In-stream aquatic habitat depends on adequate levels of dissolved oxygen. Human alteration of the landscape has an extensive influence on the biogeochemical processes that drive oxygen cycling in streams. Historic datasets allow researchers to track trends in chemical parameters concomitant with urbanization, while land cover change analysis allows researchers to identify linkages between water quality trends and landscape change. Using the Seasonal Kendall's test, I examined water quality trends in oxygen demand variables during the mid-1990s to 2003, for twelve sites in the Rock Creek sub-watershed of the Tualatin River, northwest Oregon. Significant trends occurred in each parameter. Dissolved oxygen (DO (%sat)) increased at five sites. Chemical oxygen demand (COD) decreased at seven sites. Total Kjeldahl nitrogen (TKN) decreased at five sites and increased at one site. Ammonium (NH3-N) decreased at one site and increased at one site. Multiple linear regression indicates that nitrogenous oxygen demand accounts for a significant amount of variance in COD at ten of the twelve sites (adjusted R2values from 0.14 to 0.73). Aerial photo interpretation revealed significant land cover change in agricultural land cover (-8% for the entire basin area) and residential land cover (+10% for the entire basin area). Correlation results between seasonal oxygen demand data and land cover values at multiple scales indicated that: (I) forest cover negatively influences COD at the full sub-basin scale and positively influences NH3-N at local scales, (2) residential land cover positively influences DO (%sat) values at local scales, (3) agricultural land cover does not influence oxygen demand at any land cover assessment scale, ( 4) local topography negatively influences TKN and NH3-N, and (5) urban runoff management infrastructure correlates positively with COD. Study results indicate that, with the exception of forested land, local scale land cover and landscape variables dominate influence on oxygen demand in the Rock Creek basin. Since DO conditions have improved in these streams, watershed management efforts should emphasize local influences in order to continue to maintain stream health.

Water quality models in the Colorado River Basin have been developed for the basin, river, and individual reservoirs. They are used to support water quality programs within the basin. The models are periodically reviewed and updated to improve the accuracy of simulations. Improving the usefulness of the Lake Powell model, one of the key reservoirs in the basin, is the subject of this study. Lake Powell is simulated using a hydrodynamic and water quality model, CE-QUAL-W2. Previously the model has been used at Lake Powell to simulate hydrodynamics, temperature, and total dissolved solids with a reasonable degree of accuracy. An additional parameter, dissolved oxygen, will be added to the simulations and then calibrated with observed data to verify accuracy. Dissolved oxygen distributions in Lake Powell vary seasonally and change under different hydrologic cycles. They are a function of physical, biological, and chemical processes. Few measurements of these processes in Lake Powell exist. To compensate for the lack of data an empirical method of loading oxygen demand to the model is developed and tested. Observed limnological processes in the reservoir guide the development of the empirical methods. The methods are then tested in 16 year model simulations and compared with dissolved oxygen measurements from the 16 year period. By accurately reproducing the dissolved oxygen distributions the Lake Powell model will have improved accuracy and also broaden its usefulness.

The agricultural sector is one of the largest consumers of fresh water. With the ever-increasing problem of water scarcity, urbanization, over-population, and climate change, fresh water resources used by agriculture could be put to better use by redirecting it for drinking water purposes. In this context, many countries reuse treated urban waste water for irrigation, to overcome this problem. While this is a sustainable practice, the reuse of urban wastewater could facilitate the spread of pathogenic bacteria (or antibiotic resistant bacteria) in the subsoil region and consequently the groundwater. Since groundwater is one of the main sources of drinking water, the contaminants could pose a risk to human health. Furthermore, obtaining scientific data for emerging contaminants during water reuse is the need of the hour. The objective of this work is to build a mechanistic model that can aid in the development of large-scale risk assessment models; thus facilitating the setup of water reuse regulations for the relevant pathogenic organisms. In the present study, process based models were developed and evaluated using lab scale results. Then, the relative time scales of the processes are compared, and the relative importance of the various process studies are assessed. When assessing time scales of the processes, it is kept in mind that processes with relatively fast time scales can be approximated using equilibrium models, relatively slow processes can be neglected, and only the rate limiting processes can neither be neglected or further simplified in further model development. Therefore, an idea of the rate limiting processes assessed in lab scale can serve as important tools facilitating model simplification when evaluating larger scale models. A combined experimental and modelling approach has been used to study relevant transport and reactive processes during bacteria transport through sandy sediments. The mechanistic model contained transport processes which were implemented using the advective dispersive equation. An additional straining process was added using non-linear rate law. The biological processes of decay, respiration, attachment, and growth were expressed using linear rate laws. This mechanistic model was verified using data from fully water saturated, sediment packed lab-scale column experiments. Continuous injection of tracer, microspheres, and Enterococci (in water environments with and without dissolved oxygen and nutrients) was performed. The experiment was verified for three flow velocities (0.13, 0.08 and 0.02 cm/min), and the parameter values were compared for these flow velocities using dimensionless numbers. The linear rate coefficients were converted to a dimensionless form (Peclet and Damkoehler numbers respectively) to facilitate the comparison of processes across the various flow velocities. The results indicate that the processes of attachment and growth are flow dependent. Furthermore, in the presence of dissolved oxygen, attachment of bacteria to sediment was the most influential process. Sensitivity analysis showed that the parameters representing growth and respiration were influential, and care must be taken when using the results for field-scale experiments or models. These processes and parameters add new knowledge on the impact of urban wastewater reuse on the spread of pathogenic bacteria (especially resilient species like Enterococci), and emphasizes the importance of research in this area. Future work could focus on obtaining data from culture independent methods and extension of the model framework, and include (where necessary) non-linear rate laws. This will provide a critical pathway to developing a decision support framework for use by regulatory frameworks, policy makers, stakeholders, local and global environmental agencies, World Health Organization, or the United Nations.:List of Figures vii List of Tables xi List of Abbreviations xiii List of Symbols xv Summary xvii Zussamenfassung xix 1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Broad Scope. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Hypotheses and Research objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Outline of the work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 Concepts, terminologies, and methodology 7 2.1 Concepts and terminologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.2 The vadose zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.3 Porosity and pore models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.4 Darcy’s law . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Bacteria strain used and Processes Studied . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2.1 Enterococcus faecalis JH2-2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2.2 Advection and Dispersion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2.3 Straining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.4 Microbial Decay and Respiration . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.5 Microbial Attachment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.2.6 Microbial Growth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.2.7 Dimensionless numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.3 Experimental design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.4 Model setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3 Reactive-transport modelling of Enterococcus faecalis JH2-2 passage through water saturated sediment columns. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.2 Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2.1 Experimental study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2.2 Modeling and data analysis procedure. . . . . . . . . . . . . . . . . . . . . . . . 40 3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.3.1 Determination of hydraulic and non-reactive transport parameters (experiments E1 and E2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.3.2 Determination of parameters related to the bacteria transport (E3 series) . . . 45 3.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.4.1 Physical processes (E1 and E2) . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.4.2 Biological Processes (E3 series) . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.5 Conclusions and Outlook. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.6 Supplementary material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 4 Determining the impact of flow velocities on reactive processes associated with Enterococcus faecalis JH2-2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 4.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4.2 Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.2.1 Experimental setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.2.2 Model Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4.3.1 Tracer and microsphere experiments. . . . . . . . . . . . . . . . . . . . . . . . . 74 4.3.2 Bacteria experiments - comparison of processes. . . . . . . . . . . . . . . . . . . 75 4.4 Conclusions and Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 4.5 Supplementary material 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 4.6 Supplementary Material 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 5 Synthesis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.1 Discussion and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.2 Critical review, pathways towards future work . . . . . . . . . . . . . . . . . . . . . . . 91 Bibliography. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Note on the commencement of the doctoral procedure. . . . . . . . . . . . . . . . . . . . 107 Übereinstimmungserklärung. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 List of Publications and conference presentations. . . . . . . . . . . . . . . . . . . . . . . . 111 Acknowledgements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 / Der Agrarsektor ist einer der größten Verbraucher von Süßwasser. Angesichts der zunehmenden Wasserknappheit, der Verstädterung, der Überbevölkerung und des Klimawandels könnten die von der Landwirtschaft genutzten Süßwasserressourcen besser genutzt werden, indem sie für Trinkwasserzwecke umgewidmet werden. In diesem Zusammenhang verwenden viele Länder aufbereitetes kommunales Abwasser für die Bewässerung, um dieses Problem zu lösen. Dies ist zwar eine nachhaltige Praxis, aber die Wiederverwendung von kommunalem Abwasser könnte die Ausbreitung pathogener Bakterien (oder antibiotikaresistenter Bakterien) im Untergrund und damit im Grundwasser fördern. Da das Grundwasser eine der Hauptquellen für Trinkwasser ist, könnten diese Schadstoffe eine Gefahr für die menschliche Gesundheit darstellen. Darüber hinaus ist es ein Gebot der Stunde, wissenschaftliche Daten über neu auftretende Verunreinigungen bei der Wasserwiederverwendung zu gewinnen. Ziel dieser Arbeit ist es, ein mechanistisches Modell zu erstellen, das bei der Entwicklung groß angelegter Risikobewertungsmodelle behilflich sein kann und somit die Aufstellung von Vorschriften für die Wiederverwendung von Wasser für die relevanten pathogenen Organismen erleichtert. In der vorliegenden Studie wurden prozessbasierte Modelle entwickelt und anhand von Ergebnissen im Labormaßstab bewertet. Anschließend werden die relativen Zeitskalen der Prozesse verglichen und die relative Bedeutung der verschiedenen Prozessstudien bewertet. Bei der Bewertung der Zeitskalen der Prozesse wird berücksichtigt, dass Prozesse mit relativ schnellen Zeitskalen durch Gleichgewichtsmodelle angenähert werden können, relativ langsame Prozesse können vernachlässigt werden, und nur die ratenbegrenzenden Prozesse dürfen in der weiteren Modellentwicklung weder vernachlässigt noch vereinfacht werden. Daher kann eine Vorstellung von den ratenbegrenzenden Prozessen, die im Labormaßstab bewertet werden, als wichtiges Instrument zur Vereinfachung des Modells bei der Bewertung von Modellen in größerem Maßstab dienen. Ein kombinierter experimenteller und modellierender Ansatz wurde verwendet, um relevante Transport- und reaktive Prozesse während des Bakterientransports durch sandige Sedimente zu untersuchen. Das mechanistische Modell enthielt Transportprozesse, die mit Hilfe der Advektions-Dispersions-Gleichung implementiert wurden. Ein zusätzlicher Filtrationsprozess ('straining') wurde mit Hilfe nichtlinearer Ratengesetze hinzugefügt. Die biologischen Prozesse des Zerfalls, der Atmung, der Anhaftung und des Wachstums wurden durch lineare Ratengesetze ausgedrückt. Dieses mechanistische Modell wurde anhand von Daten aus vollständig wassergesättigten, sedimentgefüllten Säulenexperimenten im Labormaßstab verifiziert. Kontinuierliche Injektion von Tracer, Mikrosphären und Enterokokken (in Wasserumgebungen mit und ohne gelösten Sauerstoff und Nährstoffe) wurde durchgeführt. Das Experiment wurde für drei Strömungsgeschwindigkeiten (0,13, 0,08 und 0,02 cm/min) verifiziert, und die Parameterwerte wurden für diese Strömungsgeschwindigkeiten anhand dimensionsloser Zahlen verglichen. Die linearen Ratengesetze wurden in eine dimensionslose Form umgewandelt (Peclet- bzw. Damköhler-Zahlen), um den Vergleich der Prozesse bei den verschiedenen Strömungsgeschwindigkeiten zu erleichtern. Die Konzentrationen wurden in regelmäßigen Abständen sowohl am Einlass als auch am Auslass der Kolonnen gemessen. Die überprüften Prozesse waren Advektion, Dispersion, Filtration, Zerfall, Atmung, Wachstum und Anhaftung. Der Versuch wurde für drei Strömungsgeschwindigkeiten (0,13, 0,08 und 0,02 cm/min) wiederholt, und die verifizierten Parameterwerte wurden für diese Strömungsgeschwindigkeiten verglichen. Die Ergebnisse zeigen, dass die Prozesse der Anhaftung und des Wachstums strömungsabhängig sind. Darüber hinaus war bei Vorhandensein von gelöstem Sauerstoff die Anhaftung der Bakterien an das Sediment der einflussreichste Prozess. Die Sensitivitätsanalyse zeigte, dass die Parameter, die das Wachstum und die Atmung repräsentieren, einflussreich sind, so dass bei der Verwendung der Ergebnisse für Experimente oder Modelle im Feldmaßstab Vorsicht geboten ist. Diese Prozesse und Parameter liefern neue Erkenntnisse über die Auswirkungen der Wiederverwendung von kommunalem Abwasser auf die Ausbreitung pathogener Bakterien (insbesondere widerstandsfähiger Arten wie Enterokokken) und unterstreichen die Bedeutung der Forschung in diesem Bereich. Zukünftige Arbeiten könnten sich auf die Gewinnung von Daten aus kulturunabhängigen Methoden und die Erweiterung des Modellrahmens konzentrieren und (wo nötig) nichtlineare Parameter einbeziehen. Dies wird einen entscheidenden Weg zur Entwicklung eines Rahmens für die Entscheidungsfindung darstellen, der von Regulierungsbehörden, politischen Entscheidungsträgern, Interessengruppen sowie lokalen und globalen Umweltbehörden, der Weltgesundheitsorganisation oder den Vereinten Nationen genutzt werden kann.:List of Figures vii List of Tables xi List of Abbreviations xiii List of Symbols xv Summary xvii Zussamenfassung xix 1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Broad Scope. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Hypotheses and Research objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Outline of the work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 Concepts, terminologies, and methodology 7 2.1 Concepts and terminologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.2 The vadose zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.3 Porosity and pore models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.4 Darcy’s law . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Bacteria strain used and Processes Studied . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2.1 Enterococcus faecalis JH2-2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2.2 Advection and Dispersion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2.3 Straining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.4 Microbial Decay and Respiration . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.5 Microbial Attachment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.2.6 Microbial Growth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.2.7 Dimensionless numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.3 Experimental design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.4 Model setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3 Reactive-transport modelling of Enterococcus faecalis JH2-2 passage through water saturated sediment columns. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.2 Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2.1 Experimental study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2.2 Modeling and data analysis procedure. . . . . . . . . . . . . . . . . . . . . . . . 40 3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.3.1 Determination of hydraulic and non-reactive transport parameters (experiments E1 and E2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.3.2 Determination of parameters related to the bacteria transport (E3 series) . . . 45 3.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.4.1 Physical processes (E1 and E2) . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.4.2 Biological Processes (E3 series) . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.5 Conclusions and Outlook. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.6 Supplementary material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 4 Determining the impact of flow velocities on reactive processes associated with Enterococcus faecalis JH2-2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 4.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4.2 Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.2.1 Experimental setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.2.2 Model Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4.3.1 Tracer and microsphere experiments. . . . . . . . . . . . . . . . . . . . . . . . . 74 4.3.2 Bacteria experiments - comparison of processes. . . . . . . . . . . . . . . . . . . 75 4.4 Conclusions and Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 4.5 Supplementary material 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 4.6 Supplementary Material 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 5 Synthesis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.1 Discussion and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.2 Critical review, pathways towards future work . . . . . . . . . . . . . . . . . . . . . . . 91 Bibliography. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Note on the commencement of the doctoral procedure. . . . . . . . . . . . . . . . . . . . 107 Übereinstimmungserklärung. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 List of Publications and conference presentations. . . . . . . . . . . . . . . . . . . . . . . . 111 Acknowledgements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

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Dissolved oxygen concentrations are declining in the bottom waters of many lakes around the world, posing critical water quality concerns. Throughout my dissertation, I assessed how bottom-water dissolved oxygen may mediate the effects of climate and land use change on water quality in lakes. First, I characterized causes of variation in summer bottom-water temperature and dissolved oxygen. I demonstrated that spring air temperatures may play a greater role than summer air temperatures in shaping summer bottom-water dynamics. I then characterized the effects of declining bottom-water oxygen concentrations across diverse scales of analysis (i.e., using microcosm incubations, whole-ecosystem oxygenation experiments, and data analysis of >600 widespread lakes). I found that low dissolved oxygen concentrations contributed to release of nutrients and organic carbon from lake sediments, potentially altering the role of lakes in global biogeochemical cycles. Importantly, I also found support for a previously-hypothesized Anoxia Begets Anoxia feedback, whereby bottom-water anoxia (i.e., no dissolved oxygen) in a given year promotes increasingly severe occurrences of anoxia in following summers. This finding demonstrates the need for forecasts of future oxygen dynamics in lakes, as management actions to preempt the first occurrence of anoxia will be more effective than actions to restore ecological function after oxygen concentrations have already declined. To build the capacity for such forecasts, I led a systematic review of ecological forecasting literature that characterized the state of the field, emerging best practices, and relative predictability of four ecological variables. Combined, my dissertation provides a mechanistic examination of the effects of climate change on water quality in lakes worldwide, ultimately helping to anticipate, mitigate, and preempt future water quality declines. / Doctor of Philosophy / Changes in climate and land use have caused dissolved oxygen concentrations to decline in many lakes around the world. These declines are concerning because low oxygen concentrations can cause substantial water quality problems. If we could better predict future water quality, we may be able to develop more effective lake management programs. To help meet this need, I analyzed how dissolved oxygen has mediated historical changes in water quality, and how dissolved oxygen may affect water quality in the future. I focused on bottom-water (rather than surface-water) dissolved oxygen, because bottom waters are more likely to experience very low oxygen concentrations that can lead to water quality problems. I started by assessing the drivers of summer bottom-water dissolved oxygen in 615 lakes. Across these lakes, spring air temperatures played a greater role than summer air temperatures in shaping summer bottom-water temperature and dissolved oxygen. I then characterized the effects of declining bottom-water oxygen concentrations using small-scale incubations in the lab, manipulations of oxygen concentrations in a whole reservoir, and data analysis across 656 lakes. I found that low dissolved oxygen conditions led to the release of nutrients and organic carbon from lake sediments, which may worsen water quality. Importantly, I also found support for a feedback effect, whereby low bottom-water dissolved oxygen in one summer perpetuates oxygen declines in following summers. This finding motivates the need for forecasts of future dissolved oxygen concentrations, as management actions to stop the first occurrence of low oxygen concentrations will be more effective than actions to restore water quality after oxygen concentrations have already started to decline. To build capacity for lake oxygen forecasts, I synthesized many published papers that have predicted future ecological states, and I documented proposed best practices in this emerging field. Ultimately, by advancing our understanding of how climate and land use change affect water quality in lakes worldwide, my dissertation research will help to anticipate, mitigate, and preempt future water quality declines.

L-asparaginase (L-ASNase) é uma enzima com propriedades interessantes para a indústria médica, farmacêutica e de alimentos, que tem recebido atenção especial, inclusive no Brasil, por fazer parte do protocolo de tratamento de distúrbios linfoproliferativos, como a leucemia linfoblástica aguda (LLA). No mercado desde a década de 1970, as enzimas de origem bacteriana enfrentam algumas limitações por provocarem reações adversas graves em quase 80% dos pacientes em tratamento. Nesse contexto, L-ASNases provenientes de leveduras se destacam como alternativa, por serem mais próximas às congêneres humanas. A Antártica ainda é um ambiente pouco explorado, com grande diversidade de microrganismos com potencial para a produção de moléculas biológicas de interesse industrial. Nesse contexto, 150 leveduras isoladas de amostras de sedimento marinho coletadas na Península Antártica como parte do projeto MICROSFERA (PROANTAR/CNPq) foram avaliadas para a produção de L-ASNase. A triagem resultou em 9 isolados produtores, dos quais 7 pertencem ao gênero Leucosporidium. A linhagem L. muscorum CRM 1648 foi a que produziu mais enzima (540 U.L-1), com maior produtividade (5,6 U.L-1.h-1) e, por isso, foi alvo deste estudo. A análise univariada de fontes de carbono e nitrogênio indicou maior crescimento desse microrganismo e produção de L-ASNase em meio CD com extrato de levedura, prolina e sacarose. Ureia, cloreto de amônio e sulfato de amônio resultaram em baixa ou nenhuma produção da enzima, sugerindo que a metabolização de fontes de nitrogênio por essa linhagem está sob a influência do fenômeno de repressão catabólica pelo nitrogênio (RCN). Dois delineamentos experimentais do tipo fatorial completo resultaram em um aumento de 10 vezes na produção e produtividade da enzima (4582,5 U.L-1 e 63,6 U.L-1.h-1, respectivamente). A análise univariada da concentração inicial de inóculo (X0), pH inicial do meio, temperatura e adição de água do mar mostrou que a melhor condição para a produção foi: pH = 5,5 ou 6,5, cultivo a 15°C com adição de água do mar (25-50% m/v). A variável X0 não foi significativa nas concentrações avaliadas. Cultivos em biorreator (batelada) foram conduzidos em quatro diferentes níveis de oxigênio dissolvido (OD): (1) OD não controlado e abaixo de 20%, (2) OD não controlado e acima de 20%, (3) OD controlado em 80% e (4) OD controlado em 20%. Os resultados mostraram que OD é fator limitante para o crescimento de L. muscorum CRM 1648 e produção de L-ASNase por essa levedura e deve ser mantido acima de 35% para maior produção da enzima.Neste trabalho, a composição do meio e condições de cultivo foram estabelecidas para favorecer a produção de uma nova L-ASNase livre de atividade glutaminásica por levedura adaptada ao frio, abrindo espaço para novos estudos acerca de seu potencial antileucêmico e possível uso como alternativa às enzimas já existentes no mercado no tratamento de LLA. / L-asparaginase (L-ASNase) is an enzyme with interesting properties for medical, pharmaceutical and food industry, which has received special consideration, especially in Brazil, for being part of lymphoproliferative disorders treatment, such as acute lymphoblastic leukemia (ALL). Bacterial enzymes are on the market since the 1970s and face some limitations related to theirserious adverse reactions that reach almost 80% of all patients in treatment. In this context, L-ASNases from yeasts are highlighted as important alternative to bacterial enzymes, due to the closerphylogeny to human congeners. Antarctic environment has much to be explored, with a vast diversity of microorganisms with potential to produce biomolecules with industrial interest. A total of 150 yeasts isolated from Antarctic marine sediments as part of MICROSFERA project (PROANTAR/CNPq) were evaluated for L-ASNase production. The screening resulted in 9 producers, 7 species from the genus Leucosporidium. L. muscorum CRM 1648 was the strain that yielded the highest L-ASNase activity (540 U.L-1) and volumetric productivity (5.6 U.L-1.h-1). Carbon and Nitrogen sources were evaluated by a method of one-factor at a time (OFAT). From the gather results, sucrose, yeast extract and proline resulted in a maximal growth and highest enzyme production.The absence or low production of L-ASNase in medium with urea, ammonium chloride and ammonium sulfate suggests the presence of nitrogen catabolic repression (NCR). Carbon and nitrogen concentration were evaluated by full factorial design and yielded about ten times higher enzyme and volumetric productivity (4582.5 U.L-1 and 63.6 U.L-1.h-1, respectively). Initial inoculum concentration (X0), initial pH, temperature and concentration of seawater in the culture were evaluated by OFAT analysis and the best condition for L-ASNase production was: pH = 5.5 or 6.5, at 15 °C with addition of seawater (25-50 wt%). X0 was not considered a significant variable. Bioreactor assays (in batch regime) were performed in four different dissolved oxygen (DO) levels: (1) without DO control (DO remained under 20%), (2) without DO control (DO remained above 20%), (3) DO controlled at 80%, and (4) DO controlled at 20%.The results showed that DO is a key factor for growth of L. muscorum CRM 1648 and production of L-ASNase by this yeast and should be maintained above 35% for higher production of this enzyme.At this work, the medium and culture conditions were established to support the production of a novel glutaminase-free L-ASNase by a cold adapted yeast, opening a new path for further studies regarding its antileukemic potential and possible use as an alternative for ALL treatment.

Source water protection is important to maintain public health by keeping harmful pathogens out of drinking water. Non-point source pollution is often times a major contributor of pollution to surface waters, and this form of pollution can be difficult to quantify. This study examined physical, chemical, and microbiological water quality parameters that may indicate pollution and may help to identify sources of pollution. These included measures of organic matter, particles, and indicator organisms (fecal coliforms and E. coli). The parameters were quantified in the West Boylston Brook, which serves as a tributary to the Wachusett Reservoir and is part of the drinking water supply for the Metropolitan Boston area. Water quality was determined over four seasons at seven locations in the brook that were selected to isolate specific land uses. The water quality parameters were first analyzed for trends by site and by season. Then, a correlation analysis was performed to determine relationships among the water quality parameters. Lastly, ANOVA analyses were used to determine statistically significant variations in water quality along the tributary.

Water quality parameters including ammonia, nitrate+nitrite, phosphate, total suspended solids, Escherichia coli, and dissolved oxygen were statistically evaluated from sampling data collected by the Bureau of Water Quality (City of Muncie, Indiana) at five sampling locations in Delaware County over a five-year period (2002-2006). These data were also compared with water quality standards/guidelines to determine how sample values compared to acceptable levels of these parameters. Friedman's non-parametric test was used to study the differences between sites and seasons. Spearman's Rank Correlation was used to study the correlations between water quality parameters at each sampling site. Significant differences were observed for individual parameters when evaluated relative to sampling location based on pooled monthly collected data as well as data evaluated on a seasonal basis. These differences indicated the fact that different sources were responsible for observed concentrations at a particular location and that seasonal phenomenon such as precipitation, discharge and temperature also affected sample concentrations at individual sampling locations. Most notable were differences in geometric mean concentrations of ammonia, nitrate+nitrite, phosphate and E. coli upstream and downstream of the wastewater treatment plant (WWTP), with highest concentrations downstream, indicating the significant impact of the WWTP on water quality in the White River. Significant correlations observed among some study parameters suggested that sample concentrations may have been affected by similar sources. In comparison to water quality standards, concentrations of ammonia, nitrate+nitrite, phosphate, and E. coli were at unacceptable levels at most sampling locations. / Department of Natural Resources and Environmental Management