Das Projekt "Co-estimation of the Earth main magnetic field and the ionospheric variation field" wird vom Umweltbundesamt gefördert und von Universität Potsdam, Institut für Mathematik durchgeführt. The aim of this project is to co-estimate models of the core and ionosphere magnetic fields, with the longer-term view of building a 'comprehensive' model of the Earths magnetic field. In this first step we would like to take advantage of the progresses made in the understanding of the ionosphere by global M-I-T modelling to better separate the core and ionospheric signals in satellite data. The magnetic signal generated in the ionosphere is particularly difficult to handle because satellite data provide only information on a very narrow local time window at a time. To get around this difficulty, we would like to apply a technique derived from assimilation methods and that has been already successfully applied in outer-core flow studies. The technique relies on a theoretical model of the ionosphere such as the Upper Atmosphere Model (UAM), where statistics on the deviations from a simple background model are estimated. The derived statistics provided in a covariance matrix format can then be use directly in the magnetic data inversion process to obtain the expected core and ionospheric models. We plan to apply the technique on the German CHAMP satellite data selected for magnetically quiet times. As an output we should obtain a model of the ionospheric magnetic variation field tailored for the selected data and a core-lithosphere field model where possible leakage from ionospheric signals are avoided or at least reduced. The technique can in theory be easily extended to handle the large-scale field generated in the magnetosphere.
Das Projekt "Carbon, water and nutrient dynamics in vascular plant- vs. Sphagnum-dominated bog ecosystems in southern Patagonia" wird vom Umweltbundesamt gefördert und von Universität Münster, Mathematisch-Naturwissenschaftliche Fakultät, Fachbereich 14 - Geowissenschaften durchgeführt. In bog ecosystems, vegetation controls key processes such as the retention of carbon, water and nutrients. In northern hemispherical bogs, a shift from Sphagnum- to vascular plant-dominated vegetation is often traced back to Climate Change and increased anthropogenic nitrogen deposition and coincides with substantially reduced capacities in carbon, water and nutrient retention. In southern Patagonia, bogs dominated by Sphagnum and vascular plants coexist since millennia under similar environmental settings. Thus, South Patagonian bogs may serve as ideal examples for the long-term effect of vascular plant invasion on carbon, water and nutrient balances of bog ecosystems. The contemporary balances of carbon and water of both a bog dominated by Sphagnum and vascular plants are determined by CO2- H2O and CH4 flux measurements and an estimation of lateral water losses as well as losses via dissolved organic and inorganic carbon compounds. The high time resolution of simultaneous eddy covariance measurements of CO2 and H2O in both bog types and the strong interaction between climatic variables and the physiology of bog plants allow for direct comparisons of carbon and water fluxes during cold, warm, dry, wet, cloudy or sunny periods. By the combination with leaf-scale measurements of gas exchange and fluorescence, plant-physiological controls of photosynthesis and transpiration can be identified. Long-term peat accumulation rates will be determined by carbon density and age-depth profiles including a characterization of peat humification characteristics. A reciprocal transplantation experiment with incorporated shading, liming and labeled N addition treatments is conducted to explore driving factors affecting competition between Sphagnum and vascular plants as well as the interactions between CO2-, CH4-, and water fluxes and decisive plant functional traits affecting key processes for carbon sequestration and nutrient cycling. Decomposition rates and driving below ground processes are analyzed with a litter bag field experiment and an incubation experiment in the laboratory.
Das Projekt "Drivers and mechanisms of 13C discrimination in Cleistogenes squarrosa (C4) - reducing uncertainties on bundle sheath leakiness" wird vom Umweltbundesamt gefördert und von Technische Universität München, Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt, Lehrstuhl für Grünlandlehre durchgeführt. The energetic efficiency of C4 photosynthesis is strongly affected by bundle sheath leakiness, which is commonly assessed with the 'linear version' of the Farquhar model of 13C discrimination, and leaf gas exchange and 13C composition data. But, the linear Farquhar model is a simplification of the full mechanistic theory of ? in C4 plants, potentially generating errors in the estimation of leakiness. In particular, post-photosynthetic C isotope fractionation could cause large errors, but has not been studied in any detail. The present project aims to improve the understanding of the ecological and developmental/physiological factors controlling discrimination and leakiness of the perennial grass Cleistogenes squarrosa. C. squarrosa is the most important member of the C4 community which has spread significantly in the Mongolia grasslands in the last decades. It has an unusually high and variable discrimination, which suggests very high (and potentially highly variable) leakiness. Specifically, we will conduct the first systematic study of respiratory 13C fractionation in light and dark at leaf- and stand-scale in this C4 species, and assess its effect on discrimination and estimates of leakiness. These experiments are conducted in specialized 13CO2/12CO2 gas exchange mesocosms using ecologically relevant scenarios, testing specific hypotheses on effects of environmental drivers and plant and leaf developmental stage on discrimination and leakiness.
Das Projekt "Effects of water content, input of roots and dissolved organic matter and spatial inaccessibility on C turnover & determination of the spatial variability of subsoil properties" wird vom Umweltbundesamt gefördert und von Universität Kassel, Lehr- und Forschungsgebiet Umwelt- und Lebensmittelwissenschaften, Fachgebiet Umweltchemie durchgeführt. It is well established that reduced supply of fresh organic matter, interactions of organic matter with mineral phases and spatial inaccessibility affect C stocks in subsoils. However, quantitative information required for a better understanding of the contribution of each of the different processes to C sequestration in subsoils and for improvements of subsoil C models is scarce. The same is true for the main controlling factors of the decomposition rates of soil organic matter in subsoils. Moreover, information on spatial variabilities of different properties in the subsoil is rare. The few studies available which couple near and middle infrared spectroscopy (NIRS/MIRS) with geostatistical approaches indicate a potential for the creation of spatial maps which may show hot spots with increased biological activities in the soil profile and their effects on the distribution of C contents. Objectives are (i) to determine the mean residence time of subsoil C in different fractions by applying fractionation procedures in combination with 14C measurements; (ii) to study the effects of water content, input of 13C-labelled roots and dissolved organic matter and spatial inaccessibility on C turnover in an automatic microcosm system; (iii) to determine general soil properties and soil biological and chemical characteristics using NIRS and MIRS, and (iv) to extrapolate the measured and estimated soil properties to the vertical profiles by using different spatial interpolation techniques. For the NIRS/MIRS applications, sample pretreatment (air-dried vs. freeze-dried samples) and calibration procedures (a modified partial least square (MPLS) approach vs. a genetic algorithm coupled with MPLS or PLS) will be optimized. We hypothesize that the combined application of chemical fractionation in combination with 14C measurements and the results of the incubation experiments will give the pool sizes of passive, intermediate, labile and very labile C and N and the mean residence times of labile and very labile C and N. These results will make it possible to initialize the new quantitative model to be developed by subproject PC. Additionally, we hypothesize that the sample pretreatment 'freeze-drying' will be more useful for the estimation of soil biological characteristics than air-drying. The GA-MPLS and GA-PLS approaches are expected to give better estimates of the soil characteristics than the MPLS and PLS approaches. The spatial maps for the different subsoil characteristics in combination with the spatial maps of temperature and water contents will presumably enable us to explain the spatial heterogeneity of C contents.
Das Projekt "Analysis of dairy production systems differentiated by location" wird vom Umweltbundesamt gefördert und von Universität Bonn, Institut für Lebensmittel- und Ressourcenökonomik (ILR), Professur Wirtschafts- und Agrarpolitik durchgeführt. Dairy farming across Germany displays diverse production systems. Factor endowment, management, technology adoption as well as competitive dynamics in the local or regional land, agribusiness and dairy processing sectors contribute to this differentiation on farm level. These differences impact on the ability of dairy farms and regional dairy production systems to successfully respond to pressures arising from future market and policy changes. The overall objective of the research activities of which this project is a part of, is to develop a thorough understanding of the processes that govern the spatial dynamics of dairy farm development in different regions in Germany. The central hypothesis of this research project is that management system and technological choices differ systematically across local production and market conditions. The empirical approach will focus on the estimation of farm specific nonparametric cost functions for dairy farms located in across Germany differentiated by time and location. A spatially differentiated data base with information on input use, resource availability, as well as local market conditions for land and output markets will be compiled. The nonparametric approach is specifically suited to disclose a more accurate representation of dairy production system heterogeneity across locations and time compared to parametric concepts as it provides the necessary flexibility to accommodate non-linearities relevant for a wide domain of explanatory variables. The methodology employed goes beyond the state of the art of the literature as it combines kernel density estimation with a Bayesian sampling approach to provide theory consistent parameters for each farm in the data sample.The specific methodological hypothesis is that the nonparametric approach is superior to current parametric techniques and this hypothesis is tested using statistical model evaluation. Regarding the farm management and technological choices, we hypothesize that land suitability for feed production determines the farm intensity of dairy production and thus management and technological choices. With respect to the ability of farms to successfully respond to market pressures we hypothesize that farms at the upper and lower tail of the intensity distribution both can generate positive returns from dairy production. These last two hypotheses will be tested using the estimated spatially differentiated farm specific costs and marginal costs.The expected outcomes are of relevance for the agricultural sector and the food supply chain economy as a whole as fundamental market structure changes in the dairy sector are ongoing due to the abolition of the quota regulation in the years 2014/2015. Thus, exact knowledge about differences and development of dairy cost heterogeneity of farms within and between regions are an important factor for the actors involved in the market as well as the political support of this process.
Das Projekt "Methodologies for dealing with uncertainties in landscape planning and related modeling; Uncertainty of predicted hydro-biogeochemical fluxes and trace gas emissions on the landscape scale under climate and land use change" wird vom Umweltbundesamt gefördert und von Universität Gießen, Institut für Landschaftsökologie und Ressourcenmanagement, Professur für Landschafts-, Wasser- und Stoffhaushalt durchgeführt. Water, carbon and nitrogen are key elements in all ecosystem turnover processes and they are related to a variety of environmental problems, including eutrophication, greenhouse gas emissions or carbon sequestration. An in-depth knowledge of the interaction of water, carbon and nitrogen on the landscape scale is required to improve land use and management while at the same time mitigating environmental impact. This is even more important under the light of future climate and land use changes.In the frame of the proposal 'Uncertainty of predicted hydro-biogeochemical fluxes and trace gas emissions on the landscape scale under climate and land use change' we advocate the development of fully coupled, process-oriented models that explicitly simulate the dynamic interaction of water, carbon and nitrogen turnover processes on the landscape scale. We will use the Catchment Modelling Framework CMF, a modular toolbox to implement and test hypothesis of hydrologic behaviour and couple this to the biogeochemical LandscapeDNDC model, a process-based dynamic model for the simulation of greenhouse gas emissions from soils and their associated turnover processes.Due to the intrinsic complexity of the models in use, the predictive uncertainty of the coupled models is unknown. This predictive (global) uncertainty is composed of stochastic and structural components. Stochastic uncertainty results from errors in parameter estimation, poorly known initial states of the model, mismatching boundary conditions or inaccuracies in model input and validation data. Structural uncertainty is related to the flawed or simplified description of natural processes in a model.The objective of this proposal is therefore to quantify the global uncertainty of the coupled hydro-biogeochemical models and investigate the uncertainty chain from parameter uncertainty over forcing data uncertainty up the structural model uncertainty be setting up different combinations of CMF and LandscapeDNDC. A comprehensive work program has been developed structured in 4 work packages, that consist of (1) model set up, calibration and uncertainty assessment on site scale followed by (2) an application and uncertainty assessment of the coupled model structures on regional scale, (3) global change scenario analyses and finally (4) evaluating model results in an ensemble fashion.Last but not least, a further motivation of this proposal is to provide project results in a manner that they support planning and decision taking under uncertainty, as this proposal is part of the package proposal on 'Methodologies for dealing with uncertainties in landscape planning and related modelling'.
Das Projekt "Ecological-physical linkages in fluvial eco-hydromorphology" wird vom Umweltbundesamt gefördert und von Technische Universität Dresden, Institut für Wasserbau und Technische Hydromechanik durchgeführt. Recent discussions on the path eco-hydromorphic research has followed in the past decades highlight the need for greater ecological input into this field. Traditional approaches have been criticized for being largely correlation-based (Vaughan et al., 2009) ecological black boxes (Leclerc, 2005) and strongly relying on weak, disproven and/or outdated assumptions about the dynamics of stream biota (Lancaster & Downes, 2010). In recognition of this, process-oriented research aiming at elucidating and quantifying causal mechanisms has been proposed as a promising approach, though challenging, to study the relations between flow, morphodynamics and biological populations in running waters. In terms of levels of biological organization, it has been recognized that processes determining the response of aquatic biota to hydromorphological alteration occur mainly at the population level. In this sense, relating demographic rates to flow and morphology seems to offer great potential for progress (Lancaster & Downes, 2010). Thus, tapping into existing ecological knowledge (e.g., key patch approach for habitat networks, Verboom et al. 2001; metapopulation theory, Levins 1970; Hanski & Gaggiotti 2004, landscape-scale estimations of habitat suitability and carrying capacity, Reijnen et al. 1995; Duel et al. 1995 2003; population-level viability estimations; Akçakaya 2001; resource utilization scales, ONeill et al. 1988; habitat-use patterns, Milne et al. 1989) in order to link ecology to hydromorphology at a more fundamental level constitutes an important path towards better science and management.
Das Projekt "Multiple-site seismic hazard assessment" wird vom Umweltbundesamt gefördert und von Karlsruher Institut für Technologie (KIT), Geophysikalisches Institut durchgeführt. The classical point wise Cornell-McGuire probabilistic seismic hazard assessment (PSHA), which is widely used for seismic hazard mapping and development of design codes, does not allow direct estimation of multiple-location hazard for distributed structures and facilities: what is the (annual) probability that specific level of ground motion will be exceeded simultaneously in several sites? It is possible to extent the classical methodology to the multiple sites problem considering also ground-motion correlation. We study multiple-location PSHA, as compared with the classical point wise PSHA, using Monte Carlo simulation. Specific items are:(1) Development of the algorithms for multiple-location PSHA;(2) Analysis of the role of the geometry of multiple sites, correlation of ground motion, and evel of seimicity for multiple-location PSHA;(3) Study of correspondence and differences between multiple-location PSHA and classical point wise PSHA and analysis of possibility of utilization of classical PSHA procedures for simplified multiple-location hazard assessment.The project is innovative because only few attempts have been made so far regarding our research questions.
Das Projekt "Root distribution and dynamics and their contribution to subsoil C-fluxes" wird vom Umweltbundesamt gefördert und von Universität Göttingen, Albrecht-von-Haller-Institut für Pflanzenwissenschaften, Abteilung Pflanzenökologie und Ökosystemforschung durchgeführt. It has been suggested that dying and decaying fine roots and root exudation represent important, if not the most important, sources of soil organic carbon (SOC) in forest soils. This may be especially true for deep-reaching roots in the subsoil, but precise data to prove this assumption are lacking. This subproject (1) examines the distribution and abundance of fine roots (greater than 2 mm diameter) and coarse roots (greater than 2 mm) in the subsoil to 240 cm depth of the three subsoil observatories in a mature European beech (Fagus sylvatica) stand, (2) quantifies the turnover of beech fine roots by direct observation (mini-rhizotron approach), (3) measures the decomposition of dead fine root mass in different soil depths, and (4) quantifies root exudation and the N-uptake potential with novel techniques under in situ conditions with the aim (i) to quantify the C flux to the SOC pool upon root death in the subsoil, (ii) to obtain a quantitative estimate of root exudation in the subsoil, and (iii) to assess the uptake activity of fine roots in the subsoil as compared to roots in the topsoil. Key methods applied are (a) the microscopic distinction between live and dead fine root mass, (b) the estimation of fine and coarse root age by the 14C bomb approach and annual ring counting in roots, (c) the direct observation of the formation and disappearance of fine roots in rhizotron tubes by sequential root imaging (CI-600 system, CID) and the calculation of root turnover, (d) the measurement of root litter decomposition using litter bags under field and controlled laboratory conditions, (e) the estimation of root N-uptake capacity by exposing intact fine roots to 15NH4+ and 15NO3- solutions, and (f) the measurement of root exudation by exposing intact fine root branches to trap solutions in cuvettes in the field and analysing for carbohydrates and amino acids by HPLC and Py-FIMS (cooperation with Prof. A. Fischer, University of Trier). The obtained data will be analysed for differences in root abundance and activity between subsoil (100-200 cm) and topsoil (0-20 cm) and will be related to soil chemical and soil biological data collected by the partner projects that may control root turnover and exudation in the subsoil. In a supplementary study, fine root biomass distribution and root turnover will also be studied at the four additional beech sites for examining root-borne C fluxes in the subsoil of beech forests under contrasting soil conditions of different geological substrates (Triassic limestone and sandstone, Quaternary sand and loess deposits).
Das Projekt "Development of an integrated forest carbon monitoring system with field sampling and remote sensing for tropical forests in Indonesia" wird vom Umweltbundesamt gefördert und von Universität Göttingen, Burckhardt-Institut, Abteilung Waldinventur und Fernerkundung durchgeführt. Forests play a relevant role in mitigation of climate change. A major issue, however, is the scientifically well founded, transparent and verifyable monitoring of achievements in forest carbon sequestration through reduction of deforestation and forest degradation, and through fostering sustainable forest management. Monitoring is particularly difficult in diverse and inaccessible humid tropical forest areas. The proposed research will contribute to the improvement of forest carbon monitoring under the challenging conditions of humid tropical forests. Sample based field observations and model based biomass predictions will be linked to area-wide satellite remote sensing imagery (RapidEye) and to strip samples of LiDAR imagery. Techniques of linking these data sources will be further developed and analysed with respect to (1) precision of carbon estimation and (2) accuracy of carbon regionalization. The proposed project implies research on methodological improvements of both sample based forest inventories (resampling techniques for biomass, imputation of non-response) and remote sensing application to forest monitoring (regionalization, sample based application of LiDAR data). At the core of this research is the analysis of the error variance components that each data source brings into the system. Such error analysis will allow identifying optimal resource allocation for the efficient improvement of forest carbon monitoring systems.
| Origin | Count |
|---|---|
| Bund | 32 |
| Type | Count |
|---|---|
| Förderprogramm | 32 |
| License | Count |
|---|---|
| offen | 32 |
| Language | Count |
|---|---|
| Deutsch | 4 |
| Englisch | 29 |
| Resource type | Count |
|---|---|
| Keine | 32 |
| Topic | Count |
|---|---|
| Boden | 27 |
| Lebewesen & Lebensräume | 30 |
| Luft | 25 |
| Mensch & Umwelt | 32 |
| Wasser | 23 |
| Weitere | 32 |