Um die Kontraktion einer Herzmuskelzelle durch den Kalziumeinstrom zu ermöglichen, ist die Kopplung von Erregung und Kontraktion (ECC) von zentraler Bedeutung. Durch das elektrische Signal einer Nachbarzelle wird die Depolarisation des Sarkolemmas verursacht, wodurch sich die L-Typ-Kalziumkanäale (LKK) öffnen und der Amplifizierungsprozess eingeleitet wird. Letzterer ist bekannt als Kalzium induzierte Kalzium Freisetzung (CICR). Durch die LKK wird ein Kalziumeinstrom in die Zelle ermöglicht, welcher zur Öffnung der Ryanodinrezeptoren (RyR) des Sarkoplasmatischen Retikulums (SR) führt. Durch die Kalziumfreisetzung des SR wird dieses im Cytoplasma akkumuliert. Modelle für diese Prozesse werden seit mehreren Jahrzenten entwickelt. Bisher fehlte jedoch die Kombination aus räumlich aufgelösten Kalziumkonzentrationen der dyadischen Spalte mit stochastischen Simulationen der einzelnen Kalziumkanäle und die Kalziumdynamiken in der ganzen Zelle mit einem Elektrophysiologiemodell einer ganzen Herzmuskelzelle. In dieser Arbeit entwickleten wir ein neues Modell, in welchem die Konzentrationsgradienten von einzelnen Kanälen bis zum Ganzzelllevel räumlich aufgelöst werden. Es wurde der quasistatische Ansatz und die Finite-Elemente-Methode zur Integration partieller Differentialgleichungen verwendet. Es wurden Simulationen mit unterschiedlichen RyR Markow-Kette-Modellen, verschiedenen Parametern für die Bestandteile des SR, verschiedenen Konditionen des Natrium-Kalzium-Austauschers und unter Einbindung der Mitochondrien durchgeführt. Ziel war es, das physiologische Verhalten einer Kaninchen-Herzmuskelzelle zu simulieren. In dem neu entwickelten Multiskalenmodell wurden Hochleistungsrechner verwendet, um detaillierte Informationen über die Verteilung, die Regulation und die Relevanz von den im ECC involvierten Komponenten aufzuzeigen. Zukünftig soll das entwickelte Modell Anwendung bei der Untersuchung von Herzkontraktionen und Herzmuskelversagen finden. / Excitation contraction coupling (ECC) is of central importance to enable the contraction of the cardiac myocyte via calcium in ux. The electrical signal of a neighbouring cell causes the membrane depolarization of the sarcolemma and L-type Ca2+ channels (LCCs) open. The amplifcation process is initiated. This process is known as calcium-induced calcium release (CICR). The calcium in ux through the LCCs activates the ryanodine receptors (RyRs) of the sarcoplasmic reticulum (SR). The Ca2+ release of the SR accumulates calcium in the cytoplasm. For many decades models for these processes were developed. However, previous models have not combined the spatially resolved concentration dynamics of the dyadic cleft including the stochastic simulation of individual calcium channels and the whole cell calcium dynamics with a whole cardiac myocyte electrophysiology model. In this study, we developed a novel approach to resolve concentration gradients from single channel to whole cell level by using quasistatic approximation and finite element method for integrating partial differential equations. We ran a series of simulations with different RyR Markov chain models, different parameters for the SR components, sodium-calcium exchanger conditions, and included mitochondria to approximate physiological behaviour of a rabbit ventricular cardiac myocyte. The new multi-scale simulation tool which we developed makes use of high performance computing to reveal detailed information about the distribution, regulation, and importance of components involved in ECC. This tool will find application in investigation of heart contraction and heart failure.

The complex demographic changes that underlie the expansion of anatomically modern humans out of Africa have important consequences on the dynamics of natural selection and our ability to detect it. In this thesis, I aimed to refine our knowledge on human population history using ancient genomes, and then used a climate-informed, spatially explicit framework to explore the interplay between complex demographies and selection. I first analysed a high-coverage genome from Upper Palaeolithic Romania from ~37.8 kya, and demonstrated an early diversification of multiple lineages shortly after the out-of-Africa expansion (Chapter 2). I then investigated Late Upper Palaeolithic (~13.3ky old) and Mesolithic (~9.7 ky old) samples from the Caucasus and a Late Upper Palaeolithic (~13.7ky old) sample from Western Europe, and found that these two groups belong to distinct lineages that also diverged shortly after the out of Africa, ~45-60 ky ago (Chapter 3). Finally, I used East Asian samples from ~7.7ky ago to show that there has been a greater degree of genetic continuity in this region compared to Europe (Chapter 4). In the second part of my thesis, I used a climate-informed, spatially explicit demographic model that captures the out-of-Africa expansion to explore natural selection. I first investigated whether the model can represent the confounding effect of demography on selection statistics, when applied to neutral part of the genome (Chapter 5). Whilst the overlap between different selection statistics was somewhat underestimated by the model, the relationship between signals from different populations is generally well-captured. I then modelled natural selection in the same framework and investigated the spatial distribution of two genetic variants associated with a protective effect against malaria, sickle-cell anaemia and β⁰ thalassemia (Chapter 6). I found that although this model can reproduce the disjoint ranges of different variants typical of the former, it is incompatible with overlapping distributions characteristic of the latter. Furthermore, our model is compatible with the inferred single origin of sickle-cell disease in most regions, but it can not reproduce the presence of this disorder in India without long-distance migrations.

Die vermiedene tropische Entwaldung und zusätzliche Aufforstungen sind von zentraler Bedeutung für die Klimawandelvermeidung, üben aber zusätzlichen Druck auf die globalen Landressourcen zur Produktion von Nahrungsgütern, Futtermittel, Fasern, Bioenergie und Rundholz dar. Die Ziele der Studie beziehen sich auf die Analyse der Verzichtskosten in der Land- und Forstwirtschaft sowie das Potential zur Klimawandelvermeidung in globalen Wäldern durch normative und marktbasierte Klimaschutzprogramme. Das globale ökonomische Landnutzungsmodell ''Model of Agricultural Production and its Impact on the Environment'' (MAgPIE) wurde um eine konsistente Landnutzungsdatenbank und den Forstsektor erweitert. Es simuliert die räumlich-explizite Landnutzung und deren Änderungen während die Kosten land- und forstwirtschaftlicher Produktion unter gegebener Nachfrage nach Gütern geschätzt werden. Szenarien zu Klimaschutzmaßnahmen werden verglichen mit Referenzszenarien über Zeithorizonte bis zum Jahr 2100. Die Ergebnisse verweisen auf ein begrenztes Mitigationspotential normativen tropischen Waldschutzes zu geringen zusätzlichen Kosten in der Landwirtschaft. Lateinamerika profitiert von ausreichenden Landreserven und geringem Anstieg in der Güternachfrage und geringer Referenzentwaldung. Die Verlagerung von Emissionen durch regionalen Waldschutz hat Auswirkungen auf die sektoralen Produktionskosten und verringert das globale ökonomische Potential. Die Schlussfolgerungen betreffen 1) den Bedarf an substantieller Ertragssteigerung in Sub-Sahara Afrika als Voraussetzung für die erfolgreiche Umsetzung vermiedener Entwaldung, 2) die erhöhte Gefahr der Verlagerung von Emissionen aus Entwaldung durch die Umsetzung regionaler Klimaschutzprogramme und der Liberalisierung des Holzhandels, 3) das hohe ökonomische Potential integrierter Klimaschutzprogramme zu moderaten Verzichtskosten, sowie 4) die Notwendigkeit zusätzlicher Forschung bezüglich der Unsicherheiten in Parametern und Modellprozessen. / Avoiding tropical deforestation and additional afforestation are of primary importance for climate change mitigation but exert additional pressure on global land resources for the production of food, feed, fibre, bioenergy and timber. The study objectives relate to the analysis of the foregone economic benefits, the opportunity costs, in agriculture and forestry and the climate change mitigation potential of global forests in normative and market-based programmes. The global economic ‘Model of Agricultural Production and its Impact on the Environment'' (MAgPIE) has been extended by a consistent land use database and the forestry sector. It simulates spatially-explicit land use and land use changes while estimating the costs of production in agriculture and forestry to satisfy a prescribed demand. Climate change mitigation scenarios are contrasted to baselines for time horizons up to the year 2100. The results show the limited mitigation potential of normative forest conservation in tropical regions at low additional costs in agriculture. Latin America benefits from sufficient land endowments and low increases in crop demand leading to relatively low baseline deforestation. The displacement of carbon emissions between regions impacts the regional agriculture and forestry production costs and reduces the global economic potential. The conclusions pertain to the 1) need for high rates of yield increase in Sub-Saharan Africa as a precondition for successfully avoided deforestation, 2) increased threat of regional carbon emission leakage from implementing mitigation programmes and liberalized trade of timber, 3) high economic potential of climate change mitigation from integrating afforestation and avoided deforestation at moderate costs, and 4) additional research needs to account for significant uncertainties from growth and cost parameters and model processes.

Cette thèse porte sur le rôle de l’espace dans l’organisation et dans la dynamique des communautés écologiques multi-espèces. Deux carences peuvent être identifiées dans les études théoriques actuelles portant sur la dimension spatiale des communautés écologiques : l’insuffisance de modèles multi-espèces représentant la dimension spatiale explicitement, et le manque d’attention portée aux interactions positives, tel le mutualisme, en dépit de la reconnaissance de leur ubiquité dans les systèmes écologiques. Cette thèse explore cette problématique propre à l’écologie des communautés, en utilisant une approche théorique s’inspirant de la théorie des systèmes complexes et de la mécanique statistique. Selon cette approche, les communautés d’espèces sont considérées comme des systèmes complexes dont les propriétés globales émergent des interactions locales entre les organismes qui les composent, et des interactions locales entre ces organismes et leur environnement. Le premier objectif de cette thèse est de développer un modèle de métacommunauté multi-espèces, explicitement spatial, orienté à l’échelle des individus et basé sur un réseau d’interactions interspécifiques générales comprenant à la fois des interactions d’exploitation, de compétition et de mutualisme. Dans ce modèle, les communautés locales sont formées par un processus d’assemblage des espèces à partir d’un réservoir régional. La croissance des populations est restreinte par une capacité limite et leur dynamique évolue suivant des mécanismes simples de reproduction et de dispersion des individus. Ces mécanismes sont dépendants des conditions biotiques et abiotiques des communautés locales et leur effet varie en fonction des espèces, du temps et de l’espace. Dans un deuxième temps, cette thèse a pour objectif de déterminer l’impact d’une connectivité spatiale croissante sur la dynamique spatiotemporelle et sur les propriétés structurelles et fonctionnelles de cette métacommunauté. Plus précisément, nous évaluons différentes propriétés des communautés en fonction du niveau de dispersion des espèces : i) la similarité dans la composition des communautés locales et ses patrons de corrélations spatiales; ii) la biodiversité locale et régionale, et la distribution locale de l’abondance des espèces; iii) la biomasse, la productivité et la stabilité dynamique aux échelles locale et régionale; et iv) la structure locale des interactions entre les espèces. Ces propriétés sont examinées selon deux schémas spatiaux. D’abord nous employons un environnement homogène et ensuite nous employons un environnement hétérogène où la capacité limite des communautés locales évoluent suivant un gradient. De façon générale, nos résultats révèlent que les communautés écologiques spatialement distribuées sont extrêmement sensibles aux modes et aux niveaux de dispersion des organismes. Leur dynamique spatiotemporelle et leurs propriétés structurelles et fonctionnelles peuvent subir des changements profonds sous forme de transitions significatives suivant une faible variation du niveau de dispersion. Ces changements apparaissent aussi par l’émergence de patrons spatiotemporels dans la distribution spatiale des populations qui sont typiques des transitions de phases observées généralement dans les systèmes physiques. La dynamique de la métacommunauté présente deux régimes. Dans le premier régime, correspondant aux niveaux faibles de dispersion des espèces, la dynamique d’assemblage favorise l’émergence de communautés stables, peu diverses et formées d’espèces abondantes et fortement mutualistes. La métacommunauté possède une forte diversité régionale puisque les communautés locales sont faiblement connectées et que leur composition demeure ainsi distincte. Par ailleurs dans le second régime, correspondant aux niveaux élevés de dispersion, la diversité régionale diminue au profit d’une augmentation de la diversité locale. Les communautés locales sont plus productives mais leur stabilité dynamique est réduite suite à la migration importante d’individus. Ce régime est aussi caractérisé par des assemblages incluant une plus grande diversité d’interactions interspécifiques. Ces résultats suggèrent qu’une augmentation du niveau de dispersion des organismes permet de coupler les communautés locales entre elles ce qui accroît la coexistence locale et favorise la formation de communautés écologiques plus riches et plus complexes. Finalement, notre étude suggère que le mutualisme est fondamentale à l’organisation et au maintient des communautés écologiques. Les espèces mutualistes dominent dans les habitats caractérisés par une capacité limite restreinte et servent d’ingénieurs écologiques en facilitant l’établissement de compétiteurs, prédateurs et opportunistes qui bénéficient de leur présence. / This thesis is a study of the role of space in the organization and dynamics of multi-species ecological communities. Two weaknesses can be identified from previous theoretical studies concerned with the spatial dimension of ecological communities: the scarcity of multi-species models based on a spatially explicit representation of space, and the lack of attention toward positive interspecific interactions, such as mutualism, despite the recognition of their ubiquity in ecological systems. This thesis explores this problematic by adopting a theoretical framework based on complex system theory and statistical mechanics. Following this approach, ecological communities can be viewed as complex systems whose global properties emerge from the local interactions between the organisms that composed them, and between the organisms and their environment. The first objective of this thesis is to develop a multi-species metacommunity model which is spatially explicit, individual-based, and centered on a general interspecific interaction web containing exploitation, competition as well as mutualism. In this model, local communities are created by an assembly process whereby species are drawn from a regional pool. Population growth is restricted by a carrying capacity and its dynamics is driven by simple reproduction and dispersal mechanisms acting at the level of single individual. These mechanisms depend on the biotic and abiotic conditions of the local communities and their effect varies with species, time and space. The second objective of this thesis is to determine the impact of an increasing spatial connectivity on the dynamics, and structural and functional properties of this metacommunity. More precisely, we set out to evaluate different community properties under changes in the level of species dispersal: i) the similarity in local community composition and its patterns of spatial correlations, ii) the local and regional diversity and the local species abundance, iii) the local and regional biomass, productivity and dynamical stability, and iv) the structure of the local interaction webs. These properties are examined under two spatial schemes. First, we employ a homogeneous environment, and second we employ a heterogeneous environment whereby the carrying capacity of local communities evolves along a gradient. In general, our results reveal that spatially distributed ecological communities are extremely sensitive to the modes and levels of species dispersal. Their spatiotemporal dynamics as well as their structural and functional properties can undergo profound changes in the form of significant transitions under slight changes of the level of dispersal. These changes are also highlighted by the emergence of spatiotemporal patterns in the spatial distribution of the populations, which are characteristics of phase transition generally observed in physical systems. The metacommunity presents two dynamical regimes. In the first regime, corresponding to weak levels of species dispersal, the assembly dynamics promotes the emergence of species-poor but stable communities made of abundant and strongly mutualistic species. The metacommunity has a high regional diversity since weakly connected communities conserve a distinct assemblage of species. On the other hand, in the second regime, corresponding to strong dispersal rates, regional diversity decreases at the benefit of an increase in local diversity. Local communities are more productive but their stability is reduced due to the important migration of individuals. This regime is also characterized by assemblages containing a richer diversity of interspecific interactions. These results suggest that an augmentation in the level of species dispersal permits organisms to couple local communities together which increases local coexistence and promotes the organization of richer and more complex ecological communities. Finally, our results suggest that mutualism is fundamental to the organization and persistence of ecological communities. Mutualistic species dominate in habitats characterized by a restricted carrying capacity and serve as ecological engineer by facilitating the establishment of competitors, predators and opportunists which benefit from their presence.

This thesis analyses the highly structured and densely populated farmland surrounding Kakamega Forest (western Kenya) in a spatially-explicit manner. The interdisciplinary approach combines methodologies and technologies from different scientific disciplines: remote sensing with OBIA, GIS and spatially explicit modelling (geomatics and geographic science) with socio-economic as well as agro-economic considerations (human and social sciences) as well as cartographic science. Furthermore, the research is related to conservation biology (biological sciences). Based on an in-situ ground truthing and visual image interpretation, very high spatial resolution QuickBird satellite imagery covering 466 km² of farmland was analysed using the concept of object-based image analysis (OBIA). In an integrative workflow, statistical analysis and expert knowledge were combined to develop a sophisticated rule set. The classification result distinguishing 15 LULC classes was used alongside with temporally extrapolated and spatially re-distributed population data as well as socio-/agro-economic factors in order to create a spatially-explicit typology of the farmland and to model scenarios of rural livelihoods. The farmland typology distinguishes ten types of farmland: 3 sugarcane types (covering 48% of the area), 3 tea types (30%), 2 transitional types (15%), 1 steep terrain type (2%), and 1 central type (5%). The scenarios consider different developments of possible future yields and prices for the main agricultural products sugarcane, tea, and maize. Out of all farmland types, the ‘marginal sugarcane type’ is best prepared to cope with future problems. Besides a comparably low population density, a high share of land under cultivation of food crops coupled with a moderate cultivation of cash crops is characteristic for this type. As part of the research conducted, several novel methodologies were introduced. These include a new conceptual framework for categorizing parameter optimization studies, the area fitness rate (AFR) as a novel discrepancy measure, the technique of ‘classification-based nearest neighbour classification’ for classes which are difficult to separate from others, and a novel approach for accessing the accuracy of OBIA classifications. Finally, this thesis makes a number of recommendations and elaborates promising starting points for further scientific research. / Die vorliegende Arbeit untersucht räumlich-expliziten das stark strukturierte und dicht besiedelte Agrarland um den Kakamega Wald (Westkenia). Dabei kombiniert der interdisziplinäre Ansatz Methoden und Technologien verschiedener Wissenschaftsbereiche: die Fernerkundung mit der objekt-basierten Bildanalyse (OBIA), GIS und die räumlich-explizite Modellierung (Geoinformatik und Geographie) mit sozio- und agro-ökonomische Aspekten (Human- und Sozialwissenschaft) sowie der Kartographie. Zudem steht die Arbeit in Bezug zum Schutz der biologischen Vielfalt (Biologie). Ausgehend von einer Referenzdatenerfassung vor Ort und einer visuellen Bildinterpretation wurden räumlich sehr hochauflösende QuickBird-Satellitenbilddaten, die 466 km² des Agrarlandes abdecken, mit Hilfe von OBIA ausgewertet. In einem integrativen Ansatz wurden dabei statistische Verfahren und Expertenwissen kombiniert, um einen ausgefeilten Regelsatz zur Klassifizierung zu erzeugen. Das Klassifizierungsergebnis unterscheidet 15 Klassen der Landnutzung bzw. -bedeckung; zusammen mit zeitlich extrapolierten und räumlich neu verteilten Bevölkerungsdaten sowie sozio- und agro-ökonomischen Faktoren ermöglichte es, eine räumlich-explizite Typologie des Agrarlandes zu erstellen und Szenarien zum ländlichen Auskommen zu modellieren. Die Agrarlandtypologie unterscheidet zehn Landtypen: 3 Zuckerrohr-dominierte Typen (48% des Gebietes), 3 Tee-dominierte Typen (30%), 2 Übergangstypen (15%), 1 Typ steilen Geländes (2%) und 1 zentralen Typ (5%). Die Szenarien betrachten mögliche zukünftige Entwicklungen der Erträge und Preise der Hauptanbauarten Zuckerrohr, Tee und Mais. Von allen Agrarlandtypen ist der „marginal Zuckerrohr-dominierte Typ“ am besten gerüstet, um zukünftigen Problemen zu begegnen. Bezeichnend für diesen Typ sind – neben einer vergleichsweise geringen Bevölkerungsdichte – ein hoher Anteil an Nahrungsmittelanbau zusammen mit einem gemäßigten Anbau von exportorientierten Agrarprodukten. Als Teil der Forschungsarbeit werden verschiedene neuartige Methoden vorgestellt, u.a. ein neuer konzeptioneller Rahmen für das Kategorisieren von Studien zur Parameteroptimierung, die „area fitness rate“ (AFR) als neue Messgröße für Flächendiskrepanzen, die klassifikations-basierte Nächster-Nachbar Klassifizierung sowie ein Ansatz zum Bestimmen der Güte von OBIA-Klassifizierungen. Schließlich gibt die Arbeit eine Reihe von Empfehlungen und bietet vielversprechende Ausgangspunkte für weiterführende wissenschaftliche Forschungen.

Advanced monitoring of the spatio-temporal distribution of process parameters in large-scale vessels and containers such as stirred chemical or bioreactors offers a high potential for the investigation and further optimization of plants and embedded processes. This applies especially to large-scale fermentation biogas reactors where the process performance including the biological processes highly depend on mixing parameters of the complex bio-substrates. Sufficient mixing is a basic requirement for a stable operation of the process and adequate process performance. However, this condition is rarely met in agricultural biogas plants and the process efficiency is often reduced dramatically by inhomogeneities in the agitated vessels. Without a doupt, investigation and monitoring of biochemical parameters, such as the fermentation rate, pH distribution as well as O2 and CO2 concentration is of great importance. Nevertheless, also understanding of non-biological parameters, such as fluid dynamics (flow velocity profiles, circulation times), suspension mixing (homogeneity, location of dead zones and short-circuits) and heat transfer (temperature profiles), is necessary to analyze the impact of mixing on the biological system and also to improve the process efficiency. However, in most industrial scale applications the acquisition of these parameters and their spatial distributions in the large-scale vessels is hampered by the limited access to the process itself, because sensor mounting or cable connections are not feasible or desired. Therefore, state of the art instrumentation of such reactors is commonly limited to few spatial positions where it is doubtfully assumed that the measured parameters are representative for the whole reaction mixture. In this work, a concept of flow following sensor particles was developed. The sensor particles allow long-term measurement of spatially distributed process parameters in the chemically and mechanically harsh environments of agitated industrial vessels. Each sensor particle comprises of an onboard measurement electronics that logs the signals of measurement devices, namely temperature, absolute pressure (immersion depth, axial position) and 3D acceleration. The whole electronics is enclosed in a robust neutrally buoyant capsule (equivalent diameter 58.2 mm; sphericity 0.91), to allow free movement with the flow. The sensor particles were tested in pilot fermenters under comparable flow conditions of biogas fermenters. The experiments proved the applicability of the sensor particles and the robustness to resist the harsh environments of mixing processes. Moreover, the results show the capabilities of the sensor particles to monitor the internal conditions of the vessel correctly and thus deliver significant information about the flow regime. Therefore effects of liquid rheology, vessel geometry, impeller speed and axial impeller position on the macro-mixing process were properly detected. Evaluation of the impeller efficiency and the mixing processes was done based on mixing homogeneity, location of dead zones, axial velocity profiles, circulation time distributions as well as average circulation times, acceleration spectra and temperature profiles that were extracted from the measured data. Furthermore, it is shown, that parameters of mixing models such as circulation number, impeller head, PECLÉT-number and variance of suspended solid particles can be estimated from the measured data. The main achievement of this work is therefore the development and validation of instrumented flow followers for the investigation of macro-mixing effects in agitated vessels. The sensor particles show potential for employment to real applications such as biogas fermenters or large bioreactors and to monitor and improve the mixing and heating regimes.

Advanced monitoring of the spatio-temporal distribution of process parameters in large-scale vessels and containers such as stirred chemical or bioreactors offers a high potential for the investigation and further optimization of plants and embedded processes. This applies especially to large-scale fermentation biogas reactors where the process performance including the biological processes highly depend on mixing parameters of the complex bio-substrates. Sufficient mixing is a basic requirement for a stable operation of the process and adequate process performance. However, this condition is rarely met in agricultural biogas plants and the process efficiency is often reduced dramatically by inhomogeneities in the agitated vessels. Without a doupt, investigation and monitoring of biochemical parameters, such as the fermentation rate, pH distribution as well as O2 and CO2 concentration is of great importance. Nevertheless, also understanding of non-biological parameters, such as fluid dynamics (flow velocity profiles, circulation times), suspension mixing (homogeneity, location of dead zones and short-circuits) and heat transfer (temperature profiles), is necessary to analyze the impact of mixing on the biological system and also to improve the process efficiency. However, in most industrial scale applications the acquisition of these parameters and their spatial distributions in the large-scale vessels is hampered by the limited access to the process itself, because sensor mounting or cable connections are not feasible or desired. Therefore, state of the art instrumentation of such reactors is commonly limited to few spatial positions where it is doubtfully assumed that the measured parameters are representative for the whole reaction mixture. In this work, a concept of flow following sensor particles was developed. The sensor particles allow long-term measurement of spatially distributed process parameters in the chemically and mechanically harsh environments of agitated industrial vessels. Each sensor particle comprises of an onboard measurement electronics that logs the signals of measurement devices, namely temperature, absolute pressure (immersion depth, axial position) and 3D acceleration. The whole electronics is enclosed in a robust neutrally buoyant capsule (equivalent diameter 58.2 mm; sphericity 0.91), to allow free movement with the flow. The sensor particles were tested in pilot fermenters under comparable flow conditions of biogas fermenters. The experiments proved the applicability of the sensor particles and the robustness to resist the harsh environments of mixing processes. Moreover, the results show the capabilities of the sensor particles to monitor the internal conditions of the vessel correctly and thus deliver significant information about the flow regime. Therefore effects of liquid rheology, vessel geometry, impeller speed and axial impeller position on the macro-mixing process were properly detected. Evaluation of the impeller efficiency and the mixing processes was done based on mixing homogeneity, location of dead zones, axial velocity profiles, circulation time distributions as well as average circulation times, acceleration spectra and temperature profiles that were extracted from the measured data. Furthermore, it is shown, that parameters of mixing models such as circulation number, impeller head, PECLÉT-number and variance of suspended solid particles can be estimated from the measured data. The main achievement of this work is therefore the development and validation of instrumented flow followers for the investigation of macro-mixing effects in agitated vessels. The sensor particles show potential for employment to real applications such as biogas fermenters or large bioreactors and to monitor and improve the mixing and heating regimes.

This thesis analyses the highly structured and densely populated farmland surrounding Kakamega Forest (western Kenya) in a spatially-explicit manner. The interdisciplinary approach combines methodologies and technologies from different scientific disciplines: remote sensing with OBIA, GIS and spatially explicit modelling (geomatics and geographic science) with socio-economic as well as agro-economic considerations (human and social sciences) as well as cartographic science. Furthermore, the research is related to conservation biology (biological sciences). Based on an in-situ ground truthing and visual image interpretation, very high spatial resolution QuickBird satellite imagery covering 466 km² of farmland was analysed using the concept of object-based image analysis (OBIA). In an integrative workflow, statistical analysis and expert knowledge were combined to develop a sophisticated rule set. The classification result distinguishing 15 LULC classes was used alongside with temporally extrapolated and spatially re-distributed population data as well as socio-/agro-economic factors in order to create a spatially-explicit typology of the farmland and to model scenarios of rural livelihoods. The farmland typology distinguishes ten types of farmland: 3 sugarcane types (covering 48% of the area), 3 tea types (30%), 2 transitional types (15%), 1 steep terrain type (2%), and 1 central type (5%). The scenarios consider different developments of possible future yields and prices for the main agricultural products sugarcane, tea, and maize. Out of all farmland types, the ‘marginal sugarcane type’ is best prepared to cope with future problems. Besides a comparably low population density, a high share of land under cultivation of food crops coupled with a moderate cultivation of cash crops is characteristic for this type. As part of the research conducted, several novel methodologies were introduced. These include a new conceptual framework for categorizing parameter optimization studies, the area fitness rate (AFR) as a novel discrepancy measure, the technique of ‘classification-based nearest neighbour classification’ for classes which are difficult to separate from others, and a novel approach for accessing the accuracy of OBIA classifications. Finally, this thesis makes a number of recommendations and elaborates promising starting points for further scientific research.:1. Introduction 2. Geodata and reference data 3. Object-based image analysis (OBIA) 4. Optimization of segmentation parameters 5. Feature selection and threshold determination 6. OBIA classification: rule set development and realisation 7. Classification results 8. Spatial farmland typology 9. Spatially explicit planning scenarios of rural livelihoods 10. Discussion / Die vorliegende Arbeit untersucht räumlich-expliziten das stark strukturierte und dicht besiedelte Agrarland um den Kakamega Wald (Westkenia). Dabei kombiniert der interdisziplinäre Ansatz Methoden und Technologien verschiedener Wissenschaftsbereiche: die Fernerkundung mit der objekt-basierten Bildanalyse (OBIA), GIS und die räumlich-explizite Modellierung (Geoinformatik und Geographie) mit sozio- und agro-ökonomische Aspekten (Human- und Sozialwissenschaft) sowie der Kartographie. Zudem steht die Arbeit in Bezug zum Schutz der biologischen Vielfalt (Biologie). Ausgehend von einer Referenzdatenerfassung vor Ort und einer visuellen Bildinterpretation wurden räumlich sehr hochauflösende QuickBird-Satellitenbilddaten, die 466 km² des Agrarlandes abdecken, mit Hilfe von OBIA ausgewertet. In einem integrativen Ansatz wurden dabei statistische Verfahren und Expertenwissen kombiniert, um einen ausgefeilten Regelsatz zur Klassifizierung zu erzeugen. Das Klassifizierungsergebnis unterscheidet 15 Klassen der Landnutzung bzw. -bedeckung; zusammen mit zeitlich extrapolierten und räumlich neu verteilten Bevölkerungsdaten sowie sozio- und agro-ökonomischen Faktoren ermöglichte es, eine räumlich-explizite Typologie des Agrarlandes zu erstellen und Szenarien zum ländlichen Auskommen zu modellieren. Die Agrarlandtypologie unterscheidet zehn Landtypen: 3 Zuckerrohr-dominierte Typen (48% des Gebietes), 3 Tee-dominierte Typen (30%), 2 Übergangstypen (15%), 1 Typ steilen Geländes (2%) und 1 zentralen Typ (5%). Die Szenarien betrachten mögliche zukünftige Entwicklungen der Erträge und Preise der Hauptanbauarten Zuckerrohr, Tee und Mais. Von allen Agrarlandtypen ist der „marginal Zuckerrohr-dominierte Typ“ am besten gerüstet, um zukünftigen Problemen zu begegnen. Bezeichnend für diesen Typ sind – neben einer vergleichsweise geringen Bevölkerungsdichte – ein hoher Anteil an Nahrungsmittelanbau zusammen mit einem gemäßigten Anbau von exportorientierten Agrarprodukten. Als Teil der Forschungsarbeit werden verschiedene neuartige Methoden vorgestellt, u.a. ein neuer konzeptioneller Rahmen für das Kategorisieren von Studien zur Parameteroptimierung, die „area fitness rate“ (AFR) als neue Messgröße für Flächendiskrepanzen, die klassifikations-basierte Nächster-Nachbar Klassifizierung sowie ein Ansatz zum Bestimmen der Güte von OBIA-Klassifizierungen. Schließlich gibt die Arbeit eine Reihe von Empfehlungen und bietet vielversprechende Ausgangspunkte für weiterführende wissenschaftliche Forschungen.:1. Introduction 2. Geodata and reference data 3. Object-based image analysis (OBIA) 4. Optimization of segmentation parameters 5. Feature selection and threshold determination 6. OBIA classification: rule set development and realisation 7. Classification results 8. Spatial farmland typology 9. Spatially explicit planning scenarios of rural livelihoods 10. Discussion

<div><p><br></p></div><p>This study makes use of a Time-Resolved Raman Spectroscopy (TRRS) system developed in the Purdue Civil Engineering spectroscopy laboratory to advance technology critical to enable field deployment of Raman spectroscopic systems, with a primary focus on developing solutions to overcome two specific barriers to Raman analysis in the natural environment: (1) obtaining Raman spectra of chemical compounds at field-relevant concentrations, and (2) realizing economical spatial monitoring. To inform both streams of activity, this work first explores the role of component choice and apparatus design on Raman system output. A component-level Raman system transfer function is developed in terms of intensity, wavelength, and time which yields detailed insight into system performance that greatly exceeds traditional single “system factor” treatments of apparatus effects. The modelling frame provided by the transfer function is universally applicable in that it is inclusive of the majority of component choices that may be encountered in any open-path or closed-path Raman system, and is likely to be valuable in efforts to assess the performance benefits and limitations of system designs, modify or tailor apparatus layouts, facilitate experiment design, and compare results obtained on different systems. </p><p><br></p><p>The system characterization offered by the transfer function is then employed to develop a multi-photon counting algorithm realized through digital signal processing (DSP) which captures photon arrivals traditionally ignored in conventional counting methods. This approach increases acquired Raman intensity for any given analyte by using detector output voltage or a voltage-time product as an energy proxy – an approach that is likey broadly applicable to any spectroscopic techniques employing detectors that make use of the photoelectric effect. In experiments carried out on analytes (nitrate, isopropanol, and rhodamine 6G) in aqueous solutions, enhanced observations enabled by the multi-photon counting algorithm are shown to increase observed Raman intensities of low Raman-yield solutions 2.0-3.1-fold compared to single-threshold analysis, and also extend the upper observation limit of strong Raman-yield solutions that would traditionally saturate detectors using a binary photon counting scheme. Notably, the improved performance offered by the multi-photon counting algorithm is realized through comparison of multi-photon and conventional counting algorithms applied to the same data in a post-processing exercise, thus eliminating any effects of test-to-test variation on results, and highlighting the ability to employ the developed counting approach without modification of traditional systems.</p><p><br></p><p>Additional insights from the system transfer function are also used to inform exploration of a novel approach to enable spatial environmental monitoring via Raman spectroscopy by combining fiber optics, optical switch technology, and the Raman system prototype. Tests designed to evaluate the system configured as a multiplexed optically switched fiber optic network demonstrate the potential to deliver excitation and collect Raman scattering from different desired monitoring locations with a sole excitation source and a single detector over substantial distances. Using nitrate as an example compound of interest, it is demonstrated that the system has a detection limit of 5 ppm within approximately 1.5 meters, which increases to 15 ppm at 100 m, and 38 ppm at 200 m. Modelling informed using the developed system transfer function highlights that improving the prototype by eliminating fiber connectors and making use of commercially available visible-light optimized fiber can substantially extend the range of the system, offering a 15-ppm nitrate detection limit at 2100 m. As increases in laser power, testing time, and collection optic efficiency are all also straightforward and viable, the prototype demonstrates realistic potential to achieve field relevant detection sensitivity over great distance.</p><p><br></p><p>As a final demonstration of system potential, a set of experiments on aqueous nitrate solutions is performed to understand the influence of turbidity, fluorescence, optics size, and varied raw data integration lengths on Raman observations. Results demonstrate that cumulative advances in the TRRS system establish a new generation of Raman spectroscopic sensing amenable to long-term environmental monitoring over significant spatial extent in complex in-situ conditions. Specific advances made herein include enhanced power delivery and scattered light collection informed by the system transfer function, increases in sensitivity from multi-photon counting, and incorporation of optical multiplexing. Overall, the Time-Resolved Raman Spectroscopic System (TRRS) now offers a set of capabilities that bring in-field deployment within practical reach.</p>

Die Arbeit beschäftigt sich mit laser-induzierter Plasmaspektroskopie (LIBS) im Kontext der robotischen Mars-Erkundung. Bei LIBS wird Plasma analysiert, das durch Ablation von Probenmaterial gebildet wird. Die Methode wird seit 2012 von dem Instrument ChemCam des Mars-Rovers Curiosity eingesetzt, um das Gestein und den Boden der Marsoberfläche zu untersuchen. Sie wird auch in der NASA-Mission Mars 2020 und in der chinesischen Mission HX-1 eingesetzt werden, welche im Jahr 2020 zum Mars starten sollen. Zwei Studien dieser Arbeit betrachten Emissionen von Molekülen, die sich im Plasma bilden. Diese können zur Detektion von Chlor und Fluor eingesetzt werden, die von geologischem Interesse für Mars sind. Emissionen von MgCl und CaCl werden in simulierten Marsbedingungen für die Bestimmung der Chlorkonzentration untersucht. Nur das CaCl-Signal wird als stark genug befunden. Dieses ist am stärksten bei vergleichsweise geringen Chlorkonzentrationen, was durch einen Nichtgleichgewichtszustand des Plasmas erklärt werden kann. In der zweiten Studie werden die Emissionen von CaCl und CaF verglichen. Beide können mit demselben Modell in Abhängigkeit der Konzentrationen der Reaktionspartner beschrieben werden. Allerdings werden auch starke Matrixeffekte beobachtet, die die Emissionen beeinträchtigen können. Im letzten Teil der Arbeit wird der Plasma-Imaging-Aufbau beschrieben, der aufgebaut wurde. Der Aufbau ermöglicht räumlich aufgelöste Messungen der Emissionsspektren. Es werden erste Ergebnisse vorgestellt, die mit diesem Aufbau erzielt wurden. Diese zeigen, dass CaCl und CaF nur im Plasmazentrum emittieren, was mit einer Verdünnung und Ausbildung eines Niedertemperaturbereichs im Plasmazentrum erklärt werden kann. Atomare Emissionen von Wasserstoff, Kohlenstoff und Sauerstoff sind dagegen intensiver an der Plasmafront und zeigen Verwirbelungen auf, was auf komplexe Temperaturverteilungen und auf einen starken Einfluss von Strömungen im Plasma hinweist. / In this thesis, laser-induced breakdown spectroscopy (LIBS) is investigated in the context of the robotic exploration of Mars. In LIBS, the plasma formed by laser-ablated sample material is analyzed spectroscopically. Since 2012, it is employed by the ChemCam instrument on board the Mars rover Curiosity to analyze rocks and soil on the Martian surface. The technique will also be used in NASA's Mars 2020 mission and in the Chinese HX-1 mission, which are both scheduled to launch to Mars in 2020. The first two studies are concerned with emissions of molecules that form in the laser-induced plasma. These can be used to detect chlorine and fluorine, which are of geological interest for Mars. In the first study, MgCl and CaCl emissions are investigated for the detection and quantification of chlorine in Martian atmospheric conditions. Only the CaCl signal is found to be intense enough for this purpose. The CaCl signal is found to be skewed towards low chlorine concentrations, which is explained by a non-equilibrium model of the laser-induced plasma. In the second study, the emissions of CaCl and CaF are compared. The same model is used to describe the dependence of both signals on the respective reactant concentrations. Strong matrix effects are observed that affect the observed intensities. In the final part of the thesis the plasma imaging setup that was developed in the context of this thesis is presented. It enables spatially resolved measurements of the plasma emission spectra. First results show that CaCl and CaF emissions are confined close to the plasma center, likely because rarefaction leads to a low-temperature center in which molecules can form. Atomic emissions of hydrogen, carbon, and oxygen are more stable at the plasma front and show signs of vorticity, indicating a complex temperature distribution and a strong influence of flows within the plasma.