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Premessa
(2021)
Dante e Botticelli
(2021)
We develop a model of optimal carbon taxation and redistribution taking into account horizontal equity concerns by considering heterogeneous energy efficiencies. By deriving first- and second-best rules for policy instruments including carbon taxes, transfers and energy subsidies, we then investigate analytically how horizontal equity is considered in the social welfare maximizing tax structure. We calibrate the model to German household data and a 30 percent emission reduction goal. Our results show that energy-intensive households should receive more redistributive resources than energy-efficient households if and only if social inequality aversion is sufficiently high. We further find that redistribution of carbon tax revenue via household-specific transfers is the first-best policy. Equal per-capita transfers do not suffer from informational problems, but increase mitigation costs by around 15 percent compared to the first- best for unity inequality aversion. Adding renewable energy subsidies or non-linear energy subsidies, reduces mitigation costs further without relying on observability of households’ energy efficiency.
Forschendes Lernen und die digitale Transformation sind zwei der wichtigsten Einflüsse auf die Entwicklung der Hochschuldidaktik im deutschprachigen Raum. Während das forschende Lernen als normative Theorie das sollen beschreibt, geben die digitalen Werkzeuge, alte wie neue, das können in vielen Bereichen vor.
In der vorliegenden Arbeit wird ein Prozessmodell aufgestellt, was den Versuch unternimmt, das forschende Lernen hinsichtlich interaktiver, gruppenbasierter Prozesse zu systematisieren. Basierend auf dem entwickelten Modell wurde ein Softwareprototyp implementiert, der den gesamten Forschungsprozess begleiten kann. Dabei werden Gruppenformation, Feedback- und Reflexionsprozesse und das Peer Assessment mit Bildungstechnologien unterstützt. Die Entwicklungen wurden in einem qualitativen Experiment eingesetzt, um Systemwissen über die Möglichkeiten und Grenzen der digitalen Unterstützung von forschendem Lernen zu gewinnen.
Hacker und Haecksen zählen zur Avantgarde der Computerisierung. Seit den späten 1970er-Jahren bildeten sie sich in der Bundesrepublik und in der DDR zu eigensinnigen ComputernutzerInnen mit einschlägigem Wissen heraus. Sie eigneten sich das Medium spielerisch an, schufen Kontakträume und brachten sich so aktiv in den Prozess der Computerisierung ein. Durch ihre Grenzüberschreitungen zeigten sie dabei Chancen und Risiken der Digitalisierung auf.
Julia Gül Erdogan geht der Entstehung der Hackerkulturen in Ost- und Westdeutschland nach. Sie analysiert, wie deren teils subversive Praktiken Machtgefüge in Politik, Wirtschaft und Gesellschaft herausforderten. Zugleich verdeutlicht die Arbeit Gemeinsamkeiten und Unterschiede der frühen sub- und gegenkulturellen Computernutzung in den beiden deutschen Teilstaaten.
The aim of the doctoral project was to answer the question of whether the structural word-initial noun capitalization, as it can otherwise only be found in Luxembourgish alongside German, has a function that is advantageous for the reader. The overriding hypothesis was that an advantage is achieved by activating a syntactic category, namely the core of a noun phrase, through the parafoveal perception of the capital letters. This perception from the corner of the eye should make it possible to preprocess the following noun. As a result, sentence processing should be facilitated, which should ultimately be reflected in overall faster reading times and fixation durations.
The structure of the project includes three studies, some of which included different participant groups:
Study 1:
Study design: Semantic priming using garden-path sentences should bring out the functionality of noun capitalization for the reader
Participant groups: German natives reading German
Study 2:
Study design: same design as study 1, but in English
Participant groups:
English natives without any knowledge of German reading English
English natives who regularly read German reading English
German with high proficiency in English reading English
Study 3:
Study design:
Influence of the noun frequency on a potential preprocessing using the boundary paradigm; Study languages: German and English
Participant groups:
German natives reading German
English natives without any knowledge of German reading English
German with high proficiency in English reading English
Brief summary: The noun capitalization clearly has an impact on sentence processing in both German and English. It cannot be confirmed that this has a substantial, decisive advantage.
We investigate how the economic consequences of the pandemic, and of the government-mandated measures to contain its spread, affect the self-employed – particularly women – in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are 35% more likely to experience income losses than their male counterparts. Conversely, we do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, i.e. the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.
In den letzten Jahren erlebte der Rechtspopulismus in Europa einen Aufstieg. Die ‚Alternative für Deutschland‘ (AfD) erhielt bei der deutschen Bundestagswahl 2017 beispielsweise 12,7 % der abgegebenen Stimmen und war darüber hinaus gerade im Osten des Landes erfolgreich. Im Rahmen dieser Arbeit wird vergleichend untersucht, welche sprachlichen Manipulationsstrategien der AfD dazu beitragen und wie sie wirken. Die Arbeit gliedert sich grob in zwei Teile: die Analyse des Sprachgebrauchs der AfD und schließlich der Vergleich mit jenem der Nationalsozialist:innen. Ziel der Arbeit ist es nicht, die AfD als Kopie der NSDAP zu entlarven, sondern ihre sprachlichen Manipulationsstrategien im historischen Kontext ergebnisoffen zu analysieren und so ein tieferes Verständnis dieser zu ermöglichen, um eine Grundlage für die zukünftige Erarbeitung möglicher Gegenstrategien zu schaffen.
Dabei stellt sich die Verwendung von diskriminierenden Sprechakten als wesentlicher Teilaspekt der Strategie heraus. So kann aus den Ergebnissen geschlussfolgert werden, dass die Polarisierung der Gesellschaft in zwei Teile (Ingroup und Outgroup) sowie die damit verbundene Diskriminierung der Outgroup als Ziel des Sprachgebrauchs der AfD bezeichnet werden können. Auf diesem Weg kann eine zunehmende Radikalisierung des Sprachgebrauchs innerhalb der letzten Jahre festgestellt werden.
Im zweiten Teil der Arbeit werden im Vergleich mit den Nationalsozialist:innen zahlreiche Parallelen deutlich: Über gemeinsame Stilmittel wie Metaphorik, Verwendung von Superlativen oder bestimmten Begrifflichkeiten hinaus ist hier vor allem die Diskriminierung eines konkreten Feindbildes sowie die angestrebte Spaltung der Bevölkerung zu nennen. Zugleich gilt es auch, die deutlichen Unterschiede zwischen dem Sprachgebrauch im Nationalsozialismus und jenem der AfD zu akzentuieren, um eine ebenso leichtfertige wie unangemessene Gleichsetzung zu verhindern. Zentral ist hier die Eindeutigkeit des Sprachgebrauchs. Die Vergleiche mit verschiedenen Quellen aus dem Dritten Reich verdeutlichen, dass der Sprachgebrauch im Nationalsozialismus direkter und viel radikaler war. Die AfD ist hingegen oftmals darauf bedacht, ihre Aussagen nur augenscheinlich eindeutig zu formulieren, sich insgesamt aber immer eine Möglichkeit des sprachlichen Zurückruderns offen zu halten. Ein offensichtlicher Grund dürften die unterschiedlichen gesellschaftlichen Bedingungen zu beiden Zeiten sein. Für die AfD ist es heute schwieriger, eine ausreichend große Masse an mindestens unsicheren Menschen zu mobilisieren. Begründet werden kann dies mit einer im Vergleich zur Weimarer Republik über Jahrzehnte hinweg gesetzlich, politisch und gesellschaftlich etablierten und sehr stabilen Demokratie. Deshalb ist die AfD darauf angewiesen, eine mehrdeutige Sprache zu verwenden, die ihnen im Bedarfsfall eine Rechtfertigung und somit einen Weg zurück ermöglicht. Darüber hinaus ermöglicht ihnen ein solcher Sprachgebrauch aber auch, sich einerseits gegenüber den Institutionen der Demokratie (beispielsweise dem Verfassungsschutz) zu rechtfertigen und andererseits insbesondere der konservativen Wählerschaft das Gefühl zu geben, dass sie keine rechtsextreme Partei wählen.
Aus den Ergebnissen der Arbeit lässt sich darüber hinaus die These ableiten, dass eine Veränderung des Sprachgebrauchs allein nicht dazu führt, dass Menschen einer Ideologie folgen. Der historische Vergleich deutet aber darauf hin, dass ein diskriminierender Sprachgebrauch zur Entstehung eines Nährbodens einer solchen Ideologie beitragen kann, wenn der gesellschaftliche und politische Rahmen es zulässt. Diesen Rahmen versucht die AfD Stück für Stück in ihrem Sinne zu verschieben. In den letzten Jahren gelang es ihr zunehmend, den öffentlichen Diskurs zu ihren Gunsten mitzubestimmen und zu verändern. Dafür ist der manipulative Gebrauch von Sprache entscheidend. Durch ihn sind sie in der Lage, die ›gefühlte‹ Wahrheit im Kampf gegen Fakten siegen zu lassen und Diskurse wie die Klima-Debatte oder die Diskussionen um Maßnahmen gegen die Coronapandemie zu beeinflussen.
Die Arbeit macht aber auch deutlich, wie kompliziert das Vorhaben der Polarisierung in einer heterogenen Gesellschaft wie der heutigen deutschen ist. Sogar innerhalb der AfD kommt es immer häufiger zu Uneinigkeiten.
In this paper, we study the effect of exogenous global crop price changes on migration from agricultural and non-agricultural households in Sub-Saharan Africa. We show that, similar to the effect of positive local weather shocks, the effect of a locally-relevant global crop price increase on household out-migration depends on the initial household wealth. Higher international producer prices relax the budget constraint of poor agricultural households and facilitate migration. The order of magnitude of a standardized price effect is approx. one third of the standardized effect of a local weather shock. Unlike positive weather shocks, which mostly facilitate internal rural-urban migration, positive income shocks through rising producer prices only increase migration to neighboring African countries, likely due to the simultaneous decrease in real income in nearby urban areas. Finally, we show that while higher producer prices induce conflict, conflict does not play a role for the household decision to send a member as a labor migrant.
"Terrae motus factus est magnus". In diesen und ähnlichen Worten erinnern mittelalterliche Geschichtsschreiber stets an das verspürte Eintreten von Erdbeben. Für die ereignisgeschichtliche Rekonstruktion der historischen Seismizität besitzt das Verständnis, dieser seit dem Frühmittelalter zunehmend standardisiert gebrauchten Narrativen, einen hohen Wert. Daher ist es wichtig, mit den bislang nahezu unerkannt geblieben Intentionen, Vorstellungsstrukturen und Argumentationsstrategien früh- und hochmittelalterlicher Geschichtsschreiber bekannt zu werden. Ausgehend von den antiken Ursprüngen ermittelt diese Arbeit die Bandbreite einer auf "terrae motus" aufbauenden, spezifisch mittelalterlichen Traditionsbildung und setzt sie in den Kontext zum Wissens- und Erfahrungshorizont früh- und hochmittelalterlicher Gelehrter. Erdbeben besaßen ein außerordentliches hermeneutisches Potential für das mittelalterliche Weltverständnis. Somit sind mittelalterliche Erdbebenbeschreibungen hinsichtlich ihrer deskriptiven Qualität und argumentativen Wertigkeit verschieden. Die Historiographie- und Ideengeschichte sowie die seismologische Parametrisierung von mittelalterlichen Erdbeben wird von diesem Wissen gleichermaßen profitieren.
Diabetes is a major public health problem with increasing global prevalence. Type 2 diabetes (T2D), which accounts for 90% of all diagnosed cases, is a complex polygenic disease also modulated by epigenetics and lifestyle factors. For the identification of T2D-associated genes, linkage analyses combined with mouse breeding strategies and bioinformatic tools were useful in the past. In a previous study in which a backcross population of the lean and diabetes-prone dilute brown non-agouti (DBA) mouse and the obese and diabetes-susceptible New Zealand obese (NZO) mouse was characterized, a major diabetes quantitative trait locus (QTL) was identified on chromosome 4. The locus was designated non-insulin dependent diabetes from DBA (Nidd/DBA). The aim of this thesis was (i) to perform a detailed phenotypic characterization of the Nidd/DBA mice, (ii) to further narrow the critical region and (iii) to identify the responsible genetic variant(s) of the Nidd/DBA locus. The phenotypic characterization of recombinant congenic mice carrying a 13.6 Mbp Nidd/DBA fragment with 284 genes presented a gradually worsening metabolic phenotype. Nidd/DBA allele carriers exhibited severe hyperglycemia (~19.9 mM) and impaired glucose clearance at 12 weeks of age. Ex vivo perifusion experiments with islets of 13-week-old congenic mice revealed a tendency towards reduced insulin secretion in homozygous DBA mice. In addition, 16-week-old mice showed a severe loss of β-cells and reduced pancreatic insulin content. Pathway analysis of transcriptome data from islets of congenic mice pointed towards a downregulation of cell survival genes. Morphological analysis of pancreatic sections displayed a reduced number of bi-hormonal cells co-expressing glucagon and insulin in homozygous DBA mice, which could indicate a reduced plasticity of endocrine cells in response to hyperglycemic stress. Further generation and phenotyping of recombinant congenic mice enabled the isolation of a 3.3 Mbp fragment that was still able to induce hyperglycemia and contained 61 genes. Bioinformatic analyses including haplotype mapping, sequence and transcriptome analysis were integrated in order to further reduce the number of candidate genes and to identify the presumable causative gene variant. Four putative candidate genes (Ttc39a, Kti12, Osbpl9, Calr4) were defined, which were either differentially expressed or carried a sequence variant. In addition, in silico ChIP-Seq analyses of the 3.3 Mbp region indicated a high number of SNPs located in active regions of binding sites of β-cell transcription factors. This points towards potentially altered cis-regulatory elements that could be responsible for the phenotype conferred by the Nidd/DBA locus. In summary, the Nidd/DBA locus mediates impaired glucose homeostasis and reduced insulin secretion capacity which finally leads to β-cell death. The downregulation of cell survival genes and reduced plasticity of endocrine cells could further contribute to the β-cell loss. The critical region was narrowed down to a 3.3 Mbp fragment containing 61 genes, of which four might be involved in the development of the diabetogenic Nidd/DBA phenotype.
‘Smart’ Janus emulsions
(2021)
Emulsions constitute one of the most prominent and continuously evolving research areas in Colloid Chemistry, which involves the preparation of mixtures or dispersions of immiscible components in a continuous medium. Besides conventional oil-in-water or water-in-oil emulsions, other emulsions of complex droplet morphologies have recently attracted significant research interests. Especially Janus emulsions, in which each droplet is comprised of two distinct sub-regions, have shown versatile potential applications. One of their advantages is the possibility of compartmentalization, which enables to play with two different chemistries in a single droplet. Though microfluidic methods are conventionally used to prepare Janus emulsions, their industrial applications are largely hindered by low throughput and extensive instrumentations. Recently, it has been discovered that simply one-pot moderate/high energy emulsification is also capable of developing Janus morphology, although their preparation and stabilization remain rather substantially challenging. This cumulative doctoral thesis focuses on the preparation and characterization of ‘smart’ Janus emulsions, i.e. Janus emulsions with special stimuli-responsive features. One-step moderate/high energy emulsification of olive and silicone oil in an aqueous medium was carried out. Special consideration was devoted to the interfacial tensions among the components to maintain the criteria of forming characteristic droplet architectures, in addition to avoiding multiple emulsion destabilization phenomena like imminent phase separation or even separated droplet formation. A series of investigations were conducted related to the formation of complexes of charged macromolecules and role of them as stabilizers to achieve stable Janus emulsions for a realistic timeframe (more than 3 months). The correlation between the size of the stabilizer particles and the droplet size of emulsion was established. Furthermore, it was observed that Janus emulsion gels with interesting rheological properties can be fabricated in the presence of suitable polyelectrolyte complexes. Janus emulsions that could be influenced by pH, temperature or magnetic field were successfully produced in presence of characteristic stimuli-responsive stabilizers. Afterwards, the effect of these changes was studied by different characterization techniques. The size and morphology could be tuned easily by changing the pH. The incorporation of iron oxide magnetic nanoparticles (synthesized separately by a co-precipitation method) to one component of the Janus emulsion was carried out so that the movement and orientation of the complex droplets in aqueous media could be controlled by an external magnetic field. Additionally, temperature-triggered instantaneous reversible breakdown of Janus droplets was also accomplished. The responses of the Janus droplets by the stimuli were well-documented and explained. Another goal of the present contribution was to exploit this special morphological feature of emulsions as a template for producing porous materials. This was demonstrated by the preparation of ultralight magnetic responsive aerogels, utilizing Janus emulsion gels. The produced aerogels also showed the capacity to separate toxic dye from water. To the best of our knowledge, this is the first example of investigation towards batch scale production of Janus emulsion with such special stimuli-responsive properties by a simple bulk emulsification method.
In the light of climate change, rising demands for agricultural products and the intensification and specialization of agricultural systems, ensuring an adequate and reliable supply of food is fundamental for food security. Maintaining diversity and redundancy has been postulated as one generic principle to increase the resilience of agricultural production and other ecosystem services. For example, if one crop fails due to climate instability and extreme events, others can compensate the losses. Crop diversity might be particularly important if different crops show asynchronous production trends. Furthermore, spatial heterogeneity has been suggested to increase stability at larger scales as production losses in some areas can be buffered by surpluses in undisturbed ones. Besides systematically investigating the mechanisms underlying stability, identifying transformative pathways that foster them is important.
In my thesis, I aim at answering the following questions: (i) How does yield stability differ between nations, regions and farms, and what is the effect of crop diversity on yield stability in relation to agricultural inputs, climate heterogeneity, climate instability and time at the national, regional or farm level? (ii) Is asynchrony between crops a better predictor of production stability than crop diversity? (iii) What is the effect of asynchrony between and within crops on stability and how is it related to crop diversity and space, respectively? (iv) What is the state of the art and what are knowledge gaps in exploring resilience and its multidimensionality in ecological and social-ecological systems with agent-based models and what are potential ways forward?
In the first chapter, I provide the theoretical background for the subsequent analyses. I stress the need to better understand the resilience of social-ecological systems and particularly the stability of agricultural production. Moreover, I introduce diversity and spatial heterogeneity as two prominently discussed resilience mechanisms and describe approaches to assess resilience.
In the second chapter, I combined agriculture and climate data at three levels of organization and spatial extents to investigate yield stability patterns and their relation to crop diversity, fertilizer, irrigation, climate heterogeneity and instability and time of nations globally, regions in Europe and farms in Germany using statistical analyses. Yield stability decreased from the national to the farm level. Several nations and regions substantially contributed to larger-scale stability. Crop diversity was positively associated with yield stability across all three levels of organization. This effect was typically more profound at smaller scales and in variable climates. In addition to crop diversity, climate heterogeneity was an important stabilizing mechanism especially at larger scales. These results confirm the stabilizing effect of crop diversity and spatial heterogeneity, yet their importance depends on the scale and agricultural management.
Building on the findings of the second chapter, I deepened in the third chapter my research on the effect of crop diversity at the national level. In particular, I tested if asynchrony between crops, i.e. between the temporal production patterns of different crops, better predicts agricultural production stability than crop diversity. The stabilizing effect of asynchrony was multiple times higher than the effect of crop diversity, i.e. asynchrony is one important property that can explain why a higher diversity supports the stability of national food production. Therefore, strategies to stabilize agricultural production through crop diversification also need to account for the asynchrony of the crops considered.
The previous chapters suggest that both asynchrony between crops and spatial heterogeneity are important stabilizing mechanisms. In the fourth chapter, I therefore aimed at better understanding the relative importance of asynchrony between and within crops, i.e. between the temporal production patterns of different crops and between the temporal production patterns of different cultivation areas of the same crop. Better understanding their relative importance is important to inform agricultural management decisions, but so far this has been hardly assessed. To address this, I used crop production data to study the effect of asynchrony between and within crops on the stability of agricultural production in regions in Germany and nations in Europe. Both asynchrony between and within crops consistently stabilized agricultural production. Adding crops increased asynchrony between crops, yet this effect levelled off after eight crops in regions in Germany and after four crops in nations in Europe. Combining already ten farms within a region led to high asynchrony within crops, indicating distinct production patters, while this effect was weaker when combining multiple regions within a nation. The results suggest, that both mechanisms need to be considered in agricultural management strategies that strive for more resilient farming systems.
The analyses in the foregoing chapters focused at different levels of organization, scales and factors potentially influencing agricultural stability. However, these statistical analyses are restricted by data availability and investigate correlative relationships, thus they cannot provide a mechanistic understanding of the actual processes underlying resilience. In this regard, agent-based models (ABM) are a promising tool. Besides their ability to measure different properties and to integrate multiple situations through extensive manipulation in a fully controlled system, they can capture the emergence of system resilience from individual interactions and feedbacks across different levels of organization. In the fifth chapter, I therefore reviewed the state of the art and potential knowledge gaps in exploring resilience and its multidimensionality in ecological and social-ecological systems with ABMs. Next, I derived recommendations for a more effective use of ABMs in resilience research. The review suggests that the potential of ABMs is not utilized in most models as they typically focus on a single dimension of resilience and are mostly limited to one reference state, disturbance type and scale. Moreover, only few studies explicitly test the ability of different mechanisms to support resilience. To solve real-world problems related to the resilience of complex systems, ABMs need to assess multiple stability properties for different situations and under consideration of the mechanisms that are hypothesized to render a system resilient.
In the sixth chapter, I discuss the major conclusions that can be drawn from the previous chapters. Moreover, I showcase the use of simulation models to identify management strategies to enhance asynchrony and thus stability, and the potential of ABMs to identify pathways to implement such strategies.
The results of my thesis confirm the stabilizing effect of crop diversity, yet its importance depends on the scale, agricultural management and climate. Moreover, strategies to stabilize agricultural production through crop diversification also need to account for the asynchrony of the crops considered. As spatial heterogeneity and particularly asynchrony within crops strongly enhances stability, integrated management approaches are needed that simultaneously address multiple resilience mechanisms at different levels of organization, scales and time horizons. For example, the simulation suggests that only increasing the number of crops at both the pixel and landscape level avoids trade-offs between asynchrony between and within crops. If their potential is better exploited, agent-based models have the capacity to systematically assess resilience and to identify comprehensive pathways towards resilient farming systems.
The co-occurrence of warm spells and droughts can lead to detrimental socio-economic and ecological impacts, largely surpassing the impacts of either warm spells or droughts alone. We quantify changes in the number of compound warm spells and droughts from 1979 to 2018 in the Mediterranean Basin using the ERA5 data set. We analyse two types of compound events: 1) warm season compound events, which are extreme in absolute terms in the warm season from May to October and 2) year-round deseasonalised compound events, which are extreme in relative terms respective to the time of the year. The number of compound events increases significantly and especially warm spells are increasing strongly – with an annual growth rates of 3.9 (3.5) % for warm season (deseasonalised) compound events and 4.6 (4.4) % for warm spells –, whereas for droughts the change is more ambiguous depending on the applied definition. Therefore, the rise in the number of compound events is primarily driven by temperature changes and not the lack of precipitation. The months July and August show the highest increases in warm season compound events, whereas the highest increases of deseasonalised compound events occur in spring and early summer. This increase in deseasonalised compound events can potentially have a significant impact on the functioning of Mediterranean ecosystems as this is the peak phase of ecosystem productivity and a vital phenophase.
The co-occurrence of warm spells and droughts can lead to detrimental socio-economic and ecological impacts, largely surpassing the impacts of either warm spells or droughts alone. We quantify changes in the number of compound warm spells and droughts from 1979 to 2018 in the Mediterranean Basin using the ERA5 data set. We analyse two types of compound events: 1) warm season compound events, which are extreme in absolute terms in the warm season from May to October and 2) year-round deseasonalised compound events, which are extreme in relative terms respective to the time of the year. The number of compound events increases significantly and especially warm spells are increasing strongly – with an annual growth rates of 3.9 (3.5) % for warm season (deseasonalised) compound events and 4.6 (4.4) % for warm spells –, whereas for droughts the change is more ambiguous depending on the applied definition. Therefore, the rise in the number of compound events is primarily driven by temperature changes and not the lack of precipitation. The months July and August show the highest increases in warm season compound events, whereas the highest increases of deseasonalised compound events occur in spring and early summer. This increase in deseasonalised compound events can potentially have a significant impact on the functioning of Mediterranean ecosystems as this is the peak phase of ecosystem productivity and a vital phenophase.
Arbeit, Religion, Ruf
(2021)
Die Arbeit als Dienstmädchen stellte im Europa des 19. Jahrhunderts die weitverbreitetste Erwerbstätigkeit von Frauen dar. Oft erwies sie sich als die einzige Möglichkeit, trotz mangelnder Schulbildung und fehlender beruflicher Qualifikationen einen Lebensunterhalt zu bestreiten. In der Regel bewarben sich junge Mädchen, die vor der Gründung eines eigenen Haushalts Geld verdienen wollten. Aber auch ältere Frauen, die unverheiratet blieben, waren teils ihr Leben lang auf den Beruf als Dienstbotin angewiesen.
In den jüdischen Bürgerhaushalten der Niederlande, insbesondere in den zu dieser Zeit blühenden jüdischen Gemeinden in Amsterdam und anderen Großstädten, sah dies nicht anders aus. Auch dort putzten, kochten und stickten Dienstmädchen. Sie nahmen sich der Kindererziehung an und interagierten mit KollegInnen und ArbeitgeberInnen. Vor allem wegen eines Mangels an schriftlichen Quellen ist bisher jedoch wenig über dieses Kapitel jüdischer und weiblicher Erwerbsgeschichte bekannt.
Die vorliegende Studie wirft mit Hilfe von Stellenanzeigen für und von jüdischen Dienstmädchen Licht auf diese Berufsgruppe in den Jahren zwischen 1894 und 1925. Es wird ein Korpus von 540 Inseraten aus der vielgelesenen niederländischen Wochenzeitung Nieuw Israelietisch Weekblad diskursanalytisch untersucht, was neue Erkenntnisse über Leben und Arbeit der Dienstbotinnen zu Tage fördert. Die Anzeigen thematisieren sowohl das gesellschaftliche Ansehen der Frauen, ihre Aufgaben, Qualifikationen und finanziellen Ansprüche sowie ihre Religiosität. Durch einen Vergleich von Anzeigen aus drei Jahrzehnten kann die Studie aufzeigen, wie sich Einstellungen gegenüber dem Dienstmädchenberuf veränderten und sowohl Angestellte als auch ArbeitgeberInnen im Laufe der Zeit neue Maßstäbe an die häusliche Arbeit anlegten.
Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms that cause extreme impacts, such as crop failure, is of crucial importance to improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers of extreme impacts can be identified using the least absolute shrinkage and selection operator (LASSO) in a model environment, a method that allows for automated variable selection and is able to handle collinearity between variables. As an example of an extreme impact, we investigate crop failure using annual wheat yield as simulated by the Agricultural Production Systems sIMulator (APSIM) crop model driven by 1600 years of daily weather data from a global climate model (EC-Earth) under present-day conditions for the Northern Hemisphere. We then apply LASSO logistic regression to determine which weather conditions during the growing season lead to crop failure. We obtain good model performance in central Europe and the eastern half of the United States, while crop failure years in regions in Asia and the western half of the United States are less accurately predicted. Model performance correlates strongly with annual mean and variability of crop yields; that is, model performance is highest in regions with relatively large annual crop yield mean and variability. Overall, for nearly all grid points, the inclusion of temperature, precipitation and vapour pressure deficit is key to predict crop failure. In addition, meteorological predictors during all seasons are required for a good prediction. These results illustrate the omnipresence of compounding effects of both meteorological drivers and different periods of the growing season for creating crop failure events. Especially vapour pressure deficit and climate extreme indicators such as diurnal temperature range and the number of frost days are selected by the statistical model as relevant predictors for crop failure at most grid points, underlining their overarching relevance. We conclude that the LASSO regression model is a useful tool to automatically detect compound drivers of extreme impacts and could be applied to other weather impacts such as wildfires or floods. As the detected relationships are of purely correlative nature, more detailed analyses are required to establish the causal structure between drivers and impacts.
Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms that cause extreme impacts, such as crop failure, is of crucial importance to improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers of extreme impacts can be identified using the least absolute shrinkage and selection operator (LASSO) in a model environment, a method that allows for automated variable selection and is able to handle collinearity between variables. As an example of an extreme impact, we investigate crop failure using annual wheat yield as simulated by the Agricultural Production Systems sIMulator (APSIM) crop model driven by 1600 years of daily weather data from a global climate model (EC-Earth) under present-day conditions for the Northern Hemisphere. We then apply LASSO logistic regression to determine which weather conditions during the growing season lead to crop failure. We obtain good model performance in central Europe and the eastern half of the United States, while crop failure years in regions in Asia and the western half of the United States are less accurately predicted. Model performance correlates strongly with annual mean and variability of crop yields; that is, model performance is highest in regions with relatively large annual crop yield mean and variability. Overall, for nearly all grid points, the inclusion of temperature, precipitation and vapour pressure deficit is key to predict crop failure. In addition, meteorological predictors during all seasons are required for a good prediction. These results illustrate the omnipresence of compounding effects of both meteorological drivers and different periods of the growing season for creating crop failure events. Especially vapour pressure deficit and climate extreme indicators such as diurnal temperature range and the number of frost days are selected by the statistical model as relevant predictors for crop failure at most grid points, underlining their overarching relevance. We conclude that the LASSO regression model is a useful tool to automatically detect compound drivers of extreme impacts and could be applied to other weather impacts such as wildfires or floods. As the detected relationships are of purely correlative nature, more detailed analyses are required to establish the causal structure between drivers and impacts.
Flooding is a vast problem in many parts of the world, including Europe. It occurs mainly due to extreme weather conditions (e.g. heavy rainfall and snowmelt) and the consequences of flood events can be devastating. Flood risk is mainly defined as a combination of the probability of an event and its potential adverse impacts. Therefore, it covers three major dynamic components: hazard (physical characteristics of a flood event), exposure (people and their physical environment that being exposed to flood), and vulnerability (the elements at risk). Floods are natural phenomena and cannot be fully prevented. However, their risk can be managed and mitigated. For a sound flood risk management and mitigation, a proper risk assessment is needed. First of all, this is attained by a clear understanding of the flood risk dynamics. For instance, human activity may contribute to an increase in flood risk. Anthropogenic climate change causes higher intensity of rainfall and sea level rise and therefore an increase in scale and frequency of the flood events. On the other hand, inappropriate management of risk and structural protection measures may not be very effective for risk reduction. Additionally, due to the growth of number of assets and people within the flood-prone areas, risk increases. To address these issues, the first objective of this thesis is to perform a sensitivity analysis to understand the impacts of changes in each flood risk component on overall risk and further their mutual interactions. A multitude of changes along the risk chain are simulated by regional flood model (RFM) where all processes from atmosphere through catchment and river system to damage mechanisms are taken into consideration. The impacts of changes in risk components are explored by plausible change scenarios for the mesoscale Mulde catchment (sub-basin of the Elbe) in Germany.
A proper risk assessment is ensured by the reasonable representation of the real-world flood event. Traditionally, flood risk is assessed by assuming homogeneous return periods of flood peaks throughout the considered catchment. However, in reality, flood events are spatially heterogeneous and therefore traditional assumption misestimates flood risk especially for large regions. In this thesis, two different studies investigate the importance of spatial dependence in large scale flood risk assessment for different spatial scales. In the first one, the “real” spatial dependence of return period of flood damages is represented by continuous risk modelling approach where spatially coherent patterns of hydrological and meteorological controls (i.e. soil moisture and weather patterns) are included. Further the risk estimations under this modelled dependence assumption are compared with two other assumptions on the spatial dependence of return periods of flood damages: complete dependence (homogeneous return periods) and independence (randomly generated heterogeneous return periods) for the Elbe catchment in Germany. The second study represents the “real” spatial dependence by multivariate dependence models. Similar to the first study, the three different assumptions on the spatial dependence of return periods of flood damages are compared, but at national (United Kingdom and Germany) and continental (Europe) scales. Furthermore, the impacts of the different models, tail dependence, and the structural flood protection level on the flood risk under different spatial dependence assumptions are investigated.
The outcomes of the sensitivity analysis framework suggest that flood risk can vary dramatically as a result of possible change scenarios. The risk components that have not received much attention (e.g. changes in dike systems and in vulnerability) may mask the influence of climate change that is often investigated component.
The results of the spatial dependence research in this thesis further show that the damage under the false assumption of complete dependence is 100 % larger than the damage under the modelled dependence assumption, for the events with return periods greater than approximately 200 years in the Elbe catchment. The complete dependence assumption overestimates the 200-year flood damage, a benchmark indicator for the insurance industry, by 139 %, 188 % and 246 % for the UK, Germany and Europe, respectively. The misestimation of risk under different assumptions can vary from upstream to downstream of the catchment. Besides, tail dependence in the model and flood protection level in the catchments can affect the risk estimation and the differences between different spatial dependence assumptions.
In conclusion, the broader consideration of the risk components, which possibly affect the flood risk in a comprehensive way, and the consideration of the spatial dependence of flood return periods are strongly recommended for a better understanding of flood risk and consequently for a sound flood risk management and mitigation.