Die Anzahl der verfügbaren Wolkenkondensationskerne (CCN) beeinflusst maßgeblich die mikrophysikalischen Wolkeneigenschaften, wie z.B. die Wolkentropfenanzahlkonzentration (CDNC) und deren Größenverteilung. CDNC und die Tropfengröße steuern sowohl die Strahlungseigenschaften als auch die Lebensdauer von Wolken. Dies wirkt sich komplex auf die Energiebilanz der Erde aus. Aktuelle Klimamodelle basieren häufig auf Annahmen über CCN Anzahlkonzentrationen und andere CCN bezogene Eigenschaften (z.B. Hygroskopizität), da für viele Regionen auf der Erde repräsentative Daten fehlen. Wenn vorhanden, handelt es sich bei diesen CCN Daten um bodengebundene Messungen, welche somit nicht - mit Ausnahme von Bergstationen - in der für Wolkenbildungsprozesse relevanten Höhe durchgeführt wurden. Für die Karibikregion wurde gezeigt, dass die bodengebundenen CCN Messungen für die gesamte marine Grenzschicht repräsentativ zu sein scheinen also auch für die Wolkenbildungsregionen. Im hier vorgeschlagenen Projekt wollen wir überprüfen, ob bodengebundene CCN Messungen auch in anderen Erdregionen repräsentativ sind für die CCN Anzahl in der Wolkenbildungsregion, und wenn ja, unter welchen Bedingungen. Dies würde die Anwendung von CCN Daten in Modellen stark vereinfachen. Dazu wird die Gültigkeit der Beobachtungen in der Karibik, in zwei gegensätzlichen Umgebungen getestet werden, einmal in einer marinen und einmal in einer kontinentalen Umgebung. Die Messkampagne zu marinen CCN soll auf den Azoren (Portugal) durchgeführt werden. Wir werden kontinuierlich verfügbare CCN Daten von der Azoren Eastern Nordatlantik (ENA) Station auf der Insel La Graciosa (auf Meereshöhe) mit Daten von der Bergstation Pico (Pico Island, 2225 m ü.d.M.) kombinieren. Ergänzend werden CCN und CDNC Messungen auf der Helikopter-Messplattform (ACTOS) durchgeführt, um die vertikale Lücke zwischen den Meeresspiegel- und Bergmessungen zu schließen. Die kontinentalen bodengebundenen CCN Messungen werden kontinuierlich an der ACTRIS Station Melpitz durchgeführt. Die vertikale CCN und CDNC Verteilung wird in Melpitz mit Hilfe eines Ballons in mehreren einwöchigen Kampagnen einmal pro Jahreszeit gemessen werden. Darüber hinaus werden wir mit Hilfe der Aerosol-Wolken-Wechselwirkungsmetrik (ACI) die in der Wolke in-situ gemessen CCN Eigenschaften (das heißt Anzahl und Hygroskopizität) mit den CDNC quantitativ verbinden. Es wird außerdem eine Sensitivitätsstudie mit einem Cloud-Parcel Model durchgeführt, welches durch die realen Messungen in der Atmosphäre angetrieben werden wird. Dies wird einen Einblick in das Übersättigungsregime von frisch gebildeten Wolken gewähren.Die CCN Daten selbst, die Erkenntnisse zu CCN Eigenschaften und ihrer vertikalen Verteilung sowie die quantitative Verbindung zwischen CCN und CDNC werden im Hinblick auf das Verständnis und die Modellierung der Wolkentropfenaktivierung sowie der mikrophysikalischen Wolkeneigenschaften von außerordentlichem Wert sein.
Das Projekt betrachtet den Zusammenhang zwischen dem Streben nach ökonomischen und ökologischen Zielen; dabei konzentriert es sich auf die Wertsteigerungspotentiale von Umweltaspekten. Das Hauptziel ist die Erstellung einer ganzheitlichen, theoretischen Konzeption. Hierbei soll zugleich ein empirischer Einblick in das Thema gewonnen werden.
Subproject 3 will investigate the effect of shifting from continuously flooded rice cropping to crop rotation (including non-flooded systems) and diversified crops on the soil fauna communities and associated ecosystem functions. In both flooded and non-flooded systems, functional groups with a major impact on soil functions will be identified and their response to changing management regimes as well as their re-colonization capability after crop rotation will be quantified. Soil functions corresponding to specific functional groups, i.e. biogenic structural damage of the puddle layer, water loss and nutrient leaching, will be determined by correlating soil fauna data with soil service data of SP4, SP5 and SP7 and with data collected within this subproject (SP3). In addition to the field data acquired directly at the IRRI, microcosm experiments covering the broader range of environmental conditions expected under future climate conditions will be set up to determine the compositional and functional robustness of major components of the local soil fauna. Food webs will be modeled based on the soil animal data available to gain a thorough understanding of i) the factors shaping biological communities in rice cropping systems, and ii) C- and N-flow mediated by soil communities in rice fields. Advanced statistical modeling for quantification of species - environment relationships integrating all data subsets will specify the impact of crop diversification in rice agro-ecosystems on soil biota and on the related ecosystem services.
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.
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.
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.
Das Hauptziel des Projekts ist die Untersuchung und die Entwicklung von Methoden nicht nur zur punktuellen, sondern auch zur flächenhaften Bestimmung der Bodenfeuchte. Zur Anwendung sollen Geländetechniken wie Time-Domain Reflectrometry (TDR), Georadar (GPR), Elektrische Widerstand (ER), Elektromagnetische Induktion (EMI) sowie GNSS Scatterometry kommen. Eine der methodischen Hauptfragen ist die Nutzung der GNSS Scatterometry zur Ermittlung der Bodenfeuchte im Feldmaßstab. Eine weitere grundlegende Forschungsfrage wird die weitere Entwicklung der elektrischen und elektromagnetischen geophysikalischen Techniken für bodenkundliche Anwendungen sein.
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.
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