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.
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.
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.
Current and future global warming will cause the degradation of mountain permafrost, which may strongly influence the stability of permafrost slopes or rock walls with potentially hazardous consequences. Due to the strong heterogeneity of both the thermal regime and the ground composition of mountain permafrost, its response to atmospheric forcing can however be highly variable for different landforms and within short distances. The spatial distribution of ice and liquid water is important for determining the sensitivity of a specific permafrost occurrence to climate change because of their large influence on the pace of temperature changes (by effects of latent heat) and their importance for geotechnical properties of the ground. Detailed knowledge of the material properties and internal structures of frozen ground is therefore an important prerequisite to determine the sensitivity of permafrost to climate change. Except for the active layer ice and water contents and their temporal and spatial variability usually cannot be measured directly. Geophysical methods are sensitive for the ice and liquid water content in the ground. With the proposed collaboration, two similar but complementary approaches to quantify the composition of the ground based on 2D sections of geophysical data will be combined for an improved determination of ice and water contents in permafrost regions. The so-called 4-phase model (4PM) is based on two simple petrophysical relationships for electrical resistivity and seismic velocity and estimates volumetric fractions of ice, water, and air within the pore volume of a rock matrix by jointly using complementary data sets from electric and seismic measurements. Due to inherent ambiguities in the model it is still restricted to specific cases and often allows only a rough estimation of the phase fractions. Major drawbacks of the current 4PM comprise the unsatisfactory discrimination between rock and ice and its under-determinedness, requiring the prescription of the porosity and further parameters. The so-called RSANN model (developed and used by the host institution) uses the technique of simulated annealing (a Monte-Carlo-type stochastic simulation approach) as an optimization tool for the integration of electrical resistivity and P-wave velocity to derive 2D sections of porosity, water saturation and volumetric water content. The simulated annealing technique allows - due to its iterative procedure - more parameters to be predicted instead of being prescribed as in the 4PM. The objective of the proposed collaboration is to combine the advantages of the two algorithms (4PM and RSANN) to overcome the shortcomings of the 4PM in order to improve the reliability of the determined ice and liquid water contents. (...)
The goal of the proposal is to explore the structure and functioning of metacommunities in ecological compensation areas at a multi-trophic level. First, we will assess the effect of plant diversity and herbivore and/or predator exclusion on metacommunity functioning in sown wildflower strips. We will document the communities inhabiting these experimental plots, paying attention at interactions between species, and with consideration of larger consumers linking these habitats with the surrounding matrix. Second, we will explore the relationship between various measures of the environment (isolation, habitat size) and descriptors of the metacommunities (diversity, composition, abundances, and productivity of various taxonomic groups, food-web structure, temporal variability, local invasions and extinctions). Third, using a high-quality dataset on quantitative food webs and the present data, we will conduct meta-analyses to test various models of community organisation (neutral models of biodiversity, species-area relationship in trophic levels, regional similarity hypothesis, food-web structure). Fourth, we will develop various models describing food-web structure and metacommunities dynamics. We will synthesize our results to develop a theory of 'meta food-webs'. Fifth, we will apply the gained knowledge to improve current agri-environment schemes. The study of species interactions in spatially structured metacommunities is comprehensive and global. As such, this project has a strong potential to provide fundamental insight into conservation biology. This project is multidisciplinary, putting together practitioners, ecologists and mathematicians, and is expected to yield important results both of fundamental and conservation relevance. We will use various methodologies to reach our goals. For the first part, we will set up an experiment with replicated sown wildflower strips where plant species richness and the abundance of major predators (foxes and birds of prey) and/or of major herbivores (voles and slugs) will be controlled (balanced incomplete block design). The other parts will rely on classical meta-analyses, multivariate statistics, and mathematical modelling. For the latter part, we will develop stochastic models to explore the dynamics of communities.
In contrast to their advances in other areas, weather forecast models have not been successful in improving the Quantitative Precipitation Forecast during the last 16 years. One reason for this stagnation is the lack of comprehensive, high-quality data sets usable for model validation as well as for data assimilation, thus leading to improved initial fields in numerical models. Theoretical analyses have identified the requirements measured data have to meet in order to close the gaps in process understanding. In field campaigns, it has been shown that the newest generation of remote sensing systems has the potential to yield data sets of the required quality. It is therefore time to combine the most powerful remote sensing instruments with proven ground-based and airborne measurement techniques in an Intensive Observations Period (IOP). Its goal is to serve as a backbone for the SPP 1167 by producing the demanded data sets of unachieved accuracy and resolution. This requires a sophisticated scientific preparation and a careful coordination between the efforts of the institutions involved. For the first time, the pre-convective environment, the formation of clouds and the onset and development of precipitation as well as its intensity will be observed in four dimensions simultaneously in a region of sufficient size. This shall be achieved by combining the IOP with international programs and by collaboration between leading scientists in Europe, US and other countries. Thus, the IOP is a unique opportunity to make Germany the setting of an international field campaign featuring the newest generation of measurement systems such as scanning radar and lidar and leading to outstanding advances in atmospheric sciences.
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.
The HGF Alliance 'Remote Sensing and Earth System Dynamics' aims at the development and evaluation of novel bio/geo-physical information products derived from data acquired by a new generation of remote sensing satellites; and their integration in Earth system models for improving understanding and modelling ability of global environmental processes and ecosystem change. The Earth system comprises a multitude of processes that are intimately meshed through complex interactions. In times of accelerated global change, the understanding and quantification of these processes is of primary importance. Spaceborne remote sensing sensors are predestined to produce bio-geo-information products on a global scale. The upcoming generation of spaceborne remote sensing configurations will be able to provide global data sets and products with unprecedented spatial and temporal resolution in the context of a consistent and systematic observation strategy. The integration of these data sets in existing environmental and climate science components will allow a new global view of the Earth system and its dynamics, initiating a performance leap in ecosystem and climate change modelling.
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).