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Peak oil is forcing our society to shift from fossil to renewable resources. However, such renewable resources are also scarce, and they too must be used in the most efficient and sustainable way possible. Biorefining is a concept that represents both resource efficiency and sustainability. This approach initiates a cascade use, which means food and feed production before material use, and an energy-related use at the end of the value-added chain. However, sustainability should already start in the fields, on the agricultural side, where the industrially-used biomass is produced. Therefore, the aim of my doctoral thesis is to analyse the sustainable feedstock supply for biorefineries. In contrast to most studies on biorefineries, I focus on the sustainable provision of feedstock and not on the bioengineering processing of whatever feedstock is available.
Grasslands provide a high biomass potential. They are often inefficiently used, so a new utilisation concept based on the biorefining approach can increase the added value from grasslands. Fodder legumes from temporary and permanent grasslands were chosen for this study. Previous research shows that they are a promising feedstock for industrial uses, and their positive environmental impact is an important byproduct to promote sustainable agricultural production systems.
Green Biorefineries are a class of biorefineries that use fresh green biomass, such as grasses or fodder legumes, as feedstock. After fractionation, an organic solution (press juice) forms; this is used for the production of organic acids, chemicals and extracts, as well as fertilisers. A fibre component (press cake) is also created to produce feed, biomaterials and biogas. This thesis examines a specific value chain, using alfalfa and clover/grass as feedstock and generating lactic acid and one type of cattle feed from it. The research question is if biomass production needs to be adapted for the utilisation of fodder legumes in the Green Biorefinery approach. I have attempted to give a holistic analysis of cultivation, processing and utilisation of two specific grassland crops. Field trials with alfalfa and clover/grass at different study sites were carried out to obtain information on biomass quality and quantity depending on the crop, study site and harvest time. The fresh biomass was fractionated with a screw press and the composition of press juices and cakes was analysed. Fermentation experiments took place to determine the usability of press juices for lactic acid production. The harvest time is not of high importance for the quality of press juices as a fermentation medium. For permanent grasslands, late cuts, often needed for reasons of nature conservation, are possible without a major influence on feedstock quality. The press cakes were silaged for feed-value determination.
Following evidence that both intermediate products are suitable feedstocks in the Green Biorefinery approach, I developed a cost-benefit analysis, comparing different production scenarios on a farm. Two standard crop rotations for Brandenburg, producing either only market crops or market crops and fodder legumes for ruminant feed production, were compared to a system that uses the cultivated fodder legumes for the Green Biorefinery value chain instead of only feed production. Timely processing of the raw material is important to maintain quality for industrial uses, so on-site processing at the farm is assumed in Green Biorefinery scenario. As a result, more added value stays in the rural area. Two farm sizes, common for many European regions, were chosen to examine the influence of scale. The cost site of farmers has also been analysed in detail to assess which farm characteristics make production of press juices for biochemical industries viable. Results show that for large farm sizes in particular, the potential profits are high. Additionally, the wider spectrum of marketable products generates new sources of income for farmers.
The holistic analysis of the supply chain provides evidence that the cultivation processes for fodder legumes do not need to be adapted for use in Green Biorefineries. In fact, the new utilisation approach even widens the cultivation and processing spectrum and can increase economic viability of fodder legume production in conventional farming.
Anthropogenic activities have transformed the Earth's environment, not only on local level, but on the planetary-scale causing global change. Besides industrialization, agriculture is a major driver of global change. This change in turn impairs the agriculture sector, reducing crop yields namely due to soil degradation, water scarcity, and climate change. However, this is a more complex issue than it appears. Crop yields can be increased by use of agrochemicals and fertilizers which are mainly produced by fossil energy. This is important to meet the increasing food demand driven by global demographic change, which is further accelerated by changes in regional lifestyles. In this dissertation, we attempt to address this complex problem exploring agricultural potential globally but on a local scale. For this, we considered the influence of lifestyle changes (dietary patterns) as well as technological progress and their effects on climate change, mainly greenhouse gas (GHG) emissions. Furthermore, we examined options for optimizing crop yields in the current cultivated land with the current cropping patterns by closing yield gaps. Using this, we investigated in a five-minute resolution the extent to which food demand can be met locally, and/or by regional and/or global trade. Globally, food consumption habits are shifting towards calorie rich diets. Due to dietary shifts combined with population growth, the global food demand is expected to increase by 60-110% between 2005 and 2050. Hence, one of the challenges to global sustainability is to meet the growing food demand, while at the same time, reducing agricultural inputs and environmental consequences. In order to address the above problem, we used several freely available datasets and applied multiple interconnected analytical approaches that include artificial neural network, scenario analysis, data aggregation and harmonization, downscaling algorithm, and cross-scale analysis.
Globally, we identified sixteen dietary patterns between 1961 and 2007 with food intakes ranging from 1,870 to 3,400 kcal/cap/day. These dietary patterns also reflected changing dietary habits to meat rich diets worldwide. Due to the large share of animal products, very high calorie diets that are common in the developed world, exhibit high total per capita emissions of 3.7-6.1 kg CO2eq./day. This is higher than total per capita emissions of 1.4-4.5 kg CO2eq./day associated with low and moderate calorie diets that are common in developing countries. Currently, 40% of the global crop calories are fed to livestock and the feed calorie use is four times the produced animal calories. However, these values vary from less than 1 kcal to greater 10 kcal around the world. On the local and national scale, we found that the local and national food production could meet demand of 1.9 and 4.4 billion people in 2000, respectively. However, 1 billion people from Asia and Africa require intercontinental agricultural trade to meet their food demand. Nevertheless, these regions can become food self-sufficient by closing yield gaps that require location specific inputs and agricultural management strategies. Such strategies include: fertilizers, pesticides, soil and land improvement, management targeted on mitigating climate induced yield variability, and improving market accessibility. However, closing yield gaps in particular requires global N-fertilizer application to increase by 45-73%, P2O5 by 22-46%, and K2O by 2-3 times compare to 2010. Considering population growth, we found that the global agricultural GHG emissions will approach 7 Gt CO2eq./yr by 2050, while the global livestock feed demand will remain similar to 2000. This changes tremendously when diet shifts are also taken into account, resulting in GHG emissions of 20 Gt CO2eq./yr and an increase of 1.3 times in the crop-based feed demand between 2000 and 2050. However, when population growth, diet shifts, and technological progress by 2050 were considered, GHG emissions can be reduced to 14 Gt CO2eq./yr and the feed demand to nearly 1.8 times compare to that in 2000. Additionally, our findings shows that based on the progress made in closing yield gaps, the number of people depending on international trade can vary between 1.5 and 6 billion by 2050. In medium term, this requires additional fossil energy. Furthermore, climate change, affecting crop yields, will increase the need for international agricultural trade by 4% to 16%.
In summary, three general conclusions are drawn from this dissertation. First, changing dietary patterns will significantly increase crop demand, agricultural GHG emissions, and international food trade in the future when compared to population growth only. Second, such increments can be reduced by technology transfer and technological progress that will enhance crop yields, decrease agricultural emission intensities, and increase livestock feed conversion efficiencies. Moreover, international trade dependency can be lowered by consuming local and regional food products, by producing diverse types of food, and by closing yield gaps. Third, location specific inputs and management options are required to close yield gaps. Sustainability of such inputs and management largely depends on which options are chosen and how they are implemented. However, while every cultivated land may not need to attain its potential yields to enable food security, closing yield gaps only may not be enough to achieve food self-sufficiency in some regions. Hence, a combination of sustainable implementations of agricultural intensification, expansion, and trade as well as shifting dietary habits towards a lower share of animal products is required to feed the growing population.
The standing stock and production of organismal biomass depends strongly on the organisms’ biotic environment, which arises from trophic and non-trophic interactions among them. The trophic interactions between the different groups of organisms form the food web of an ecosystem, with the autotrophic and bacterial production at the basis and potentially several levels of consumers on top of the producers. Feeding interactions can regulate communities either by severe grazing pressure or by shortage of resources or prey production, termed top-down and bottom-up control, respectively. The limitations of all communities conglomerate in the food web regulation, which is subject to abiotic and biotic forcing regimes arising from external and internal constraints. This dissertation presents the effects of alterations in two abiotic, external forcing regimes, terrestrial matter input and long-lasting low temperatures in winter. Diverse methodological approaches, a complex ecosystem model study and the analysis of two whole-lake measurements, were performed to investigate effects for the food web regulation and the resulting consequences at the species, community and ecosystem scale. Thus, all types of organisms, autotrophs and heterotrophs, at all trophic levels were investigated to gain a comprehensive overview of the effects of the two mentioned altered forcing regimes. In addition, an extensive evaluation of the trophic interactions and resulting carbon fluxes along the pelagic and benthic food web was performed to display the efficiencies of the trophic energy transfer within the food webs. All studies were conducted in shallow lakes, which is worldwide the most abundant type of lakes. The specific morphology of shallow lakes allows that the benthic production contributes substantially to the whole-lake production. Further, as shallow lakes are often small they are especially sensitive to both, changes in the input of terrestrial organic matter and the atmospheric temperature. Another characteristic of shallow lakes is their appearance in alternative stable states. They are either in a clear-water or turbid state, where macrophytes and phytoplankton dominate, respectively. Both states can stabilize themselves through various mechanisms.
These two alternative states and stabilizing mechanisms are integrated in the complex ecosystem model PCLake, which was used to investigate the effects of the enhanced terrestrial particulate organic matter (t-POM) input to lakes. The food web regulation was altered by three distinct pathways: (1) Zoobenthos received more food, increased in biomass which favored benthivorous fish and those reduced the available light due to bioturbation. (2) Zooplankton substituted autochthonous organic matter in their diet by suspended t-POM, thus the autochthonous organic matter remaining in the water reduced its transparency. (3) T-POM suspended into the water and reduced directly the available light. As macrophytes are more light-sensitive than phytoplankton they suffered the most from the lower transparency. Consequently, the resilience of the clear-water state was reduced by enhanced t-POM inputs, which makes the turbid state more likely at a given nutrient concentration. In two subsequent winters long-lasting low temperatures and a concurrent long duration of ice coverage was observed which resulted in low overall adult fish biomasses in the two study lakes – Schulzensee and Gollinsee, characterized by having and not having submerged macrophytes, respectively. Before the partial winterkill of fish Schulzensee allowed for a higher proportion of piscivorous fish than Gollinsee. However, the partial winterkill of fish aligned both communities as piscivorous fish are more sensitive to low oxygen concentrations. Young of the year fish benefitted extremely from the absence of adult fish due to lower predation pressure. Therefore, they could exert a strong top-down control on crustaceans, which restructured the entire zooplankton community leading to low crustacean biomasses and a community composition characterized by copepodites and nauplii. As a result, ciliates were released from top-down control, increased to high biomasses compared to lakes of various trophic states and depths and dominated the zooplankton community. While being very abundant in the study lakes and having the highest weight specific grazing rates among the zooplankton, ciliates exerted potentially a strong top-down control on small phytoplankton and particle-attached bacteria. This resulted in a higher proportion of large phytoplankton compared to other lakes. Additionally, the phytoplankton community was evenly distributed presumably due to the numerous fast growing and highly specific ciliate grazers. Although, the pelagic food web was completely restructured after the subsequent partial winterkills of fish, both lakes were resistant to effects of this forcing regime at the ecosystem scale. The consistently high predation pressure on phytoplankton prevented that Schulzensee switched from the clear-water to the turbid state. Further mechanisms, which potentially stabilized the clear-water state, were allelopathic effects by macrophytes and nutrient limitation in summer. The pelagic autotrophic and bacterial production was an order of magnitude more efficient transferred to animal consumers than the respective benthic production, despite the alterations of the food web structure after the partial winterkill of fish. Thus, the compiled mass-balanced whole-lake food webs suggested that the benthic bacterial and autotrophic production, which exceeded those of the pelagic habitat, was not used by animal consumers. This holds even true if the food quality, additional consumers such as ciliates, benthic protozoa and meiobenthos, the pelagic-benthic link and the potential oxygen limitation of macrobenthos were considered. Therefore, low benthic efficiencies suggest that lakes are primarily pelagic systems at least at the animal consumer level.
Overall, this dissertation gives insights into the regulation of organism groups in the pelagic and benthic habitat at each trophic level under two different forcing regimes and displays the efficiency of the carbon transfer in both habitats. The results underline that the alterations of external forcing regimes affect all hierarchical level including the ecosystem.
Magnetite nanoparticles and their assembly comprise a new area of development for new technologies. The magnetic particles can interact and assemble in chains or networks. Magnetotactic bacteria are one of the most interesting microorganisms, in which the assembly of nanoparticles occurs. These microorganisms are a heterogeneous group of gram negative prokaryotes, which all show the production of special magnetic organelles called magnetosomes, consisting of a magnetic nanoparticle, either magnetite (Fe3O4) or greigite (Fe3S4), embedded in a membrane. The chain is assembled along an actin-like scaffold made of MamK protein, which makes the magnetosomes to arrange in mechanically stable chains. The chains work as a compass needle in order to allow cells to orient and swim along the magnetic field of the Earth.
The formation of magnetosomes is known to be controlled at the molecular level. The physico–chemical conditions of the surrounding environment also influence biomineralization. The work presented in this manuscript aims to understand how such external conditions, in particular the extracellular oxidation reduction potential (ORP) influence magnetite formation in the strain Magnetospirillum magneticum AMB-1. A controlled cultivation of the microorganism was developed in a bioreactor and the formation of magnetosomes was characterized.
Different techniques have been applied in order to characterize the amount of iron taken up by the bacteria and in consequence the size of magnetosomes produced at different ORP conditions. By comparison of iron uptake, morphology of bacteria, size and amount of magnetosomes per cell at different ORP, the formation of magnetosomes was inhibited at ORP 0 mV, whereas reduced conditions, ORP – 500 mV facilitate biomineralization process.
Self-assembly of magnetosomes occurring in magnetotactic bacteria became an inspiration to learn from nature and to construct nanoparticles assemblies by using the bacteriophage M13 as a template. The M13 bacteriophage is an 800 nm long filament with encapsulated single-stranded DNA that has been recently used as a scaffold for nanoparticle assembly. I constructed two types of assemblies based on bacteriophages and magnetic nanoparticles. A chain – like assembly was first formed where magnetite nanoparticles are attached along the phage filament. A sperm – like construct was also built with a magnetic head and a tail formed by phage filament.
The controlled assembly of magnetite nanoparticles on the phage template was possible due to two different mechanism of nanoparticle assembly. The first one was based on the electrostatic interactions between positively charged polyethylenimine coated magnetite nanoparticles and negatively charged phages. The second phage –nanoparticle assembly was achieved by bioengineered recognition sites. A mCherry protein is displayed on the phage and is was used as a linker to a red binding nanobody (RBP) that is fused to the one of the proteins surrounding the magnetite crystal of a magnetosome.
Both assemblies were actuated in water by an external magnetic field showing their swimming behavior and potentially enabling further usage of such structures for medical applications. The speed of the phage - nanoparticles assemblies are relatively slow when compared to those of microswimmers previously published. However, only the largest phage-magnetite assemblies could be imaged and it is therefore still unclear how fast these structures can be in their smaller version.
Obesity is a major health problem for many developing and industrial countries. Increasing rates reach almost 50 % of the population in some countries and related metabolic diseases including cardiovascular events and T2DM are challenging the health systems. Adiposity, an increase in body fat mass, is a major hallmark of obesity. Adipose tissue is long known not only to store lipids but also to influence whole-body metabolism including food intake, energy expenditure and insulin sensitivity. Adipocytes can store lipids and thereby protect other tissue from lipotoxic damage. However, if the energy intake is higher than the energy expenditure over a sustained time period, adipose tissue will expand. This can lead to an impaired adipose tissue function resulting in higher levels of plasma lipids, which can affect other tissue like skeletal muscle, finally leading to metabolic complications. Several studies showed beneficial metabolic effects of weight reduction in obese subjects immediately after weight loss. However, weight regain is frequently observed along with potential negative effects on cardiovascular risk factors and a high intra-individual response.
We performed a body weight maintenance study investigating the mechanisms of weight maintenance after intended WR. Therefore we used a low caloric diet followed by a 12-month life-style intervention. Comprehensive phenotyping including fat and muscle biopsies was conducted to investigate hormonal as well as metabolic influences on body weight regulation. In this study, we showed that weight reduction has numerous potentially beneficial effects on metabolic parameters. After 3-month WR subjects showed significant weight and fat mass reduction, lower TG levels as well as higher insulin sensitivity. Using RNA-Seq to analyse whole fat and muscle transcriptome a strong impact of weight reduction on adipose tissue gene expression was observed. Gene expression alterations over weight reduction included several cellular metabolic genes involved in lipid and glucose metabolism as well as insulin signalling and regulatory pathways. These changes were also associated with anthropometric parameters assigning body composition. Our data indicated that weight reduction leads to a decreased expression of several lipid catabolic as well as anabolic genes. Long-term body weight maintenance might be influenced by several parameters including hormones, metabolic intermediates as well as the transcriptional landscape of metabolic active tissues. Our data showed that genes involved in biosynthesis of unsaturated fatty acids might influence the BMI 18-month after a weight reduction phase. This was further supported by analysing metabolic parameters including RQ and FFA levels. We could show that subjects maintaining their lost body weight had a higher RQ and lower FFA levels, indicating increased metabolic flexibility in subjects.
Using this transcriptomic approach we hypothesize that low expression levels of lipid synthetic genes in adipose tissue together with a higher mitochondrial activity in skeletal muscle tissue might be beneficial in terms of body weight maintenance.
The high-latitudinal thermospheric processes driven by the solar wind and Interplanetary Magnetic Field (IMF) interaction with the Earth magnetosphere are highly variable parts of the complex dynamic plasma environment, which represent the coupled Magnetosphere – Ionosphere – Thermosphere (MIT) system. The solar wind and IMF interactions transfer energy to the MIT system via reconnection processes at the magnetopause. The Field Aligned Currents (FACs) constitute the energetic links between the magnetosphere and the Earth ionosphere. The MIT system depends on the highly variable solar wind conditions, in particular on changes of the strength and orientation of the IMF.
In my thesis, I perform an investigation on the physical background of the complex MIT system using the global physical - numerical, three-dimensional, time-dependent and self-consistent Upper Atmosphere Model (UAM). This model describes the thermosphere, ionosphere, plasmasphere and inner magnetosphere as well as the electrodynamics of the coupled MIT system for the altitudinal range from 80 (60) km up to the 15 Earth radii.
In the present study, I developed and investigated several variants of the high-latitudinal electrodynamic coupling by including the IMF dependence of FACs into the UAM model. For testing, the various variants were applied to simulations of the coupled MIT system for different seasons, geomagnetic activities, various solar wind and IMF conditions. Additionally, these variants of the theoretical model with the IMF dependence were compared with global empirical models. The modelling results for the most important thermospheric parameters like neutral wind and mass density were compared with satellite measurements. The variants of the UAM model with IMF dependence show a good agreement with the satellite observations. In comparison with the empirical models, the improved variants of the UAM model reproduce a more realistic meso-scale structures and dynamics of the coupled MIT system than the empirical models, in particular at high latitudes. The new configurations of the UAM model with IMF dependence contribute to the improvement of space weather prediction.
Water resources from Central Asia’s mountain regions have a high relevance for the water supply of the water scarce lowlands. A good understanding of the water cycle in these mountain regions is therefore needed to develop water management strategies. Hydrological modeling helps to improve our knowledge of the regional water cycle, and it can be used to gain a better understanding of past changes or estimate future hydrologic changes in view of projected changes in climate. However, due to the scarcity of hydrometeorological data, hydrological modeling for mountain regions in Central Asia involves large uncertainties.
Addressing this problem, the first aim of this thesis was to develop hydrological modeling approaches that can increase the credibility of hydrological models in data sparse mountain regions. This was achieved by using additional data from remote sensing and atmospheric modeling. It was investigated whether spatial patterns from downscaled reanalysis data can be used for the interpolation of station-based precipitation data. This approach was compared to other precipitation estimates using a hydrologic evaluation based on hydrological modeling and a comparison of simulated and observed discharge, which demonstrated a generally good performance of this method. The study further investigated the value of satellite-derived snow cover data for model calibration. Trade-offs of good model performance in terms of discharge and snow cover were explicitly evaluated using a multiobjective optimization algorithm, and the results were contrasted with single-objective calibration and Monte Carlo simulations. The study clearly shows that the additional use of snow cover data improved the internal consistency of the hydrological model. In this context, it was further investigated for the first time how many snow cover scenes were required for hydrological model calibration.
The second aim of this thesis was the application of the hydrological model in order to investigate the causes of observed streamflow increases in two headwater catchments of the Tarim River over the recent decades. This simulation-based approach for trend attribution was complemented by a data-based approach. The hydrological model was calibrated to discharge and glacier mass balance data and considered changes in glacier geometry over time. The results show that in the catchment with a lower glacierization, increasing precipitation and temperature both contributed to the streamflow increases, while in the catchment with a stronger glacierization, increasing temperatures were identified as the dominant driver.
Earthquake clustering has proven the most useful tool to forecast changes in seismicity rates in the short and medium term (hours to months), and efforts are currently being made to extend the scope of such models to operational earthquake forecasting. The overarching goal of the research presented in this thesis is to improve physics-based earthquake forecasts, with a focus on aftershock sequences. Physical models of triggered seismicity are based on the redistribution of stresses in the crust, coupled with the rate-and-state constitutive law proposed by Dieterich to calculate changes in seismicity rate. This type of models are known as Coulomb- rate and-state (CRS) models. In spite of the success of the Coulomb hypothesis, CRS models typically performed poorly in comparison to statistical ones, and they have been underepresented in the operational forecasting context. In this thesis, I address some of these issues, and in particular these questions: (1) How can we realistically model the uncertainties and heterogeneity of the mainshock stress field? (2) What is the effect of time dependent stresses in the postseismic phase on seismicity? I focus on two case studies from different tectonic settings: the Mw 9.0 Tohoku megathrust and the Mw 6.0 Parkfield strike slip earthquake. I study aleatoric uncertainties using a Monte Carlo method. I find that the existence of multiple receiver faults is the most important source of intrinsic stress heterogeneity, and CRS models perform better when this variability is taken into account. Epistemic uncertainties inherited from the slip models also have a significant impact on the forecast, and I find that an ensemble model based on several slip distributions outperforms most individual models. I address the role of postseismic stresses due to aseismic slip on the mainshock fault (afterslip) and to the redistribution of stresses by previous aftershocks (secondary triggering). I find that modeling secondary triggering improves model performance. The effect of afterslip is less clear, and difficult to assess for near-fault aftershocks due to the large uncertainties of the afterslip models. Off-fault events, on the other hand, are less sensitive to the details of the slip distribution: I find that following the Tohoku earthquake, afterslip promotes seismicity in the Fukushima region. To evaluate the performance of the improved CRS models in a pseudo-operational context, I submitted them for independent testing to a collaborative experiment carried out by CSEP for the 2010-2012 Canterbury sequence. Preliminary results indicate that physical models generally perform well compared to statistical ones, suggesting that CRS models may have a role to play in the future of operational forecasting. To facilitate efforts in this direction, and to enable future studies of earthquake triggering by time dependent processes, I have made the code open source. In the final part of this thesis I summarize the capabilities of the program and outline technical aspects regarding performance and parallelization strategies.
Plant cell walls are complex structures that underpin plant growth and are widely exploited in diverse human activities thus placing them with a central importance in biology. Cell walls have been a prominent area of research for a long time, but the chemical complexity and diversity of cell walls not just between species, but also within plants, between cell-types, and between cell wall micro-domains pose several challenges. Progress accelerated several-fold in cell wall biology owing to advances in sequencing technology, aided soon thereafter by advances in omics and imaging technologies. This development provides additional perspectives of cell walls across a rapidly growing number of species, highlighting a myriad of architectures, compositions, and functions.
Furthermore, rather than the component centric view, integrative analysis of the different cell wall components across system-levels help to gain a more in-depth understanding of the structure and biosynthesis of the cell envelope and its interactions with the environment.
To this end, in this work three case studies are detailed, all pertaining to the integrative analysis of heterogeneous cell wall related data arising from different system-levels and analytical techniques. A detailed account of multiblock methods is provided and in particular canonical correlation and regression methods of data integration are discussed. In the first integrative analysis, by employing canonical correlation analysis - a multivariate statistical technique to study the association between two datasets - novel insight to the relationship between glycans and phenotypic traits is gained. In addition, sparse partial least squares regression approach that adapts Lasso penalization and allows for the selection of a subset of variables was employed. The second case study focuses on an integrative analysis of images obtained from different spectroscopic techniques. By employing yet another multiblock approach - multiple co-inertia analysis, insitu biochemical composition of cell walls from different cell-types is studied thereby highlighting the common and complementary parts of the two hyperspectral imaging techniques. Finally, the third integrative analysis facilitates gene expression analysis of the Arabidopsis root transcriptome and translatome for the identification of cell wall related genes and compare expression patterns of cell wall synthesis genes. The computational analysis considered correlation and variation of expression across cell-types at both system-levels, and also provides insight into the degree of co-regulatory relationships that are preserved between the two processes.
The integrative analysis of glycan data and phenotypic traits in cotton fibers using canonical methods led to the identification of specific polysaccharides which may play a major role during fiber development for the final fiber characteristics. Furthermore, this analysis provides a base for future studies on glycan arrays in case of developing cotton fibers. The integrative analysis of images from infrared and Raman spectroscopic approaches allowed the coupling of different analytical techniques to characterize complex biological material, thereby, representing various facets of their chemical properties. Moreover, the results from the co-inertia analysis demonstrated that the study was well adapted as it is relevant for coupling data tables in a symmetric way. Several indicators are proposed to investigate how the global and block scores are related. In addition, studying the root cells of \textit{Arabidopsis thaliana} allowed positing a novel pipeline to systematically investigate and integrate the different levels of information available at the global and single-cell level. The conducted analysis also confirms that previously identified key transcriptional activators of secondary cell wall development display highly conserved patterns of transcription and translation across the investigated cell-types. Moreover, the biological processes that display conserved and divergent patterns based on the cell-type-specific expression and translation levels are identified.
This thesis contains three experimental studies addressing the interplay between deformation and the mineral reaction between natural calcite and magnesite. The solid-solid mineral reaction between the two carbonates causes the formation of a magnesio-calcite precursor layer and a dolomite reaction rim in every experiment at isostatic annealing and deformation conditions.
CHAPTER 1 briefly introduces general aspects concerning mineral reactions in nature and diffusion pathways for mass transport. Moreover, results of previous laboratory studies on the influence of deformation on mineral reactions are summarized. In addition, the main goals of this study are pointed out.
In CHAPTER 2, the reaction between calcite and magnesite single crystals is examined at isostatic annealing conditions. Time series performed at a fixed temperature revealed a diffusion-controlled dolomite rim growth. Two microstructural domains could be identified characterized by palisade-shaped dolomite grains growing into the magnesite and granular dolomite growing towards calcite. A model was provided for the dolomite rim growth based on the counter-diffusion of CaO and MgO. All reaction products exhibited a characteristic crystallographic relationship with respect to the calcite reactant. Moreover, kinetic parameters of the mineral reaction were determined out of a temperature series at a fixed time. The main goal of the isostatic test series was to gain information about the microstructure evolution, kinetic parameters, chemical composition and texture development of the reaction products. The results were used as a reference to quantify the influence of deformation on the mineral reaction.
CHAPTER 3 deals with the influence of non-isostatic deformation on dolomite and magnesio-calcite layer production between calcite and magnesite single crystals. Deformation was achieved by triaxial compression and by torsion. Triaxial compression up to 38 MPa axial stress at a fixed time showed no significant influence of stress and strain on dolomite formation. Time series conducted at a fixed stress yield no change in growth rates for dolomite and magnesio-calcite at low strains. Slightly larger magnesio-calcite growth rates were observed at strains above >0.1. High strains at similar stresses were caused by the activation of additional glide systems in the calcite single crystal and more mobile dislocations in the magnesio-calcite grains, providing fast diffusion pathways. In torsion experiments a gradual decrease in dolomite and magnesio-calcite layer thickness was observed at a critical shear strain. During deformation, crystallographic orientations of reaction products rearranged with respect to the external framework. A direct effect of the mineral reaction on deformation could not be recognized due to the relatively small reaction product widths.
In CHAPTER 4, the influence of starting material microfabrics and the presence of water on the reaction kinetics was evaluated. In these experimental series polycrystalline material was in contact with single crystals or two polycrystalline materials were used as reactants. Isostatic annealing resulted in different dolomite and magnesio-calcite layer thicknesses, depending on starting material microfabrics. The reaction progress at the magnesite interface was faster with smaller magnesite grain size, because grain boundaries provided fast pathways for diffusion and multiple nucleation sites for dolomite formation. Deformation by triaxial compression and torsion yield lower dolomite rim thicknesses compared to annealed samples for the same time. This was caused by grain coarsening of polycrystalline magnesite during deformation. In contrast, magnesio-calcite layers tended to be larger during deformation, which triggered enhanced diffusion along grain boundaries. The presence of excess water had no significant influence on the reaction kinetics, at least if the reactants were single crystals.
In CHAPTER 5 general conclusions about the interplay between deformation and the mineral reaction in the carbonate system are presented.
Finally, CHAPTER 6 highlights possible future work in the carbonate system based on the results of this study.