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.
Objective: Integrated assessment and energy-economy models have become central tools for informing long-term global and regional climate mitigation strategies. There is a large demand for improved representations of complex system interactions and thorough validation of model behaviour in order to increase user confidence in climate policy assessments. ADVANCE aims to respond to this demand by facilitating the development of a new generation of integrated assessment models. This will be achieved by substantial progress in key areas where model improvements are greatly needed: end use and energy service demand; representation of heterogeneity, behaviour, innovation and consumer choices; technical change and uncertainty; system integration, path dependencies and resource constraints; and economic impacts of mitigation policies. In the past, methodological innovations and improvements were hindered by the unavailability of suitable input data. The ADVANCE project will make a large and coordinated effort to generate relevant datasets. These datasets, along with newly developed methodologies, will be made available to the broader scientific community as open-access resources. ADVANCE will also put a focus on improved model transparency, model validation, and data handling. A central objective of ADVANCE is to evaluate and to improve the suitability of models for climate policy impact assessments. The improved models will be applied to an assessment of long-term EU climate policy in a global context, and disseminated to the wider community. The ADVANCE consortium brings together long-standing expertise in integrated assessment and energy-economy modelling with a strong expertise in material flows, energy system integration, and energy service demand.
Ongoing land-use and management changes in various European mountain ecosystems may alter their role as important carbon reservoirs. For soil carbon in particular meaningful data on drivers, stocks and rates is scarce and thus predictive studies on the effect of land-use and management change on carbon stored in mountain ecosystems are highly uncertain. In addition, management is a major control on standing biomass in mountain forests but as for soil carbon, the data base is poor. Reliable data are not only needed for a more substantiated assessment of land-use and management effects on ecosystem carbon storage, but also for developing management recommendations, improved mechanistic modeling and, finally, the corresponding model application in the context of greenhouse gas reporting. The project will provide carbon stocks and accumulation rates from both measurements and modeling for typical but climatically different mountain ecosystems in four European mountain ranges. The goal of the proposed research is a quantitative understanding of carbon change rates, their drivers, the implementation of results in to models currently used for national greenhouse gas inventories and, finally, the development of management recommendations for mountain ecosystems with respect to their carbon storage function. We will (i) sample soils and forest floor from well studied experimental adjacent sites differing in land-use (grasslands, forests) as well as experimental management gradients/types within grasslands and forests and make use (ii) of already existing data sets along land-use gradients. Sites span a wide range of edaphic, management, and climatic conditions in the Balkan Mountains, the Rhodope Mountains, Rila Mountains and the Alps. Auxiliary climate data for model application are available. These data will be used to derive carbon change rates for the different activities, information on the stability of sequestered carbon and to formulate management recommendations. Radiocarbon measurements of soil and roots from various sites will be used to derive carbon turnover rates. The project builds on extensive previous experience with research projects on management, land-use and related carbon sequestration in cropland, grassland, abandonment, and forest ecosystems in the Alps and in Bulgarian mountains. The main deliverables of the project will be: Knowledge rules, transfer functions and recommendations to policy makers, Comprehensive data sets that allow for scaling up from the plot to a regional landscape level and thus to settle a close link between model validation, application, and improvement. Validated mechanistic models to be used in national greenhouse gas reporting, sector land use, land use change and forestry, and Tools for implementation of both reporting issues and management recommendations in Bulgaria and Switzerland.
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 accuracy of hydrology and weather predictions depends to a large extent on our understanding of small-scale flow phenomena at the land-atmosphere interface. The overall goal of this grant concerns improved understanding of the effects of complex alpine terrain on included field studies of air flow over steep slopes during morning and evening transition periods and thermal circulations that develop driven by differential heating on the earths surface from variations in solar heating and surface thermal properties. We have also developed improved turbulence simulations of the lower atmosphere using the immersed boundary method (IBM) and have tested our results against measurement studies in the open literature (laboratory and field). This grant has supported two PhD students (Daniel Nadeau & Marc Diebold). Nadeau was responsible for field studies and analysis of flows over steep slopes and successfully defended his PhD at the end of 2011 and is now Assistant Professor at Polytechnique in Montreal. Diebold is primarily focused on numerical simulation based upon the Large Eddy Simulation (LES) technique and is completing field campaigns (2011-2013) in the Val Ferret watershed on turbulent flow over snow covered terrain. His numerical work has focused on the implementation of new ideas in IBM and subgrid-scale (sgs) modeling. Simulation of local atmospheric flows around complex topography is of great importance for several applications in wind energy (e.g. short term wind forecasting and turbine siting and control), local weather predictions in mountainous regions and avalanche risk assessment. However atmospheric simulations around steep mountain topography remain difficult as the typical strategy used to introduce topographic elements, terrain following coordinates, becomes numerically unstable if the topography is too steep. The IBM provides a unique approach that is particularly well suited for efficient and numerically stable simulation of flows around steep terrain. To date the IBM has been used in conjunction with the EPFL-LES and tested against two unique data sets. In the first comparison, the LES was used to reproduce the experimental results from a wind tunnel study of a smooth three-dimensional hill. In the second study, we simulated the wind field around the Bolund Island, Denmark, and made direct comparisons with field measurements (this has been published recently in Boundary Layer Meteorology journal in 2013).
Warm conveyor belts (WCBs) are coherent airstreams that typically develop along cold fronts associated with extratropical cyclones. These airstreams originate in the moist subtropical marine boundary layer and ascend within 1-2 days to the upper troposphere whilst moving more than 2000 km towards the pole. They occur most frequently during winter in the western North Pacific and North Atlantic where they are responsible for the major part of precipitation. The key role of WCBs for the dynamics of the synoptic and large-scale atmospheric flow stems from their profound impact upon the tropospheric distribution of potential vorticity (PV). The coherent ascent of WCBs leads to the diabatic production of a positive PV anomaly in the lower troposphere and of a negative PV anomaly in upper-level ridges just below the tropopause. When interacting with the extratropical waveguide, these negative PV anomalies can exert a profound impact upon the downstream flow evolution. Hence a WCB can be the trigger for the amplification and breaking of an upper-level Rossby wave, which is particularly relevant in situations where Rossby wave breaking events act as precursors of high-impact weather systems (e.g., heavy precipitation in the western Mediterranean, Saharan dust storms, cold air outbreaks). Recent studies indicate that errors in medium-range numerical weather predictions might be related to the inaccurate representation of WCBs and their effect on upper-level PV. In order to advance the basic understanding of these complex, non-linear and highly important dynamical processes, this project will (i) investigate the parameters and processes that determine the intensity of a WCB, its associated PV evolution and downstream effects, (ii) assess the errors in global models' analyses and forecasts associated with the different stages of a WCB life cycle, (iii) quantify the climatological frequency of the triggering and intensification of upper-level Rossby waves by WCBs, and (iv) provide clear guidance for investigating the dynamics of WCBs within the framework of THORPEX field experiments. In three subprojects, complementary techniques will be applied in order to reach these objectives, including idealized simulations of moist baroclinic waves, real case sensitivity experiments, diagnostic investigations based upon (re-)analysis and forecast data, and a feature-based verification of WCBs in global models using independent observational datasets. In this way this project will contribute to an improved basic understanding of the dynamical effects of WCBs on the downstream evolution of upper-level Rossby waves and (high-impact) surface weather events.
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.
The Earth's climate is changing as a response to anthropogenic emissions of fossil fuels, and is very likely to do so over the next decades to centuries. The projected changes from multiple numerical climate models differ significantly, because some feedbacks and processes are poorly understood or cannot be resolved in the models. Yet a quantitative picture of the uncertainty associated with the expected changes on regional and global scales is crucial, in order to quantify impacts, and decide on adaptation and mitigation measures. The objective of this project is to assess the uncertainty in large-scale regional to global climate change projections based on the CMIP3 dataset, a collection of simulations of about twenty global climate models coordinated for the recent IPCC report. While the amount of data produced by climate models and the desire for ever more detailed projections and probabilistic information is growing rapidly, there is a lack of understanding on how to define the skill of a climate model for a forecast that in practice cannot be verified. So far, models are often averaged regardless of their ability to satisfy even basic requirements, and the community is reluctant to define a set of metrics that would seem important for a model to be credible. Also, a consensus of uncertainty in climate change projections on regional to global scales is missing. We propose to develop a framework to evaluate climate models for their suitability in predicting changes by a set of metrics that are important to be simulated correctly from a physical point of view, rather than comparing present day simulations to observations. In addition, by treating one model M as observations, statistical methods can be used to find optimal predictors and to define model weight, such that a weighted mean or a probabilistic method using the rest of the models can best predict M. The issue of common model error and model dependence will be addressed. We also propose novel methods to aggregate results in regional averages using clustering techniques, and a more flexible approach to communicating results using climate change indices. As milestones of the project, we will attempt to answer the following questions: How large are the uncertainties of model projections on different spatial and temporal scales? On what spatial scale can the current models provide robust information? How can we quantify model performance for projections, and use that to define model weight? Is a small set of 'good' models more useful than a large number of 'good' and 'bad' models? How do model dependence, common biases, and overconfidence affect projection uncertainties? How can we attach confidence to climate change indices? The proposed work combines efforts in climate research and statistics. The results will be used in improving a Bayesian hierarchical model to generate probabilistic climate change information for the spatial scales on which .