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Während es eine Vielzahl von Arbeiten zu der technologischen Entwicklung im Bereich der erneuerbaren Energien gibt, fehlt es jedoch bislang an einer mikroökonomischen Analyse
der Verhaltensmuster der Akteure im Umfeld von Anlagen nach dem EEG. Als Akteure kommen hier in erster Linie der Anlagenbetreiber selbst und der Staat in Betracht.
Im Hinblick auf Anlagenbetrieb und Vergütung der erzeugten Energie können beide mit unterschiedlichsten Interessen und Nutzenkalkülen aufeinander treffen. Diese Arbeit untersucht
mikroökonomische Aspekte des EEG-Förderungssystems. Im Mittelpunkt der Betrachtung stehen die Förderungsmechanismen für Biogasanlagen, die im Hinblick auf mögliche Prinzipal-Agenten-Konflikte einer Untersuchung unterzogen werden.
The role of alternative resources for pollinators and aphid predators in agricultural landscapes
(2021)
The world wide decline of insects is often associated with loss of natural and semi-natural habitat caused by intensified land-use. Many insects provide important ecosystem services to agriculture, such as pest control or pollination. To efficiently promote insects on remaining semi-natural habitat we need precise knowledge of their requirements to non-crop habitat. This thesis focuses on identifying
the most important semi-natural habitats (forest edges, grasslands, and semi-open habitats) for pollinators and natural enemies of crop pests with respect to their food resource requirements. Special
attention is given to floral resources and their spatio-temporal distribution in agricultural landscapes.
Floral resource maps might get closer at characterizing landscapes the way they are experienced by insects compared to classical habitat maps. Performance of the two map types was compared on the prediction of wild bees and natural enemies that consume nectar and pollen, identifying habitats of special importance in the process. In wild bees, influences of spatio-temporal floral resource availability were analysed as well as habitat preferences of specific groups of bees. Understanding dietary needs of natural enemies of crop pests requires additional knowledge on prey use. To this end, ladybird gut contents have been analysed by means of high-throughput sequencing for insight into aphid prey-use.
Results showed, that wild bees were predicted better by floral resource maps compared to classical habitat maps. Forest edge area, as well as floral resources in forest edges had positive effects on abundance and diversity of rare bees and important crop pollinators. Similar patterns were retained for grassland diversity. Especially early floral resources seemed to have positive effects on wild bees. Crops and fruit trees produced a resource pulse in April that exceeded floral resource availability in May and June by tenfold. Most floral resources in forest edges appeared early in the season, with the highest floral density per area. Grasslands provided the lowest amount of floral resources but highest diversity, which was evenly distributed over the season.
Despite natural enemies need for floral resources, classical habitat maps performed better at predicting natural enemies of crop pests compared to floral resource maps. Classical habitat maps revealed a positive effect of forest edge habitat on the abundance of pest enemies, which translated into improved aphid control. Results from gut content analysis reveal high portions of pest aphid species and nettle aphids as well as a broader insight into prey spectra retained from ladybirds collected from sticky traps compared to individuals collected by hand. The aphid specific primer designed for this purpose will be helpful for identifying aphid consumption by ladybirds in future studies.
Findings of this thesis show the potential of floral resource maps for understanding interactions of wild bees and the landscape but also indicate that natural enemies are limited by other resources. I would like to highlight the positive effects of forest edges for different groups of bees as well as natural enemies and their performance on pest control.
In the present study the flora and vegetation of Kakamega Forest, an East African rainforest in Western Kenya, was investigated. Kakamega Forest is highly degraded and fragmented and is an ideal model to study the anthropogenic influence on the forest inventory. The main focus was to analyse the influence of human impact on the vascular plant species composition. During five field phases in the years 2001 to 2004 a total of 19 study sites scattered over the whole forest including all fragments were investigated regarding forest structure, species composition and plant communities. The different forest sites were analysed by three different methods, phytosociological relevés, line-transect and with the variable-area transect method. The forest survey revealed about 400 taxa of vascular plant species, among them 112 trees, 62 shrubs, 58 climbers and 114 herbs. Several species are restricted to this forest in Kenya, but only one endemic species, the herb Commelina albiflora, could be discovered. About 15 species were recorded as new for Kenya and probably at least one species is new to science. Kakamega Forest is a unique mixture of Guineo-Congolian and Afromontane floral elements. About one half of the vascular plant species has its origin in the lowland forests of the Congo basin and one third originates from Afromontane habitats. The present study represents the first description of plant communities of Kakamega Forest. An analysis of different forest sites and plantations resulted in 17 different vegetation units. For the mature forest sites eleven plant communities were described. The young succession stage consists of two plant communities. Since the disturbance history and the age of the different plant communities could be estimated, their chronology was also described. An exception are the study sites within the plantations and afforested sites. The four defined vegetation units were not described as plant communities, because they are highly affected by man and do not belong to the natural succession of Kakamega Forest. Nevertheless, the regeneration potential of such forests was investigated. Due to the different succession stages the changing species composition along a disturbance gradient could be analysed. Most of Kakamega Forest consists of middle-aged secondary forest often surrounded by very young secondary forest. A true primary rainforest could not be found due the massive influence by over-exploitation. In all parts of the forest the anthropogenic influence could be observed. The forest develops towards a climax stage, but a 2 Abstract comparison with former surveys shows that the regeneration is much slower than expected. Human impact has to be avoided to allow the forest to develop into a primary-like rainforest. But several climax tree species might be missing anyway, because after the broad logging activities in the past there are not enough seed trees remaining. Species richness was highest in disturbed forest sites. A mixture of pioneer, climax and bushland species could be recorded there. Therefore, a high species richness is not a suitable indicator for forest quality. The proportion of climax species typical for Kakamega Forest would be a better measure. Compared to the main forest block the forest fragments do not lack in diversity as expected due to fragmentation processes. Instead, the only near primary forest could be recorded in Kisere, a northern fragment. The high amount of climax species and the more or less undisturbed forest structure is a result of the strict protection by the Kenya Wildlife Service and due to low logging activities. Differences in species composition between the studied forest sites are either a result of the different logging history or management regime rather than due to different edaphic or climatic conditions.
For decades a worldwide decline of biological diversity has been reported. Landscapes are influenced by several kinds of anthropogenic disturbances. Agricultural land use, application of fertilizers and pesticides and the removal of corridors simplify and homogenize a landscape whereas others like road constructions lead to fragmentation. Both kinds lead to a constraint of habitats, reduce living environment and gene pool, hinder gene flow and change the functional characteristics of species. Furthermore, it facilitates the introduction of alien species. On the other hand, disturbances of different temporal and spatial dimensions lead to a more diverse landscape because they prevent competitive exclusion and create niches where species are able to coexist.
This study focuses on the complexity of disturbance regimes and its influence on phytodiversity. It differs from other studies that mostly select one or few disturbance types in including all identifiable disturbances. Data were derived from three study sites in the north of Bavaria and are subject to different land-use intensities. Two landscapes underlie agriculture and forestry, of which one is intensively used and the second one rather moderate and small-scaled. The third dataset was collected on an actively used military training area. The first part of the study deals with the influence of disturbance regimes on phytodiversity, first with the focus on military disturbances, afterwards in comparison with the agricultural landscapes. The second part examines the influence of disturbance regimes on red-listed species, the distribution of neophytes and generalist plant species and the homogenization of the landscape. All analyses were conducted on landscape and local scale.
A decisive role was played by the variety of disturbance types, especially in different temporal and spatial dimensions and not by single kinds of disturbances, which significantly was proven in the military training area with its multiple and undirected disturbance regime. Homogeneous disturbance regimes that typically are found in agricultural landscapes led to a reduced species number. On local scale, the abiotic heterogeneity which originated of recent and historical disturbances superimposed the positive effects of disturbance regimes, whereas dry and nutrient-poor sites showed a negative effect. Due to a low tree density and moderate treatment species numbers were significantly higher in forest in the training area than in the two agricultural landscapes.
Numbers of red-listed species were positively correlated to the total number of species in all three sites. However, the military training area showed a significantly higher abundance within the area in comparison to the agricultural landscapes where rare species were mostly found on marginal strips. Furthermore, numbers of neophytes and generalist species were lower and consequently homogenization.
In conclusion, the military training area is an ideal landscape from a nature conservation point of view. The moderately used agricultural area showed high species numbers and agricultural productivity. However, yield is too low to withstand either abandonment or land-use intensification.
Recent estimates have confirmed that inland waters emit a considerable amount of CH4 and CO2 to the atmosphere at the regional and global scale. But these estimates are based on extrapolated measured data and lack of data from inland waters in arid and semi-arid regions and carbon sources from wastewater treatment plants (WWTPs) as well insufficient resolution of the spatiotemporal variability of these emissions.
Through this study, we analyzed monthly hydrological, meteorological and water quality data from three irrigation and drinking water reservoirs in the lower Jordan River basin and estimated the atmospheric emission rates of CO2. We investigated the effect of WWTPs on surrounding aquatic systems in term of CH4 and CO2 emission by presenting seasonally resolved data for dissolved concentrations of both gases in the effluents and in the receiving streams at nine WWTPs in Germany.
We investigated spatiotemporal variability of CH4 and CO2 emission from aquatic ecosystems by using of simple low-cost tools for measuring CO2 flux and bubble release rate from freshwater systems. Our estimates showed that reservoirs in semi-arid regions are oversaturated with CO2 and acted as net sources to the atmosphere. The magnitude of observed fluxes at the three water reservoirs in Jordan is comparable to those from tropical reservoirs (3.3 g CO2 m-2 d-1). The CO2 emission rate from these reservoirs is linked to changes of water surface area, which is the result of water management practices. WWTPs have been shown to discharge a considerable amount of CH4 (30.9±40.7 kg yr-1) and CO2 (0.06±0.05 Gg yr-1) to their surrounding streams, and emission rates of CH4 and CO2 from these streams are significantly enhanced by effluents of WWTPs up to 1.2 and 8.6 times, respectively.
Our results showed that both diffusive flux and bubble release rate varied in time and space, and both of emission pathways should be included and variability should be resolved adequately in further sampling and measuring strategies. We conclude that future emission measurements and estimates from inland waters may consider water management practices, carbon sources from WWTPs as well spatial and temporal variability of emission.
The bio-insecticide Bacillus thuringiensis israelensis (Bti) has worldwide become the most commonly used agentin mosquito control programs that pursue two main objectives: the control of vector-borne diseases and the reduction of nuisance, mainly coming frommosquitoes that emerge in large quantities from seasonal wetlands. The Upper Rhine Valley, a biodiversity hotspot in Germany, has been treated withBti for decades to reduce mosquito-borne nuisance and increase human well-being.Although Btiis presumed to be an environmentally safe agent,adverse effects on wetland ecosystems are still a matter of debate especially when it comes to long-term and indirect effects on non-target organisms. In light of the above, this thesis aims at investigating direct and indirect effects of Bti-based mosquito control on non-target organisms within wetland food chains.Effects were examinedin studies with increasingeco(toxico)logical complexity, ranging from laboratory over mesocosm to field approaches with a focus on the non-biting Chironomidae and amphibian larvae (Rana temporaria, Lissotriton sp.).In addition, public acceptance of environmentally less invasive alternative mosquito control methods was evaluated within surveys among the local population.
Chironomids were the most severely affected non-target aquatic invertebrates. Bti substantially reduced larval and adult chironomid abundances and modified their species composition. Repeated exposures to commonly used Bti formulations induced sublethal alterations of enzymatic biomarkers activityin frog tadpoles. Bti-induced reductions of chironomid prey availability indirectly decreased body size of newts at metamorphosis and increased predation on newt larvae in mesocosm experiments. Indirect effects of severe reductions in midge biomassmight equally be passed through aquatic but also terrestrial food chains influencing predators of higher trophic levels. The majority ofaffectedpeople in the Upper Rhine Valley expressed a high willingness to contributefinancially to environmentally less harmful mosquito control.Alternative approaches could still include Bti applications excepting treatment of ecologically valuable areas. Potentially rising mosquito levels could be counteracted with local acting mosquito traps in domestic and urban areas because mosquito presence was experienced as most annoying in the home environment.
As Bti-based mosquito control can adversely affect wetland ecosystems, its large-scale applications, including nature conservation areas, should be considered more carefully to avoid harmful consequences for the environmentat the Upper Rhine Valley.This thesis emphasizesthe importance to reconsiderthe current practice of mosquito control and encourage research on alternative mosquito control concepts that are endorsed by the local population. In the context ofthe ongoing amphibian and insect declinesfurther human-induced effects onwetlands should be avoided to preserve biodiversity in functioning ecosystems.
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.
Efficient Cochlear Implant (CI) surgery requires prior knowledge of the cochlea’s size and its characteristics. This information helps to select suitable implants for different patients. Registered and fused images helps doctors by providing more informative image that takes advantages of different modalities. The cochlea’s small size and complex structure, in addition to the different resolutions and head positions during imaging, reveals a big challenge for the automated registration of the different image modalities. To obtain an automatic measurement of the cochlea length and the volume size, a segmentation method of cochlea medical images is needed. The goal of this dissertation is to introduce new practical and automatic algorithms for the human cochlea multi-modal 3D image registration, fusion, segmentation and analysis. Two novel methods for automatic cochlea image registration (ACIR) and automatic cochlea analysis (ACA) are introduced. The proposed methods crop the input images to the cochlea part and then align the cropped images to obtain the optimal transformation. After that, this transformation is used to align the original images. ACIR and ACA use Mattes mutual information as similarity metric, the adaptive stochastic gradient descent (ASGD) or the stochastic limited memory Broyden–Fletcher–Goldfarb–Shanno (s-LBFGS) optimizer to estimate the parameters of 3D rigid transform. The second stage of nonrigid registration estimates B-spline coefficients that are used in an atlas-model-based segmentation to extract cochlea scalae and the relative measurements of the input image. The image which has segmentation is aligned to the input image to obtain the non-rigid transformation. After that the segmentation of the first image, in addition to point-models are transformed to the input image. The detailed transformed segmentation provides the scala volume size. Using the transformed point-models, the A-value, the central scala lengths, the lateral and the organ of corti scala tympani lengths are computed. The methods have been tested using clinical 3D images of total 67 patients: from Germany (41 patients) and Egypt (26 patients). The atients are of different ages and gender. The number of images used in the experiments is 217, which are multi-modal 3D clinical images from CT, CBCT, and MRI scanners. The proposed methods are compared to the state of the arts ptimizers related medical image registration methods e.g. fast adaptive stochastic gradient descent (FASGD) and efficient preconditioned tochastic gradient descent (EPSGD). The comparison used the root mean squared distance (RMSE) between the ground truth landmarks and the resulted landmarks. The landmarks are located manually by two experts to represent the round window and the top of the cochlea. After obtaining the transformation using ACIR, the landmarks of the moving image are transformed using the resulted transformation and RMSE of the transformed landmarks, and at the same time the fixed image landmarks are computed. I also used the active length of the cochlea implant electrodes to compute the error aroused by the image artifact, and I found out an error ranged from 0.5 mm to 1.12 mm. ACIR method’s RMSE average was 0.36 mm with a standard deviation (SD) of 0.17 mm. The total time average required for registration of an image pair using ACIR was 4.62 seconds with SD of 1.19 seconds. All experiments are repeated 3 times for justifications. Comparing the RMSE of ACIR2017 and ACIR2020 using paired T-test shows no significant difference (p-value = 0.17). The total RMSE average of ACA method was 0.61 mm with a SD of 0.22 mm. The total time average required for analysing an image was 5.21 seconds with SD of 0.93 seconds. The statistical tests show that there is no difference between the results from automatic A-value method and the manual A-value method (p-value = 0.42). There is no difference also between length’s measurements of the left and the right ear sides (p-value > 0.16). Comparing the results from German and Egypt dataset shows there is no difference when using manual or automatic A-value methods (p-value > 0.20). However, there is a significant difference when using ACA2000 method between the German and the Egyptian results (p-value < 0.001). The average time to obtain the segmentation and all measurements was 5.21 second per image. The cochlea scala tympani volume size ranged from 38.98 mm3 to 57.67 mm3 . The combined scala media and scala vestibuli volume size ranged from 34.98 mm 3 to 49.3 mm 3 . The overall volume size of the cochlea should range from 73.96 mm 3 to 106.97 mm 3 . The lateral wall length of scala tympani ranged from 42.93 mm to 47.19 mm. The organ-of-Corti length of scala tympani ranged from 31.11 mm to 34.08 mm. Using the A-value method, the lateral length of scala tympani ranged from 36.69 mm to 45.91 mm. The organ-of-Corti length of scala tympani ranged from 29.12 mm to 39.05 mm. The length from ACA2020 method can be visualised and has a well-defined endpoints. The ACA2020 method works on different modalities and different images despite the noise level or the resolution. In the other hand, the A-value method works neither on MRI nor noisy images. Hence, ACA2020 method may provide more reliable and accurate measurement than the A-value method. The source-code and the datasets are made publicly available to help reproduction and validation of my result.
Human action recognition from a video has received growing attention in computer vision and has made significant progress in recent years. Action recognition is described as a requirement to decide which human actions appear in videos. The difficulties involved in distinguishing human actions are due to the high complexity of human behaviors as well as appearance variation, motion pattern variation, occlusions, etc. Many applications use human action recognition on captured video from cameras, resulting in video surveillance systems, health monitoring, human-computer interaction, and robotics. Action recognition based on RGB-D data has increasingly drawn more attention to it in recent years. RGB-D data contain color (Red, Green, and Blue (RGB)) and depth data that represent the distance from the sensor to every pixel in the object (object point). The main problem that this thesis deals with is how to automate the classification of specific human activities/actions through RGB-D data. The classification process of these activities utilizes a spatial and temporal structure of actions. Therefore, the goal of this work is to develop algorithms that can distinguish these activities by recognizing low-level and high-level activities of interest from one another. These algorithms are developed by introducing new features and methods using RGB-D data to enhance the detection and recognition of human activities. In this thesis, the most popular state-of-the-art techniques are reviewed, presented, and evaluated. From the literature review, these techniques are categorized into hand-crafted features and deep learning-based approaches. The proposed new action recognition framework is based on these two categories that are approved in this work by embedding novel methods for human action recognition. These methods are based on features extracted from RGB-D data that are
evaluated using machine learning techniques. The presented work of this thesis improves human action recognition in two distinct parts. The first part focuses on improving current successful hand-crafted approaches. It contributes into two significant areas of state-of-the-art: Execute the existing feature detectors, and classify the human action in the 3D spatio-temporal domains by testing a new combination of different feature representations. The contributions of this part are tested based on machine learning techniques that include unsupervised and supervised learning to evaluate this suitability for the task of human action recognition. A k-means clustering represents the unsupervised learning technique, while the supervised learning technique is represented by: Support Vector Machine, Random Forest, K-Nearest Neighbor, Naive Bayes, and Artificial Neural Networks classifiers. The second part focuses on studying the current deep-learning-based approach and how to use it with RGB-D data for the human action recognition task. As the first step of each contribution, an input video is analyzed as a sequence of frames. Then, pre-processing steps are applied to the video frames, like filtering and smoothing methods to remove the noisy data from each frame. Afterward, different motion detection and feature representation methods are used to extract features presented in each frame. The extracted features
are represented by local features, global features, and feature combination besides deep learning methods, e.g., Convolutional Neural Networks. The feature combination achieves an excellent accuracy performance that outperforms other methods on the same RGB-D datasets. All the results from the proposed methods in this thesis are evaluated based on publicly available datasets, which illustrate that using spatiotemporal features can improve the recognition accuracy. The competitive experimental results are achieved overall. In particular, the proposed methods can be better applied to the test set compared to the state-of-the-art methods using the RGB-D datasets.
Im Zentrum der Untersuchung steht die Entwicklung des künstlerischen Siebdrucks in Deutschland seit dem Zweiten Weltkrieg. Nach der thematischen Einführung und einer ersten kritischen Bestandsaufnahme der Forschung zum Siebdruck wird im Folgenden der Verlauf und die methodische Vorgehensweise der Arbeit verdeutlicht. Im zweiten Kapitel „Etablierung einer künstlerischen Technik“ wird zuerst die Geschichte des Siebdrucks dem Rahmen dieser Arbeit gemäß nachgezeichnet. Nachfolgend wird in einem Unterkapitel dargestellt, wie sich die Serigrafie als künstlerisches Verfahren parallel zum industriellen Siebdruck etablierte. In der Folge wendet sich die Untersuchung der Entstehung und Entwicklung des künstlerischen Siebdrucks in Deutschland zu. Dabei wird Willi Baumeister als Beispiel für die erste Generation von Künstlern in Deutschland herangezogen, die sich mit der Serigrafie beschäftigte. Im nächsten Schritt wird ein Überblick zu den Willi Baumeister nachfolgenden deutschen bzw. deutschsprachigen Serigrafie–Künstlern präsentiert. In dem sich anschließenden Exkurs-Kapitel liegt der Schwerpunkt auf der Zusammenarbeit zwischen Künstler und Drucker. Dabei werden an Beispielen namhafter Drucker wie Luitpold Domberger und Hans-Peter Haas unter anderem Einflüsse der Drucker auf die Entstehung und den Ausdruck der Kunstwerke aufgezeigt.Nach einer Einführung in die Entstehung und Geschichte der Serigrafie in Deutschland und einem ersten Überblick über deutsche Serigrafie-Künstler wird im vierten Kapitel der Einsatz der Serigrafie-Technik bei verschiedenen Künstlern aus unterschiedlichen Zeiträumen eingehend untersucht. Besonderes Augenmerk gilt dabei dem Einfluss der Technik auf die Ausdrucksmöglichkeiten und Inhalte der Werke, die Anwendung innerhalb einer und verschiedener Kunstrichtungen sowie die Experimente, die mit der Siebdrucktechnik gemacht wurden. Dazu werden Werke ausgewählter Künstler analysiert. Im Fokus stehen Künstler der Pop Art, des Neuen und des Kritischen Realismus, der Abstrakten und Konkreten Kunst. Ferner werden Künstler, deren Werk durch einen expressiven, bisweilen primitiven Charakter geprägt ist, in die Betrachtung mit einbezogen. Eine weitere Gruppe bilden Künstler, die die Serigrafie in einen Zusammenhang zur Architektur und zum öffentlichen Raum stellen. Die aus der Untersuchung hervorgehenden Ergebnisse dienen insbesondere dazu, die Charakteristika der Technik in ihrer künstlerischen Verwendung herauszustellen und Aspekte einer künstlerisch motivierten Weiterentwicklung aufzuzeigen. Die Entwicklung des druckgraphischen Werkes und der Technik von Gerd Winner werden in Kapitel 5 eingehend untersucht. Auf diese Weise lässt sich eine systematische, nicht rein formale, sondern ästhetische und inhaltliche Darstellung der Serigrafie in Deutschland erstellen. Ein besonderes Augenmerk liegt dabei auf der Frage, wie sich die Technik und deren Neuerungen auf den Inhalt auswirkten.