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.
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.
Die südecuadorianischen Anden beherbergen eine außergewöhnlich hohe Artenvielfalt. Viele verschiedene Umweltfaktoren beeinflussen sich auf sehr limitiertem Raum und erschaffen so einzigartige und komplexe Ökosysteme. Dieses Gebiet ist jedoch auf Grund des zunehmenden menschlichen Einflusses durch die fortschreitende Intensivierung der Landnutzung und des globalen Wandels hochgefährdet. Wir wissen nur wenig über die paläoökologische Geschichte und Landschaftsdynamik dieses Gebiets. Die Information über das warum und wie einer Veränderung von Ökosystemen ist unerlässlich für die Entwicklung innovativer Strategien für Naturschutz und im Hinblick auf zukünftige Klimaveränderungen. In der vorliegenden Studie werden palynologische Analysen aus den südecuadorianischen Anden vorgestellt, die dazu beitragen, Muster und Prozesse heutiger und vergangener Ökosysteme zu beleuchten. Eine paläoökologische Studie des Quimsacocha-Vulkanbeckens auf der östlichen Erhebung der Westkordillere der südecuadorianischen Anden deckt Klima-, Vegetations- und Brandregimeveränderungen in dieser Region seit dem frühen Holozän auf. Das mittlere Holozän war eine Zeit starker Umweltveränderungen, verursacht durch ein trockenes und wohl wärmeres Klima. Während des späten Holozäns wechselten sich mehrere Kalt-und Warmphasen ab. Brände können seit dem frühen Holozän im Gebiet verzeichnet werden. Sie könnten ein erstes Zeichen menschlichen Einflusses darstellen. Mit anderen paläoökologischen Aufzeichnungen aus den südecuadorianischen Anden verglichene multivariate Analysen decken teilweise konstrastierende Entwicklungen an den verschieden Standorten auf, die vermutlich durch die Heterogenität der Umweltfaktoren zu erklären sind. Weiterhin wurden Studien zum Verhältnis von heutigem Pollenregen mit der Vegetation in der Podocarpus Nationalpark-Region durchgeführt, um die Pollenverbreitungsmuster innerhalb der verschiedenen Vegetationstypen, prämontaner Wald, unterer Bergwald, oberer Bergwald und Páramo, zu verstehen und damit eine bessere Grundlage zur Interpretation fossiler Pollendaten zu schaffen. Ein Vergleich von Abundanz und An-/Abwesenheitsdaten von Familien als taxonomischer Einheit für Pollen- und Vegetation zeigt, dass Diversität, Verbreitung und Häufigkeiten beider Datensätze gut miteinander in Verbindung gebracht werden können. Dennoch werden die Muster durch variierende Anteile von durch Ferntransport eingetragenen Pollenkörnern sowie durch unterschiedliche Pollenproduktivität verschiedener Taxa und heterogene Windsysteme beeinflusst. Analysen der Pollenakkumulationsraten, die über drei Jahre erfasst wurden, lassen auf eine geringe inter-annuelle aber hohe räumliche Variation in den Daten schließen. (Text gekürzt)
The goal of this study was to enable a prognosis on the future rainfall conditions of the Nile Equatorial Lakes regions by delivering time-series of monthly rainfall sums for the time-period from 2021 to 2050 that can be used for all kinds of applications. One example might be the dimensioning of hydraulic structures. In these very long lasting investments, future climatic conditions have to be considered during present planning and construction.The principal sources of information on future climate conditions are General Circulation Models (GCMs). These are physically based atmospheric models that resemble a numerical weather prediction system but on a much coarser scale. This forecast cannot be perfect. Especially, it cannot predict single values, e. g. if January 2050 will be rather wet or dry, but only climatic references, i.e. state, if Januaries in general will become wetter or dryer in the future. Even if the predictions of a GCM were perfect, its output could not be used directly for hydrological purposes, due to its coarse resolution. The monthly precipitation values that are provided by the GCM present the spatially averaged precipitation over a grid cell of several thousand square kilometres. This 'block rainfall' can differ significantly from rainfall measured at the ground. Rain gauges are influenced by local effects like micro climatic conditions or orographic effects of mountain ranges that GCMs are not able to resolve.This study combined the information from different data sources. As global trend information, monthly precipitation values from two GCMs (ECHAM5 and HadCM3) were used. Three CO2-emission scenarios (A1b, A2 and B1) were considered in this data. As local ground reference observed monthly rainfall sums from several rain gauges in East Africa as well as from three reanalysis projects (Climate Research Unit, University of Delaware and GPCC) were used.At each rain gauge or observation point in the reanalysis a technique called 'Quantile-Quantile-Transformation' was applied to establish a relationship between the Cumulative Distribution Function (CDF) of the GCMs and that of the ground references during the calibration period from 1961-1990. The CDFs were fitted by non-parametric Kernel-Smoothing. To account for potential shifts in the annual cycles of GCMs and ground references, the transformations was done separately for each month.Assuming that the relation between Global Model and local response will be constant in the future, the global predictions of the GCM can be downscaled to local scale, leading to future rainfall scenarios that are coherent with observed past rainfall.Combining the data from three CO2-emission scenarios of two GCM with three reanalysis data sets, an ensemble of 18 different rainfall time-series was created for each observation point. The range of this ensemble helps to estimate the possible uncertainties in the prognosis of future monthly precipitation sums from 2021 to 2050.
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.
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.
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.
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.
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