The majority of the worlds forests has undergone some form of management, such as clear-cut or thinning. This management has direct relevance for global climate: Studies estimate that forest management emissions add a third to those from deforestation, while enhanced productivity in managed forests increases the capacity of the terrestrial biosphere to act as a sink for carbon dioxide emissions. However, uncertainties in the assessment of these fluxes are large. Moreover, forests influence climate also by altering the energy and water balance of the land surface. In many regions of historical deforestation, such biogeophysical effects have substantially counteracted warming due to carbon dioxide emissions. However, the effect of management on biogeophysical effects is largely unknown beyond local case studies. While the effects of climate on forest productivity is well established in forestry models, the effects of forest management on climate is less understood. Closing this feedback cycle is crucial to understand the driving forces behind past climate changes to be able to predict future climate responses and thus the required effort to adapt to it or avert it. To investigate the role of forest management in the climate system I propose to integrate a forest management module into a comprehensive Earth system model. The resulting model will be able to simultaneously address both directions of the interactions between climate and the managed land surface. My proposed work includes model development and implementation for key forest management processes, determining the growth and stock of living biomass, soil carbon cycle, and biophysical land surface properties. With this unique tool I will be able to improve estimates of terrestrial carbon source and sink terms and to assess the susceptibility of past and future climate to combined carbon cycle and biophysical effects of forest management. Furthermore, representing feedbacks between forest management and climate in a global climate model could advance efforts to combat climate change. Changes in forest management are inevitable to adapt to future climate change. In this process, is it possible to identify win-win strategies for which local management changes do not only help adaptation, but at the same time mitigate global warming by presenting favorable effects on climate? The proposed work opens a range of long-term research paths, with the aim of strengthening the climate perspective in the economic considerations of forest management and helping to improve local decisionmaking with respect to adaptation and mitigation.
The project DIGSTER - Map and Go (Digital Based Terrain Mapping) aims at the technical aspects of digital terrrain mapping. For many questions in administration, planning and expertise terrrain mappings are indispensable. The whole process starting with the data acquisition in the field and ending with map products will be digitally performed by the system. Therefore, a platform appropriate for the use in the field (PDA) is combined with technologies from the disciplines of satellite navigation, remote sensing, communication, and mobile geoinformation systems. For DIGSTER a lot of practical applications already exist in connection with policies and directives on the national and also European level.
Methane (CH4) is a major greenhouse gas of which the atmospheric concentration has more than doubled since pre-industrial times. Soils can act as both, source and sink for atmospheric CH4, while upland forest soils generally act as CH4 consumers. Oxidation rates depend on factors influenced by the climate like soil temperature and soil moisture but also on soil properties like soil structure, texture and chemical properties. Many of these parameters directly influence soil aeration. CH4 oxidation in soils seems to be controlled by the supply with atmospheric CH4, and thus soil aeration is a key factor. We aim to investigate the importance of soil-gas transport-processes for CH4 oxidation in forest soils from the variability the intra-site level, down to small-scale (0.1 m), using new approaches of field measurements. Further we will investigate the temporal evolution of soil CH4 consumption and the influence of environmental factors during the season. Based on previous results, we hypothesize that turbulence-driven pressure-pumping modifies the transport of CH4 into the soil, and thus, also CH4 consumption. To improve the understanding of horizontal patterns of CH4 oxidation we want to integrate the vertical dimension on the different scales using an enhanced gradient flux method. To overcome the constraints of the classical gradient method we will apply gas-diffusivity measurements in-situ using tracer gases and Finite-Element-Modeling. Similar to the geophysical technique of Electrical Resistivity Tomography we want to develop a Gas Diffusivity Tomography. This will allow to derive the three-dimensional distribution of soil gas diffusivity and methane oxidation.
Farm structures are often characterized by regional heterogeneity, agglomeration effects, sub-optimal farm sizes and income disparities. The main objective of this study is to analyze whether this is a result of path dependent structural change, what the determinants of path dependence are, and how it may be overcome. The focus is on the German dairy sector which has been highly regulated and subsidized in the past and faces severe structural deficits. The future of this sector in the process of an ongoing liberalization will be analyzed by applying theoretical concepts of path dependence and path breaking. In these regards, key issues are the actual situation, technological and market trends as well as agricultural policies. The methodology will be based on a participative use of the agent-based model AgriPoliS and participatory laboratory experiments. On the one hand, AgriPoliS will be tested as a tool for stakeholder oriented analysis of mechanisms, trends and policy effects. This part aims to analyze whether and how path dependence of structural change can be overcome on a sector level. In a second part, AgriPoliS will be extended such that human players (farmers, students) can take over the role of agents in the model. This part aims to compare human agents with computer agents in order to overcome single farm path dependence.
Most soils develop distinct soil architecture during pedogenesis and soil organic carbon (SOC) is sequestered within a hierarchical system of mineral-organic associations and aggregates. Permafrost soils store large amounts of carbon due to their permanently frozen subsoil and a lack of oxygen in the active layer, but they lack complex soil structure. With permafrost thaw more oxidative conditions and increasing soil temperature presumably enhance the build-up of more complex units of soil architecture and may counterbalance, at least partly, SOC mineralization. We aim to explore the development of mineral-organic associations and aggregates under different permafrost impact with respect to SOC stabilization. This information will be linked to environmental control factors relevant for SOC turnover at the pedon and stand scale to bridge processes occurring at the aggregate scale to larger spatial dimensions. We will combine in situ spectroscopic techniques with fractionation approaches and identify mechanisms relevant for SOC turnover at different scales by multivariate statistics and variogram analyses. From this we expect a deeper knowledge about soil architecture formation in the transition of permafrost soils to terrestrial soils and a scale-spanning mechanistic understanding of SOC cycling in permafrost regions.
The geomagnetic field shields our habitat against solar wind and radiation from space. Due to the geometry of the field, the shielding in general is weakest at high latitudes. It is also anomalously weak in a region around the south Atlantic known as South Atlantic Anomaly (SAA), and the global dipole moment has been decreasing by nearly 10 percent since direct measurements of field intensity became possible in 1832. Due to our limited understanding of the geodynamo processes in Earths core, it is impossible to reliably predict the future evolution of both dipole moment and SAA over the coming decades. However, lack of magnetic field shielding as would be a consequence of further weakening of dipole moment and SAA region field intensity would cause increasing problems for modern technology, in particular satellites, which are vulnerable to radiation damage. A better understanding of the underlying processes is required to estimate the future development of magnetic field characteristics. The study of the past evolution of such characteristics based on historical, archeo- and paleomagnetic data, on time-scales of centuries to millennia, is essential to detect any recurrences and periodicities and provide new insights in dynamo processes in comparison to or in combination with numerical dynamo simulations. We propose to develop two new global spherical harmonic geomagnetic field models, spanning 1 and 10 kyrs, respectively, and designed in particular to study how long the uninterrupted decay of the dipole moment has been going on prior to 1832, and if the SAA is a recurring structure of the field.We will combine for the first time all available historical and archeomagnetic data, both directions and intensities, in a spherical harmonic model spanning the past 1000 years. Existing modelling methods will be adapted accordingly, and existing data bases will be complemented with newly published data. We will further acquire some new archeomagnetic data from the Cape Verde islands from historical times to better constrain the early evolution of the present-day SAA. In order to study the long-term field evolution and possible recurrences of similar weak field structures in this region, we will produce new paleomagnetic records from available marine sediment cores off the coasts of West Africa, Brazil and Chile. This region is weakly constrained in previous millennial scale models. Apart from our main aim to gain better insights into the previous evolution of dipole moment and SAA, the models will be used to study relations between dipole and non-dipole field contributions, hemispheric symmetries and large-scale flux patterns at the core-mantle boundary. These observational findings will provide new insights into geodynamo processes when compared with numerical dynamo simulation results.Moreover, the models can be used to estimate past geomagnetic shielding above Earths surface against solar wind and for nuclide production from galactic cosmic rays.
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.
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.
Electrical conductivity is a key parameter in models of magnetic field generation in planetary interiors through magneto-hydrodynamic convection. Measurements of this key material parameter of liquid metals is not possible to date by experiments at relevant conditions, and dynamo models rely on extrapolations from low pressure/temperature experiments, or more recently on ab-initio calculations combining molecular dynamics and linear response calculations, using the Kubo-Greenwood formulation of transport coefficients. Such calculations have been performed for Fe, Fe-alloys, H, He and H-He mixtures to cover the interior of terrestrial and giant gas planets. These simulations are computationally expensive, and an efficient accurate scheme to determine electrical conductivities is desirable. Here we propose a model that can, at much lower computational costs, provide this information. It is based on Ziman theory of electrical conductivity that uses information on the liquid structure, combined with an internally consistent model of potentials for the electron-electron, electron-atom, and atom-atom interactions. In the proposal we formulate the theory and expand it to multi-component systems. We point out that fitting the liquid structure factor is the critical component in the process, and devise strategies on how this can be done efficiently. Fitting the structure factor in a thermodynamically consistent way and having a transferable electron-atom potential we can then relatively cheaply predict the electrical conductivity for a wide range of conditions. Only limited molecular dynamics simulations to obtain the structure factors are required.In the proposed project we will test and advance this model for liquid aluminum, a free-electron like metal, that we have studied with the Kubo-Greenwood method previously. We will then be able to predict the conductivities of Fe, Fe-light elements and H, He, as well as the H-He system that are relevant to the planetary interiors of terrestrial and giant gas planets, respectively.
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.
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