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.
Both lakes and oceans are important for the global carbon cycle and thus the regulation of climate processes. Due to climate change and human activities, aquatic systems are subject to increasing pressure with changes already observed at multiple levels affecting their functioning. It is therefore urgent to understand the dynamic of aquatic systems, if one wants to predict their response to changing conditions. Phytoplankton, act as engineers, initiating the incorporation of terrestrial and atmospheric compounds into the food chain and driving their biogeochemical cycling. They not only respond rapidly to their environment, they also profoundly alter aquatic chemistry, affecting the reactivity, recycling, remineralisation and therefore fate of many elements. As such, phytoplankton affect the dynamics of aquatic systems with effects at both local and global scales. Phytoplankton can thus be used as sentinel to assess the dynamics and changes in aquatic systems. One of the most prominent reported controls of phytoplankton biomass, biodiversity and productivity is nutrient limitation, reported in most of the ocean and numerous lakes. Iron (Fe), nitrogen (N) and phosphorous (P) are the main limiting nutrients in aquatic systems. Nutrient limitation affects the functioning of aquatic systems and their contribution to the global carbon cycle. Despite numerous studies, the parameters controlling nutrient limitation and their accessibility to phytoplankton (viz. bioavailability) remain largely unknown. The aim of this project is to identify nutrient (Fe, N, P) limitation in different aquatic systems, and to improve our understanding of aquatic biogeochemistry - from gene expression, chemistry and bioavailability through to the impact on biodiversity under current and future conditions. The study regions include the largest lake in Western Europe, Lake Geneva; the Southern Ocean, a pivotal region for the global carbon cycle; and the Tasman Sea, one of the most sensitive regions to predicted climate change. All these regions are associated with significant socio-economical value. Here, a rigorous multi-disciplinary laboratory and field approach will be used to provide complementary data sets to shed light on how nutrients affect the biodiversity, the biogeochemical cycles of key elements and the functioning of natural systems. The laboratory approach (1) explore the mechanisms controlling nutrient biological accessibility using relevant axenic phytoplankton cultures and (2) allows the calibration and validation of biological and chemical sensors to rapidly monitor nutrient limitation in aquatic systems. In addition, field work will (1) explore the link and the seasonality between important physical, biological and chemical parameters and (2) use perturbation experiments to investigate the complexity of the link between nutrients and natural planktonic assemblages. (...)
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 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).
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.
An estimate of sediment transport rates in alluvial rivers is important in the context of erosion, sedimentation, flood control, long-term morphological assessment, etc. Extensive research during the last decades has produced a plethora of sediment transport models. Sediment transport is complex and often subject to semi-empirical or empirical treatment. Most of the sediment transport functions are based on simplified assumptions that the rate of sediment transport could be determined by one or two dominant factors, such as water discharge, average flow velocity, energy slope, and shear stress (Yang, 1996). In many practical situations prediction errors of these models are observed to be high.An alternative approach is to use data driven modelling, which is especially attractive for modelling processes about which adequate knowledge of the physics is limited, like in the case of sediment transport. Over the last decade fuzzy rule-based models have been introduced in engineering as a powerful alternative modelling tool. The fuzzy rule-based approach introduced by Zadeh (1965) is being widely utilized in various fields of engineering. It is a qualitative modelling scheme in which the system behaviour is described using a natural language (Sugeno & Yasukawa, 1993). This research focuses on the applicability of a data-driven fuzzy rule-based modelling approach in estimating sediment transport rates. It also aims at the comparison of the results of the fuzzy rule-based model with the results of other commonly utilized sediment transport functions.A number of variables play important roles in determining sediment transport capacity. These variables are: flow depth, particle fall velocity, particle diameter, flow velocity, energy or water surface slope, shear velocity, shear stress, fluid density, sediment density, stream power, unit stream power, and discharge. Additionally; size, shape, and unit weight of bed composition; morphology of bed forms and availability of sediment from source area affect sediment transport capacity. The most significant factors affecting sediment transport capacity will be identified and used for constructing a fuzzy model. The fuzzy model identification is usually carried out in two steps: (1) determining the number of fuzzy rules and their associated membership functions and (2) optimizing the fuzzy model. The fuzzy logic toolbox in MATLAB will be used for performing the fuzzy modelling.A general fuzzy system has the components of fuzzification, fuzzy rule base, fuzzy output engine, and defuzzification. Fuzzification converts each piece of input data to degrees of membership by a look-up in one or more several membership functions. Intuition, fuzzy clustering, neural networks, genetic algorithms, and inductive reasoning can be among many ways to assign membership values or functions to fuzzy variables...
Quality standards to assess the chemical status of water bodies under the Water Framework Directive are often based on a few standardized laboratory tests and fixed assessment factors for extrapolation to the field situation. If larger data sets including tests with non-standard species are available, a statistical extrapolation approach, the Species Sensitivity Distribution approach (SSD) is applied. For assessing the remaining uncertainty on the SSD, the threshold concentration derived can be compared with data from field monitoring or model ecosystem studies. Taking the priority substance Ni as an example we present the use of microcosms to test the protectiveness of the quality standard derived from laboratory toxicity tests. The study was conducted in 14 microcosms including a natural sediment layer and an overlaying water volume of 750 L located in a greenhouse. After a pre-treatment period for establishing a diverse aquatic community of phytoplankton, zooplankton, periphyton and snails, Ni solution was added to reach concentrations of 6, 12, 24, 48 and 96 micro g Ni/L in two microcosms each. Four microcosms served as untreated controls. To achieve the intended constant exposure over the test period of four months, Ni concentrations were frequently determined in the microcosms and appropriate amounts of nickel solution were added mostly on a daily basis. Parameters known to affect Ni toxicity, i.e. water hardness, pH, and dissolved organic carbon, were also measured. Population abundance and community structure were analysed for difference to the dynamics in the controls. In the microcosms with 48 and 96 micro g Ni/L long-term effects on phytoplankton, rotifers, snails and, due to reduced grazing by snails, indirectly on the periphyton biomass were observed. Only minor, and/or temporary deviations from controls, i.e., for single sampling dates, were found for a few algae taxa at lower concentrations. Because these deviations showed no clear dose-response and were not found at the end of the study they were not seen as adverse effects. However, for the snail (Lymnaea stagnalis), effects on the trend of population development could not be excluded at 24 micro g/L. Thus, the overall No Observed Effect Concentration (NOEC) for a chronic exposure to nickel in this microcosm study was considered to be 12 micro g Ni/L. This NOEC confirms the protectiveness of the quality standard derived from the laboratory single species tests.
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