Graduate Theses & Dissertations

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Intra-seasonal Variation in Black Tern Nest-site Selection and Survival
Resources and risk are in constant flux and an organism’s ability to manage change may improve their likelihood of persistence. I examined intra-seasonal variation in nest-site selection and survival of a declining wetland bird, the Black Tern (Chlidonias niger surinamensis). I modelled nest site occupancy and survival of early and late-nesting birds as a function of static and dynamic factors. Early-nesting birds selected nest sites based on the degree and direction of habitat change that occurred over the nesting cycle, while late-nesting birds selected sites based on static conditions near the time of nest-site selection. Nest age had the strongest influence on daily survival rate for both early and late-nesting birds, but the shape of this relationship showed intra-seasonal differences. Additionally, early-season survival improved slightly with increasing vegetation coverage and distance between conspecific nests, while late-season survival increased with clutch size. My results suggest that intra-seasonal variation in nest-site selection and survival is driven by changing habitat conditions and predator behavior. Author Keywords: Black Tern, Chlidonias niger surinamensis, daily survival rate, intra-seasonal variation, nest-site selection
Developing social skills
Guidelines regarding social skills interventions for children with ASD suggest incorporating a holistic approach. This includes increasing the family’s understanding of deficits associated with ASD, integrations of natural environments, and parents as active agents while supporting their well-being. The current availability of holistic parent-mediated interventions for children with ASD is limited, with no qualitative understanding of its potential benefits for either the parent or child. The current study examined qualitative parent reports on a parent-mediated social skills intervention for children with ASD (TalkAbilityTM) incorporating a longitudinal approach (i.e., 6-month follow-up). Following Braun and Clarke’s model of thematic analysis, data was coded into four themes: 1) communication difficulties, frustrations and progress, 2) social relationships and concerns, 3) communication strategies, and 4) thoughts and emotions surrounding TalkAbilityTM. Results highlight the importance of considering parent experiences regarding interventions for their child’s social communication skills through a qualitative viewpoint. Author Keywords: autism spectrum disorder, parent-mediated intervention, qualitative review
In situ measurements of trace metal species in the Athabasca and Mackenzie Rivers using diffusive gradient in thin films (DGT) devices
This study assesses the bioavailable metal (Cu, Ni, Zn, Pb) species in the Athabasca-Mackenzie watersheds using diffusive gradient in thin films (DGT) devices. Metal toxicity is not only based on the concentration of metal in natural waters, but also on the nature of metal species. Four main forms in aquatic systems are: free ion, inorganic species, DOM bound (humic) species and metal colloidal species. The free ion and inorganic species and very small humic species are known as DGT-labile species and, are considered to be more bioavailable to micro-organisms due to the size and thus may be toxic to microorganisms. In this study, DGT devices were applied to (1) monitor the DGT-labile metal species in the lower Athabasca River and the Mackenzie River watershed and (2) assess the DGT-labile metal concentrations on temporal and spatial scales. In the lower Athabasca River, comparison between the DGT results and the Windermere Humic Acid Model (WHAM) calculation indicated good agreements for all metals when the precipitated iron(III) hydroxide was assumed as an active binding surface. No significant variations in labile species were found over 2003-2012 (RAMP database) despite the development of oil sands. In the Mackenzie River, no significant difference in DGT-labile metal concentrations and DOC concentrations was found in yearly basis 2012-2014. Only DOC was lower in August (6.98 and 3.85 ppm, respectively; p< 0.05) due to dilution from heavy rain events. Spatially, DGT-labile Cu and Ni in the downstream Mackenzie River were higher than upstream (1.79 and 0.58 ppb for Cu, 1.68 and 0.77 ppb for Ni, 4.06 and 6.91 ppm for DOC; p < 0.05). Overall the in situ measurements of metals constitute a benchmark for future studies in water quality and be helpful in environmental management in Alberta and the Northwest Territories in Canada. Author Keywords: Athabasca River, DGT, Mackenzie River, Speciation, Trace Metal, WHAM
Novel Silica Sol-Gel Passive Sampler for Mercury Monitoring in Aqueous Systems
A novel passive sampler for mercury monitoring was prepared using organosilica sol-gel materials. It comprises a binding layer with thiol groups for mercury complexation and a porous diffusive layer through which mercury can diffuse and arrive at the binding layer. Our study demonstrated that this new sampler follows the principle of passive sampling. The mass of mercury accumulated in the binding layer depends linearly on the mercury concentration in solution, the sampling rate and the exposure time. A typical sol-gel sampler is characterized by a diffusive layer of 1.2 &mum, in which mercury ions diffuse with a coefficient of D = 0.09~10-6 cm2/s. The capacity for mercury uptake is approximately 0.64 &mug/cm2. Mercury diffusion and binding in the passive sampler are independent of the type of mercury-chloride complex. Its sampling rate increases with increasing water turbulence and decreases with increasing DOM amount. The field trial of sol-gel sampler in Miller Creek shows the concentration gained from the sol-gel passive sampler is slightly lower than that from the spot sampling. Author Keywords:
Time Series Algorithms in Machine Learning - A Graph Approach to Multivariate Forecasting
Forecasting future values of time series has long been a field with many and varied applications, from climate and weather forecasting to stock prediction and economic planning to the control of industrial processes. Many of these problems involve not only a single time series but many simultaneous series which may influence each other. This thesis provides methods based on machine learning of handling such problems. We first consider single time series with both single and multiple features. We review the algorithms and unique challenges involved in applying machine learning to time series. Many machine learning algorithms when used for regression are designed to produce a single output value for each timestamp of interest with no measure of confidence; however, evaluating the uncertainty of the predictions is an important component for practical forecasting. We therefore discuss methods of constructing uncertainty estimates in the form of prediction intervals for each prediction. Stability over long time horizons is also a concern for these algorithms as recursion is a common method used to generate predictions over long time intervals. To address this, we present methods of maintaining stability in the forecast even over large time horizons. These methods are applied to an electricity forecasting problem where we demonstrate the effectiveness for support vector machines, neural networks and gradient boosted trees. We next consider spatiotemporal problems, which consist of multiple interlinked time series, each of which may contain multiple features. We represent these problems using graphs, allowing us to learn relationships using graph neural networks. Existing methods of doing this generally make use of separate time and spatial (graph) layers, or simply replace operations in temporal layers with graph operations. We show that these approaches have difficulty learning relationships that contain time lags of several time steps. To address this, we propose a new layer inspired by the long-short term memory (LSTM) recurrent neural network which adds a distinct memory state dedicated to learning graph relationships while keeping the original memory state. This allows the model to consider temporally distant events at other nodes without affecting its ability to model long-term relationships at a single node. We show that this model is capable of learning the long-term patterns that existing models struggle with. We then apply this model to a number of real-world bike-share and traffic datasets where we observe improved performance when compared to other models with similar numbers of parameters. Author Keywords: forecasting, graph neural network, LSTM, machine learning, neural network, time series
Positive Solutions for Boundary Value Problems of Second Order Ordinary Differential Equations
In this thesis, we study modelling with non-linear ordinary differential equations, and the existence of positive solutions for Boundary Value Problems (BVPs). These problems have wide applications in many areas. The focus is on the extensions of previous work done on non-linear second-order differential equations with boundary conditions involving first-order derivative. The contribution of this thesis has four folds. First, using a fixed point theorem on order intervals, the existence of a positive solution on an interval for a non-local boundary value problem is obtained. Second, considering a different boundary value problem that consists of the first-order derivative in the non-linear term, an increasing solution is obtained by applying the Krasnoselskii-Guo fixed point theorem. Third, the existence of two solutions, one solution and no solution for a BVP is proved by using fixed point index and iteration methods. Last, the results of Green's function unify some methods in studying the existence of positive solutions for BVPs of nonlinear differential equations. Examples are presented to illustrate the applications of our results. Author Keywords: Banach Space, Boundary Value Problems, Differential Equations, Fixed Point, Norm, Positive Solutions
Emotional Competencies in Mothers and Children and their Relationship with Health Care Utilization, Somatization and Health Anxiety.
Young children learn their emotion regulation skills by modeling and internalizing their caregivers' emotional competencies. Inadequate or problematic emotional competencies in parents can result in insufficient development of these competencies in children, which can have severe consequences on multiple domains of their lives, including physical wellbeing. This study examined the relationship between emotional competencies, health care usage rates, somatization and health anxiety in the context of a family with young children. Participants were mothers of children 4-11 years old recruited in the community. The results revealed a relationship between mother’s emotional competencies and mother and child’s health care usage rates. Mother’s health care usage rates were also linked to mother’s health anxiety and child’s somatic symptoms. These findings add to our understanding of the relationship between emotional competencies of parents and children, and the effects it can have on both mother’s and child’s physical wellbeing. Implications and avenues for future research are discussed. Author Keywords: emotional competencies, health care usage, mother and child, somatization
evolutionary ecology of Alaska's mountain goats with management implications
The integration of genetic and environmental information can help wildlife managers better understand the factors affecting a species’ population structure and their response to disturbance. This thesis uses genetic techniques to assess the broad and fine scale population structure of mountain goats in Alaska. The first chapter aims to determine the number of genetically distinct subpopulations and model the demographic history of mountain goats in Alaska. The second chapter investigates the population structure and demographic history of mountain goats in Glacier Bay National Park and examines the impact that climate change will have on these mountain goats. My results indicate that Alaska has eight subpopulations which diverged during the Wisconsin glaciation. In Glacier Bay, population structure is reflective of the landscape during colonization, and mountain goat population density and movement corridors are likely to decline due to future climate change. Author Keywords: Alaska, biogeography, gene flow, landscape genetics, mountain goat, population genetic structure
Mfsd8 regulates growth and multicellular development in Dictyostelium discoideum
The neuronal ceroid lipofuscinoses (NCLs), commonly known as Batten disease, are a family of inherited neurodegenerative lysosomal storage disorders. CLN7 disease is a subtype of NCL that is caused by mutations in the MFSD8 gene. MFSD8 encodes a lysosomal transmembrane protein that is predicted to play a role in transporting small substrates across membranes. However, little is known about its role and substrate specificity. Previous work identified an ortholog of human MFSD8 in the social amoeba Dictyostelium discoideum and reported its localization to endocytic compartments. In this study, the effects of mfsd8 loss during Dictyostelium growth and multicellular development were further characterized. Dictyostelium mfsd8- cells displayed increased rates of proliferation and pinocytosis in liquid media. During growth, loss of mfsd8 altered lysosomal enzymatic activities and reduced the intracellular and extracellular levels of autocrine proliferation repressor A. mfsd8- cells grown on a lawn of bacteria formed plaques in a shorter period of time compared to WT cells, providing additional support for the enhanced growth of mfsd8- cells. Upon starvation, the aggregation of mfsd8- cells was delayed, and mfsd8- cells formed more mounds that were smaller in size, which may be attributed to the reduced cell-substrate adhesion and altered lysosomal enzymatic activities observed for mfsd8- cells. Following aggregation, tipped mound formation was delayed, however, loss of mfsd8 did not affect the timing of slug/finger and fruiting body formation. Additionally, slug migration was reduced in mfsd8- cells. These aberrant phenotypes, excluding fruiting body formation, were effectively or partially rescued when Mfsd8-GFP was introduced into mfsd8- cells. Overall, these results show that Mfsd8 plays a role in regulating growth and developmental processes in Dictyostelium via lysosomal-associated functions. Author Keywords: CLN7, Dictyostelium discoideum, Lysosomes, MFSD8, Neuronal Ceroid Lipofuscinoses
Electrochemical Characterization of Giardia Intestinalis Cytochromes b5
Giardia intestinalis is a protozoan parasite that causes waterborne diarrheal disease in animals and humans. It is an unusual eukaryote as it lacks the capacity for heme biosynthesis; nonetheless it encodes heme proteins, including three cytochrome b5 isotypes (gCYTB5s) of similar size. Homology modelling of their structures predicts increased heme pocket polarity compared to mammalian isotypes, which would favour the oxidized state and lower their reduction potentials (E°’). This was confirmed by spectroelectrochemical experiments, which measured E°’ of -171 mV, -140 mV and -157 mV for gCYTB5-I, II, III respectively, compared to +7 mV for bovine microsomal cytochrome b5. To explore the influence of heme pocket polarity in more detail, five gCYTB5-I mutants in which polar residues were replaced by nonpolar residues at one of three positions were investigated. While these substitutions all increased the reduction potential, replacement of a conserved tyrosine residue at position-61 with phenylalanine had the most significant effect, raising E°’ by 106 mV. This tyrosine residue occurs in all gCYTB5s and is likely the greatest contributor to their low reduction potentials. Finally, complementary substitutions were made into a bovine microsomal cytochrome b5 triple mutant to lower its reduction potential. These not only lowered the E°’ by more than 140 mV but also weakened the interaction of heme with the protein. The lower reduction potentials of the gCYTB5s may indicate that these proteins have different roles from their more well-known mammalian counterparts. Author Keywords:
Application of One-factor Models for Prices of Crops and Option Pricing Process
This thesis is intended to support dependent-on-crops farmers to hedge the price risks of their crops. Firstly, we applied one-factor model, which incorporated a deterministic function and a stochastic process, to predict the future prices of crops (soybean). A discrete form was employed for one-month-ahead prediction. For general prediction, de-trending and de-cyclicality were used to remove the deterministic function. Three candidate stochastic differential equations (SDEs) were chosen to simulate the stochastic process; they are mean-reverting Ornstein-Uhlenbeck (OU) process, OU process with zero mean, and Brownian motion with a drift. Least squares methods and maximum likelihood were used to estimate the parameters. Results indicated that one-factor model worked well for soybean prices. Meanwhile, we provided a two-factor model as an alternative model and it also performed well in this case. In the second main part, a zero-cost option package was introduced and we theoretically analyzed the process of hedging. In the last part, option premiums obtained based on one-factor model could be compared to those obtained from Black-Scholes model, thus we could see the differences and similarities which suggested that the deterministic function especially the cyclicality played an essential role for the soybean price, thus the one-factor model in this case was more suitable than Black-Scholes model for the underlying asset. Author Keywords: Brownian motion, Least Squares Method, Maximum Likelihood Method, One-factor Model, Option Pricing, Ornstein-Uhlenbeck Process
Fish and invertebrate use of invasive Phragmites in a Great Lakes freshwater delta
Invasive Phragmites australis ssp. australis (herein “Phragmites”) has established and rapidly spread throughout many coastal areas of the Great Lakes. Known to displace native vegetation communities as it forms large, monotypic stands, Phragmites has a bad reputation when it comes to losses of biodiversity and habitat provision for wildlife. However, the extent to which Phragmites provides habitat for fish and invertebrates in coastal freshwater wetlands remains relatively unquantified. Thus, this study assessed whether fish assemblages and invertebrate communities in stands of Phragmites differ from those in stands of two native emergent vegetation communities, Typha spp. and Schoenoplectus spp. The findings showed significant differences in habitat variables among the vegetation communities in terms of water depth, macrophyte species richness, stem density and water quality. While abundance of the functional feeding group filterer-collectors was found to be significantly less in stands of Phragmites when compared to Schoenoplectus, no difference was observed in invertebrate taxa richness among vegetation communities. Lastly, no difference in fish assemblage or invertebrate community was detected when using multivariate analyses, implying that invasive Phragmites provides habitat that appears to be as valuable for fish and invertebrates as other emergent vegetation types in the St. Clair River Delta. The findings of this study will ultimately benefit the literature on invasive Phragmites and its role as fish habitat in freshwater wetlands, and aid management agencies in decisions regarding control of the invasive species. Author Keywords: aquatic invasive species, aquatic macroinvertebrates, freshwater fish, freshwater wetlands, nMDS, Phragmites

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