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.
Soil moisture - the water stored in soil within reach of the plants - is a crucial parameter for a large number of applications. Consequently, the field of microwave remote sensing of soil moisture has been an important research topic since the 1970s. But only in the last few years significant progress towards operational soil moisture services has been made. This progress became possible due to advances in sensor technology and new algorithmic approaches. With the improved algorithms it has been possible to derive soil moisture from existing operational microwave sensors. The first global soil moisture dataset derived from ERS-1/2 scatterometer measurements was released in 2002. The first near-real-time operational soil moisture service was started by EUMETSAT in May 2008 based on METOP ASCAT, which is the successor instrument of the ERS-1/2 scatterometer. Austria has made important contributions to these developments. The algorithms for retrieving soil moisture from the C-band scatterometers on board of ERS-1/2 and METOP have been developed by the Vienna University of Technology (TU Wien). Within EUMETSAT's Satellite Application Facility in Support to Operational Hydrology and Water Management (Hydrology SAF) the Austrian meteorological service (ZAMG) coordinates the soil moisture activities and is responsible for building up operational services for value-added METOP ASCAT soil moisture products. The overall goal of the proposed project is to advance the use of soil moisture services based on METOP ASCAT and complementary satellite systems, most importantly SMOS and ENVISAT ASAR, by extending the Hydrology SAF products to Africa and Australia, carrying out extensive calibration and validation (Cal/Val) activities and by developing novel water hazards applications. The considered applications are weather forecasting, drought and yield monitoring, hydrologic prediction, epidemiological modelling, climate change, desertification monitoring and societal risks assessment. A project of comparable thematic focus and breath has not been proposed before. It is expected that the interdisciplinary cooperation of specialists from different fields will lead to important scientific innovations that will promote a wide use of satellite technology in water hazards applications.
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.
Farm households, whose living standard largely depend on the successful management of natural resources, have a low per capita income and are in danger of further impoverishment due to unsustainable resource management. Investigations in the first phase confirmed the hypothesis. A great number of farms were analyzed and clustered in representative types in both countries. Sustainability was measured using a sustainability index, which indicates tremendous environmental effects and variation between individual farms and ethnic groups.Sub-project G1.1 will follow three major tasks. The first is to evaluate sustainability strategies on the farm and farming system level, as it was done in the previous phase, but on the basis of a significantly extended data base. The second is to aggregate farm household data to the regional level. For this, a comparative-static approach is chosen. The third is to develop a multi-agent-based simulation model. Multi-agent simulation models (MAS) as well as GIS-tools are gaining increasing importance as tools for simulating future agriculture resource use, since they allow the integration of a wide range of different stakeholder's perceptions. It becomes possible to simulate the dynamic effects of changing land use patterns, environmental policy options, and technical innovation together with environmental constraints and structural change issues. The MAS approach is used to model heterogeneous farm-household and political decision makers perspectives by capturing their socio-economic, environmental, and spatial interactions explicitly. The integration of economic and spatial processes facilitates the consideration of feedback effects and the efficient use of scarce land resources. The simulation runs of the model will be carried out with a socio-economic and GIS data set, which is provided by the previous project phase in the attempt to generate effective ways of land use resource management. Land use efficiency is strongly influenced by the overall land allocation policy analyzed in project F1. Therefore, this is an important area further integrated research using MAS in combination with GIS as modeling tools.To achieve a continuous integration of results in the best possible way, a computer-based discussion/communication platform is developed. This serves as the conceptual basis for the development of the final multi-agent simulation model. Results of the discussion/communication platform and the agent-based simulation model will continuously be passed on to downstream sub-projects to be integrated into the ongoing research activities.
Objective: eMOTION aims to specify a Europe-wide multi-modal traffic information service that offers real time information for road and public transport users by means of on-trip-devices like PDA/Smart Phones or in-car-systems. The project develops policies and scenarios for a Europe-wide information service integrating content providers, service operators/providers with different legal status, coming from public and commercial sectors all over Europe. Policies and scenarios cover legal/organisational aspects as well as implementation and data safety policies, and meet in an organisational and legal framework for the service architecture and finally in a proof-of-the-concept. A system architecture with web-based application services calculates the information request of the user. The data content is organised in distributed databases providing the information on request. To enable distributed data management data sets will use common data protocols and interfaces.
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.
Das räumlich explizite klimasensitive 3D-Waldökosystemmodell PICUS wurde kürzlich durch ein biogeochemisches Bodenmodul (TRACE) zur Simulation von C- und N-Kreisläufen ergänzt und steht derzeit in einer anhand von Literaturdaten und Expertenwissen parametrisierten Version für Szenarioanalysen zur Verfügung. Ziel des gegenständlichen Projektes ist es, das ergänzte Modell PICUS v1.41 anhand von Daten von Dauerversuchsflächen des BFW (unbehandelte Parzellen von Düngungsversuchen mit Beobachtungszeiträumen von bis zu 35 Jahren) zu validieren um es in einer überprüften und zuverlässigen Version für die Analyse von Konzepten zur nachhaltigen Waldbewirtschaftung zur Verfügung zu stellen. Für die hier beschriebenen Experimente konnten die Versuchsflächen Grottenhof, Helfenberg und Karlstift verwendet werden. Insgesamt kann festgestellt werden, dass die letztendliche Bereitstellung der Vergleichswerte für C und N Pools für die Versuchsflächen zahlreiche Probleme aufwirft, deren Lösung meist mit zusätzlicher Unsicherheit in den Vergleichswerten verbunden ist. Die Ergebnisse der Vergleiche von simulierten und beobachteten Systemgrößen waren für die oberirdische Biomasseentwicklung (Bestandesparameter) i.A. sehr zufriedenstellend. Bei den Boden-Pools für C und N konnte in den meisten Fällen der allgemeine Entwicklungstrend reproduziert werden. Details (Form der Ab- bzw. Zunahme über die Beobachtungsperiode, absolute Größenordnung der Veränderungen in den Poolgrößen) aber von PICUS nicht immer zufriedenstellend simuliert werden konnte. Grund dafür ist vor allem, dass kurzfristige Trendumkehren in C und N Pools von Bodenmodellen aufgrund deren Konzeption i.A. nicht simuliert werden können, soferne keine exogenen Faktoren den dafür benötigten Impuls liefern. Dies kann zum Beispiel durch Streuinput oder durch Veränderungen in der N-Deposition bewerkstelligt werden. Berücksichtigt man die generische Initialisierung und Parameterisierung von PICUS v1.41, dann sind die Ergebnisse als vielversprechend zu bezeichnen. Bei standorts- und parzellenspezifischen Kalibrierungsschritten ist eine noch bessere Anpassung der simulierten and die beobachteten C und N Pools zu erwarten. Damit einhergehen würde allerdings die Möglichkeit, PICUS v1.41 für großflächige regionale und nationale Simulationsstudien einzusetzen. Als Folgerung aus diesen Erkenntnissen wird demnächst versucht werden, den Initialisierungansatz für Erhebungspunkte der Waldinventur weiter zu verbessern.
Working group 7 (Agriculture) under the European Climate Change Programme has so far mainly dealt with mitigation potentials of GHG. A thorough integrated economic and environmental assessment in the area of agriculture and sinks has not yet been carried out. In order to support the international negotiation process and for the development of good policies the Integrated Sink Enhancement Assessment (INSEA) project's objective is to develop an analytical tool to assess economic and environmental effects for enhancing carbon sinks in agriculture and forestry. The approach is centered on spatially explicit databases that will allow the calculation of 'cost-landscapes' taking on an engineering approach to integrated costs computation of additional sink enhancement measures and negative emission technologies. The various model structures will be applied to detailed European data sets and less detailed global data sets assessing the marginal abatement cost and long-term scenarios of sink enhancement measures. Concise policy conclusions from the modeling exercise will aim at supporting the implementation of the Kyoto Protocol commitments as well as post Kyoto negotiations. In the proposal we advocate a spatially explicit approach that is motivated by the fact that LULUCF activities are by their very nature spatial entities and aggregate non-spatial treatment could, according to our experience, lead to serious biases in the assessment. Furthermore, we propose not only a simple and easily tractable static and deterministic approach for cost calculations, but also more comprehensive, dynamic, and uncertainty (risk)-based treatments. We believe that such a multidimensional approach is necessary since ecosystems are more complicated and complex in their responses and therefore robustness and consistency across a variety of decision rules will guarantee sustainable management of this natural resource.