Graduate Theses & Dissertations

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Impacts of Cover Crops on Soil Health, Soil Nitrogen Dynamics, and Cytokinin Profiles
In Ontario, the dominant cash crop rotations consist of soybean (SB), which is a leguminous crop grown in rotation with maize (MZ) and winter wheat (WW). In addition to these crops, some farmers integrate cover crops (CC) into crop rotation, especially during the fallow period and winter seasons, to reduce nitrogen (N) losses via nitrate (NO3-) leaching and emission of N2 and the greenhouse gas nitrous oxide (N2O). This thesis focused on understanding the impact of crop phases in a MZ-(SB-WW)-CC rotation on the abundance of N-cycling bacterial communities that mediate nitrification and denitrification pathways. In addition, the influence of CCs on soil cytokinin (CK) profiles, which are plant growth-promoting hormones, were studied in a greenhouse trial to assess their potential impacts when integrating CCs into crop rotations. In particular, the relationship between traditional soil health parameters and the soil CK profiles was studied to understand how CKs might reflect biotic interactions and soil vitality. Results indicate N fertilizer application mono ammonium phosphate (MAP) and starter N:P: K (24:6:24) during WW planting in fall largely supported nitrifying bacterial communities (amoA) and potentially contributed to NO3- leaching. Management of MZ, which included spring-applied MAP resulted in larger denitrifying (nirK) bacterial communities, increasing the potential risk of N-loss via emission of dinitrogen gas (N2) and greenhouse gas N2O. However, CC soils had significantly lower nirK than MZ, reflecting the importance of strong and deep root systems of CCs, which have a higher ability to scavenge the substrates for denitrifying communities (NO3-). This highlights the importance of growing CCs in reducing the potential risk for N-loss via leaching and denitrification. Additionally, in the greenhouse trial, the ability of CCs to affect CK was detected, highlighting the importance of integrating CC in crop rotations. This is particularly noteworthy, given that total CK profiles showed strong associations with traditional soil health parameters such as labile or active carbon and soil microbial community diversity. It was concluded that total soil CK can be used as a novel and dynamic soil health measure. Future research on quantifying N2O fluxes and levels of NO3- in leachates would provide a more precise understanding of the impact of different crop rotation phases on N-dynamics in these fields. Further studies on single or combined measures of soil CKs are warranted to develop its potential as a practical and effective soil health parameter. Author Keywords: Cover crops, Crop rotations, Cytokinin hormone, Nitrogen Cycle, qPCR, Soil health
Deep learning for removal of non-resonant background in CARS hyperspectroscopy
In this work, a deep learning approach proposed by Valensise et al. [3] for extracting Raman resonant spectra from measured broadband CARS spectra was explored to see how effective it is at removing NRB from our experimentally measured “spectral-focusing”-based approach to CARS. A large dataset of realistic simulated CARS spectra was used to train a model capable of performing this spectral retrieval task. The non-resonant background shape used in creating the simulated CARS spectra was altered, to mimic our experimentally measured NRB response. Two models were trained: one using the original approach (Specnet) and one using the updated NRB “Specnet Plus”, and then tested their ability to retrieve the vibrationally resonant spectrum from simulated and measured CARS spectra. An error analysis was performed to compare the model's retrieval performance on two simulated CARS spectra. The modified model's mean squared error value was five and two times lower for the first and second simulated CARS spectra, respectively. Specnet Plus was found to be more effective at extracting the resonant signals. Finally, the NRB extraction abilities of both models are tested on two experimentally measured CARS hyperspectroscopy samples (starch and chitin), with the updated NRB model (Specnet Plus) outperforming the original Specnet model. These results suggest that tailoring the approach to reflect what we observe experimentally will improve our spectral analysis workflow and increase our imaging potential. Author Keywords:
Effect of Attending a Virtual Oncology Camp on Childhood Cancer Patient's Pyshcosocial Functioning and Parental Stress - A Pilot Study
Objectives/purpose: The current study examined whether attending a 1-month virtual oncology camp (VOC) improved resilience and hope in childhood cancer patients and parental/caregiver stress. Methods:Childhood cancer patients/survivors and their parent/caregivers enrolled for VOC, participated in an online anonymous survey: before, after and 3-months after VOC. The survey included the Child and Youth Resilience Measure (CYRM) and the Snyder’s Children’s Hope Scale (CHS) for the childhood cancer patients/survivors and the Pediatric Inventory for Parents (PIP) for parent/caregivers. Results:CYRM scores increased from T1 to T2 (d=0.86). Compared to T1, at T2 CHS scores also increased (d=1.33). Both CHS and CYRM scores remained higher at T3 compared with T1 (d=1.34; d=0.86). There were no changes in PIP scores between any time points. Conclusion and significance: Our study demonstrated that participation in a VOC improved children’s resilience and hope but did not change parental stress. Highlighting the clinical significance of these VOCs and the impacts they have on childhood cancer patients/survivors. Author Keywords: cancer, children, hope, parental stress, resilience, virtual oncology camp
Vulnerability and resilience
The Minority Stress Model proposes that LGBTQ+ people experience stressors unique to their identity that negatively impact their mental well-being. The model also outlines that, in the case of the LGBTQ+ community, two minority coping resources - social support and connection to the LGBTQ+ community – may act as potential minority stress buffers; however, research has been unable to determine if these are effective buffers. The current study used multiple regression and multilevel modelling to test the processes of the Minority Stress Model among 451 LGBTQ+ people over 25 timepoints during the COVID-19 pandemic. Although minority stressors and coping resources were associated with psychological distress in the expected directions, an interesting interaction between the two measures of minority stress was revealed and neither minority coping resource was found to buffer the association between minority stress and distress. In conclusion, the present study found partial support for the Minority Stress Model using longitudinal data but highlights the complex nature of these processes and how they are conceptualised in research. Author Keywords: identity concealment, LGBTQ+ community, mental health, minority coping, minority stress model, social support
Organic Matter and Total Mercury in Acid-Sensitive Lakes in Ireland
The following study measured dissolved organic carbon (DOC) and total mercury (THg) concentrations in acid sensitive lakes in the Republic of Ireland. Sixty-eight upland lakes and 48 lowland lakes were sampled for DOC; the upland lakes were additionally sampled for THg. Spatial variability of DOC was explained by regional precipitation and soil organic matter. A subset of lakes was tested for long-term trends and in contrast to reports of rising DOC in European surface waters, changes in DOC were minor. Spatial variability in THg was explained by DOC and organic matter aromaticity. Long-term THg concentrations increased, likely caused by inputs of terrestrial THg. A subset of lakes was sampled for sediment and soil and the results suggested soils drove THg variation in lake water and sediment. Lake water and sediment THg was low and consistent with background regions, while soil THg was relatively high due to high organic content. Author Keywords: Dissolved Organic Carbon, Lakes, Organic Matter, Soil, Total Mercury, Water
Active layer thermal regime in subarctic wetlands at the southern edge of continuous permafrost in Canada
The fine-scale controls of active layer dynamics in the subarctic at the southern edge of continuous permafrost are currently poorly understood. The goal of this thesis was to understand how environmental conditions associated with upland tundra heath, open graminoid fen, and palsas/peat plateaus affected active layer thermal regime in a subarctic peatland in northern Canada. Indices of active layer thermal regime were derived from in-situ measurements of ground temperature and related to local measurements of air temperature, snow depth, and surface soil moisture. Active layer thaw patterns differed among landforms, with palsas and tundra heath having the least and greatest amount of thaw, respectively. Tundra heath thaw patterns were influenced by the presence of gravel and sandy soils, which had higher thermal conductivity than the mineral and organic soils of fens and palsas. Vegetation also influenced thaw patterns; the lichen cover of palsas better protected the landform from incoming solar radiation than the moss, lichen, and low-lying shrub cover of upland tundra heath, thus allowing for cooler ground temperatures. Air temperature was the most significant predictor of active layer thermal regime. Surface soil moisture varied among landforms and greater surface soil moisture reduced the amount of active layer thaw. These findings improved understanding of how landform and climate can interact to affect the active layer. Author Keywords: Active layer thermal regime, Active layer thickness, Climate change, Peatland, Permafrost, Subarctic
Machine Learning for Aviation Data
This thesis is part of an industry project which collaborates with an aviation technology company on pilot performance assessment. In this project, we propose utilizing the pilots' training data to develop a model that can recognize the pilots' activity patterns for evaluation. The data will present as a time series, representing a pilot's actions during maneuvers. In this thesis, the main contribution is focusing on a multivariate time series dataset, including preprocessing and transformation. The main difficulties in time series classification is the data sequence of the time dimension. In this thesis, I developed an algorithm which formats time series data into equal length data. Three classification and two transformation methods were used. In total, there are six models for comparison. The initial accuracy was 40%. By optimization through resampling, we increased the accuracy to 60%. Author Keywords: Data Mining, K-NN, Machine Learning, Multivariate Time Series Classification, Time Series Forest
Linking large scale monitoring and spatially explicit capture–recapture models to identify factors shaping large carnivore densities
Understanding the spatial ecology of large carnivores in increasingly complex, multi-use landscapes is critical for effective conservation and management. Complementary to this need are robust monitoring and statistical techniques to understand the effect of bottom-up and top-down processes on wildlife population densities. However, for wide-ranging species, such knowledge is often hindered by difficulties in conducting studies over large spatial extents to fully capture the range of processes influencing populations. This thesis addresses research gaps in the above themes in the context of the American black bear (Ursus americanus) in the multi-use landscape of Ontario, Canada. First, I assess the performance of a widely adopted statistical modelling technique – spatially explicit capture-recapture (SECR) – for estimating densities of large carnivores (Chapter 2). Using simulations, I demonstrate that while SECR models are generally robust to unmodeled spatial and sex-based variation in populations, ignoring high levels of this variation can lead to bias with consequences for management and conservation. In Chapter 3, I investigate fine-scale drivers of black bear population density within study areas and forest regions by applying SECR models to a large-scale, multi-year black bear spatial capture-recapture dataset. To identify more generalizable patterns, in Chapter 4 I then assess patterns of black bear density across the province and within forest regions as a function of coarse landscape-level factors using the same datasets and assess the trade-offs between three different modeling techniques. Environmental variables were important drivers of black bear density across the province, while anthropogenic variables were more important in structuring finer-scale space use within study areas. Within forest regions these variables acted as both bottom-up and top-down processes that were consistent with ecological influences on black bear foods and intensity of human influences on the species’ avoidance of developed habitats. Collectively, this thesis highlights the opportunities and challenges of working across multiple scales and over expansive landscapes within a SECR framework. Specifically, the multi-scale approach of this thesis allows for robust inference of the mechanisms structuring fine and broad scale patterns in black bear densities and offers insight to the relative influence of top-down and bottom-up forces in driving these patterns. Taken together, this thesis provides an approach for monitoring large carnivore population dynamics that can be leveraged for the species conservation and management in increasingly human-modified landscapes. Author Keywords: animal abundance, black bear, capture-recapture, density estimation, statistical ecology, wildlife management
Green Leadership in the Classroom
Concerns about climate change means that there is an urgent need to understand teachers’ role in educating students about environmental issues and sustainability. However, little is known about teachers’ environmental leadership and how that affects their competencies in the classroom, their general well-being and connections with nature, or what kinds of personality characteristics shape these teachers. A sample of current, future, and past Canadian teachers (N = 260) completed an online survey which included quantitative and qualitative questionnaires. Correlational and regression analyses determined teachers who possess environmental leadership qualities have a greater connection with nature, more positive well-being, and are more confident in their abilities to teach students outdoors. Furthermore, positive personality traits predict teachers’ environmental leadership. Qualitative data revealed both structural and psychological barriers reduced the likelihood of teachers taking students outdoors and that greater support, resources and training are needed to enable teachers to implement more nature-based learning. Author Keywords: competence, environmental leadership, nature relatedness, personality, teachers, well-being
Does boredom lead to ego-depletion? Examining the association between boredom and ego-depletion
Ego-depletion refers to the observation that using self-control at Time 1 (T1) in the sequential-task paradigm leads to worse self-control at Time 2 (T2; Baumeister et al., 1998). Self-control is often manipulated by varying the difficulty of the task used at T1. Recently, Wolff and colleagues (2020) suggested that failures to replicate the ego-depletion phenomenon may arise because simple tasks may be boring, therefore requiring self-control to maintain attention on the task. Three experiments (Experiment 1, N=60; Experiment 2, N=61; Experiment 3, N=59) are reported that examined whether boredom at T1 predicted self-control at T2. A simple Go/No-Go task was used at T1. The ratio of Go to No-Go trials was changed across experiments to explore how the properties of the boring task impacted the association between boredom and self-control. When responding was frequent, increased boredom at T1 was associated with fewer anagrams correctly solved (Experiment 1 and 3), and more self-reported fatigue at T2 (Experiment 1), consistent with boredom leading to ego-depletion. However, when responding was infrequent (Experiment 2), increased boredom at T1 was associated with more correctly solved anagrams at T2, suggesting that the properties of a boring task change the psychological outcome that task has on self-control. Author Keywords: attention, boredom, ego-depletion, executive function, self-control
Land Cover Effects on Hydrologic Regime within Mixed Land Use Watersheds of East-Central Ontario
Land cover change has the potential to alter the hydrologic regime from its natural state. Southern Ontario contains the largest and fastest growing urban population in Canada as well as the majority of prime (Class I) agricultural land. Expansions in urban cover at the expense of agricultural land and resultant ‘agricultural intensification’, including expansion of tile drainage, have unknown effects on watershed hydrology. To investigate this, several streams with a range of landcovers and physiographic characteristics were monitored for two years to compare differences of flashiness and variability of streamflow using several hydrologic metrics. Urban watersheds were usually the flashiest while agriculture had moderate flashiness and natural watersheds were the least flashy across all seasons, signifying that landcover effects were consistent across seasons. Tile drainage increased stream flashiness during wet periods, but minimized the stream response to an extreme rain event in the summer, perhaps due to increases in soil moisture storage. A sixty-year flow analysis showed that flashiness and streamflow increased (p < 0.05) above a development threshold of ~10% of watershed area. Flashiness was also greater in wetter years suggesting that climate shifts may enhance stream variability in developed watersheds. Author Keywords: Agriculture, Flashiness, Hydrologic Metrics, Hydrologic Regime, Landcover Change, Urban
What Happens in Childhood, Does Not Stay in Childhood
Researchers have found associations between attachment, childhood adversity, and posttraumatic stress symptoms; however, the underlying mechanisms between these variables remains unknown. The present study explored the moderating effects of childhood adversity on the relationship between adult attachment and posttraumatic stress symptoms in two samples. In total, 533 undergraduate students and 357 individuals recruited from online communities completed measures of childhood adversity, adult attachment, and posttraumatic stress symptoms. Hierarchical regression analyses were used to test the moderating effect on childhood adversity. One-way ANOVA post hoc analyses were run to assess mean differences of attachment and posttraumatic stress across five childhood adversity groups. The results suggested that attachment and childhood adversity do predict posttraumatic stress symptoms; however, there was no significant moderating effect of adversity found. The post hoc analyses revealed significant mean differences for secure attachment, avoidant attachment, and posttraumatic stress symptoms. The findings suggest that attachment and childhood adversity are significantly associated with posttraumatic stress symptoms. Author Keywords: adult attachment, childhood adversity, posttraumatic stress symptoms, trauma

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Format: 2023/02/09