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Global environmental changes and the subsequent biodiversity loss has raised concerns over the consequences for the functioning of ecosystems and human well-being. This thesis provides new mechanistic insights into the role of tree diversity in regulating forest productivity and forests’ responses to climate change. The thesis also addresses the overlooked functional role of ecological continuity in mediating ecosystem processes in the context of multiple global environmental changes. The findings of the thesis emphasize the need to retain the functional integrity of forest ecosystem by preserving biodiversity and acknowledging the ecological memory forests.
In this dissertation, advanced nonlinear control strategies and nonlinear minimum-variance observation are combined, in order to improve the estimation and/or tracking quality within control and fault detection tasks, for several types of systems from the fields of electromobility and conventional drivetrain technology that have some potential for sustainability or performance improvements. The application-specific innovations in terms of nonlinear Kalman filter methods are: (1) Improved state of charge estimation for Lithium-ion battery cells, powered by a novel self-adaptive EKF that uses a high-order polynomial curve fit as a decomposition of the uncertain nonlinear output equation with intentionally redundant bases, and with a reduced number of polynomial parameters that are adapted online by the EKF itself. (2) Online estimation of the time delay between two periodic signals of roughly the same shape that have pronounced uncorrelated noise, based on a fractional-order approximation of the transcendent transfer function of the time delay which is used as a model in a novel kind of EKF. (3) Using two (E)KFs (one for the linear subsystem and one for the nonlinear subsystem of a new kind of multi-stage piezo-hydraulic actuator) in a cascaded loop structure in order to reduce the computation load of the estimation, by appropriate 'interfacing' between the two observers (using one shared system model equation, among other aspects). - The innovations in terms of nonlinear control methods are powered by observation, as well: (1) Sliding mode velocity control of a DC drive that is subject to nonlinear friction and unknown load torques, enhanced by an equivalent control law, and with a new intelligent switching gain adaptation scheme (for reduced control chattering and, thus, less energy consumption and actuator wear), which is powered by Taylor-linearized model predictive control, which in turn requires observer-based disturbance compensation (by a KF with a double-integrator disturbance model) for model-matching purposes in order to function correctly. (2) Direct speed control of permanent-magnet three-phase synchronous motors that have a high power-to-volume ratio, based on sliding mode control in a rotating d,q coordinate system, with a new equivalent control method that exploits both system inputs and with a secondary sliding surface to ensure compliance with the current-trajectory of maximum efficiency for the required torque, and which works without measurement of the rotor angle (thanks to a new kind of EKF that estimates all states in the stationary α,β coordinate system, as well as the disturbance/load torque and its derivative). In all instances, improvements (compared to methods existing in the literature) in terms of control and estimation performance have been achieved and confirmed using simulation studies or real experiments.
Educational research has shown that reflection and feedback are crucial for substantial development of pre-service teachers' professional competence. However, reflection and feedback sessions are not a standard element of teaching practicums due to time- and location-constraints. Digital practicum environments can lift these constraints. Digital reflection and feedback environments have typically applied either textual accounts or video sequences of classroom practice, with varying effects. Consequently, the studies presented in this cumulative dissertation are focused on how the use of text- or video-based digital reflection and feedback environments during a practicum influence specific components of pre-service teachers' professional competence (i.e., beliefs about teaching and learning, self-efficacy, professional vision of classroom management, feedback competence). All studies followed a quasi-experimental, pre-test-post-test design. Pre-service teachers at the fourth-semester bachelor level in a German university took part in the studies. Pre-service teachers participated in a four-week teaching practicum at local schools. During the teaching practicum, pre-service teachers were divided into five different groups. The control group (CG) took part in a traditional practicum with live observations and face-to-face reflection and feedback with peers and experts. Pre-service teachers of the intervention groups (IG 1, IG 2, IG 3, IG 4) reflected and received feedback in highly structured text- or video-based digital environments. Intervention groups 1 (IG 1) and 2 (IG 2) participated in a text-based digital reflection and feedback environment. While IG 1 participants only received feedback from peers, IG 2 pre-service teachers also received expert feedback. Intervention groups 3 (IG 3) and 4 (IG 4) took part in a video-based digital reflection and feedback environment. IG 3 pre-service teachers only received peer feedback, whereas IG 4 participants also received expert feedback. Mixed methods were applied by generating quantitative and quantitative-qualitative data was with questionnaires, a standardized video-based test and content analysis. The studies demonstrated that classroom videos and video-based digital reflection and feedback environments can effectively enhance pre-service teachers' professional competence. This finding can be predominantly attributed to two characteristics of the application in the digital reflection and feedback environments: (a) being able to revisit a multitude of authentic teaching situations without time pressure and (b) the degree of decomposition by deliberate, focused practice and scaffolding elements. Furthermore, expert feedback seemed to be of better quality and entailed more substantial effects than peer feedback. The results of the conducted studies on professional vision of classroom management, beliefs about teaching and learning and feedback competence showed that expert feedback can be seen as a lens reducing and focusing classroom complexity, enabling pre-service teachers to perceive crucial teaching situations that would have otherwise gone unnoticed and to benefit from expert modelling of high-quality feedback. Consequently, video-based digital reflection and feedback environments with expert feedback can significantly improve pre-service teachers' professional competence during teaching practicums and, thus, better prepare pre-service teachers for future classroom challenges, leading to better learning environments for school students.
Sustainable landscape development is the main goal of decision makers worldwide. Achieving this goal in the long term leads to achieving social, economic and environmental sustainability. Remote sensing has been playing an essential role in monitoring remote areas. This study has employed part of the role of remote sensing in supporting the direction of decision makers towards sustainable landscape development. The study has focused on some of the main elements affecting sustainable environment: land uses, specifically agricultural land uses, water quality, forests, and water hazards such as floods. Three research programs were undertaken to investigate the role of Terrasar-x imagery, as a source of remote sensing data, in monitoring the environment and achieving the previous stated elements. The investigation was intended to investigate the effectiveness of TSX imagery in identifying the cropping pattern of selected study areas by employing a pixel-based supervised maximum likelihood classifier, as published in Paper I, assessment of the efficiency of using TSX imagery in determining land use and the flood risk maps by applying an object-based decision tree classifier as published in Paper II, and determination of the potential of inferential statistics tests such as the two samples Z-test and multivariate analysis, for example Factor Analysis, for identifying the kind of forest canopy, based on the backscattering coefficient of TSX imagery of forest plots, as presented in Paper III. Papers I and II covered two pilot areas in the Lower Saxonian Elbe Valley Biosphere Reserve “das Biosphärenreservat "Niedersächsische Elbtalaue" around Walmsburger Werder and Wehninger Werder. Paper III focused on the Fuhrberger Feld water protection area near Hanover in Germany. The inputs for this research were mainly SAR Imagery and the ground truth data collected from field surveys, in addition to databases, geo-databases and maps. The study presented in Paper I used two filters to decrease speckle noise namely De-Grandi as multi-temporal speckle filter, and Lee as an adaptive filter. A multi-temporal classification method was used to identify the different crops using a pixel-based maximum likelihood classifier. The classification accuracy was assessed based on the external user accuracy for each crop, the external producer accuracy for each crop, the Kappa index and the external total accuracy for the entire classification. Three cropping pattern maps were produced namely the cropping pattern map of Wehninger Werder in 2011 and the cropping pattern maps of Walmsburger Werder in 2010 and in 2011. The study showed that image filtering was essential for enhancing the accuracy of crop classification. The multi-temporal filter De-Grandi enhanced the producer accuracy by about 10% compared to the Lee filter. Furthermore, gathering and utilizing large ground truth data greatly enhanced the accuracy of the classification. The research verified that using sequence images covering the growing season usually improved the classification results. The results exposed the effect of the polarization and demonstrate that the majority of the classifications produced according to the crop calendar had higher total producer accuracy than using all acquisitions. The study demonstrated undertaken in Paper II applied the decision tree object-based classifier in determining the major land uses and the inundation extent areas in 2011 and 2013 using the Lee-filtered imagery. Based on the maps produced for the land uses and inundation areas, the hazard areas due to the floods in 2011 and 2013 were identified. The study illustrated that 95% of the inundated area was classified correctly, that 90% of vegetated lands were accurately determined, and around 80% of the forest and the residential areas were correctly recognized. The research undertaken in Paper III statistically analyzed the backscattering coefficient of the Lee-filtered TSX in some forest plots by the Factor Analysis and two sample Z-test. The study showed that Factor analysis tools succeeded in differentiating between the coniferous forest and the deciduous forest and mixed forest, but failed to discriminate between the deciduous and the mixed forest. On one hand, only one factor was extracted for each sample plot of the coniferous forest with approximately equal loadings during the whole acquisition period from March 2008 to January 2009. On the other hand, two factors were extracted for each deciduous or mixed forest sample plot, where one factor had high loadings during the leaf-on period from May to October, and the other one had high loadings during the leaf-off period from November to April. Furthermore, the research revealed that the two sample Z-test enabled not only differentiation between the deciduous and the mixed forest against the coniferous forest, but also discrimination between deciduous forest and the mixed forest. Statistically significant differences were observed between the mean backscatter values of the HH-polarized acquisitions for the deciduous forest and the mixed forest during the leaf-off period, but no statistically significant difference was found during the leaf-on period. Moreover, plot samples for the deciduous forest had slightly higher mean backscattering coefficients than those for the mixed forest during the leaf-off period.
Tropical forests worldwide support high biodiversity and contribute to the sustenance of local people’s livelihoods. However, the conservation and sustainability of these forests are threatened by land-use changes and a rapidly increasing human population. This dissertation, therefore, aimed to characterize biodiversity patterns in the moist Afromontane forests of southwestern Ethiopia and to examine how biodiversity patterns are affected by land-use and land-use changes (mediated by coffee management intensity, landscape attributes and housing development) in a context of a rapidly growing rural population. To achieve this goal, the author takes an interdisciplinary approach where, first, she examined the effects of coffee management intensity on diversity patterns of woody plants and birds, spanning a gradient of site-level disturbance from nearly undisturbed forest interior to highly managed shade coffee forests. Results showed that specialized species of woody plants (forest specialists) and birds (forest specialists, insectivores and frugivores) were affected by coffee management intensity. The richness of forest specialist trees and the richness and/or abundance of insectivores, frugivores and forest specialist birds decrease with increasing levels of disturbance. Second, the author investigated the effects of landscape context on woody plants, birds and mammals. Community composition and specialist species of woody plants and birds were sensitive to landscape context, where woody plants responded positively to gradients of edge-interior and birds to gradients of edge-interior and forest cover. Further results showed that a diverse mammal community, with 26 species, occurs at the forest edge of shade coffee forests and that the leopard, an apex predator in the region depended on large areas of natural forest. A closer examination of leopard activity patterns revealed a shift in the diel activity as a response to human disturbance inside the forest, further highlighting the importance of natural undisturbed forests for leopards in the region. Together, these findings demonstrate the value of low managed shade coffee forests for biodiversity, and importantly, emphasize the irreplaceable value of undisturbed natural forests for biodiversity. Third, the researcher investigated the effects of prospective rural population growth (mediated by housing development) on the forest mammal community. Here, population growth was projected to negatively influence several mammal species, including the leopard. Housing development that encroached the forest entailed worse outcomes for biodiversity than a combination of prioritized development in already developed areas and coffee forest protection. Fourth, to understand the motivations behind high human fertility rates in the region, she examined the determinants of women fertility preferences, including their perceptions on social and biophysical stressors affecting local livelihoods such as food insecurity and environmental degradation. Fertility preferences were influenced by underlying social norms and mindsets, a perceived utilitarian value of children and male dominance within the household, and were only marginally affected by perceptions of social and biophysical stressors. The findings suggest the need for new deliberative and culturally sensitive approaches that engage with pervasive social norms to slow down population growth. Overall, this dissertation demonstrates the key value of moist Afromontane forests in southwestern Ethiopia for biodiversity conservation. It indicates the need to promote coffee management practices that reduce forest degradation and highlights that high priority should be given to the conservation of undisturbed natural forests. It also suggests the need to integrate conservation goals with housing development in landscape planning. A promising approach to achieve the above conservation priorities would be the creation of a Biosphere Reserve and to promote the ecological connectivity between the larger forest remnants in the region. Finally, this dissertation demonstrates the importance of placed-based holistic approaches in conservation that consider both proximate and distal drivers of forest biodiversity decline.
The aim of this paper is to determine how a carbon footprint label for grocery products can be designed to facilitate a sustainable consumption behaviour. Therefore, a mixed-method approach was used consisting out of a review of relevant literature and an explorative quantitative survey with n=158 participants. It was found that consumers generally have a positive attitude towards carbon labelling, but they lack understanding of the term, its underlying concepts and the emissions caused by grocery products. In regard to the design criteria of a carbon label, labels with a coloured scale are preferred most by consumers. Also, the mechanisms of consumer behaviour imply that not all parts of the behaviour are visible and controllable for individuals themselves. The concluding concept proposal summarises important criteria of a carbon labelling system that has the goal to educate consumers and facilitate a lower carbon consumption behaviour, such as a simple visual design, the use of a colour scale, a design enabling a comparison, the provision of a link to further information, the public enforcement of the system and overall uniformity.
The wide accessibility of the Internet and web-based programs enable an increased volume of online interventions for mental health treatment. In contrast to traditional face-to-face therapy, online treatment has the potential to overcome some of the barriers such as improved geographical accessibility, individual time planning, and reduced costs. The availability of clients' treatment data fuels research to analyze the collected data to obtain a better understanding of the relationship among symptoms in mental disorders and derive outcome and symptom predictions. This research leads to predictive models that can be integrated into the online treatment process to assist clinicians and clients. This dissertation discusses different aspects of the development of predictive modeling in online treatment: Categorization of predictive models, data analyses for predictive purposes, and model evaluation. Specifically, the categorization of predictive models and barriers against the uptake of mental health treatment are discussed in the first part of this dissertation. Data analysis and predictive modeling are emphasized in the second part by presenting methods for inference and prediction of mood as well as the prediction of treatment outcome and costs. Prediction of future and current mood can be beneficial in many aspects. Inference of users' mood levels based on unobtrusive measures or diary data can provide crucial information for intervention scheduling. Prediction of future mood can be used to assess clients' response to the treatment and expected treatment outcome. Prediction of the expected treatment costs and outcomes for different treatment types allows simultaneous optimization of these objectives and to increase the cost-effectiveness of the treatment. In the third part, a systematic predictive model evaluation incorporating simulation analyses is demonstrated and a method for model parameter estimation for computationally limited devices is presented. This dissertation aims to overcome the current challenges of predictive model development and its use in online treatment. The development of predictive models for varies data collected in online treatment is demonstrated and how these models can be applied in practice. The derived results contribute to computer science and mental health research with client individual data analysis, the development ofpredictive models, and their statistical evaluation.
Establishing the identity of asylum seekers in the absence of credible documents represents a significant challenge for governments. To support decision-making processes in identity determination and verification procedures, Germany’s Federal Office for Migration and Refugees introduced three digital identification systems under the “Integrated Identity Management - plausibility, data quality and security aspects (IDMS)” programme. Because these algorithmic systems are deployed in highly political settings affecting vulnerable populations on the move, this research investigates how the Federal Office legitimises the policy and use of IDM-S that indicate a new direction of governance driven by so-called “innovative technologies”. In this context, legitimacy - considered a core virtue of just, democratic institutions - is understood as a justificatory concept seen in conjunction with (good) governance and the right to privacy as guaranteed under Article 17 of the International Covenant on Civil and Political Rights. The data justice framework is applied to structure the evaluation of state practices. In addition, the qualitative content analysis is used to find patterns in publicly available documents. Expert interviews were carried out to include experiences of affected individuals and to verify identified information provided by the government. The analysis revealed that efforts to legitimise IDM-S included four patterns: referring to the rule of law and national security concerns, non-disclosing delegitimising information and limiting accountability, emphasising performance efficiency and the systems’ high level of innovation, implying objective operations by means of a mathematical-technical approach. The results underscore profound discrepancies between justifications and state practices, outlining severe privacy violations as well as the lack of compliance to qualitative values in governance that pertain to participation, transparency, accountability, impartiality and scientific soundness of state operations.
Viable communication systems
(2020)
Society has come to the point that it requires a "Great Transformation" towards sustainability to ensure the viability of the planet for a vital society. The energy transition plays a central role for this transformation. For transforming the patterns of energy production and use in an energy transition as part of the "Great Transformation", this process of change now needs to strengthen its focus on information, communication, and knowledge systems. Human society needs to establish a knowledge system that has the potential to create usable knowledge for sustainability solutions. This requires organizing a communication system that is sufficiently complex, interconnected, and, at the same time, efficient for integrating reflexive, open-ended, inter- and transdisciplinary learning, evaluation, and knowledge co-production processes across multiple levels. This cumulative dissertation contributes to research in this direction by applying a systemic sustainability perspective on the content and organization of communication in the field of research on sustainable energy and the operational level of municipal climate action as part of the energy transition. Regarding sustainability, this thesis uses strong sustainability and its principles as a frame for evaluating the content of communication. Regarding the systemic perspective, the thesis particularly relies on the following theories: (i) the human-environment system model by R. Scholz as an overarching framework regarding interactions between humans and nature, (ii) social systems theory by N. Luhmann to reflect the complexity of society, (iii) knowledge management to consider the human character of knowledge and a practice-oriented perspective, and (iv) management cybernetics, in particular, the Viable System Model by S. Beer as a framework to analyze and assess organizational structures. Furthermore, the thesis leverages the potential of text mining as a method to identify and visualize patterns in texts that reflect prevalent paradigms in communication. The thesis applies the above conceptual and methodological basis in three case studies. Case Study 1 investigates the measures proposed in 16 municipal climate action plans of regional centers in Lower Saxony, Germany. It uses a text mining approach in the form of an Summary interpretation network analysis. It analyzes how different societal subsystems are connected at the semantic level and to what extent sustainability principles can be recognized. Case Study 2 analyzes and reflects paradigms and discursive network structures in international scientific publications on sustainable energy. The study investigates 26533 abstracts published from 1990 to 2016 using a text mining approach, in particular topic modeling via latent Dirichlet allocation. Case Study 3 turns again to the cases of municipal climate action in Lower Saxony examined in Case Study 1. It examines the involvement of climate action managers of these cities in multilevel knowledge processes. Using design principles for knowledge systems, it evaluates to what extent knowledge is managed in this field across levels for supporting the energy transition and to what extent local innovation potential is leveraged or supported. The three case studies show that international research on sustainable energy and municipal climate action in Germany provide promising contributions to achieve a transformation towards sustainability but do not fully reflect the complexity of society and still support a growth paradigm, in contrast to a holistic sustainability paradigm. Further, the case studies show that research and local action are actively engaging with the diversity of energy technologies but are lagging in dealing with the socio-epistemic (communication) system, especially with regard to achieving cohesion. Using the example of German municipalities, Case Studies 1 and 3 highlight the challenges of achieving coherent local action for sustainability and bottom-up organizational learning due to incomplete or uncoordinated multilevel knowledge exchange.
Contemporary liberal-democracies are under stress and traditional political parties have become detached from their electorates. Since the 1980s, parties have been experiencing a crisis of legitimation, whose effects have become intensive especially in the early twenty-first century. New populist challengers have tried to fill the representative void left by mainstream parties; at the same time, technocracy has become one of the most prominent form of representation. Political responsibility and responsiveness appear often incompatible in the eyes of voters. Moreover, political personalization and processes of presidentialization have led to a situation where single political leaders have become the crucial political actors, to the detriment of party organizations. This Habilitation thesis investigates the linkage between representative democratic institutions in parliamentary and semi-presidential systems and political elites, trying to understand how this linkage has been affected by the change of party democracy. In particular, the thesis analyzes political institutions’ functioning in democratic contexts as well as parties’ responses and elites’ paths to power as indicators of a process of adaptation. Four main research questions inform the analysis: what structural opportunities and constraints do political elites meet when it comes to exercising political power?; how have the decline of party government and political personalization modified opportunity structures?; how do parties and elites cope with democratic change?; has democratic change produced new criteria for successful political careers? The institutional focus is on political executives and representative assemblies at different levels of government. Findings highlight that political elites adopts strategies of resistance and respond to democratic change through incremental steps. In other words, rather than anticipatory, political elites appear reactive, when they are confronted with substantial modifications of the political opportunity structure. Overall, the study contributes to the debate about the changing role of parties and political elites as connectors between the state and the society and provides insights about future developments.