TY - THES A1 - Synodinos, Alexios D. T1 - Savanna dynamics under extreme conditions T1 - Savannendynamik unter extremen Bedingungen BT - insights from a mathematical model N2 - Savannas cover a broad geographical range across continents and are a biome best described by a mix of herbaceous and woody plants. The former create a more or less continuous layer while the latter should be sparse enough to leave an open canopy. What has long intrigued ecologists is how these two competing plant life forms of vegetation coexist. Initially attributed to resource competition, coexistence was considered the stable outcome of a root niche differentiation between trees and grasses. The importance of environmental factors became evident later, when data from moister environments demonstrated that tree cover was often lower than what the rainfall conditions would allow for. Our current understanding relies on the interaction of competition and disturbances in space and time. Hence, the influence of grazing and fire and the corresponding feedbacks they generate have been keenly investigated. Grazing removes grass cover, initiating a self-reinforcing process propagating tree cover expansion. This is known as the encroachment phenomenon. Fire, on the other hand, imposes a bottleneck on the tree population by halting the recruitment of young trees into adulthood. Since grasses fuel fires, a feedback linking grazing, grass cover, fire, and tree cover is created. In African savannas, which are the focus of this dissertation, these feedbacks play a major role in the dynamics. The importance of these feedbacks came into sharp focus when the notion of alternative states began to be applied to savannas. Alternative states in ecology arise when different states of an ecosystem can occur under the same conditions. According to this an open savanna and a tree-dominated savanna can be classified as alternative states, since they can both occur under the same climatic conditions. The aforementioned feedbacks are critical in the creation of alternative states. The grass-fire feedback can preserve an open canopy as long as fire intensity and frequency remain above a certain threshold. Conversely, crossing a grazing threshold can force an open savanna to shift to a tree-dominated state. Critically, transitions between such alternative states can produce hysteresis, where a return to pre-transition conditions will not suffice to restore the ecosystem to its original state. In the chapters that follow, I will cover aspects relating to the coexistence mechanisms and the role of feedbacks in tree-grass interactions. Coming back to the coexistence question, due to the overwhelming focus on competition and disturbance another important ecological process was neglected: facilitation. Therefore, in the first study within this dissertation I examine how facilitation can expand the tree-grass coexistence range into drier conditions. For the second study I focus on another aspect of savanna dynamics which remains underrepresented in the literature: the impacts of inter-annual rainfall variability upon savanna trees and the resilience of the savanna state. In the third and final study within this dissertation I approach the well-researched encroachment phenomenon from a new perspective: I search for an early warning indicator of the process to be used as a prevention tool for savanna conservation. In order to perform all this work I developed a mathematical ecohydrological model of Ordinary Differential Equations (ODEs) with three variables: soil moisture content, grass cover and tree cover. Facilitation: Results showed that the removal of grass cover through grazing was detrimental to trees under arid conditions, contrary to expectation based on resource competition. The reason was that grasses preserved moisture in the soil through infiltration and shading, thus ameliorating the harsh conditions for trees in accordance with the Stress Gradient Hypothesis. The exclusion of grasses from the model further demonstrated this: tree cover was lower in the absence of grasses, indicating that the benefits of grass facilitation outweighed the costs of grass competition for trees. Thus, facilitation expanded the climatic range where savannas persisted into drier conditions. Rainfall variability: By adjusting the model to current rainfall patterns in East Africa, I simulated conditions of increasing inter-annual rainfall variability for two distinct mean rainfall scenarios: semi-arid and mesic. Alternative states of tree-less grassland and tree-dominated savanna emerged in both cases. Increasing variability reduced semi-arid savanna tree cover to the point that at high variability the savanna state was eliminated, because variability intensified resource competition and strengthened the fire disturbance during high rainfall years. Mesic savannas, on the other hand, became more resilient along the variability gradient: increasing rainfall variability created more opportunities for the rapid growth of trees to overcome the fire disturbance, boosting the chances of savannas persisting and thus increasing mesic savanna resilience. Preventing encroachment: The breakdown in the grass-fire feedback caused by heavy grazing promoted the expansion of woody cover. This could be irreversible due to the presence of alternative states of encroached and open savanna, which I found along a simulated grazing gradient. When I simulated different short term heavy grazing treatments followed by a reduction to the original grazing conditions, certain cases converged to the encroached state. Utilising woody cover changes only during the heavy grazing treatment, I developed an early warning indicator which identified these cases with a high risk of such hysteresis and successfully distinguished them from those with a low risk. Furthermore, after validating the indicator on encroachment data, I demonstrated that it appeared early enough for encroachment to be prevented through realistic grazing-reduction treatments. Though this dissertation is rooted in the theory of savanna dynamics, its results can have significant applications in savanna conservation. Facilitation has only recently become a topic of interest within savanna literature. Given the threat of increasing droughts and a general anticipation of drier conditions in parts of Africa, insights stemming from this research may provide clues for preserving arid savannas. The impacts of rainfall variability on savannas have not yet been thoroughly studied, either. Conflicting results appear as a result of the lack of a robust theoretical understanding of plant interactions under variable conditions. . My work and other recent studies argue that such conditions may increase the importance of fast resource acquisition creating a ‘temporal niche’. Woody encroachment has been extensively studied as phenomenon, though not from the perspective of its early identification and prevention. The development of an encroachment forecasting tool, as the one presented in this work, could protect both the savanna biome and societies dependent upon it for (economic) survival. All studies which follow are bound by the attempt to broaden the horizons of savanna-related research in order to deal with extreme conditions and phenomena; be it through the enhancement of the coexistence debate or the study of an imminent external threat or the development of a management-oriented tool for the conservation of savannas. N2 - Savannen sind gekennzeichnet durch die Koexistenz von Gräsern und Bäumen. Sie bedecken circa 20% der globalen Landfläche und Millionen Menschen hängen von ihrer Intaktheit ab. Allerdings bedrohen sowohl der Klimawandel als auch Landnutzung dieses Biom. In dieser Studie werden die Existenz von Savannen unter sehr trockenen Bedingungen, ihre Reaktionen auf steigende Fluktuationen des Niederschlags und die Quantifizierung ihrer Resilienz untersucht. Die Ergebnisse zeigen, dass unter extrem trockenen Bedingungen der positive Einfluss von Gräsern auf Bäume eine wichtige Rolle für das Überleben der Bäume spielt. Kommt es hingegen zu einer Erhöhung der Niederschlagsvariabilität, wird dadurch eine starke Konkurrenz zwischen den beiden Lebensformen verursacht. Die Resilienz der Savannen und ihre Veränderungen lassen sich quantifizieren und mit dem im letzten Teil dieser Dissertation präsentierten Werkzeug erkennen. Meine Arbeit demonstriert, dass sich der Fokus der aktuellen Savannenforschung weiten muss, um die Reaktionen von Savannen auf sich ändernde Umweltbedingungen vorherzusagen. Um Savannen langfristig zu erhalten, müssen jedoch die bereits vorhandenen Grundlagen in einem soliden Framework zusammen gebracht werden. KW - Savanna ecology KW - mathematical modelling KW - coexistence mechanisms KW - Savanna resilience KW - woody encroachment KW - early warning signals KW - mathematische Modelierung KW - Koexistenz Mechanismen KW - Savannen Resilienz KW - Verbuschung Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-395000 ER - TY - THES A1 - Gopalakrishnan, Sathej T1 - Mathematical modelling of host-disease-drug interactions in HIV disease T1 - Mathematische Modellierung von Pathogen-Wirkstoff-Wirt-Interaktionen im Kontext der HIV Erkrankung N2 - The human immunodeficiency virus (HIV) has resisted nearly three decades of efforts targeting a cure. Sustained suppression of the virus has remained a challenge, mainly due to the remarkable evolutionary adaptation that the virus exhibits by the accumulation of drug-resistant mutations in its genome. Current therapeutic strategies aim at achieving and maintaining a low viral burden and typically involve multiple drugs. The choice of optimal combinations of these drugs is crucial, particularly in the background of treatment failure having occurred previously with certain other drugs. An understanding of the dynamics of viral mutant genotypes aids in the assessment of treatment failure with a certain drug combination, and exploring potential salvage treatment regimens. Mathematical models of viral dynamics have proved invaluable in understanding the viral life cycle and the impact of antiretroviral drugs. However, such models typically use simplified and coarse-grained mutation schemes, that curbs the extent of their application to drug-specific clinical mutation data, in order to assess potential next-line therapies. Statistical models of mutation accumulation have served well in dissecting mechanisms of resistance evolution by reconstructing mutation pathways under different drug-environments. While these models perform well in predicting treatment outcomes by statistical learning, they do not incorporate drug effect mechanistically. Additionally, due to an inherent lack of temporal features in such models, they are less informative on aspects such as predicting mutational abundance at treatment failure. This limits their application in analyzing the pharmacology of antiretroviral drugs, in particular, time-dependent characteristics of HIV therapy such as pharmacokinetics and pharmacodynamics, and also in understanding the impact of drug efficacy on mutation dynamics. In this thesis, we develop an integrated model of in vivo viral dynamics incorporating drug-specific mutation schemes learned from clinical data. Our combined modelling approach enables us to study the dynamics of different mutant genotypes and assess mutational abundance at virological failure. As an application of our model, we estimate in vivo fitness characteristics of viral mutants under different drug environments. Our approach also extends naturally to multiple-drug therapies. Further, we demonstrate the versatility of our model by showing how it can be modified to incorporate recently elucidated mechanisms of drug action including molecules that target host factors. Additionally, we address another important aspect in the clinical management of HIV disease, namely drug pharmacokinetics. It is clear that time-dependent changes in in vivo drug concentration could have an impact on the antiviral effect, and also influence decisions on dosing intervals. We present a framework that provides an integrated understanding of key characteristics of multiple-dosing regimens including drug accumulation ratios and half-lifes, and then explore the impact of drug pharmacokinetics on viral suppression. Finally, parameter identifiability in such nonlinear models of viral dynamics is always a concern, and we investigate techniques that alleviate this issue in our setting. N2 - Das Humane Immundefiecienz-Virus (HIV) widerstanden hat fast drei Jahrzehnten eff Orts targeting eine Heilung. Eine anhaltende Unterdrückung des Virus hat noch eine Herausforderung, vor allem aufgrund der bemerkenswerten evolutionären Anpassung, dass das Virus Exponate durch die Ansammlung von Medikamenten-resistenten Mutationen in seinem Genom. Aktuelle therapeutische Strategien zielen auf das Erreichen und die Erhaltung einer niedrigen virale Belastung und umfassen in der Regel mehrere Medikamente. Die Wahl der optimalen Kombinationen dieser Medikamente ist von entscheidender Bedeutung, besonders im Hintergrund der Behandlung Fehler eingetreten, die zuvor mit bestimmten anderen Medikamenten. Ein Verständnis für die Dynamik der viralen mutierten Genotypen Aids in die Bewertung der Behandlung Fehler mit einer bestimmten Kombination und der Erkundung potenzieller Bergung Behandlungsschemata. Mathematische Modelle für virale Dynamik haben sich als unschätzbar erwiesen hat im Verständnis der viralen Lebenszyklus und die Auswirkungen von antiretroviralen Medikamenten. Allerdings sind solche Modelle verwenden in der Regel simplified und grobkörnigen Mutation Regelungen, dass Aufkantungen den Umfang ihrer Anwendung auf Arzneimittel-ganz speziellec Mutation klinische Daten, um zu beurteilen, mögliche nächste-line Therapien. Statistische Modelle der Mutation Anhäufung gedient haben gut in präparieren Mechanismen der Resistenz Evolution durch Mutation Rekonstruktion Pathways unter verschiedenen Medikamenten-Umgebungen. Während diese Modelle führen gut in der Vorhersage der Ergebnisse der Behandlung durch statistische lernen, sie enthalten keine Droge E ffect mechanistisch. Darüber hinaus aufgrund einer innewohnenden Mangel an zeitlichen Funktionen in solchen Modellen, sie sind weniger informativ auf Aspekte wie die Vorhersage mutational Fülle an Versagen der Behandlung. Dies schränkt die Anwendung in der Analyse der Pharmakologie von antiretroviralen Medikamenten, insbesondere, Zeit-abhängige Merkmale der HIV-Therapie wie Pharmakokinetik und Pharmakodynamik, und auch in dem Verständnis der Auswirkungen von Drogen e fficacy auf Mutation Dynamik. In dieser Arbeit, die wir bei der Entwicklung eines integrierten Modells von In-vivo-virale Dynamik Einbeziehung drug-ganz speziellec Mutation Systeme gelernt aus den klinischen Daten. Unsere kombinierten Modellansatz ermöglicht uns die Untersuchung der Dynamik von diff schiedene mutierten Genotypen und bewerten mutational Fülle an virologischem Versagen. Als Anwendung unseres Modells schätzen wir In-vivo-fitness Merkmale der viralen Mutanten unter di fferent drug Umgebungen. Unser Ansatz erstreckt sich auch natürlich auf mehrere-Therapien. Weitere zeigen wir die Vielseitigkeit unseres Modells zeigen, wie es können Modified zu integrieren kürzlich aufgeklärt Mechanismen der Drug Action einschließlich Molekülen, dass target host Faktoren. Zusätzlich haben wir Adresse ein weiterer wichtiger Aspekt in der klinischen Management der HIV-Erkrankung, das heißt Drogen Pharmakokinetik. Es ist klar, dass die Zeit-abhängige Änderungen in In-vivo-Wirkstoffkonzentration könnten die Auswirkungen auf die antivirale E ffect und haben auch Einfluss auf die Entscheidungen über Dosierungsintervalle. Wir präsentieren ein Framework, bietet ein integriertes Verständnis der wichtigsten Merkmale von mehreren Dosierungsschemata einschließlich Kumulation Übersetzungen und Halbwertszeiten, und untersuchen Sie die Auswirkungen von Drogen auf die Pharmakokinetik Virussuppression. Schließlich, Parameter identifiFähigkeit in solchen nichtlineare Modelle der virale Dynamik ist immer ein Anliegen, und wir untersuchen Methoden, um dieses Problem in unserer Einstellung. KW - HIV KW - mathematical modelling KW - viral fitness KW - pharmacokinetics KW - parameter estimation KW - HIV Erkrankung KW - Pharmakokinetik KW - Fitness KW - mathematische Modellierung KW - Kombinationstherapie Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-100100 ER -