Graduate Theses & Dissertations

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Purification and Identification of Selenium-containing C-phycocyanin from Spirulina
Selenium is an essential trace nutrient to many organisms, yet in high concentrations it is toxic. Organic selenium is more bioavailable to aquatic biota than inorganic selenium, but is usually found in much lower concentrations. Algae are known to biotransform inorganic selenium into several organo-selenium compounds, but it is unknown whether any of these bioaccumulate in the food chain. In this study, selenium was incorporated into the methionine residues of an algal photosynthetic protein, c-phycocyanin from Spirulina spp. The extent of selenium incorporation was quantified by inductively coupled plasma-mass spectrometry (ICP-MS), and the protein was identified using electrospray mass spectrometry (ES-MS). C-phycocyanin was isolated and purified from Spirulina with a final recovery of 20-30 % of the total c-phycocyanin present. Selenomethionine replaced 92.8% ± 1.22 of the methionine residues in c-phycocyanin when grown in 2.5 ppm sodium selenite. ES-MS was used to obtain protein spectra, and pure c-phycocyanin was identified. Data of full scans provided estimated masses of both protein subunits--α-chain measured at 18,036 Da; β-chain measured at 19,250 Da--close to the theoretical masses. Protein fragmentation by collision-induced dissociation and electron capture dissociation provided approximately 52 % amino acid sequence match with c-phycocyanin from Spirulina platensis. This study demonstrates the incorporation of selenium into an algal protein, and the identification of c-phycocyanin using electrospray ionization-mass spectrometry. Author Keywords:
ROOSTING SELECTION BEHAVIOUR OF THE EASTERN WILD TURKEY AT ITS NORTHERN RANGE EDGE
As wild turkeys (Meleagris gallopavo silvestris) move farther north, informed management decisions are critical to support the sustainability of this reintroduced species. We tracked roost tree selection and patterns of the network of roost trees, for wild turkeys, over 2 years in Peterborough, ON, using GPS and VHF transmitters. Wild turkeys showed preference for taller and larger roost trees, with winter roosts closer to buildings. The roost network exhibited a scale-free network, meaning certain roosts served as hubs, while other roosts were less frequently used. The fine scale results suggest that roost trees are selected for predator avoidance, and that selection changes with the season, probably because of its influence on foraging ability. At a larger scale, winter roosts were chosen for their proximity to supplemental food sources. These findings demonstrate the dependence of wild turkeys on humans and the supplemental sources we unintentionally provide. Author Keywords:
Range-Based Component Models for Conditional Volatility and Dynamic Correlations
Volatility modelling is an important task in the financial markets. This paper first evaluates the range-based DCC-CARR model of Chou et al. (2009) in modelling larger systems of assets, vis-à-vis the traditional return-based DCC-GARCH. Extending Colacito, Engle and Ghysels (2011), range-based volatility specifications are then employed in the first-stage of DCC-MIDAS conditional covariance estimation, including the CARR model of Chou et al. (2005). A range-based analog to the GARCH-MIDAS model of Engle, Ghysels and Sohn (2013) is also proposed and tested - which decomposes volatility into short- and long-run components and corrects for microstructure biases inherent to high-frequency price-range data. Estimator forecasts are evaluated and compared in a minimum-variance portfolio allocation experiment following the methodology of Engle and Colacito (2006). Some consistent inferences are drawn from the results, supporting the models proposed here as empirically relevant alternatives. Range-based DCC-MIDAS estimates produce efficiency gains over DCC-CARR which increase with portfolio size. Author Keywords: asset allocation, DCC MIDAS, dynamic correlations, forecasting, portfolio risk management, volatility
Real-space renormalization group approach to the Anderson model
Many of the most interesting electronic behaviours currently being studied are associated with strong correlations. In addition, many of these materials are disordered either intrinsically or due to doping. Solving interacting systems exactly is extremely computationally expensive, and approximate techniques developed for strongly correlated systems are not easily adapted to include disorder. As a non-interacting disordered model, it makes sense to consider the Anderson model as a first step in developing an approximate method of solution to the interacting and disordered Anderson-Hubbard model. Our renormalization group (RG) approach is modeled on that proposed by Johri and Bhatt [23]. We found an error in their work which we have corrected in our procedure. After testing the execution of the RG, we benchmarked the density of states and inverse participation ratio results against exact diagonalization. Our approach is significantly faster than exact diagonalization and is most accurate in the limit of strong disorder. Author Keywords: disorder, localization, real-space renormalization, strong correlations
Regional Assessment of Soil Calcium Weathering Rates and the Factors that Influence Lake Calcium in the Muskoka River Catchment, Central Ontario
(MRC) in central Ontario was carried out to determine the range and spatial distribution of soil Ca weathering rates, and investigate the relationships between lake Ca and soil and catchment attributes. The MRC is acid-sensitive, and has a long history of impacts from industrial emission sources in Ontario and the United States. Small headwater catchments were sampled for soil and landscape attributes (e.g. elevation, slope, catchment area) at 84 sites. Soil Ca weathering rates, estimated with the PROFILE model, were low throughout the region (average: 188 eq/(ha·yr)) compared to global averages, and lower than Ca deposition (average: 292 eq/(ha·yr)). Multiple linear regression models of lake Ca (n= 306) were dominated by landscape variables such as elevation, which suggests that on a regional scale, landscape variables are better predictors of lake Ca than catchment soil variables. Author Keywords: Calcium, Lakes, Regional assessment, Regression, Soils, Weathering
Regional differences in the whistles of Australasian humpback dolphins (genus Sousa)
Most delphinids produce narrowband frequency-modulated whistles with a high level of plasticity to communicate with conspecifics. It is important to understand geographic variation in whistles as signal variation in other taxa has provided insight into the dispersal capabilities, genetic divergence and isolation among groups, and adaptation to ecological conditions. I investigated whistle variation of Indo-Pacific humpback dolphins (Sousa chinensis chinensis), Taiwanese humpback dolphins (S. c. taiwanensis) and Australian humpback dolphins (S. sahulensis) to test whether differences in whistles support the hypotheses of population structure, regional and species differences in the genus Sousa, which were based on morphological and genetic data. I also investigated important factors that may contribute to local distinctiveness in whistles including behavioural state, group size, and the influence of vessel noise. Multivariate analyses of seven acoustic variables supported the hypotheses of population structure, regional and species differences. Acoustic diversification between groups is likely influenced by behaviour and social contexts of whistles, and environmental noise. The use of sound to identify discrete groups of humpback dolphins may be important in future studies where genetic and morphological studies may not reveal recent differentiation or are difficult to conduct. Author Keywords: Bioacoustics, Cetacean, Geographic variation, Population biology, Sousa, Whistle characteristics
Regulation of Cytokinins During Kernel Development in High and Low Yielding Oat and Barley Lines
Cytokinins (CKs) are a family of plant phytohormones responsible for many areas of plant growth and development. There are four free base types of CKs found in higher plants, trans-zeatin (tZ), N6-(∆2-isopentenyl)adenine (iP), cis-Zeatin (cZ) and dihydrozeatin (DZ). CK biosynthesis is regulated by adenosine phosphate-isopentenyltransferase (IPT), which is encoded by a multi-gene family in many plant species. There are two types of IPT pathways responsible for CK production, the tRNA pathway and the AMP (ATP/ADP) pathway. The tRNA pathway putatively produces cZ and the latter predominantly produces iP type nucleotides. CKs have long been studied for their role in stress tolerance, signal transduction, and involvement in many areas of plant growth and development. This study focuses on the role of CKs and CK biosynthesis by IPT during kernel development and comparisons of its regulation in high and low yielding barley and oat lines. The sequence of a putative IPT encoding gene in barley and oat was identified by a blast search of other known IPT gene fragments in closely related species. Quantitative Real time PCR results based on primers designed for the putative barley and oat IPT gene revealed changes in expression of IPT during different stages of kernel development, but no significance difference was associated with yield. Correlation of IPT gene expression in barley with cZ CK profiles measured by HPLC-MS/MS, confirms a putative IPT gene is a tRNA- IPT. HPLC-MS/MS results reveal some CK types, such as benzyladenine, are more predominant in higher yielding lines. This suggests different types of CKs play a role in yield production. Future studies on more IPT genes in the barley and oat IPT gene family will outline a more clear representation of the role of IPT in barley kernel development. Author Keywords: Benzyladenine, Cereal grain, Cytokinin, Isopentenyl Transferase, Mass Spectrometry, Real Time PCR
Reintroducing species in the 21st century
Climate change has had numerous impacts on species' distributions by shifting suitable habitat to higher latitudes and elevations. These shifts pose new challenges to biodiversity management, in particular translocations, where suitable habitat is considered crucial for the reintroduced population. De-extinction is a new conservation tool, similar to reintroduction, except that the proposed candidates are extinct. However, this novel tool will be faced with similar problems from anthropogenic change, as are typical translocation efforts. Using ecological niche modelling, I measured suitability changes at translocation sites for several Holarctic mammal species under various climate change scenarios, and compared changes between release sites located in the southern, core, and northern regions of the species' historic range. I demonstrate that past translocations located in the southern regions of species' ranges will have a substantial decline in environmental suitability, whereas core and northern sites exhibited the reverse trend. In addition, lower percentages (< 50% in certain scenarios) of southern sites fall above the minimal suitability threshold for current and long-term species occurrence. Furthermore, I demonstrate that three popular de-extinction candidate species have experienced changes in habitat suitability in their historic range, owing to climate change and increased land conversion. Additionally, substantial increase in potentially suitable space is projected beyond the range-limits for all three species, which could raise concerns for native wildlife if de-extinct species are successfully established. In general, this thesis provides insight for how the selection of translocation sites can be more adaptable to continued climate change, and marks perhaps the first rigorous attempt to assess the potential for species de-extinction given contemporary and predicted changes in land use and climate. Author Keywords: climate change, de-extinction, ecological niche models, MaxEnt, reintroduction, translocation
Relationship Between Precarious Employment, Behaviour Addictions and Substance Use Among Canadian Young Adults
This thesis utilized a unique data-set, the Quinte Longitudinal Survey, to explore relationships among precarious employment and a range of mental health problems in a representative sample of Ontario young adults. Study 1 focused on various behavioural addictions (such as problem gambling, video gaming, internet use, exercise, compulsive shopping, and sex) and precarious employment. The results showed that precariously employed men were preoccupied with gambling and sex while their female counterparts preferred shopping. Gambling and excessive shopping diminished over time while excessive sexual practices increased. Study 2 focused on the association between precarious employment and substance abuse (such as tobacco, alcohol, cannabis, hallucinogens, stimulants, and other substances). The results showed that men used cannabis more than women, and the non-precarious employed group abused alcohol more than individuals in the precarious group. This research has implications for both health care professionals and intervention program developers when working with young adults in precarious jobs. Author Keywords: Behaviour Addictions, Precarious Employment, Substance Abuse, Young Adults
Relationships between Dissolved Organic Matter and Vanadium Speciation in the Churchill River, MB and the Mackenzie River Basin, NWT using diffusive gradients in thin films (DGT)
This study examines the influence of dissolved organic matter (DOM) on dissolved vanadium (V) speciation in the Churchill River and Great Slave Lake using diffusive gradients in thin film (DGT). Vanadium is commonly found in natural environments such as rivers, lakes and oceans. It regulates normal cell growth, but in excessive amounts, it can have toxic effects on human and aquatic organisms. The use of in situ, time integrated DGT devices allows to better (1) monitor the most bioavailable fraction of V, the DGT-labile V, in Arctic Rivers and (2) assess the influence of DOM on dissolved V speciation. Higher DGT-labile V was found in the the central regions of the Mackenzie River (MR), with an average of 7.7 ± 2.3 nM, likely due to sediment leaching and permafrost thawing. The Churchill River and Great Slave Lake (GSL) showed lower DGT-labile V levels (2.2 ± 1.6 nM and 3.6 ± 2.7 nM, respectively), compared to central regions in MR. The CR DGT-labile V concentrations was positively correlated to protein-like DOM concentration and abundance (r = 0.3, p < 0.05). The data collected from this study will help in developing new strategies regarding environmental health and impact assessments of environmentally hazardous waste that consist of potentially high levels of toxic vanadium species. Developments in the use of DGT devices as a sampling method will also aid in future studies involved in analyzing environmental health and specifically dissolved V species in natural waters. Author Keywords: diffusive gradients in thin-films, dissolved organic matter, fluorescence, mass spectrometry, UV-Vis, vanadium
Relationships between bird densities and distance to mines in Northern Canada
Increased mining activity in the Canadian Arctic has resulted in significant changes to the environment that may be influencing some tundra-nesting bird populations. In this thesis I examine the direct and indirect effects of mining on birds nesting in the Canadian Arctic. I first perform a literature review of the effects that mining in the Arctic has on northern environments and wildlife and outline several ways in which mines affect Arctic-breeding birds. By using the Program for Regional and International Shorebird Monitoring (PRISM) Arctic plot-based bird survey data from across the Canadian Arctic, collected from 1995 to 2018, I identify the effects of distance to mining operations on the occupancy patterns of Arctic-breeding bird species. Six species’ densities were significantly impacted by mine proximity (Canada/Cackling Goose, Long-tailed Duck, Long-tailed Jaeger, Pectoral Sandpiper, Savannah Sparrow, and Rock Ptarmigan) across five major mine sites. Each species has its own unique relationship to distance from mining activity. Author Keywords: Bird populations, Canadian Arctic, Mining, Mining activities, PRISM, Tundra-nesting birds
Representation Learning with Restorative Autoencoders for Transfer Learning
Deep Neural Networks (DNNs) have reached human-level performance in numerous tasks in the domain of computer vision. DNNs are efficient for both classification and the more complex task of image segmentation. These networks are typically trained on thousands of images, which are often hand-labelled by domain experts. This bottleneck creates a promising research area: training accurate segmentation networks with fewer labelled samples. This thesis explores effective methods for learning deep representations from unlabelled images. We train a Restorative Autoencoder Network (RAN) to denoise synthetically corrupted images. The weights of the RAN are then fine-tuned on a labelled dataset from the same domain for image segmentation. We use three different segmentation datasets to evaluate our methods. In our experiments, we demonstrate that through our methods, only a fraction of data is required to achieve the same accuracy as a network trained with a large labelled dataset. Author Keywords: deep learning, image segmentation, representation learning, transfer learning

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Format: 2024/05/18