Although global pesticide use increases steadily, our field-data based knowledge regarding exposure of non-target ecosystems is very restricted. Consequently, this meta-analysis will for the first time evaluate the worldwide available peer-reviewed information on agricultural insecticide concentrations in surface water or sediment and test the following two hypotheses: I) Insecticide concentrations in the field largely exceed regulatory threshold levels and II) Additional factors important for threshold level exceedances can be quantified using retrospective meta-analysis. A feasibility study using a restricted dataset (n = 377) suggested the significance of the expected results, i.e. an threshold level exceedance rate of more than 50Prozent of the detected concentrations. Subsequent to a comprehensive database search in the peer-reviewed literature of the past 60 years, analysis of covariance with the relevant threshold level exceedance as the continuous dependent variable (about 10,000 cases) will be performed and the impact of significant predictor variables will be quantified. Parameters not yet considered in pesticide exposure assessment will be included as independent variables, such as compound class, environmental regulatory quality, and sampling design. The simultaneous presence of several insecticide compounds as a well as their metabolites will also be considered in the evaluation. The present approach may provide an innovative and integrated view on the potential environmental side effects of global high-intensity agriculture and in particular of pesticides use.
In hydrology, the relationship between water storage and flow is still fundamental in characterizing and modeling hydrological systems. However, this simplification neglects important aspects of the variability of the hydrological system, such as stable or instable states, tipping points, connectivity, etc. and influences the predictability of hydrological systems, both for extreme events as well as long-term changes. We still lack appropriate data to develop theory linking internal pattern dynamics and integral responses and therefore to identify functionally similar hydrological areas and link this to structural features. We plan to investigate the similarities and differences of the dynamic patterns of state variables and the integral response in replicas of distinct landscape units. A strategic and systematic monitoring network is planned in this project, which contributes the essential dynamic datasets to the research group to characterize EFUs and DFUs and thus significantly improving the usual approach of subdividing the landscape into static entities such as the traditional HRUs. The planned monitoring network is unique and highly innovative in its linkage of surface and subsurface observations and its spatial and temporal resolution and the centerpiece of CAOS.
The formation of biogeochemical interfaces in soils is controlled, among other factors, by the type of particle surfaces present and the assemblage of organic matter and mineral particles. Therefore, the formation and maturation of interfaces is studied with artificial soils which are produced in long-term biogeochemical laboratory incubation experiments (3, 6, 12, 18 months. Clay minerals, iron oxides and charcoal are used as major model components controlling the formation of interfaces because they exhibit high surface area and microporosity. Soil interface characteristics have been analyzed by several groups involved in the priority program for formation of organo-mineral interfaces, sorptive and thermal interface properties, microbial community structure and function. Already after 6 months of incubation, the artificial soils exhibited different properties in relation to their composition. A unique dataset evolves on the development and the dynamics of interfaces in soil in the different projects contributing to this experiment. An integrated analysis based on a conceptual model and multivariate statistics will help to understand overall processes leading to the biogeochemical properties of interfaces in soil, that are the basis for their functions in ecosystems. Therefore, we propose to establish an integrative project for the evaluation of data obtained and for publication of synergistic work, which will bring the results to a higher level of understanding.
The investigation of high-silica rhyolitic rocks collected in the recent ICDP drilling from the Snake River Plain (SRP) volcanic province (western United States) as well as rocks from the adjacent rhyolitic complexes offers a unique opportunity to track the evolution of magma storage conditions in time and space in the 'Yellowstone hotspot' intracontinental volcanic province. The application of various geothermometers which can be used to determine pre-eruptive temperatures show a general trend indicating a general decrease of temperature over the last 16 Ma. However, the depth (or pressure) of the magma chambers is difficult to constrain and remains mainly unknown because the mineral assemblage in the rhyolitic systems is not suitable for geobarometry. As an alternative to mineral compositions, the silica content of rhyolitic melts can be used to constrain pressure, provided that the silicate melts have cotectic compositions (melts coexisting with quartz and feldspar), which is the case for most SRP rhyolites. From studies in synthetic systems, it is well known that the silica content of cotectic melts decreases with increasing pressure and that it may be used as barometer in pressure ranges of ca 1000 - 50 MPa. However, the evolution of silica content with pressure is not calibrated for natural systems containing up to 2 wtProzent Cao and 4 wtProzent FeO. In this study, we plan to determine the role of pressure on the silica content of cotectic melts compositions relevant for SRP compositions. The experimental data are crucial to interpret the natural glass compositions (matrix glass and glass inclusions) analyzed in the ICDP core samples and will be used to extract quantitative information on the depth of magma storage prior to eruption. The dataset obtained from various eruptive events (samples from ICDP drillings and other SRP rhyolites) will be used to check if there is an evolution of the depth of magma storage over the lifetime of the 'Yellowstone hotspot' in the last 16 Ma and if there is a correlation between the pre-eruptive pressure, the volume of erupted material, the temperature (or differentiation level) and the water activity of magmas. This study will be conducted in close cooperation with other U.S. groups who are in charge of the analysis of ICDP rhyolitic samples. It is emphasized that the experimental database obtained in this project can also be applied to other case studies (high silica rhyolites, A-type granites).
We intend to investigate the molecular mechanisms of mineral nutrient dependent poplar physiology with special focus on potassium. This will be accomplished using two different approaches. 1. Molecular biology: We will study the regulation of ion channels and transporters by different environmental conditions, such as the effect of nutrition, salt, hormonal action, cold and drought during wood production and the dormancy-growth transitions. Phenotype analysis of transporter sense/antisense plants will be used to gain insights into the role of the transporters in tree physiology. On the basis of a laser-micro-dissection system, we will be able to prepare cDNA of distinct cell types and generate subtractive cDNAs to determine genes, specific for the differentiation of vessels and bast fibers. 2. Electrophysiological investigations: We will compare the functional properties of the transporters. Ion-fluxes and transporters, involved in cambial activation will be characterized in vivo and in vitro. The response to changes in e.g. the extracellular medium in vitro, will provide a measure for the regulation of ion transport by apoplastic factors in vivo. Based on this data sets we should be able to establish a model on the seasonal fluxes of potassium in relation to the transporter properties and dynamics in the context of tree physiology in general and xylogenesis in particular.
Temperatures in Switzerland increased about 0.57 C over the last three decades and climate models predict that this increase will continue during the 21st century and beyond. Accompanied by changes in the water supply due to the expected increase in the frequency and intensity of heavy precipitation and/or drought events, these effects will strongly force changes in forest productivity, spatial distribution of tree species, and changes in the species composition within forests. Projections of the future dimensions and interactions of these effects require detailed understanding of short and long-term changes in eco-physiological responses to past and present climate variation. Stable isotopes in tree rings have become a significant tool in obtaining retrospective insight into the plant physiological response to climate and other environmental variables. The increasing number of isotope records, however, also highlights important unsolved questions and current limitations of this tree-ring parameter. Obviously, an improved understanding of the mechanisms leading to variations in the tree's internal carbon and water cycle in relation to climate, soil moisture conditions, transpiration and expansion of the root system is urgently needed. ISOPATH aims to decipher the origin and variability of the isotopic signal in the tree rings of two alpine species, frequently used in climate reconstructions, and to understand the environmental and physiological information encoded. We will develop weekly resolved records of carbon and oxygen isotopes in xylem and needle water, needle sugars, phloem sugars and stem wood/cellulose of two physiologically differing species (larch and spruce) growing under varying temperature, soil moisture and relative humidity conditions. Those data will be related to a large suite of external variables including precipitation and soil water, temperature, and vapour pressure deficit. We act (i) on a spatial scale by following the complete pathway of stable isotopes from the atmosphere into the tree ring under varying environmental conditions and (ii) on a temporal scale by studying seasonal cycles of the isotope signals in all these different components, covering four growth seasons (2008-2011). This unique dataset in terms of length, resolution and number of measured variables will be used to test and improve advanced models for isotope fractionation at the leaf level and in the tree ring, in relation to species-specific traits, temperature and soil moisture conditions. The measured and modelled isotope signatures will allow to predict plant physiological adaptation in the alpine environment to climate change of the 21st century.
Quantitative Precipitation Forecast (QPF) is one of the major challenges in numerical weather prediction (NWP). This is true for QPF ranging from synoptic-scale to small-scale convection. The main goal of this proposal is to improve the short-range QPF on scales of a few hundred km and a few hours. To achieve a significant improvement of QPF on these scales the atmospheric variables, which are representing the pre-convective conditions, need to be determined. Hence an innovative combination of data assimilation techniques and observations is proposed. Within this project, 4D water vapour, as well as wind and cloud data are considered. The focus is on advanced observing systems with high future potential such as GPS, lidar, passive remote sensing from geostationary satellites as well as novel in-situ sensors. Different state-of-the-art assimilation techniques will be compared to find the optimal approach to improve QPF. After the development of suitable observation operators, the optimal use of advanced remote sensing systems will be investigated using various Observing System Experiments (OSE's) and Observing System Simulation Experiments (OSSE's). To quantify the success, model independent data sets inferred from MSG/radar, GPS, and an innovative sounding system will be used for validation.
One unsolved problem of the micrometeorological community is the unclosed energy balance when its components are independently measured in the field. This so-called energy balance closure gap was investigated with focus on sinks and sources (storage change terms) and on the uncertainties involved in the estimation of the available energy. The second main topic was the assessment of the non-turbulent fluxes of sensible heat and latent heat as well as the horizontal turbulent flux in case of sensible heat. These fluxes are commonly neglected as their assessment is difficult. The third main point was the comparison of advective fluxes of sensible heat and carbon dioxide with the aim to facilitate an easier assessment of the advective fluxes of carbon dioxide. Analyses were based on the ADVEX- and the MORE II-dataset. For the investigated sites it could be shown that the energy balance closure improved when the storage terms were carefully considered. An inspection of the uncertainties involved in the available energy revealed that these uncertainties cannot explain the lack of energy balance closure alone. An inclusion of the non-turbulent advective fluxes of latent heat and sensible heat changed the corresponding budgets and improved the energy balance closure partly. However, residuals did not vanish. The horizontal turbulent flux divergence of sensible heat turned out to be negligible for the investigated site and time period. The comparison of the non-turbulent advective fluxes of sensible heat and carbon dioxide showed that advective fluxes of both scalars are larger during night than during day and that they both share a considerable scatter. On a mean diurnal basis, the advective fluxes of sensible heat and carbon dioxide turned out to be of opposite sign especially during night.
Understanding the drivers behind the loss of biodiversity currently observed is of major importance in the context of the global change discussion. For studies of biodiversity at broad spatial scales, satellite remote sensing is the premier source of information, as it is uniquely capable of covering large areas of the Earth at high temporal resolution. The underlying assumption is that satellite-derived geophysical surface parameters, such as vegetation greenness, are related to biodiversity. For that purpose, concepts such as the Dynamic Habitat Index (DHI) were recently developed. The DHI combines information on the overall greenness, the base level of vegetation cover, and vegetation seasonality at a certain location. By comparing the annual DHI with a long term mean, areas undergoing disturbances or recovery events can be delineated, which are indicative of changes in species composition and diversity. The concept of the DHI was developed for data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) post-2000. However, for climate change impact studies a longer time series is desirable. The only sensor system suitable for such applications is the Advanced Very High Resolution Radiometer (AVHRR), which has been in orbit on various platforms since the early 1980ies. The purpose of this project was to develop a methodology to derive long term information on habitat conditions at continental scales based on historical satellite data. In particular, the goal was to adopt the principle of the DHI as developed for the MODIS sensor to an AVHRR archive at 1 km spatial resolution over Canada and to analyze long term variations in the DHI. In a first project phase, an AVHRR data set of vegetation greenness, generated in the framework of the project, was validated against the reference MODIS product. The results demonstrated a very good agreement between both data sets for a wide range of vegetation types and on various spatial and temporal scales. A historical baseline of habitat conditions post-1987 based on the DHI was subsequently generated based on the long term AVHRR data. The analysis of the DHI showed that certain areas, particularly northern parts of the Province of Quebec as well as southwestern Canada, experienced significant changes over the past two decades, which may have had significant impacts on species diversity and abundance in these areas. In the future, the methods developed in the framework of this project may be used to obtain information on long term variations in habitat conditions in areas covered by other historical satellite archives, e.g., for Europe based on an AVHRR archive hosted at the University of Bern.
Satellite measurements strongly contribute to the understanding of the processes related to stratospheric ozone loss, e.g. by global and long term monitoring of ozone and its depleting substances. For instance, measurements performed in limb geometry by SCIAMACHY on ENVISAT largely improved the knowledge about the vertical distribution of species like BrO and OClO only recently. However, there are still important open questions, like e.g. the chlorine activation processes on different kinds of aerosols and polar stratospheric clouds. Also, the role of very short lived species in the stratospheric bromine budget or the effects of a possible enhancement of the Brewer-Dobson circulation are not fully understood.Globally, the vertical distribution of ozone depleting species varies significantly in space and time due to solar illumination, atmospheric chemistry and transport. Especially strong gradients occur near the twilight zone or across stratospheric transport barriers (polar vortex boundary, subtropical transport barriers). These regions are of particular importance for chemistry and transport of the lower stratosphere and upper troposphere, since they separate air masses on large scales but also enable exchange between them.Standard 1-D profile retrievals, which assume horizontal homogeneity, result in large systematic biases due to neglecting the effect of horizontal gradients on the measurement. We propose to develop, improve and apply a tomographic profile retrieval algorithm, which optimally combines the information provided by the SCIAMACHY limb and nadir measurements. An improved global dataset of 3D stratospheric profiles for NO2, BrO and OClO for the 10 years of the SCIAMACHY mission (2002-2012) will be developed, compared to atmospheric chemistry simulations and applied to selected questions of atmospheric science. The dataset developed in this project will be very useful for investigating the complex interplay of stratospheric chemistry and transport processes, and will help to reduce the uncertainties in the distribution of ozone depleting species, in particular for regions with large horizontal inhomogeneity.