Refine
Has Fulltext
- yes (165) (remove)
Year of publication
- 2021 (165) (remove)
Document Type
- Doctoral Thesis (165) (remove)
Is part of the Bibliography
- yes (165)
Keywords
- Spektroskopie (4)
- Klimawandel (3)
- Politik (3)
- climate change (3)
- spectroscopy (3)
- 3D-Visualisierung (2)
- Agrarökologie (2)
- Air pollution (2)
- Alpen (2)
- Alps (2)
Institute
- Institut für Physik und Astronomie (24)
- Institut für Geowissenschaften (22)
- Institut für Biochemie und Biologie (20)
- Institut für Chemie (20)
- Hasso-Plattner-Institut für Digital Engineering GmbH (13)
- Institut für Umweltwissenschaften und Geographie (9)
- Wirtschaftswissenschaften (9)
- Institut für Informatik und Computational Science (8)
- Department Psychologie (6)
- Extern (5)
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.
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.
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.
As society paves its way towards device miniaturization and precision medicine, micro-scale actuation and guided transport become increasingly prominent research fields, with high potential impact in both technological and clinical contexts. In order to accomplish directed motion of micron-sized objects, as biosensors and drug-releasing microparticles, towards specific target sites, a promising strategy is the use of living cells as smart biochemically-powered carriers, building the so-called bio-hybrid systems. Inspired by leukocytes, native cells of living organisms efficiently migrating to critical targets as tumor tissue, an emerging concept is to exploit the amoeboid crawling motility of such cells as mean of transport for drug delivery applications.
In the research work described in this thesis, I synergistically applied experimental, computational and theoretical modeling approaches to investigate the behaviour and transport mechanism of a novel kind of bio-hybrid system for active transport at the micro-scale, referred to as cellular truck. This system consists of an amoeboid crawling cell, the carrier, attached to a microparticle, the cargo, which may ideally be drug-loaded for specific therapeutic treatments.
For the purposes of experimental investigation, I employed the amoeba Dictyostelium discoideum as crawling cellular carrier, being a renowned model organism for leukocyte migration and, in general, for eukaryotic cell motility. The performed experiments revealed a complex recurrent cell-cargo relative motion, together with an intermittent motility of the cellular truck as a whole. The evidence suggests the presence of cargoes on amoeboid cells to act as mechanical stimulus leading cell polarization, thus promoting cell motility and giving rise to the observed intermittent dynamics of the truck. Particularly, bursts in cytoskeletal polarity along the cell-cargo axis have been
found to occur in time with a rate dependent on cargo geometrical features, as particle diameter. Overall, the collected experimental evidence pointed out a pivotal role of cell-cargo interactions in the emergent cellular truck motion dynamics. Especially, they can determine the transport capabilities of amoeboid cells, as the cargo size significantly impacts the cytoskeletal activity and repolarization dynamics along the cell-cargo axis, the latter responsible for truck displacement and reorientation.
Furthermore, I developed a modeling framework, built upon the experimental evidence on cellular truck behaviour, that connects the relative dynamics and interactions arising at the truck scale with the actual particle transport dynamics. In fact, numerical simulations of the proposed model successfully reproduced the phenomenology of the cell-cargo system, while enabling the prediction of the transport properties of cellular trucks over larger spatial and temporal scales. The theoretical analysis provided a deeper understanding of the role of cell-cargo interaction on mass transport, unveiling in particular how the long-time transport efficiency is governed by the interplay between the persistence time of cell polarity and time scales of the relative dynamics stemming from cell-cargo interaction. Interestingly, the model predicts the existence of an optimal cargo size, enhancing the diffusivity of cellular trucks; this is in line with previous independent experimental data, which appeared rather counterintuitive and had no explanation prior to this study.
In conclusion, my research work shed light on the importance of cargo-carrier interactions in the context of crawling cell-mediated particle transport, and provides a prototypical, multifaceted framework for the analysis and modelling of such complex bio-hybrid systems and their perspective optimization.
The spread of shrubs in Namibian savannas raises questions about the resilience of these ecosystems to global change. This makes it necessary to understand the past dynamics of the vegetation, since there is no consensus on whether shrub encroachment is a new phenomenon, nor on its main drivers. However, a lack of long-term vegetation datasets for the region and the scarcity of suitable palaeoecological archives, makes reconstructing past vegetation and land cover of the savannas a challenge.
To help meet this challenge, this study addresses three main research questions: 1) is pollen analysis a suitable tool to reflect the vegetation change associated with shrub encroachment in savanna environments? 2) Does the current encroached landscape correspond to an alternative stable state of savanna vegetation? 3) To what extent do pollen-based quantitative vegetation reconstructions reflect changes in past land cover?
The research focuses on north-central Namibia, where despite being the region most affected by shrub invasion, particularly since the 21st century, little is known about the dynamics of this phenomenon.
Field-based vegetation data were compared with modern pollen data to assess their correspondence in terms of composition and diversity along precipitation and grazing intensity gradients. In addition, two sediment cores from Lake Otjikoto were analysed to reveal changes in vegetation composition that have occurred in the region over the past 170 years and their possible drivers. For this, a multiproxy approach (fossil pollen, sedimentary ancient DNA (sedaDNA), biomarkers, compound specific carbon (δ13C) and deuterium (δD) isotopes, bulk carbon isotopes (δ13Corg), grain size, geochemical properties) was applied at high taxonomic and temporal resolution. REVEALS modelling of the fossil pollen record from Lake Otjikoto was run to quantitatively reconstruct past vegetation cover. For this, we first made pollen productivity estimates (PPE) of the most relevant savanna taxa in the region using the extended R-value model and two pollen dispersal options (Gaussian plume model and Lagrangian stochastic model). The REVEALS-based vegetation reconstruction was then validated using remote sensing-based regional vegetation data.
The results show that modern pollen reflects the composition of the vegetation well, but diversity less well. Interestingly, precipitation and grazing explain a significant amount of the compositional change in the pollen and vegetation spectra. The multiproxy record shows that a state change from open Combretum woodland to encroached Terminalia shrubland can occur over a century, and that the transition between states spans around 80 years and is characterized by a unique vegetation composition. This transition is supported by gradual environmental changes induced by management (i.e. broad-scale logging for the mining industry, selective grazing and reduced fire activity associated with intensified farming) and related land-use change. Derived environmental changes (i.e. reduced soil moisture, reduced grass cover, changes in species composition and competitiveness, reduced fire intensity) may have affected the resilience of Combretum open woodlands, making them more susceptible to change to an encroached state by stochastic events such as consecutive years of precipitation and drought, and by high concentrations of pCO2. We assume that the resulting encroached state was further stabilized by feedback mechanisms that favour the establishment and competitiveness of woody vegetation.
The REVEALS-based quantitative estimates of plant taxa indicate the predominance of a semi-open landscape throughout the 20th century and a reduction in grass cover below 50% since the 21st century associated with the spread of encroacher woody taxa. Cover estimates show a close match with regional vegetation data, providing support for the vegetation dynamics inferred from multiproxy analyses. Reasonable PPEs were made for all woody taxa, but not for Poaceae.
In conclusion, pollen analysis is a suitable tool to reconstruct past vegetation dynamics in savannas. However, because pollen cannot identify grasses beyond family level, a multiproxy approach, particularly the use of sedaDNA, is required. I was able to separate stable encroached states from mere woodland phases, and could identify drivers and speculate about related feedbacks. In addition, the REVEALS-based quantitative vegetation reconstruction clearly reflects the magnitude of the changes in the vegetation cover that occurred during the last 130 years, despite the limitations of some PPEs.
This research provides new insights into pollen-vegetation relationships in savannas and highlights the importance of multiproxy approaches when reconstructing past vegetation dynamics in semi-arid environments. It also provides the first time series with sufficient taxonomic resolution to show changes in vegetation composition during shrub encroachment, as well as the first quantitative reconstruction of past land cover in the region. These results help to identify the different stages in savanna dynamics and can be used to calibrate predictive models of vegetation change, which are highly relevant to land management.