use the turnover time of the RPM pool for the silt pool. These modifications improve the simulations of the forest derived C significantly and improve the simulations of the maize derived C. Future work will further evaluate and refine this approach to eventually capture the SOC dynamics associated with physical protection, including the effect of tillage/no-tillage, in a simple approach

Simulation of soil organic carbon response at forest cultivation sequences using 13 C measurements

When deforestation is followed by continuous arable cropping, a permanent decline of between 22% and 42% in the soil organic carbon (SOC) has been reported. This systematic loss of soil carbon (C) is mainly attributed to the loss of physically protected SOC. The Rothamsted Carbon model (RothC) does not include a description of the processes of physical protection of SOC and so losses of C during continuous cultivation of previously uncultivated land are not likely to be accurately simulated. Our results show that in the first years following deforestation, RothC does not capture the fast drop in forest derived soil C. However, the model does satisfactorily simulate the changes in SOC derived from the following crops. Uncertainty in input data and accounting for erosion, does not explain the underestimation of decomposition after deforestation by RothC. A simple approach to increase decomposition by multiplying rate constants is evaluated. This approach needs high multiplication rates and leads to an overestimation of plant input values to sustain SOC equilibrium levels. However, the ability of RothC to simulate changes in the forest derived SOC can be greatly improved with an implementation of a simple approach to account for SOC dynamics due to the loss of physically protected C. This approach implements a new soil carbon pool into RothC which represents the labile but protected carbon fraction which builds up under minimally disturbed land uses, and which loses its protection once the soil is disturbed. The new pool is calibrated using 13C natural abundance analysis in conjunction with soil fractionation