Das hier vorgeschlagene Projekt, RP6 in INUIT-2, zielt darauf hin, fundamentales Prozessverständnis in Bezug auf heterogene Eisnukleation zu erzielen, und hier besonders auf die Rolle von biogenen Eiskeimen und von Eiskeimen die aus Mischungen von biogenem und mineralischem Material bestehen. Der Leipzig Aerosol Cloud Interaction Simulator (LACIS) wird dazu verwendet werden, das Immersionsgefrierverhalten einer Reihe von verschiedenen Eiskeimen zu untersuchen, darunter biogene (von Pilzen stammende) Eiskeime, solche die aus einer Mischung von biogenem und mineralischem Material bestehen wie Bodenstäube und Proben die innerhalb von INUIT-2 als Test-Materialen verwendet werden. Letztere werden von verschiedenen Gruppen von innerhalb und außerhalb von INUIT vermessen werden, und die Ergebnisse werden Vergleichen unterzogen werden, ähnlich denen, die bereits für einfachere Test-Materialien in INUIT-1 erfolgreich durchgeführt worden sind. Für die Eiskeime, die zur Untersuchung in RP6 vorgeschlagen werden, wird in sinnvollen und machbaren Fallen eine Oberflächenbehandlung durchgeführt werden, mit reaktiven und mit chemisch inerten Substanzen, deren Einfluss auf die Eiskeimfähigkeit dann untersucht wird. Wie bereits in früheren LACISStudien dokumentiert, sind kontrollierte Oberflächenbehandlungen ein ausgezeichnetes Instrument um zu ermitteln, was dazu führt, dass ein Partikel ein effektiver Eiskeim ist. Zusätzlich erhellen diese Untersuchungen den Effekt der Alterung auf die Eiskeime. Es ist auch geplant, die Messungen auszuweiten, hin zu Bedingungen unter denen eine Untersättigung bezüglich Wasserdampf vorliegt. Es soll untersucht werden in wie weit sich die Eiskeimbildung unter diesen Bedingungen verhält wie es im Fall von Immersionsgefrieren in konzentrierten Lösungen zu erwarten wäre. Von all den experimentell erhaltenen Daten werden verschiedene Parametrisierungen abgeleitet, sowohl zeit-abhängige als auch zeit-unabhängige, die dann der Wissenschaftsgemeinschaft für die weitere Verwendung in Modellen zur Verfügung gestellt werden. Die hier vorgeschlagenen Studien werden die bereits erfolgreich an LACIS während INUIT-1 durchgeführten Arbeiten ergänzen, da die Arbeiten in INUIT-1 stärker auf die Untersuchung reiner Mineralstäube und reiner biogener Substanzen hinzielten. Die Untersuchung von komplexeren und entsprechend mehr atmosphärenrelevanten Eiskeimen wird signifikant dazu beisteuern, atmosphärische Eiskeimbildung generell besser zu verstehen, und die entsprechenden Beiträge von mineralischen und biogenen Substanzen zu quantifizieren.
The basidiomycete Armillaria mellea s.l. is one of the most important root rot pathogens of forest trees and comprises several species. The aim of the project is to identify the taxa occurring inSwitzerland and to understand their ecological behaviour. Root, butt and stem rots caused by different fungi are important tree diseases responsible for significant economic losses. Armillaria spp. occur world-wide and are important components of many natural and managed forest ecosystems. Armillaria spp. are known saprothrophs as well as primary and secondary pathogens causing root and butt rot on a large number of woody plants, including forest and orchard trees as well as grape vine and ornamentals. The identification of several Armillaria species in Europe warrants research in the biology and ecology of the different species. We propose to study A. cepistipes for the following reasons. First, A. cepistipes is dominating the rhizomorph populations in most forest types in Switzerland. This widespread occurrence contrasts with the current knowledge about A. cepistipes, which is very limited. Second, because the pathogenicity of A. cepistipes is considered low this fungus has the potential for using as an antagonist to control stump colonising pathogenic fungi, such as A. ostoyae and Heterobasidion annosum. This project aims to provide a better understanding of the ecology of A. cepistipes in mountainous Norway spruce (Picea abies) forests. Special emphasis will be given to interactions of A. cepistipes with A. ostoyae, which is a very common facultative pathogen and which often co-occurs with A. cepistipes. The populations of A. cepistipes and A. ostoyae will be investigated in mountainous spruce forests were both species coexist. The fungi will be sampled from the soil, from stumps and dead wood, and from the root system of infected trees to determine the main niches occupied by the two species. Somatic incompatibility will be used to characterise the populations of each species. The knowledge of the spatial distribution of individual genets will allow us to gain insights into the mode of competition and the mode of spreading. Inoculation experiments will be used to determine the variation in virulence expression of A. cepistipes towards Norway spruce and to investigate its interactions with A. ostoyae.
Web Feature Service (WFS) der Übersichtskarte über normierte Bodenrichtwerte auf Bruttobaublöcke bezogen für Hamburg Zur genaueren Beschreibung der Daten und Datenverantwortung nutzen Sie bitte den Verweis zur Datensatzbeschreibung.
The agricultural sector has experienced substantial structural changes in the past and faces continuing adjustments in the future. The implications of structural change are not only relevant for the sector itself but have broader social, economic and environmental consequences for a region. An understanding of this process is required in order to assess how (agricultural-) policy affects or, if a specific social outcome is desired, can influence this development. A common approach to gain understanding of the process is to model structural change as a Markov process. One problem in the analysis of structural change in the EU is that farm level (micro) data is rarely available such that inference about behaviour of individual farms has to be derived from aggregated (macro) data. Recently, the generalized cross entropy estimator gained popularity in this context since it allows considering prior information such that the often underdetermined 'macro data' Markov models can be estimated. However, the way prior information is considered is also the greatest drawback of the approach. Therefore, the project aims to develop a Bayesian framework as an alternative estimator that allows to consider prior information in a more efficient and transparent way. The project will further provide an evaluation of the statistical properties of the estimator as well as an exemplifying application analyzing the effects of single farm payments on agricultural structural change in the EU.
Die Erdatmosphäre unterliegt komplexen chemischen und dynamischen Prozessen, und eine genaue Kenntnis der Vertikalverteilung von Spurengasen und Aerosolen ist von größter Bedeutung für ein tiefgreifendes Verständnis des atmosphärischen Systems. Fernerkundungsmessungen sind bestens geeignet zur Bestimmung der atmosphärischen Vertikalstruktur. Boden- flugzeug- und satellitengebundene Fernerkundungsmessungen ermöglichen eine berührungslose Messung der atmosphärischen Zusammensetzung. Insbesondere stellt die Multi-Axiale Differentielle Absorptionsspektroskopie (MAX-DOAS) eine vielseitige und kostengünstige Methode zur Bestimmung der Vertikalverteilung zahlreicher Spurengase sowie von Aerosolen. Im Rahmen des beantragten Projektes wird ein neuartiger Auswertealgorithmus entwickelt, der eine vollständige Ausschöpfung des Informationsgehaltes von MAX-DOAS Streulichtmessungen zum Ziel hat. Im Gegensatz zu bisherigen Algorithmen erfolgen hierbei DOAS-Auswertung und Bestimmung des Vertikalprofils in einem einzigen Schritt. Von dieser gleichzeitigen Bestimmung von Vertikalprofilen von Spurengasen und Aerosolen direkt aus den gemessenen spektralen Radianzen erwarten wir eine signifikante Erhöhung des Gesamtinformationsgehaltes. Eine Simulation der breitbandigen spektralen Struktur, die in der traditionellen DOAS Analyse ignoriert wird, sowie eine explizite Modellierung der Rotations-Ramanstreuung (Ring-Effekt) liefern zusätzliche Informationen über den Zustand der Atmosphäre. Eine Kopplung eines T-Matrix- und/oder Mie-Streumodells an ein Strahlungstransportmodell ermöglicht in ähnlicher Weise wie bestehende Algorithmen für Aeronet Sonnenphotometermessungen die Bestimmung von mikrophysikalischen Aerosoleigenschaften, wie z.B. Größenverteilung und komplexer Brechungsindex, von Messungen im solaren Almukantarat. Dieser Algorithmus dient als Basis für eine eingehende Untersuchung des Gesamtinformationsgehaltes von MAX-DOAS Messungen bezüglich Spurengasen, Aerosolextinktion sowie mikrophysikalischen Aerosoleigenschaften. Messungen mittels eines polarisationssensitiven MAX-DOAS (PMAX-DOAS) Instruments, welches im Rahmen des Projektes entwickelt wird, ermöglichen eine weitere Erhöhung des Informationsgehaltes von Streulichtmessungen. Messungen des Himmelslicht bei verschiedenen Ausrichtungen eines rotierbaren Polarisationsfilters ermöglichen eine Rekonstruktion des Stokesvektors, und polarisationsabhängige Messungen der Intensität, der Spurengassäule sowie des Ringeffektes führen zu einer signifikanten Erhöhung der Genauigkeit von Aerosol- und Spurengasbestimmung. Zu einer vollständigen Nutzung des Informationsgehaltes von PMAX-DOAS-Messungen wird der Auswertealgorithmus auf der Basis eines vektorisierten Strahlungstransportmodells, das die Simulation des gesamten Stokes-Vektors ermöglicht, entwickelt.
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.
For surface soils, the mechanisms controlling soil organic C turnover have been thoroughly investigated. The database on subsoil C dynamics, however, is scarce, although greater than 50 percent of SOC stocks are stored in deeper soil horizons. The transfer of results obtained from surface soil studies to deeper soil horizons is limited, because soil organic matter (SOM) in deeper soil layers is exposed to contrasting environmental conditions (e.g. more constant temperature and moisture regime, higher CO2 and lower O2 concentrations, increasing N and P limitation to C mineralization with soil depth) and differs in composition compared to SOM of the surface layer, which in turn entails differences in its decomposition. For a quantitative analysis of subsoil SOC dynamics, it is necessary to trace the origins of the soil organic compounds and the pathways of their transformations. Since SOM is composed of various C pools which turn over on different time scales, from hours to millennia, bulk measurements do not reflect the response of specific pools to both transient and long-term change and may significantly underestimate CO2 fluxes. More detailed information can be gained from the fractionation of subsoil SOM into different functional pools in combination with the use of stable and radioactive isotopes. Additionally, soil-respired CO2 isotopic signatures can be used to understand the role of environmental factors on the rate of SOM decomposition and the magnitude and source of CO2 fluxes. The aims of this study are to (i) determine CO2 production and subsoil C mineralization in situ, (ii) investigate the vertical distribution and origin of CO2 in the soil profile using 14CO2 and 13CO2 analyses in the Grinderwald, and to (iii) determine the effect of environmental controls (temperature, oxygen) on subsoil C turnover. We hypothesize that in-situ CO2 production in subsoils is mainly controlled by root distribution and activity and that CO2 produced in deeper soil depth derives to a large part from the mineralization of fresh root derived C inputs. Further, we hypothesize that a large part of the subsoil C is potentially degradable, but is mineralized slower compared with the surface soil due to possible temperature or oxygen limitation.
Soil structure determines a large part of the spatial heterogeneity in water storage and fluxes from the plot to the hillslope scale. In recent decades important progress in hydrological research has been achieved by including soil structure in hydrological models. One of the main problems herein remains the difficulty of measuring soil structure and quantifying its influence on hydrological processes. As soil structure is very often of biogenic origin (macropores), the main objective of this project is to use the influence of bioactivity and resulting soil structures to describe and support modelling of hydrological processes at different scales. Therefore, local scale bioactivity will be linked to local infiltration patterns under varying catchment conditions. At hillslope scale, the spatial distribution of bioactivity patterns will be linked to connectivity of subsurface structures to explain subsurface stormflow generation. Then we will apply species distribution modelling of key organisms in order to extrapolate the gained knowledge to the catchment scale. As on one hand, bioactivity influences the hydrological processes, but on the other hand the species distribution also depends on soil moisture contents, including the feedbacks between bioactivity and soil hydrology is pivotal for getting reliable predictions of catchment scale hydrological behavior under land use change and climate change.
Iron(III) (hydr)oxide-organic associations in soils have been recognized to play an important role in the biogeochemical cycling of iron, carbon, and of nutrients like phosphate. In temporarily moist or water-logged soils such associations can form via the coprecipitation of dissolved organic matter (OM) with Fe(III) (hydr)oxides (FHOs). At present, it is generally unknown which factors control the formation and composition of Fe(III)-OM coprecipitates and how the structural properties translate into the cycling of the FHO and OM component involved. The objectives of the project are thus to elucidate (i) the structural properties of Fe(III)- OM coprecipitates under different environmental conditions, (ii) the subsequent stability of Fe(III)-OM coprecipitates against dissolution under both oxic as well as anoxic conditions, (iii) the changes in Fe(III)-OM coprecipitate composition upon redox oscillations, and (iii) their cumulative effects on oxyanion sorption. To achieve these goals, various batch experiments will be conducted. By using multiple analytical tools, this project will gain a fundamental understanding of the abiotic and biotic controls on the formation, structure, and biogeochemical reactivity of Fe(III)-OM coprecipitates in acidic and neutral temporarily moist soils and soils subject to redox oscillations.
Periods of extreme geomagnetic change such as geomagnetic excursions have frequently occurred throughout geological time. Characterizing their behaviour is essential for a full understanding of the geodynamo and the interaction of Earths magnetic field and the space environment. We propose to model the global behaviour of Earths magnetic field between 10 and 50 ka using palaeomagnetic data. During this time the geomagnetic field showed significant variability in direction and intensity, including two well documented excursions: Laschamp and Mono Lake. No model currently exists that spans the total length of this time period, yet this period could provide great insights into the geodynamo. The ultimate goal of the project is to synthesize the results from our empirical modelling with those from numerical dynamo simulations, so that a deeper physical understanding of geodynamo processes can be gained. We will compile all sedimentary and volcanic palaeomagnetic data coupled with geochronological data spanning this period. This data will be added to a community available database along with all rock magnetic and sedimentological metadata. This will allow a detailed assessment of the data used in the modelling. Low quality palaeomagnetic data and erroneous age models may distort geomagnetic field structures generated by our new model and it is a key objective of this study to assess the fidelity of the palaeomagnetic and chronological data included in the modeling. Using this data we will construct a temporally continuous global spherical harmonic geomagnetic field model through a regularized least squares inversion of the data using spherical harmonics in space and cubic B splines in time. This model will enable assessment of the geomagnetic at the core-mantle boundary, the Earths surface and at elevated altitudes. Our key scientific objective is to determine where excursions fit into the spectrum of geomagnetic field variations and how the geodynamo processes that generate excursions differ from those that produce secular variation and reversals.
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