In structured soils, the interaction of percolating water and reactive solutes with the soil matrix is mostly restricted to the surfaces of preferential flow paths. Flow paths, i.e., macropores, are formed by worm burrows, decayed root channels, cracks, and inter-aggregate spaces. While biopores are covered by earthworm casts and mucilage or by root residues, aggregates and cracks are often coated by soil organic matter (SOM), oxides, and clay minerals especially in the clay illuviation horizons of Luvisols. The SOM as well as the clay mineral composition and concentration strongly determine the wettability and sorption capacity of the coatings and thus control water and solute movement as well as the mass exchange between the preferential flow paths and the soil matrix. The objective of this proposal is the quantitative description of the small-scale distribution of physicochemical properties of intact structural surfaces and flow path surfaces and of their distribution in the soil volume. Samples of Bt horizons of Luvisols from Loess will be compared with those from glacial till. At intact structural surfaces prepared from soil clods, the spatial distribution (mm-scale) of SOM and clay mineral composition will be characterized with DRIFT (Diffuse reflectance infrared Fourier transform) spectroscopy using a self-developed mapping technique. For samples manually separated from coated surfaces and biopore walls, the contents of organic carbon (Corg) and the cation exchange capacity (CEC) will be analyzed and related to the intensities of specific signals in DRIFT spectra using Partial Least Square Regression (PLSR) analysis. The signal intensities of the DRIFT mapping spectra will be used to quantify the spatial distribution of Corg and CEC at these structural surfaces. The DRIFT mapping data will also be used for qualitatively characterizing the small scale distribution of the recalcitrance, humification, and microbial activity of the SOM from structural surfaces. The clay mineral composition of defined surface regions will be characterized by combining DRIFT spectroscopic with X-ray diffractometric analysis of manually separated samples. Subsequently, the spatial distribution of the clay mineral composition at structural surfaces will be determined from the intensities of clay mineral-specific signals in the DRIFT mapping spectra and exemplarily compared to scanning electron microscopic and infrared microscopic analysis of thin sections and thin polished micro-sections. The three-dimensional spatial distribution of the total structural surfaces in the volume of the Bt horizons will be quantified using X-ray computed tomography (CT) analysis of soil cores. The active preferential flow paths will be visualized and quantified by field tracer experiments. These CT and tracer data will be used to transfer the properties of the structural surfaces characterized by DRIFT mapping onto the active preferential flow paths in the Bt horizons.
The broad objective of the research is to gain a fundamental understanding of the surface reaction chemistry of exhaust catalysts operating under cycling conditions. Using an integrated theoretical approach we specifically target NOx abatement, with particular emphasis on the appearance and destruction of surface oxide phases as the reactor conditions cycle from oxidative to reductive during the operation of the NOx Storage Reduction (NSR) catalyst system. Methodologically this requires material-specific, quantitative and explicitly time-dependent simulation tools that can follow the evolution of the system over the macroscopic time-scales of NSR cycles, while simultaneously accounting for the atomic-scale site heterogeneity and spatial distributions at the evolving surface. To meet these challenging demands we will develop a novel multi-scale methodology relying on a multi-lattice first-principles kinetic Monte Carlo (kMC) approach. As representative example the simulations will be carried out on a PdO(101)/Pd(100) surface oxide model, but care will be taken to ensure a generalization of the multi-lattice first-principles kMC approach to other systems in which phase transformations may occur and result in a change in the surface lattice structure depending upon environmental variables.
Changes in agroecosystem management (e.g. landscape diversity, management intensity) affect the natural control of pests. The effects of agricultural change on this ecosystem service, however, are not universal and the mechanisms affecting it remain to be understood. As biological control is effectively the product of networks of interactions between pests and their natural enemies, food web analysis provides a versatile tool to address this gap of knowledge. The proposed project will utilize a molecular food web approach and examine, for the first time, how changes in plant fertilisation and landscape complexity affect quantitative aphid-parasitoid-hyperparasitoid food webs on a species-specific level to unravel how changes in food web interactions affect parasitoid aphid control. Based on the fieldderived data, cage experiments will be conducted to assess how parasitoid diversity and identity affect parasitoid interactions and pest control, complementing the field results. The work proposed here will take research on parasitoid aphid control one step further, as it will provide a clearer understanding of how plant fertilization affects whole aphid-parasitoid food webs in both simple and complex landscapes, allowing for further improvements in natural pest control.
The magnetosphere of a planet is controlled by a number of factors such as the intrinsic magnetic field, the atmosphere and ionosphere, and the solar wind. Different combinations of these control factors are at work at the terrestrial planets Mercury, Venus, Earth, and Mars, hence they form a very suitable set for quantitative comparative studies. A significant intrinsic dipolar magnetic field is present only on Earth and on Mercury. However, the configuration at Mercury differs considerably from that at Earth because Mercury does not support an atmosphere and ionosphere, the dipolar field is much weaker, the solar wind denser, and the interplanetary magnetic field stronger. Both Mars and Venus have atmospheres but lack a global planetary magnetic field, with regional crustal magnetization being present on Mars. This proposal aims at investigating and comparing electrical current systems in the space environments of terrestrial planets using magnetic vector data collected by orbiting spacecraft such as Venus Express, Mars Global Surveyor, CHAMP (Earth), and MESSENGER (Mercury). We propose to construct data-driven and physically meaningful representations that reveal and quantify the influence of various control factors. To achieve this, we will tailor Empirical Orthogonal Function (EOF) analysis and other multivariate methods to the specifics of planetary magnetic field observations. In contrast to representations that build on predefined functions like spherical harmonics, basis functions in the EOF approach are derived directly from the data. EOFs are designed to extract dominant coherent variations for further interpretation in terms of known physical phenomena, and then, in a regression step, for modeling using suitable control variables. The EOF methodology thus allows quantifying the relative importance of control factors for each planet individually, and thus contributes to the solution of topical science questions. The resulting empirical models will facilitate comparative studies of current systems at the terrestrial planets.
In the last decades agricultural policy has gained increasingly in complexity. Nowadays it influences the food and agricultural sector from the global market down to the farm level. Widespread research questions, like the impact of the WTO negotiations on the farm structure, most often require comprehensive modeling frameworks. Thus, different types of models are utilized according to their comparative advantages and combined in a strategically useful way to more accurately represent micro and macro aspects of the food and agricultural sector. Consequently, in recent years we have seen an increase in the development and application of model linkages. Given this background, the overall objective of this subproject is a systematic sensitivity analysis of model linkages that gradually involves more and more characteristics of the linkage and the corresponding transfer of results between models. In addition, the project aims to answer the following specific question: How does structural change at the farm level influence aggregate supply and technical progress? Under which conditions is it possible to derive macro-relationships from micro-relationships? How does the aggregation level influence the model results and how can possible problems be overcome? This procedure is used to quantify the effects and to derive conditions for optimal interaction of the connected models. The analysis is based on the general equilibrium model GTAP (Global Trade Analysis Project) and the farm group model FARMIS (Farm Modelling Information System) which are employed in conjunction to analyze the effects of WTO negotiations on the farm level.
Glendonites are pseudomorphs after the mineral ikaite (CaCO3 x 6H2O) and composed of calcite (CaCO3). In the past, they have been used as a paleo-thermometer because the primary mineral ikaite, according to observations and experiments, seems to be formed at temperatures near freezing, high alkalinity and high phosphate concentrations in marine sediments. An enigmatic occurrence of the largest glendonites known world-wide, in the Early Eocene Fur Formation of northwestern Denmark offers the unique possibility to shed more light on the actual mechanism and controlling parameters of ikaite formation. Right in the aftermath of the Paleocene-Eocene thermal maximum, a time known for its global pertubation in the global carbon cycle, the formation of authigenic calcium carbonate concretions start in the Fur Formation. In a specific stratigraphic interval inbetween these concretions, the glendonites can be found. We will investigate if termperature changes or changes in geochemical parameters of the Danish Basin caused the sudden formation of ikaite during a time interval that was based on known paleoclimatic reconstructions (semi tropic) not favorable for ikaite formation.
Terrestrial green algae and cyanobacteria are typical and abundant components of biological soil crusts in the Polar Regions. These communities form water-stable aggregates that have important ecological roles in primary production, nitrogen fixation, nutrient cycling, water retention and stabilization of soils. Although available data on green algae and cyanobacteria are generally very limited for the Arctic and Antarctica, their functional importance as ecosystem developers in nutrient poor environments is regarded as high. Therefore, the main goal of the interdisciplinary project is, for the first time, a precise evaluation of their 1.) Biodiversity as well as of 2.) The infra-specific genetic diversity, 3.) ecophysiological performance and 4.) transcriptomics of the most abundant taxa in biological soil crusts isolated from the Antarctic Peninsula and Arctic Svalbard. Biodiversity will be investigated using a classical culture approach in combination with molecular-taxonomical methods as well as with metagenomics. The infra-specific genetic diversity of the most abundant green algae and cyanobacteria will be studied using fingerprinting techniques, and a range of selected populations characterized in relation to their physiological plasticity. Temperature and water availability, two key environmental factors for terrestrial organisms, are currently changing in Polar Regions due to global warming, and hence their effect on growth and photosynthesis response patterns will be comparatively investigated. The data will indicate whether and how global change influence population structure and ecological performance of key organisms in polar soil crusts, and help to make predictions on the future significance of the ecological functions of these pioneer communities. Such a multiphasic approach has never been applied before to soil algae and cyanobacteria in both Polar Regions, and hence represents one of the key innovations of this proposal.
Comprehension of belowground competition between plant species is a central part in understanding the complex interactions in intercropped agricultural systems, between crops and weeds as well as in natural ecosystems. So far, no simple and rapid method for species discrimination of roots in the soil exists. We will be developing a method for root discrimination of various species based on Fourier Transform Infrared (FTIR)-Attenuated Total Reflexion (ATR) Spectroscopy and expanding its application to the field. The absorbance patterns of FTIR-ATR spectra represent the chemical sample composition like an individual fingerprint. By means of multivariate methods, spectra will be grouped according to spectral and chemical similarity in order to achieve species discrimination. We will investigate pea and oat roots as well as maize and barnyard grass roots using various cultivars/proveniences grown in the greenhouse. Pea and oat are recommendable species for intercropping to achieve superior grain and protein yields in an environmentally sustainable manner. To evaluate the effects of intercropping on root distribution in the field, root segments will be measured directly at the soil profile wall using a mobile FTIR spectrometer. By extracting the main root compounds (lipids, proteins, carbohydrates) and recording their FTIR-ATR spectra as references, we will elucidate the chemical basis of species-specific differences.
Fusarium species of the Gibberella fujikuroi species complex cause serious diseases on different crops such as rice, wheat and maize. An important group of plant pathogens is the Gibberella fujikuroi species complex (GFC) of closely related Fusarium species which are associated with specific hosts; F. verticillioides and F. proliferatum are particularly associated with maize where they can cause serious ear-, root-, and stalk rot diseases. Two other closely related species of the GFC, F. mangiferae and F. fujikuroi, which share about 90Prozent sequence identity with F. verticillioides, are pathogens on mango and rice, respectively. All of these species produce a broad spectrum of secondary metabolites such as phytohormones (gibberellins, auxins, and cytokinins), and harmful mycotoxins, such as fumonisin, fusarin C, or fusaric acid in large quantities. However, the spectrum of those mycotoxins might differ between closely related species suggesting that secondary metabolites might be determinants for host specificity. In this project, we will study the potential impact of secondary metabolites (i.e. phytohormones and certain mycotoxins) and some other species-specific factors (e.g. species-specific transcription factors) on host specificity. The recently sequenced genomes of F. mangiferae and F. fujikuroi by our groups and the planned sequencing of F. proliferatum will help to identify such determinants by genetic manipulation of the appropriate metabolic pathway(s).
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