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The use of agricultural plastic covers has become common practice for its agronomic benefits such as improving yields and crop quality, managing harvest times better, and increasing pesticide and water use efficiency. However, plastic covers are suspected of partially breaking down into smaller debris and thereby contributing to soil pollution with microplastics. A better understanding of the sources and fate of plastic debris in terrestrial systems has so far been hindered by the lack of adequate analytical techniques for the mass-based and polymer-selective quantification of plastic debris in soil. The aim of this dissertation was thus to assess, develop, and validate thermoanalytical methods for the mass-based quantification of relevant polymers in and around agricultural fields previously covered with fleeces, perforated foils, and plastic mulches. Thermogravimetry/mass spectrometry (TGA/MS) enabled direct plastic analyses of 50 mg of soil without any sample preparation. With polyethylene terephthalate (PET) as a preliminary model, the method limit of detection (LOD) was 0.7 g kg−1. But the missing chromatographic separation complicated the quantification of polymer mixtures. Therefore, a pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) method was developed that additionally exploited the selective solubility of polymers in specific solvents prior to analysis. By dissolving polyethylene (PE), polypropylene (PP), and polystyrene (PS) in a mixture of 1,2,4-trichlorobenzene and p-xylene after density separation, up to 50 g soil became amenable to routine plastic analysis. Method LODs were 0.7–3.3 mg kg−1, and the recovery of 20 mg kg−1 PE, PP, and PS from a reference loamy sand was 86–105%. In the reference silty clay, however, poor PS recoveries, potentially induced by the additional separation step, suggested a qualitative evaluation of PS. Yet, the new solvent-based Py-GC/MS method enabled a first exploratory screening of plastic-covered soil. It revealed PE, PP, and PS contents above LOD in six of eight fields (6% of all samples). In three fields, PE levels of 3–35 mg kg−1 were associated with the use of 40 μm thin perforated foils. By contrast, 50 μm PE films were not shown to induce plastic levels above LOD. PP and PS contents of 5–19 mg kg−1 were restricted to single observations in four fields and potentially originated from littering. The results suggest that the short-term use of thicker and more durable plastic covers should be preferred to limit plastic emissions and accumulation in soil. By providing mass-based information on the distribution of the three most common plastics in agricultural soil, this work may facilitate comparisons with modeling and effect data and thus contribute to a better risk assessment and regulation of plastics. However, the fate of plastic debris in the terrestrial environment remains incompletely understood and needs to be scrutinized in future, more systematic research. This should include the study of aging processes, the interaction of plastics with other organic and inorganic compounds, and the environmental impact of biodegradable plastics and nanoplastics.
In the last decades, it became evident that the world is facing an unprecedented, human-induced global biodiversity crisis with amphibians being one of the most threatened species groups. About 41% of the amphibian species are classified as endangered by the IUCN, but even in amphibian species that are listed as "least concern", population declines can be observed on a local level. With land-use change and agrochemicals (i.e. pesticides), two of the main drivers for this amphibian decline are directly linked to intensive agriculture, which is the dominant landscape type in large parts of Europe. Thus, understanding the situation of amphibians in the agricultural landscape is crucial for conservation measures. In the present thesis, I investigated the effects of viticulture on amphibian populations around Landau in der Pfalz (Germany) in terms of habitat use, pesticide exposure, biometric traits as well as genetic and age structure. From the perspective of amphibians, land-use change means usually the destruction of habitats in agricultural landscapes, which often leads to landscape fragmentation. Thus, I followed the question if also vineyards lead to the fragmentation of the landscape and if pesticides that are frequently used in viticulture have to be considered as a factor too, so if there is a chemical landscape fragmentation. Using telemetry, I could show that common toads (Bufo bufo) can be found directly in vineyards, but that they tend to avoid them as habitat. Analysing the genetic structure of common frogs (Rana temporaria) revealed that vineyards have to be considered as a barrier for amphibians. To identify if pesticides contribute to the resulting landscape fragmentation, I conducted an arena choice experiment in the laboratory in which I found evidence for an avoidance of pesticide-contaminated soil. Such an avoidance could be one of the underlying reasons for a potential chemical landscape fragmentation. By combining telemetry data with information about pesticide applications from local wine growers, I could show that a large part of the common toads is likely to come in contact with pesticides. Further, I demonstrated that the agricultural landscape, probably due to the application of pesticides, can have negative effects on the reproduction capacity of common toads. By studying palmate newts (Lissotriton helveticus) I found that adult newts from agricultural ponds are smaller than those from forest ponds. As I did not find differences in the age structure and growth, these differences might be carry-over effects from earlier life stages. While agricultural ponds might be suitable habitats for adult palmate newts, the potential carry-over effect indicates suboptimal conditions for larvae and/or juveniles. I conclude that the best management measure for sustaining amphibians in the agricultural landscape would be a heterogeneous cultural landscape with a mosaic of different habitat patches that work without or at least a reduced amount of pesticides. Green corridors between populations and different habitats would allow migrating individuals to avoid agricultural and thus pesticide-contaminated areas. This would reduce the pesticide exposure risk of amphibians, while preventing the fragmentation of the landscape and thus the isolation of populations.
Agricultural intensification is leading to a severe decline in farmland biodiversity worldwide. The resulting landscape simplification through the expansion of monocultures and removal of non-crop habitats has a major impact on arthropod communities in agricultural landscapes. While arable fields are often highly disturbed and ephemeral habitats that are unsuitable for many species, non-crop habitats in agroecosystems can provide important refugia. The creation of non-crop habitats through agri-environmental schemes (AES) in intensive agricultural landscapes, such as the ‘Maifeld’ region in western Germany, is intended to mitigate the negative effects of agricultural intensification, although the effectiveness of these measures for nature conservation is still controversial. Therefore, this work focuses on the taxonomic and functional diversity of beetles (Coleoptera) and spiders (Araneida), being important providers of ecosystem services, between wheat fields and different non-crop habitats, namely grassy field margins adjacent to wheat and oilseed rape fields, small- and large-scale set-aside areas sown with wildflowers, and permanent grassland fallows. Arthropods were collected between 2019 and 2020 using pitfall traps and suction sampling. Land-use type influenced beetle and spider diversity in the study area, with significantly higher values in grassland fallows than wheat fields. Surprisingly, species diversity differed little among all non-crop habitats, but all harboured distinct species assemblages. In particular, large long-term grassland fallows showed the largest within-group variation of beetle and spider assemblages and represented important habitats, especially for habitat specialists and threatened species, likely due to their variable soil moisture and complex habitat structure. In contrast, the homogeneous arthropod assemblages of wheat fields exhibited lower trait richness and were dominated by a few predatory species adapted to such disturbed, man-made habitats. Interestingly, all conservation measures complemented each other in that they contributed in different ways to supporting beetles and spiders in agricultural landscapes. Even small-scale non-crop habitats and existing habitat boundaries in an agricultural matrix appear to be valuable habitats for farmland arthropods by enhancing taxonomic diversity. Field margins and small wildflower-sown patches can link isolated non-crop habitats and contribute to a heterogeneous agricultural landscape. Consequently, a combination of various small- and large-scale greening measures leads to increased compositional and configurational landscape heterogeneity, resulting in improved beetle and spider diversity. Considering the ongoing loss of farmland biodiversity worldwide, agri-environmental schemes should be promoted in the future, as they are particularly important for arthropod conservation in intensive agricultural landscapes such as the Maifeld region.
To render the surface of a material capable of withstanding mechanical and electrochemical loads, and to perform well in service, the deposition of a thin film or coating is a solution. In this project, such a thin film deposition is carried out. The coating material chosen is titanium nitride (TiN) which is a ceramic material known to possess a high hardness (>10 GPa) as well as good corrosion resistance. The method of deposition selected is high power impulse magnetron sputtering (HiPIMS) that results in coatings with high quality and enhanced properties. Sputtering is a physical process that represents the removal or dislodgment of surface atoms by energetic particle bombardment. The term magnetron indicates that a magnetic field is utilized to increase the efficiency of the sputtering process. In HiPIMS, a high power is applied in pulses of low duty cycles to a cathode that is sputtered and that consists of the coating material. As result of the high power, the ionization of the sputtered material takes place giving the possibility to control these species with electric and magnetic field allowing thereby the improvement and tuning of coating properties. However, the drawback of HiPIMS is a low deposition rate.
In this project, it is demonstrated first that it is possible to deposit TiN coating using HiPIMS with an optimized deposition rate, by varying the magnetic field strength. It was found that low magnetic field strength (here 22mT) results in a deposition rate similar to that of conventional magnetron sputtering in which the average power is applied continuously, called also direct current magnetron sputtering (dcMS). The high deposition rate at low magnetic field strength was attributed to a reduction in the back attraction probability of the sputtered species. The magnetic field strength did not show noticeable influence on the mechanical properties. The proposed explanation was that the considered peak current density interval 1.22-1.72 A∙cm-2 does not exhibit dramatic changes in the plasma dynamics.
In a second part, using the optimized deposition rate, the optimized chemical composition of TiN was determined. It was shown that the chemical composition of TiN does not significantly influence the corrosion performance but impacts considerably the mechanical properties. It was also shown that the corrosion resistance of the coatings deposited using HiPIMS was higher than that of the coatings deposited using dcMS.
The third study was the effect of annealing post deposition on the properties of TiN coating deposited using HiPIMS. The hardness of the coatings showed a maximum at 400°C reaching 24.8 GPa. Above 400°C however, a lowering of the hardness was measured and was due to the oxidation of TiN which led to the formation of TiN-TiO2 composites with lower mechanical properties.
The coating microscopic properties such as crystal orientation, residual stresses, average grain size were determined from X-ray diffraction data and the roughness was measured using atomic force microscopy. These properties were found to vary with the magnetic field strength, the chemical composition as well as the annealing temperature.
Diet-related effects of antimicrobials in aquatic decomposer-shredder and periphyton-grazer systems
(2022)
Leaf-associated microbial decomposers as well as periphyton serve as important food sources for detritivorous and herbivorous macroinvertebrates (shredders and grazers) in streams. Shredders and grazers, in turn, provide not only collectors with food but also serve as prey for predators. Therefore, decomposer-shredder and periphyton-grazer systems (here summarized as freshwater biofilm-consumer systems) are highly important for the energy and nutrient supply in heterotrophic and autotrophic stream food webs. However, both systems can be affected by chemical stressors, amongst which antimicrobials (e.g., antibiotics, fungicides and algaecides) are of particular concern. Antimicrobials can impair shredders and grazers not only via waterborne exposure (waterborne effect pathway) but also through dietary exposure and microorganism-mediated alterations in the food quality of their diet (dietary effect pathway). Even though the relevance of the latter pathway received more attention in recent years, little is known about the mechanisms that are responsible for the observed effects in shredders and grazers. Therefore, the first objective of this thesis was to broaden the knowledge of indirect antimicrobial effects in a model shredder and grazer via the dietary pathway. Moreover, although freshwater biofilm-consumer systems are most likely exposed to antimicrobial mixtures comprised of different stressor groups, virtually nothing is known of these mixture effects in both systems. Therefore, the second objective was to assess and predict diet-related antimicrobial mixture effects in a model freshwater biofilm-consumer system. During this thesis, positive diet-related effects of a model antibiotic on the energy processing and physiology of the shredder Gammarus fossarum were observed. They were probably triggered by shifts in the leaf-associated microbial community in favor of aquatic fungi that increased the food quality of leaves for the shredder. Contrary to that, a model fungicide induced negative effects on the energy processing of G. fossarum via the dietary pathway, which can be explained by negative impacts on the microbial decomposition efficiency leading to a reduced food quality of leaf litter for gammarids. For diet-related antimicrobial effects in periphyton-grazer systems, a model algaecide altered the periphyton community composition by increasing nutritious and palatable algae. This resulted in an enhanced consumption and physiological fitness of the grazer Physella acuta. Finally, it was shown that complex horizontal interactions among leaf-associated microorganisms are involved, making diet-related antimicrobial mixture effects in the shredder G. fossarum difficult to predict. Thus, this thesis provides new insights into indirect diet-related effects of antimicrobials on shredders and grazers as well as demonstrates uncertainties of antimicrobial mixture effect predictions for freshwater biofilm-consumer systems. Moreover, the findings in this thesis are not only informative for regulatory authorities, as indirect effects and effects of mixtures across chemical classes are not considered in the environmental risk assessment of chemical substances, but also stimulate future research to close knowledge gaps identified during this work.
The presented study was motivated by the dynamic phenomena observed in basic catalytic surface reactions, especially by bi- and tristability, and the interactions between these stable states. In this regard, three reaction-diffusion models were developed and examined using bifurcation theory and numerical simulations.
A first model was designed to extend the bistable CO oxidation on Ir(111) to include hydrogen and its oxidation. The differential equation system was analyzed within the framework of bifurcation theory, revealing three branches of stable solutions.
One state is characterized by high formation rates (upper rate state, UR), while the other two branches display low formation rates (lower rate (LR) \& very low rate (VLR) states).
The overlapping branches form the shape of a `swallowtail', the curve of saddle-node bifurcations forming two cusps. Increasing the temperature leads to a subsequent unfolding and hence decreases the system complexity.
A series of numerical simulations representing possible experiments was conducted to illustrate the experimental accessibility (or the lack) of said states. Relaxation experiments show partially long decay times. Quasistatic scanning illustrates the existence of all three states within the tristable regime and their respective conversion once crossing a fold.
A first attempt regarding the state dominance in reaction-diffusion fronts was done. While UR seems to dominate in 1D, a 2D time-evolution shows that LR invades the interphase between UR and VLR.
Subsequently, a generic monospecies mock model was used for the comprehensive study of reaction-diffusion fronts. A quintic polynomial as reaction term was chosen, derived by the sixth-order potential associated with the `butterfly bifurcation'. This ensures up to three stable solutions($u_{0}$,$u_{1}$,$u_{2}$), depending on the four-dimensional parameter space.
The model was explored extensively, identifying regions with similar behaviors.
A term for the front velocity connecting two stable states was derived, depending only on the relative difference of the states' potential wells.
Equipotential curves were found, where the front velocity vanishes of a given front. Numerical simulations on a two-dimensional, finite disk using a triangulated mesh supported these findings.
Additionally, the front-splitting instability was observed for certain parameters. The front solution $u_{02}$ becomes unstable and divides into $u_{01}$ and $u_{12}$, exhibiting different front velocities. A good estimate for the limit of the front splitting region was given and tested using time evolutions.
Finally, the established mock model was modified from continuous to discrete space, utilizing a simple domain in 1D and three different lattices in 2D (square, hexagonal, triangular).
For low diffusivities or large distances between coupling nodes, fronts can become pinned, if the parameters are within range of the equipotential lines. This phenomenon is known as propagation failure and its extent in parameter space was explored in 1D. In 2D, an estimate was given for remarkable front orientations respective to the lattice using a pseudo-2D approximation. Near the pinning region, front velocities differ significantly from the continuous expectation as the shape of the curve potential becomes significant. Factors that decide the size and shape of the pinning regions are the coupling strength, the lattice, the front orientation relative to the lattice, and the front itself. The bifurcation diagram shows a snaking curve in the pinning region, each alternating branch representing a stable or unstable frozen front solution. Numerical simulations supported the observations concerning propagation failure and lattice dependence.
Furthermore, the influence of front orientation on the front velocity was explored in greater detail, showing that fronts with certain lattice-dependent orientations are more or less prone to propagation failure. This leads to the possibility of pattern formation, reflecting the lattice geometry. An attempt to quantify the front movement depending on angular front orientation has shown reasonable results and good agreement with the pseudo-2D approach.
Invasive species play increasing roles worldwide. Invasions are considered successful when species establish and spread in their exotic range. Subsequently, dispersal is a major determinant of species’ range dynamics. Mermessus trilobatus, native to North America, has rapidly spread in Europe via aerial dispersal. Here we investigated the interplay of ecological and evolutionary processes behind its colonisation success.
First, we examined two possible ecological mechanisms. Similar to other invasive invertebrates, the colonisation success of Mermessus trilobatus might be related to human-induced habitat disturbance. Opposite to this expectation, our results showed that densities of Mermessus trilobatus decreased with soil disturbance in grasslands suggesting that its invasion success was not connected to a ruderal strategy. Further, invasive species often escape the ecological pressures from novel enemies in their exotic ranges. Unexpectedly, invasive Mermessus trilobatus was more sensitive to a native predator than native Erigone dentipalpis during our predator susceptibility trials. This indicates that the relation between the invasive spider and its native predator is dominated by prey naïveté rather than enemy release.
The remaining three chapters of the thesis investigated the dispersal behaviour of this invasive species. Hitherto, studies of passive aerial dispersal used wind as the primary dispersal-initiating factor despite a recent demonstration of the effects of the atmospheric electric fields on spiders’ pre-dispersal behaviour. During our experiments, only the wind facilitated the flight, although electric fields induced pre-dispersal behaviour in spiders. Consequently, studies around passive aerial dispersal should control electric fields but use wind as a stimulating factor.
Rapidly expanding species might be disproportionately distributed in their exotic range, with an accumulation of dispersive genotypes at the leading edge of their range. Such imbalanced spatial segregation is possible when the dispersal behaviour of expanding species is heritable. Our results showed that the dispersal traits of Mermessus trilobatus were heritable through both parents and for both sexes with recessive inheritance of high dispersal ability in this species.
Following the heritability experiments, we documented an accelerated spread of Mermessus trilobatus in Europe and tested whether dispersal, reproduction or competing ability was at the source of this pattern. Our results showed that the accumulation of more mobile but not reproductive or competitive genotypes at the expansion front of this invasive species gave rise to an accelerated range expansion by more than 1350 km in under 45 years.
Invasive Mermessus trilobatus is inferior to native sympatric species with respect to competing ability (Eichenberger et al., 2009), disturbance tolerance and predation pressure. Nevertheless, the species successfully established in its exotic range and spread by accelerating its expansion rate. Rapid reproduction that balances the high ecological pressures might be the other potential mechanism behind its colonisation success in Europe and deserves further investigation.
Social networks are ubiquitous structures that we generate and enrich every-day while connecting with people through social media platforms, emails, and any other type of interaction. While these structures are intangible to us, they carry important information. For instance, the political leaning of our friends can be a proxy to identify our own political preferences. Similarly, the credit score of our friends can be decisive in the approval or rejection of our own loans. This explanatory power is being leveraged in public policy, business decision-making and scientific research because it helps machine learning techniques to make accurate predictions. However, these generalizations often benefit the majority of people who shape the general structure of the network, and put in disadvantage under-represented groups by limiting their resources and opportunities. Therefore it is crucial to first understand how social networks form to then verify to what extent their mechanisms of edge formation contribute to reinforce social inequalities in machine learning algorithms.
To this end, in the first part of this thesis, I propose HopRank and Janus two methods to characterize the mechanisms of edge formation in real-world undirected social networks. HopRank is a model of information foraging on networks. Its key component is a biased random walker based on transition probabilities between k-hop neighborhoods. Janus is a Bayesian framework that allows to identify and rank plausible hypotheses of edge formation in cases where nodes possess additional information. In the second part of this thesis, I investigate the implications of these mechanisms - that explain edge formation in social networks - on machine learning. Specifically, I study the influence of homophily, preferential attachment, edge density, fraction of inorities, and the directionality of links on both performance and bias of collective classification, and on the visibility of minorities in top-k ranks. My findings demonstrate a strong correlation between network structure and machine learning outcomes. This suggests that systematic discrimination against certain people can be: (i) anticipated by the type of network, and (ii) mitigated by connecting strategically in the network.
The ongoing loss of species is a global threat to biodiversity, affecting ecosystems worldwide. This also concerns arthropods such as insects and spiders, which are especially endangered in agricultural ecosystems. Here, one of the main causing factors is management intensification. In areas with a high proportion of traditionally managed grassland, extensive hay meadows that are cut only once per year can still hold high levels of biodiversity, but are threatened by conversion into highly productive silage grassland. The Westerwald mountain range, western Germany, is such a region. In this thesis, I compare the local diversity of bees, beetles, hoverflies, leafhoppers, and spiders of five grassland management regimes along a gradient of land-use intensity. These comprise naturally occurring grassland fallows, three types of traditionally managed hay meadows, and intensively used silage grassland. By using three different sampling methods, I recorded ground-dwelling, flower-visiting, and vegetation-dwelling species. The results show that in most cases species richness and diversity are highest on fallows, whereas variation among different managed grassland types is very low. Also, for most sampled taxa, fallows harbour the most distinct species assemblages, while that of other management regimes are largely overlapping. Management has the largest effect on species composition, whereas environmental parameters are of minor importance. Long-term grassland fallows seem to be highly valuable for arthropod conservation, even in a landscape with a low overall land-use intensity, providing structural heterogeneity. In conclusion, such fallows should be subsidized agri-environmental schemes, to preserve insect and spider diversity.
Social media provides a powerful way for people to share opinions and sentiments about a specific topic, allowing others to benefit from these thoughts and feelings. This procedure generates a huge amount of unstructured data, such as texts, images, and references that are constantly increasing through daily comments to related discussions. However, the vast amount of unstructured data presents risks to the information-extraction process, and so decision making becomes highly challenging. This is because data overload may cause the loss of useful data due to its inappropriate presentation and its accumulation. To this extent, this thesis contributed to the field of analyzing and detecting feelings in images and texts. And that by extracting the feelings and opinions hidden in a huge collection of image data and texts on social networks After that, these feelings are classified into positive, negative, or neutral, according to the features of the classified data. The process of extracting these feelings greatly helps in decision-making processes on various topics as will be explained in the first chapter of the thesis. A system has been built that can classify the feelings inherent in the images and texts on social media sites, such as people’s opinions about products and companies, personal posts, and general messages. This thesis begins by introducing a new method of reducing the dimension of text data based on data-mining approaches and then examines the sentiment based on neural and deep neural network classification algorithms. Subsequently, in contrast to sentiment analysis research in text datasets, we examine sentiment expression and polarity classification within and across image datasets by building deep neural networks based on the attention mechanism.