@phdthesis{Nwadinobi2013,
  author    = {Nwadinobi, Chinedum Bede},
  title     = {Environmental problems and sustainable development (a study of the Niger-Delta Region of Nigeria) : a terra incognita},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-117624},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {The tendency towards the exploitation of the resources of creation is the result of a long historical and cultural process. The modern African Communities have witnessed man's growing capacity for environmental transformative intervention. The aspect of the conquest and exploitation of resources in rural communities such as in the Niger Delta of Nigeria has become predominant and invasive, and has even reached the point of threatening the environment's hospitable function: the environment only as resource risks threatening the environment as home. In this respect, the ethical judgement of the social realities on ground is very decisive. And this is the very important aspect where the Catholic Social Ethics has a role to play. Because of the environmental crisis in this region through technological advancement, there is urgent need for a balance through the introduction of the model of a sustainable development. The socio-ethical model of sustainability in this work is a framework so constructed that women, men, families and communities in the Niger Delta are to be the agents which determine what their developmental strategies are. Although their developmental opportunities and decisions are sometimes constrained by various factors, it remains the fact that they alone bear responsibility for their environment and must live with the consequences. So if sustainable development in the Niger Delta region of Nigeria is to extend beyond narrow technical understanding, it must one that generally seek to embrace the cultural and social systems of the people. This will go a long way in reducing dependency and increase self-empowerment and will place more value on what the people understand and practice. Bede Chinedum Nwadinobi, a native of Alike Obowo in Imo State (Nigeria), is a Catholic Priest of Okigwe Diocese (Nigeria). He studied Philosophy and Theology at St. Joseph Major Seminary Ikot-Ekpene. He also worked as a Vice-Principal of Queen of Apostles College Okigwe (Nigeria). At the University of W{\"u}rzburg (Germany), he earned his doctorate in Catholic Theology specializing in Catholic Social Science.},
  subject      = {Nigeria},
  language  = {en}
}
@phdthesis{Brede2013,
  author    = {Brede, Christian},
  title     = {Peripheral alloantigen expression directs the organ specific T cell infiltration after hematopoietic cell transplantation},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-85365},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {In acute graft-versus-host disease (GVHD) alloreactive donor T cells selectively damage skin, liver, and the gastrointestinal tract while other organs are rarely affected. The mechanism of this selective target tissue infiltration is not well understood. We investigated the importance of alloantigen expression for the selective organ manifestation by examining spatiotemporal changes of cellular and molecular events after allogeneic hematopoietic cell transplantation (allo-HCT). To accomplish this we established a novel multicolor light sheet fluorescence microscopy (LSFM) approach for deciphering immune processes in large tissue specimens on a single-cell level in 3 dimensions. We combined and optimized protocols for antibody penetration, tissue clearing, and triple-color illumination to create a method for analyzing intact mouse and human tissues. This approach allowed us to successfully quantify changes in expression patterns of mucosal vascular addressin cell adhesion molecule-1 (MAdCAM-1) and T cell responses in Peyer's patches following allo-HCT. In addition, we proofed that LSFM is suitable to map individual T cell subsets after HCT and detected rare cellular events. We employed this versatile technique to study the role of alloantigen expression for the selective organ manifestation after allo-HCT. Therefore, we used a T cell receptor (TCR) transgenic mouse model of GVHD that targets a single peptide antigen and thereby mimics a major histocompatibility complex (MHC)-matched single antigen mismatched (miHAg-mismatched) HCT. We transplanted TCR transgenic (OT-I) T cells into myeloablatively conditioned hosts that either express the peptide antigen ovalbumin ubiquitously (βa-Ova) or selectively in the pancreas (RIP-mOva), an organ that is normally not affected by acute GVHD. Of note, at day+6 after HCT we observed that OT-I T cell infiltration occurred in an alloantigen dependent manner. In βa-Ova recipients, where antigen was ubiquitously expressed, OT-I T cells infiltrated all organs and were not restricted to gastrointestinal tract, liver, and skin. In RIP-mOva recipients, where cognate antigen was only expressed in the pancreas, OT-I T cells selectively infiltrated this organ that is usually spared in acute GVHD. In conditioned RIP-mOva the transfer of 100 OT-I T cells sufficed to effectively infiltrate and destroy pancreatic islets resulting in 100\% mortality. By employing intact tissue LSFM in RIP-mOva recipients, we identified very low numbers of initial islet infiltrating T cells on day+4 after HCT followed by a massive T cell migration to the pancreas within the following 24 hours. This suggested an effective mechanism of effector T cell recruitment to the tissue of alloantigen expression after initial antigen specific T cell encounter. In chimeras that either expressed the model antigen ovalbumin selectively in hematopoietic or in parenchymal cells only, transplanted OT-I T cells infiltrated target tissues irrespective of which compartment expressed the alloantigen. As IFN-γ could be detected in the serum of transplanted ovalbumin expressing recipients (βa-Ova, βa-Ova-chimeras and RIP-mOva) at day+6 after HCT, we hypothesized that this cytokine may be functionally involved in antigen specific OT-I T cell mediated pathology. In vitro activated OT-I T cells responded with the production of IFN-γ upon antigen re-encounter suggesting that IFN-γ might be relevant in the alloantigen dependent organ infiltration of antigen specific CD8+ T cell infiltration after HCT. Based on these data we propose that alloantigen expression plays an important role in organ specific T cell infiltration during acute GVHD and that initial alloreactive T cells recognizing the cognate antigen propagate a vicious cycle of enhanced T cell recruitment that subsequently culminates in the exacerbation of tissue restricted GVHD.},
  subject      = {Alloantigen},
  language  = {en}
}
@phdthesis{Ye2013,
  author    = {Ye, Yuxiang},
  title     = {Molecular and Cellular Magnetic Resonance Imaging of Myocardial Infarct Healing},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-72514},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {Myokardinfarkte (MI) sind eine der h{\"a}ufigsten Todesursachen weltweit. Eine rechtzeitige Wiederherstellung des koronaren Blutflusses im isch{\"a}mischen Myokard reduziert signifikant die Sterblichkeitsrate akuter Infarkte und vermindert das ventrikul{\"a}re Remodeling. {\"U}berlebende MI-Patienten entwickeln jedoch h{\"a}ufig eine Herzinsuffizienz, die mit einer reduzierten Lebensqualit{\"a}t, hohen Sterblichkeitsrate (10\% j{\"a}hrlich), sowie hohen Kosten f{\"u}r das Gesundheitssystem einhergeht. Die Entwicklung der Herzinsuffizienz nach einem MI ist auf den hohen Verlust kontraktiler Kardiomyozyten, w{\"a}hrend der Isch{\"a}mie-Reperfusion zur{\"u}ckzuf{\"u}hren. Anschließende komplexe strukturelle und funktionelle Ver{\"a}nderungen resultieren aus Modifikationen des infarzierten und nicht infarzierten Myokards auf molekularer und zellul{\"a}rer Ebene. Die verbesserte {\"U}berlebensrate von Patienten mit akutem MI und das Fehlen effizienter Therapien, die die Entwicklung und das Fortschreiten des ventrikul{\"a}ren Remodelings verhindern, f{\"u}hren zu einer hohen Pr{\"a}valenz der Herzinsuffizienz. Die kardiale Magnetresonanztomographie (MRT) ist eine wichtige Methode zur Diagnose und Beurteilung des Myokardinfarktes. Mit dem technologischen Fortschritt wurden die Grenzen der MRT erweitert, so dass es heute m{\"o}glich ist, auch molekulare und zellul{\"a}re Ereignisse in vivo und nicht-invasiv zu untersuchen. In Kombination mit kardialer Morphologie und Funktion k{\"o}nnte die Visualisierung essentieller molekularer und zellul{\"a}rer Marker in vivo weitreichende Einblicke in den Heilungsprozess infarzierter Herzen liefern, was zu neuen Erkenntnissen f{\"u}r ein besseres Verst{\"a}ndnis und bessere Therapien des akuten MI f{\"u}hren k{\"o}nnte. In dieser Arbeit wurden Methoden f{\"u}r die molekulare und zellul{\"a}re kardiale MRT-Bildgebung der Inflammation und des Kalziumstroms im Heilungsprozess des akuten Myokardinfarktes in vivo in einem Rattenmodel mit klinischer Relevanz etabliert.},
  subject      = {Kernspintomografie},
  language  = {en}
}
@phdthesis{Mutz2013,
  author    = {Mutz, Sebastian},
  title     = {Dynamic Statistical Modelling of Climate-Related Mass Balance Changes in Norway},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-114799},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {The glaciers in Norway exert a strong influence on Norwegian economy and society. Unlike many glaciers elsewhere and despite ongoing climate change and warming, many of them showed renewed advances and positive net mass changes in the 1980's and 1990's, followed by rapid retreats and mass losses since 2000. This difference in behaviour may be attributed to differences and shifts in the glaciological regime - the differences in the magnitude of impacts of climatic and non-climatic geographical factors on the glacier mass. This study investigates the influence of various atmospheric variables on mass balance changes of a selection of glaciers in Norway by means of Pearson correlation analyses and cross-validated stepwise multiple regression analyses. The analyses are carried out for three time periods (1949-2008, 1949-1988, 1989-2008) separately in order to take into consideration the possible shift in the glaciological regime in the 1980's. The atmospheric variables are constructed from ERA40 and NCEP/NCAR re-analysis datasets and include regional means of seasonal air temperature and precipitation rates and atmospheric circulation indices. The multiple regression models trained in these time periods are then applied to predictors reconstructed from the CMIP3 climate model dataset to generate an estimate for mass changes from the year 1950 to 2100. The temporal overlap of estimates and observations is used for calibration. Finally, observed atmospheric states in seasons that are characterised by a particularly positive or negative mass balance are categorised into time periods of modelled climate by the application of a Bayesian classification procedure. The strongest influence on winter mass balance is exerted by different indices of the North Atlantic Oscillation (NAO), Northern Annular Mode (NAM) and precipitation. The correlation coefficients and explained variances determined from the multiple regression analyses reveal an East-West gradient, suggesting a weaker influence of the NAO and NAM on glaciers underlying a more continental regime. The highest correlation coefficients and explained variances were obtained for the 1989-2008 time period, which might be due to a strong and predominantly positive phase of the NAO. Multi-model ensemble means of the estimates show a mass loss for all three eastern glaciers, while the estimates for the more maritime glaciers are ambivalent. In general, the estimates show a greater sensitivity to the training time period than to the greenhouse gas emission scenarios according to which the climates were simulated. The average net mass change by the end of 2100 is negative for all glaciers except for the northern Engabreen. For many glaciers, the Bayesian classification of observed atmospheric states into time periods of modelled climate reveals a decrease in probability of atmospheric states favouring extremes in winter, and an increase in probability of atmospheric states favouring extreme mass loss in summer for the distant future (2071-2100). This pattern of probabilities for the ablation season is most pronounced for glaciers underlying a continental and intermediate regime.},
  subject      = {Norwegen},
  language  = {en}
}
@phdthesis{Hofmann2013,
  author    = {Hofmann, Sebastian},
  title     = {Studies on the function and regulation of CD84, GPVI and Orai2 in genetically modified mice},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-87949},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {Platelet activation and aggregation at sites of vascular injury are essential processes to limit blood loss but they also contribute to arterial thrombosis, which can lead to myocardial infarction and stroke. Stable thrombus formation requires a series of events involving platelet receptors which contribute to adhesion, activation and aggregation of platelets. Regulation of receptor expression by (metallo-)proteinases has been described for several platelet receptors, but the molecular mechanisms are ill-defined. The signaling lymphocyte activation molecule (SLAM) family member CD84 is expressed in immune cells and platelets, however its role in platelet physiology was unclear. In this thesis, CD84 deficient mice were generated and analyzed. In well established in vitro and in vivo assays testing platelet function and thrombus formation, CD84 deficient mice displayed phenotypes indistinguishable from wild-type controls. It was concluded that CD84 in platelets does not function as modulator of thrombus formation, but rather has other functions. In line with this, in the second part of this thesis, a novel regulation mechanism for platelet CD84 was discovered and elucidated. Upon platelet activation, the N-terminus of CD84 was found to be cleaved exclusively by the a disintegrin and metalloproteinase 10 (ADAM10), whereas the intracellular part was cleaved by calpain. In addition, regulation of the platelet activating collagen receptor glycoprotein VI (GPVI) was studied and it was shown that GPVI is in contrast to CD84 differentially regulated by ADAM10 and ADAM17. A novel role of CD84 under pathophysiological conditions was revealed as CD84 deficient mice were protected from ischemic stroke in the model of transient middle cerebral artery occlusion and this protection was based on the lack of CD84 in T cells. Ca2+ is an essential second messenger that facilitates activation of platelets and diverse functions in different eukaryotic cell types. Store-operated Ca2+ entry (SOCE) represents the major mechanism leading to rise in intracellular Ca2+ concentration in non-excitable cells. The Ca2+ sensor STIM1 (stromal interaction molecule 1) and the SOC channel subunit protein Orai1 are established mediators of SOCE in platelets. STIM2 is the major STIM isoform in neurons, but the role of the SOC channel subunit protein Orai2 in platelets and neurons has remained elusive. In the third part of this thesis, Orai2 deficient mice were generated and analyzed. Orai2 was dispensable for platelet function, however, Orai2 deficient mice were protected from ischemic neurodegeneration and this phenotype was attributed to defective SOCE in neurons.},
  subject      = {Thrombozyt},
  language  = {en}
}
@phdthesis{Loew2013,
  author    = {L{\"o}w, Fabian},
  title     = {Agricultural crop mapping from multi-scale remote sensing data - Concepts and applications in heterogeneous Middle Asian agricultural landscapes},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-102093},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {Agriculture is mankind's primary source of food production and plays the key role for cereal supply to humanity. One of the future challenges will be to feed a constantly growing population, which is expected to reach more than nine billion by 2050. The potential to expand cropland is limited, and enhancing agricultural production efficiency is one important means to meet the future food demand. Hence, there is an increasing demand for dependable, accurate and comprehensive agricultural intelligence on crop production. The value of satellite earth observation (EO) data for agricultural monitoring is well recognized. One fundamental requirement for agricultural monitoring is routinely updated information on crop acreage and the spatial distribution of crops. With the technical advancement of satellite sensor systems, imagery with higher temporal and finer spatial resolution became available. The classification of such multi-temporal data sets is an effective and accurate means to produce crop maps, but methods must be developed that can handle such large and complex data sets. Furthermore, to properly use satellite EO for agricultural production monitoring a high temporal revisit frequency over vast geographic areas is often necessary. However, this often limits the spatial resolution that can be used. The challenge of discriminating pixels that correspond to a particular crop type, a prerequisite for crop specific agricultural monitoring, remains daunting when the signal encoded in pixels stems from several land uses (mixed pixels), e.g. over heterogeneous landscapes where individual fields are often smaller than individual pixels. The main purposes of the presented study were (i) to assess the influence of input dimensionality and feature selection on classification accuracy and uncertainty in object-based crop classification, (ii) to evaluate if combining classifier algorithms can improve the quality of crop maps (e.g. classification accuracy), (iii) to assess the spatial resolution requirements for crop identification via image classification. Reporting on the map quality is traditionally done with measures that stem from the confusion matrix based on the hard classification result. Yet, these measures do not consider the spatial variation of errors in maps. Measures of classification uncertainty can be used for this purpose, but they have attained only little attention in remote sensing studies. Classifier algorithms like the support vector machine (SVM) can estimate class memberships (the so called soft output) for each classified pixel or object. Based on these estimations, measures of classification uncertainty can be calculated, but it has not been analysed in detail, yet, if these are reliable in predicting the spatial distribution of errors in maps. In this study, SVM was applied for the classification of agricultural crops in irrigated landscapes in Middle Asia at the object-level. Five different categories of features were calculated from RapidEye time series data as classification input. The reliability of classification uncertainty measures like entropy, derived from the soft output of SVM, with regard to predicting the spatial distribution of error was evaluated. Further, the impact of the type and dimensionality of the input data on classification uncertainty was analysed. The results revealed that SMVs applied to the five feature categories separately performed different in classifying different types of crops. Incorporating all five categories of features by concatenating them into one stacked vector did not lead to an increase in accuracy, and partly reduced the model performance most obviously because of the Hughes phenomena. Yet, applying the random forest (RF) algorithm to select a subset of features led to an increase of classification accuracy of the SVM. The feature group with red edge-based indices was the most important for general crop classification, and the red edge NDVI had an outstanding importance for classifying crops. Two measures of uncertainty were calculated based on the soft output from SVM: maximum a-posteriori probability and alpha quadratic entropy. Irrespective of the measure used, the results indicate a decline in classification uncertainty when a dimensionality reduction was performed. The two uncertainty measures were found to be reliable indicators to predict errors in maps. Correctly classified test cases were associated with low uncertainty, whilst incorrectly test cases tended to be associated with higher uncertainty. The issue of combining the results of different classifier algorithms in order to increase classification accuracy was addressed. First, the SVM was compared with two other non-parametric classifier algorithms: multilayer perceptron neural network (MLP) and RF. Despite their comparatively high classification performance, each of the tested classifier algorithms tended to make errors in different parts of the input space, e.g. performed different in classifying crops. Hence, a combination of the complementary outputs was envisaged. To this end, a classifier combination scheme was proposed, which is based on existing algebraic operators. It combines the outputs of different classifier algorithms at the per-case (e.g. pixel or object) basis. The per-case class membership estimations of each classifier algorithm were compared, and the reliability of each classifier algorithm with respect to classifying a specific crop class was assessed based on the confusion matrix. In doing so, less reliable classifier algorithms were excluded at the per-class basis before the final combination. Emphasis was put on evaluating the selected classification algorithms under limiting conditions by applying them to small input datasets and to reduced training sample sets, respectively. Further, the applicability to datasets from another year was demonstrated to assess temporal transferability. Although the single classifier algorithms performed well in all test sites, the classifier combination scheme provided consistently higher classification accuracies over all test sites and in different years, respectively. This makes this approach distinct from the single classifier algorithms, which performed different and showed a higher variability in class-wise accuracies. Further, the proposed classifier combination scheme performed better when using small training set sizes or when applied to small input datasets, respectively. A framework was proposed to quantitatively define pixel size requirements for crop identification via image classification. That framework is based on simulating how agricultural landscapes, and more specifically the fields covered by one crop of interest, are seen by instruments with increasingly coarser resolving power. The concept of crop specific pixel purity, defined as the degree of homogeneity of the signal encoded in a pixel with respect to the target crop type, is used to analyse how mixed the pixels can be (as they become coarser) without undermining their capacity to describe the desired surface properties (e.g. to distinguish crop classes via supervised or unsupervised image classification). This tool can be modulated using different parameterizations to explore trade-offs between pixel size and pixel purity when addressing the question of crop identification. Inputs to the experiments were eight multi-temporal images from the RapidEye sensor. Simulated pixel sizes ranged from 13 m to 747.5 m, in increments of 6.5 m. Constraining parameters for crop identification were defined by setting thresholds for classification accuracy and uncertainty. Results over irrigated agricultural landscapes in Middle Asia demonstrate that the task of finding the optimum pixel size did not have a "one-size-fits-all" solution. The resulting values for pixel size and purity that were suitable for crop identification proved to be specific to a given landscape, and for each crop they differed across different landscapes. Over the same time series, different crops were not identifiable simultaneously in the season and these requirements further changed over the years, reflecting the different agro-ecological conditions the investigated crops were growing in. Results further indicate that map quality (e.g. classification accuracy) was not homogeneously distributed in a landscape, but that it depended on the spatial structures and the pixel size, respectively. The proposed framework is generic and can be applied to any agricultural landscape, thereby potentially serving to guide recommendations for designing dedicated EO missions that can satisfy the requirements in terms of pixel size to identify and discriminate crop types. Regarding the operationalization of EO-based techniques for agricultural monitoring and its application to a broader range of agricultural landscapes, it can be noted that, despite the high performance of existing methods (e.g. classifier algorithms), transferability and stability of such methods remain one important research issue. This means that methods developed and tested in one place might not necessarily be portable to another place or over several years, respectively. Specifically in Middle Asia, which was selected as study region in this thesis, classifier combination makes sense due to its easy implementation and because it enhanced classification accuracy for classes with insufficient training samples. This observation makes it interesting for operational contexts and when field reference data availability is limited. Similar to the transferability of methods, the application of only one certain kind of EO data (e.g. with one specific pixel size) over different landscapes needs to be revisited and the synergistic use of multi-scale data, e.g. combining remote sensing imagery of both fine and coarse spatial resolution, should be fostered. The necessity to predict and control the effects of spatial and temporal scale on crop classification is recognized here as a major goal to achieve in EO-based agricultural monitoring.},
  subject      = {Fernerkundung},
  language  = {en}
}
@phdthesis{Nube2013,
  author    = {Nube, Jacqueline Sui Lin},
  title     = {Comparative Analysis of Vaccinia Virus-Encoded Markers Reflecting Actual Viral Titres in Oncolytic Virotherapy},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-85689},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {Using viruses to treat cancer is a novel approach to an age-old disease. Oncolytic viruses are native or recombinant viruses that have the innate or enhanced capability to infect tumour cells, replicate within the tumour microenvironment and subsequently lyse those cells. One representative, the vaccinia virus (VACV), belongs to the orthopoxvirus genus of the Poxviridae family. GLV-1h68, a recombinant and attenuated vaccinia virus devel- oped by the Genelux Corporation, is a member of this family currently being tested in various phase I/II clinical trials under the name GL-ONC1. It has been shown to specif- ically replicate in tumour cells while sparing healthy tissue and to metabolise prodrug at or transport immunological payloads to the site of affliction. Since imaging modalities offer little insight into viral replication deep within the body, and because oncolytic virotherapy is dependent on replication within the target tissue, the need for a monitoring system is evident. Pharmacokinetic analysis of this oncolytic agent was to give insight into the dynamics present in tumours during treatment. This, in turn, would give clinicians the opportunity to monitor the efficacy as early as possible after the onset of treatment, to observe treatment progression and possibly to gauge prognosis, without resorting to invasive procedures, e.g. biopsies. A criteria for viable biomarkers was that it had to be directly dependent on viral replica- tion. Ideally, a marker for treatment efficacy would be specific to the treatment modality, not necessarily the treatment type. Such a marker would be highly detectable (high sen- sitivity), specific for the treatment (high specificity), and present in an easily obtained specimen (blood). Taking this into consideration, the biomarkers were chosen for their potential to be indicators of viral replication. Thus, the biomarkers analysed in this thesis are: the native proteins expressed by the viral genes A27L and B5R, the virally encoded recombinant proteins β-galactosidase, β-glucuronidase, green fluorescent protein (GFP), carboxypeptidase G2 (CPG2) and carcinoembryonic antigen (CEA). Each marker is under the control of one of five different promoters present. All recombinant viruses used in this thesis express A27L, B5R, GFP and β-glucuronidase and all are derived from the parental virus GLV-1h68. In addition to these markers, GLV-1h68 expresses β-galactosidase; GLV-1h181 expresses CPG2. [...]},
  subject      = {Onkolyse},
  language  = {en}
}
@phdthesis{Fritsch2013,
  author    = {Fritsch, Sebastian},
  title     = {Spatial and temporal patterns of crop yield and marginal land in the Aral Sea Basin: derivation by combining multi-scale and multi-temporal remote sensing data with alight use efficiency model},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-87939},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {Irrigated agriculture in the Khorezm region in the arid inner Aral Sea Basin faces enormous challenges due to a legacy of cotton monoculture and non-sustainable water use. Regional crop growth monitoring and yield estimation continuously gain in importance, especially with regard to climate change and food security issues. Remote sensing is the ideal tool for regional-scale analysis, especially in regions where ground-truth data collection is difficult and data availability is scarce. New satellite systems promise higher spatial and temporal resolutions. So-called light use efficiency (LUE) models are based on the fraction of photosynthetic active radiation absorbed by vegetation (FPAR), a biophysical parameter that can be derived from satellite measurements. The general objective of this thesis was to use satellite data, in conjunction with an adapted LUE model, for inferring crop yield of cotton and rice at field (6.5 m) and regional (250 m) scale for multiple years (2003-2009), in order to assess crop yield variations in the study area. Intensive field measurements of FPAR were conducted in the Khorezm region during the growing season 2009. RapidEye imagery was acquired approximately bi-weekly during this time. The normalized difference vegetation index (NDVI) was calculated for all images. Linear regression between image-based NDVI and field-based FPAR was conducted. The analyses resulted in high correlations, and the resulting regression equations were used to generate time series of FPAR at the RapidEye level. RapidEye-based FPAR was subsequently aggregated to the MODIS scale and used to validate the existing MODIS FPAR product. This step was carried out to evaluate the applicability of MODIS FPAR for regional vegetation monitoring. The validation revealed that the MODIS product generally overestimates RapidEye FPAR by about 6 to 15 \%. Mixture of crop types was found to be a problem at the 1 km scale, but less severe at the 250 m scale. Consequently, high resolution FPAR was used to calibrate 8-day, 250 m MODIS NDVI data, this time by linear regression of RapidEye-based FPAR against MODIS-based NDVI. The established FPAR datasets, for both RapidEye and MODIS, were subsequently assimilated into a LUE model as the driving variable. This model operated at both satellite scales, and both required an estimation of further parameters like the photosynthetic active radiation (PAR) or the actual light use efficiency (LUEact). The latter is influenced by crop stress factors like temperature or water stress, which were taken account of in the model. Water stress was especially important, and calculated via the ratio of the actual (ETact) to the potential, crop-specific evapotranspiration (ETc). Results showed that water stress typically occurred between the beginning of May and mid-September and beginning of May and end of July for cotton and rice crops, respectively. The mean water stress showed only minor differences between years. Exceptions occurred in 2008 and 2009, where the mean water stress was higher and lower, respectively. In 2008, this was likely caused by generally reduced water availability in the whole region. Model estimations were evaluated using field-based harvest information (RapidEye) and statistical information at district level (MODIS). The results showed that the model at both the RapidEye and the MODIS scale can estimate regional crop yield with acceptable accuracy. The RMSE for the RapidEye scale amounted to 29.1 \% for cotton and 30.4 \% for rice, respectively. At the MODIS scale, depending on the year and evaluated at Oblast level, the RMSE ranged from 10.5 \% to 23.8 \% for cotton and from -0.4 \% to -19.4 \% for rice. Altogether, the RapidEye scale model slightly underestimated cotton (bias = 0.22) and rice yield (bias = 0.11). The MODIS-scale model, on the other hand, also underestimated official rice yield (bias from 0.01 to 0.87), but overestimated official cotton yield (bias from -0.28 to -0.6). Evaluation of the MODIS scale revealed that predictions were very accurate for some districts, but less for others. The produced crop yield maps indicated that crop yield generally decreases with distance to the river. The lowest yields can be found in the southern districts, close to the desert. From a temporal point of view, there were areas characterized by low crop yields over the span of the seven years investigated. The study at hand showed that light use efficiency-based modeling, based on remote sensing data, is a viable way for regional crop yield prediction. The found accuracies were good within the boundaries of related research. From a methodological viewpoint, the work carried out made several improvements to the existing LUE models reported in the literature, e.g. the calibration of FPAR for the study region using in situ and high resolution RapidEye imagery and the incorporation of crop-specific water stress in the calculation.},
  subject      = {Fernerkundung},
  language  = {en}
}
@phdthesis{Hoiss2013,
  author    = {Hoiß, Bernhard},
  title     = {Effects of climate change, extreme events and management on plants, pollinators and mutualistic interaction networks},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-87919},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {I. Climate change comprises average temperatures rise, changes in the distribution of precipitation and an increased amount and intensity of extreme climatic events in the last decades. Considering these serious changes in the abiotic environment it seems obvious that ecosystems also change. Flora and fauna have to adapt to the fast changing conditions, migrate or go extinct. This might result in shifts in biodiversity, species composition, species interactions and in ecosystem functioning and services. Mountains play an important role in the research of these climate impacts. They are hotspots of biodiversity and can be used as powerful natural experiments as they provide, within short distances, the opportunity to research changes in the ecosystem induced by different climatic contexts. In this dissertation two approaches were pursued: i) surveys of biodiversity, trait dominance and assembly rules in communities depending on the climatic context and different management regimes were conducted (chapters II and III) and ii) the effects of experimental climate treatments on essential ecosystem features along the altitudinal gradient were assessed (chapters IV, V and VI). II. We studied the relative importance of management, an altitudinal climatic gradient and their interactions for plant species richness and the dominance of pollination types in 34 alpine grasslands. Species richness peaked at intermediate temperatures and was higher in grazed grasslands compared to non-managed grasslands. We found the climatic context and also management to influence the distribution and dominance structures of wind- and insect-pollinated plants. Our results indicate that extensive grazing maintains high plant diversity over the full subalpine gradient. Rising temperatures may cause an upward shift of the diversity peak of plants and may also result in changed species composition and adaptive potential of pollination types. III. On the same alpine grasslands we studied the impact of the climatic context along an altitudinal gradient on species richness and community assembly in bee communities. Species richness and abundance declined linearly with increasing altitude. Bee species were more closely related at high altitudes than at low altitudes. The proportion of social and ground-nesting species, as well as mean body size and altitudinal range of bees, increased with increasing altitude, whereas the mean geographic distribution decreased. Our results suggest that community assembly at high altitudes is dominated by environmental filtering effects, while the relative importance of competition increases at low altitudes. We conclude that ongoing climate change poses a threat for alpine specialists with adaptations to cool environments but low competitive capacities. IV. We determined the impacts of short-term climate events on flower phenology and assessed whether those impacts differed between lower and higher altitudes. For that we simulated advanced and delayed snowmelt as well as drought events in a multi site experiment along an altitudinal gradient. Flower phenology was strongly affected by altitude, however, this effect declined through the season. The manipulative treatments caused only few changes in flowering phenology. The effects of advanced snowmelt were significantly greater at higher than at lower sites, but altitude did not influence the effect of the other treatments. The length of flowering duration was not significantly influenced by treatments. Our data indicate a rather low risk of drought events on flowering phenology in the Bavarian Alps. V. Changes in the structure of plant-pollinator networks were assessed along an altitudinal gradient combined with the experimental simulation of potential consequences of climate change: extreme drought events, advanced and delayed snowmelt. We found a trend of decreasing specialisation and therefore increasing complexity in networks with increasing altitude. After advanced snowmelt or drought networks were more specialised especially at higher altitudes compared to control plots. Our results show that changes in the network structures after climate manipulations depend on the climatic context and reveal an increasing susceptibility of plant-pollinator networks with increasing altitude. VI. The aim of this study was to determine the combined effects of extreme climatic events and altitude on leaf CN (carbon to nitrogen) ratios and herbivory rates in different plant guilds. We found no overall effect of climate manipulations (extreme drought events, advanced and delayed snowmelt) on leaf CN ratios and herbivory rates. However, plant guilds differed in CN ratios and herbivory rates and responded differently to altitude. CN ratios of forbs (legume and non-legume) decreased with altitude, whereas CN ratios of grasses increased with altitude. Further, CN ratios and herbivory rates increased during the growing season, indicating a decrease of food plant quality during the growing season. Insect herbivory rates were driven by food plant quality. Contrasting altitudinal responses of forbs versus grasses give reason to expect changed dominance structures among plant guilds with ongoing climate change. VII. This dissertation contributes to the understanding of factors that determine the composition and biotic interactions of communities in different climates. The results presented indicate that warmer climates will not only change species richness but also the assembly-rules for plant and bee communities depending on the species' functional traits. Our investigations provide insights in the resilience of different ecosystem features and processes towards climate change and how this resilience depends on the environmental context. It seems that mutualistic interactions are more susceptible to short-term climate events than flowering phenology and antagonistic interactions such as herbivory. However, to draw more general conclusions more empirical data is needed.},
  subject      = {Klima{\"a}nderung},
  language  = {en}
}
@phdthesis{Heydenreich2013,
  author    = {Heydenreich, Nadine},
  title     = {Studies on the contact-kinin system and macrophage activation in experimental focal cerebral ischemia},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-94534},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {Traditionally, ischemic stroke has been regarded as the mere consequence of cessation of cerebral blood flow, e.g. due to the thromboembolic occlusion of a major brain supplying vessel. However, the simple restoration of blood flow via thrombolysis and/or mechanical recanalization alone often does not guarantee a good functional outcome. It appears that secondary detrimental processes are triggered by hypoxia and reoxygenation, which are referred to as ischemia/reperfusion (I/R) injury. During recent years it became evident that, beside thrombosis inflammation and edema formation are key players in the pathophysiology of cerebral ischemia. The contact-kinin system represents an interface between thrombotic, inflammatory and edematous circuits. It connects the intrinsic coagulation pathway with the plasma kallikrein-kinin system (KKS) via coagulation factor FXII. The serine protease inhibitor C1-inhibitor (C1-INH) has a wide spectrum of inhibitory activities and counteracts activation of the contact-kinin system at multiple levels. The first part of the thesis aimed to multimodally interfere with infarct development by C1-INH and to analyze modes of actions of human plasma derived C1-INH Berinert® P in a murine model of focal cerebral ischemia. It was shown that C57BL/6 mice following early application of 15.0 units (U) C1-INH, but not 7.5 U developed reduced brain infarctions by ~60\% and less neurological deficits in the model of transient occlusion of the middle cerebral artery (tMCAO). This protective effect was preserved at more advanced stages of infarction (day 7), without increasing the risk of intracerebral bleeding or affecting normal hemostasis. Less neurological deficits could also be observed with delayed C1-INH treatment, whereas no improvement was achieved in the model of permanent MCAO (pMCAO). Blood-brain-barrier (BBB) damage, inflammation and thrombosis were significantly improved following 15.0 U C1-INH application early after onset of ischemia. Based on its strong antiedematous, antiinflammatory and antithrombotic properties C1-INH constitutes a multifaceted therapeutic compound that protects from ischemic neurodegeneration in 'clinically meaningful' settings. The second part of the thesis addresses the still elusive functional role of macrophages in the early phase of stroke, especially the role of the macrophage-specific adhesion molecule sialoadhesin (Sn). For the first time, sialoadhesin null (Sn-/-) mice, homozygous deficient for Sn on macrophages were subjected to tMCAO to assess the clinical outcome. Neurological and motor function was significantly improved in Sn-/- mice on day 1 after ischemic stroke compared with wildtype (Sn+/+) animals. These clinical improvements were clearly detectable even on day 3 following tMCAO. Infarctions on day 1 were roughly the same size as in Sn+/+ mice and did not grow until day 3. No intracerebral bleeding could be detected at any time point of data acquisition. Twenty four hours after ischemia a strong induction of Sn was detectable in Sn+/+ mice, which was previously observed only on perivascular macrophages in the normal brain. Deletion of Sn on macrophages resulted in less disturbance of the BBB and a reduced number of CD11b+ (specific marker for macrophages/microglia) cells, which, however, was not associated with altered expression levels of inflammatory cytokines. To further analyze the function of macrophages following stroke this thesis took advantage of LysM-Cre+/-/IKK2-/- mice bearing a nuclear factor (NF)-ϰB activation defect in the myeloid lineage, including macrophages. Consequently, macrophages were not able to synthesize inflammatory cytokines under the control of NF-ϰB. Surprisingly, infarct sizes and neurological deficits upon tMCAO were roughly the same in conditional knockout mice and respective wildtype littermates. These findings provide evidence that macrophages do not contribute to tissue damage and neurological deficits, at least, not by release of inflammatory cytokines in the early phase of cerebral ischemia. In contrast, Sn which is initially expressed on perivascular macrophages and upregulated on macrophages/microglia within the parenchyma following stroke, influenced functional outcome.},
  subject      = {Blut-Hirn-Schranke},
  language  = {en}
}