Climate change

The widespread adoption of electric vehicles (EVs) is crucial for reducing transportation-related emissions and achieving sustainability goals. However, a significant research gap exists regarding specific consumer groups, such as university students, and their attitudes toward EV adoption, as they represent a demographic influential in shaping future adoption patterns. This research uses a quantitative approach to explore Trent University students' attitudes and perceptions toward EV adoption.A survey of 154 students examined the factors influencing their willingness to adopt EVs. Various quantitative data analyses, including cross-tabulation tables and chi-square tests, were employed to investigate the relationships between socio-demographic, social, environmental, and economic factors and students' willingness to adopt EVs. The findings indicate that while socio-demographic factors do not significantly influence willingness to adopt EVs, factors such as first-hand experience, knowledge about EVs, social influence, upfront costs, charging infrastructure, and government incentives significantly impact students' willingness to adopt EVs. The study revealed that although students recognize the benefits of electric vehicles (EVs), such as reduced emissions, lower operating costs, enhanced energy efficiency and health advantages, key barriers to student EV adoption include high upfront costs, limited charging infrastructure, concerns about driving range and charging time, and a need for more knowledge and awareness. The findings of this study fill a significant research gap and add to the existing literature on EV adoption. The insights generated can inform targeted strategies by policymakers, educational institutions, and EV manufacturers to promote widespread EV adoption among students. Keywords: Electric Vehicles, Internal Combustion Engine Vehicles, Zero-emission vehicles, sustainable transportation, attitudes, perceptions, University students, consumer behaviour.

Author Keywords: Consumer behaviour, Electric Vehicles, Internal Combustion Engine Vehicles, sustainable transportation, University students, Zero-emission vehicles

Long-term avian population declines, particularly for the avian insectivore guild, are a conservation concern. With widespread and continuing population trends, climate change and its negative effects on avian food resources is a plausible cross-species driver. My goal was to evaluate whether bottom-up trophic effects of climate change could be influencing avian populations. I used a space-for-time approach to assess the influence of snowpack and soil moisture variability on arthropods and subsequent effects on nest survival. In the 2010 and 2011 growing seasons, I sampled arthropods, soil moisture (soil volumetric water content; VWC), snowpack (snow water equivalent; SWE), forest floor depth (L, F, H layers) and soil texture in conifer plantations and mixed deciduous forest in Southern Ontario's Ganaraska Forest (~4, 400 ha). I used additive linear mixed effects models to assess the responses of arthropod groups' (e.g., order or class) relative biomass (g/day) and abundance (count/day) to those variables. Influences for each arthropod group's biomass and abundance were typically in the same direction. Maximum annual SWE significantly positively influenced most arthropod groups and annual relative difference in VWC positively influenced one quarter. In mixed directions, forest type influenced half of the groups and soil texture and forest floor depth each affected less than one quarter. I then used structural equation models to evaluate relationships between SWE, VWC, the biomass of three arthropod functional guilds, and logistic-exposure model calculated daily nest survival rates for American Robin (Turdus migratorius), Eastern Wood-Pewee (Contopus virens), Least Flycatcher (Empidonax minimus), Ovenbird (Seiurus aurocapilla), and Red-eyed Vireo (Vireo olivaceus). Arthropod guilds included diet-based food, predaceous arthropods and soil-dwelling bioindicators. SWE significantly positively influenced food biomass in all five models and negatively influenced predaceous arthropods in three models. Soil moisture had a mix of positive, negative, and null effects. Eastern Wood-Pewee and Red-eyed Vireo nest survival positively related to food and negatively related to predaceous arthropod biomass. American Robin, Least Flycatcher and Ovenbird nest survival did not appear to be related to arthropod biomasses. Through bottom-up relationships, predicted climate change-induced reductions in snowpack may cause food resource declines and negatively affect some forest breeding bird populations.

Author Keywords: Arthropod biomass, Bottom-up, Forest birds, Nest survival, Path analysis, Precipitation

Dissolved inorganic carbon in drainage waters is a direct measurement of carbon dioxide (CO2) removal from enhanced rock weathering (ERW) in soils. In this study, square metre scale field experiments (2021–2023) were conducted in Peterborough Ontario, Canada, each amended with kimberlite residues from Gahcho Kué Diamond Mine (Northwest Territories, Canada) or olivine powder at high application rates (100–400 t/ha). Porewater chemistry data, coupled with a water budget analysis derived from precipitation and soil moisture data, were used to quantify solubility trapping by amendment weathering revealing maximum rates of 0.04 t CO2/ha over 2 yr for olivine and 0.9 t CO2/ha over 3 yr for kimberlite. This research presents kimberlite mine wastes as an ERW feedstock alternative to basalt as projects scale-up and require more rock. Additionally, high dosage monitoring plots ensure detection of a CO2 removal signal in open systems and should be considered for large scale projects.

Author Keywords: CO2 removal, Enhanced rock weathering, Field experiment, Kimberlite, Mine wastes, Olivine

Increasing wildfire frequency, driven by climate change, can change the concentration andcomposition of dissolved organic matter (DOM) exported from land into receiving waters by removing terrestrial vegetation, changing soil hydrology, and interrupting microbial degradation. In this thesis, I tested how wildfire impacts the molecular composition and reactivity of DOM. I compared DOM from boreal headwater streams in northwestern Ontario, Canada between 10 catchments recently affected and 10 comparable catchments that were undisturbed for at least 20 years. Using optical spectroscopy, ultra-high-resolution mass spectrometry, and incubation experiments, I found that burned streams had 29% higher average DOM concentrations and contained less bioavailable DOM, which resulted in microbes respiring more CO2 in burned streams rather than using carbon to build biomass. These results indicate that the impacts of wildfire on carbon sequestration have been underestimated and highlight the need to consider wildfire in forest carbon budgets.

Author Keywords: boreal forest, carbon flux, dissolved organic matter, Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), headwater streams, Wildfire

ABSTRACT

Development of Forest Degradation Indicators from Long-term Trajectories of Multispectral Satellite Images, and their Projections into the Future under Climate Change, in Ontario, Canada

Md. Mozammel Hoque

Ontario forests are affected by natural and anthropogenic disturbances leading to forest degradation, which significantly impact local ecosystems, health, safety, and economy. This thesis develops a methodology for the continuous assessment, mapping, and monitoring of present and historic (1972–2020) forest disturbances, and future forest degradation trends and projections, using remote sensing data, ground measurements, and predictive models in an Ontario forested area. After testing four supervised classification algorithms, support vector machine was found to be the most robust, consistent, and effective for land cover classification. Seven vegetation indices derived from Landsat and MODIS platforms were used to derive forest degradation indicators (FDIs), which were combined into one composite forest degradation indicator (CFDI) for each year, using the principal component analysis image fusion approach. The CFDI was the most informative indicator. The computed FDIs from available large multispectral image stacks were statistically related to historical climate variables. These relationships were used to project future FDIs related to climate variables derived from General Circulation Models through multiple linear regression models. Spatially-explicit maps of relevant climatic variables and of long-term historical forest degradation were developed from the LandTrendr trajectory analysis. Climate variables P, MA1, MA2, and CFDI were strongly correlated, allowing for the development of a model with a high coefficient of determination, R2 (0.93), and low RMSE (0.28) to predict future values. Forest disturbances (as CFDI) were also monitored from 1972–2020. Overall, these relationships allowed for to the creation of spatially-explicit, long-term historical forest degradation maps derived from the Landtrendr trajectory analysis. Historical and future forest degradation maps identified the areas with projected high vulnerability to climate change, as well as the actual and potential changes in forest cover under climate change. The results indicated 2050 will experience an average temperature increase of 3.0°C, projected yearly decrease in precipitation of 109.5 mm, evapotranspiration increase of 73.0 mm, and moisture deficits of 28.47 mm (MA1) and 37.60 mm (MA2), leading to increased forest degradation.

Author Keywords: Climate change impacts, Forest degradation indicators, Forest disturbance and degradation, Land cover classification, Projections of 2050 forest degradation under climate change, Remote sensing technology

Crutzen and Stoermer's (2000) announcement of the Anthropocene draws attention to the agentic nature of the nonhuman world as it appears to be striking back against human intervention through an environmental crisis that is threatening humans and nonhumans alike. Their narrative reveals complex relationalities where humans are now revealed to beinseparable from the nonhuman world and both the material and discursive nature of their practices (historical, social, economic, and political) prove to be central to (re)shaping the earth, causing climate change, species extinctions as well as racism, sexism, and slavery. Rising sea levels is an important aspect of climate change that threatens major coastal places with disappearance. My dissertation offers a new approach that uses Karen Barad's (2003; 2007; 2017) agential realism and diffractive methodology to study a place called Lyme Regis – a town in west Dorset, England, threatened with disappearance as a result of rising sea levels caused by climate change – as an agential phenomenon shaped by complex multilayered material-discursive practices (political, economic, scientific, and social). Whereas current research on Barad's philosophy mainly focuses on discussions about the theory: explaining, critiquing, or defending (Gandorfer 2021; Lettow 2017; Graham 2016; Segal 2014; Geerts 2013; 2016; 2021; van der Tuin 2011; Alaimo and Hekman 2008; Rouse 2004 and more ), my project is the first ethico-political study of a place, Lyme, that applies Barad's agential realist perspective by engaging the activism of Barad's concept of "re-membering." The processual nature of the concept is particularly relevant today since its nonlinear understanding of time allows me to see how past violent material and discursive practices (racism, sexism, and slavery) at Lyme unfolds in the present troubled time of the Anthropocene. This process of re-membering that I undertake in this study involves concurrently examining the overlapping historical, economic, scientific, literary, and geological intra-acting practices through a method that Barad describes as diffractive reading. I rethink these practices in their relation to material practices and illuminate multiple layers of meaning and relationalities that constitute Lyme as an agential phenomenon, unsettling boundaries between humans and nonhumans, epistemology and ontology, material and discursive practices as well as boundaries between scientific, historical, cultural, and literary aspects of life. Therefore, within the context of the Anthropocene, chapter one rethinks how the scientific discourse (re)shapes nature and demonstrates how prioritizing the needs of human over nonhuman inhabitants in the name of saving Lyme could entail the destruction of both. Chapter two rethinks the dehumanizing and marginalizing effect of the scientific discourse by illuminating the agentic role of Mary Anning and Saartjie Baartman in the apparatus of scientific knowledge production that earned Lyme its heritage status. Finally, chapter three rethinks the entangled nature of scientific and literary practices, arguing for an agential realist account of the sublime that celebrates Lyme as a place of transformative human-nonhuman kinship based on Austen's elaborate depiction in Persuasion (1817). This reading shows science and literature as material-discursive practices operating along the unsettled boundaries between the novel and everyday life, allowing us to rethink Austen's writing as a process in constant flux.

Author Keywords: Agential Realism, Anthropocene, Diffractive Methodology, Lyme Regis, Persuasion, Posthumanist Sublime

The widespread adoption of electric vehicles (EVs) is crucial for reducing transportation-related emissions and achieving sustainability goals. However, a significant research gap exists regarding specific consumer groups, such as university students, and their attitudes toward EV adoption, as they represent a demographic influential in shaping future adoption patterns. This research uses a quantitative approach to explore Trent University students' attitudes and perceptions toward EV adoption.A survey of 154 students examined the factors influencing their willingness to adopt EVs. Various quantitative data analyses, including cross-tabulation tables and chi-square tests, were employed to investigate the relationships between socio-demographic, social, environmental, and economic factors and students' willingness to adopt EVs. The findings indicate that while socio-demographic factors do not significantly influence willingness to adopt EVs, factors such as first-hand experience, knowledge about EVs, social influence, upfront costs, charging infrastructure, and government incentives significantly impact students' willingness to adopt EVs. The study revealed that although students recognize the benefits of electric vehicles (EVs), such as reduced emissions, lower operating costs, enhanced energy efficiency and health advantages, key barriers to student EV adoption include high upfront costs, limited charging infrastructure, concerns about driving range and charging time, and a need for more knowledge and awareness. The findings of this study fill a significant research gap and add to the existing literature on EV adoption. The insights generated can inform targeted strategies by policymakers, educational institutions, and EV manufacturers to promote widespread EV adoption among students. Keywords: Electric Vehicles, Internal Combustion Engine Vehicles, Zero-emission vehicles, sustainable transportation, attitudes, perceptions, University students, consumer behaviour.

Author Keywords: Consumer behaviour, Electric Vehicles, Internal Combustion Engine Vehicles, sustainable transportation, University students, Zero-emission vehicles

Long-term avian population declines, particularly for the avian insectivore guild, are a conservation concern. With widespread and continuing population trends, climate change and its negative effects on avian food resources is a plausible cross-species driver. My goal was to evaluate whether bottom-up trophic effects of climate change could be influencing avian populations. I used a space-for-time approach to assess the influence of snowpack and soil moisture variability on arthropods and subsequent effects on nest survival. In the 2010 and 2011 growing seasons, I sampled arthropods, soil moisture (soil volumetric water content; VWC), snowpack (snow water equivalent; SWE), forest floor depth (L, F, H layers) and soil texture in conifer plantations and mixed deciduous forest in Southern Ontario's Ganaraska Forest (~4, 400 ha). I used additive linear mixed effects models to assess the responses of arthropod groups' (e.g., order or class) relative biomass (g/day) and abundance (count/day) to those variables. Influences for each arthropod group's biomass and abundance were typically in the same direction. Maximum annual SWE significantly positively influenced most arthropod groups and annual relative difference in VWC positively influenced one quarter. In mixed directions, forest type influenced half of the groups and soil texture and forest floor depth each affected less than one quarter. I then used structural equation models to evaluate relationships between SWE, VWC, the biomass of three arthropod functional guilds, and logistic-exposure model calculated daily nest survival rates for American Robin (Turdus migratorius), Eastern Wood-Pewee (Contopus virens), Least Flycatcher (Empidonax minimus), Ovenbird (Seiurus aurocapilla), and Red-eyed Vireo (Vireo olivaceus). Arthropod guilds included diet-based food, predaceous arthropods and soil-dwelling bioindicators. SWE significantly positively influenced food biomass in all five models and negatively influenced predaceous arthropods in three models. Soil moisture had a mix of positive, negative, and null effects. Eastern Wood-Pewee and Red-eyed Vireo nest survival positively related to food and negatively related to predaceous arthropod biomass. American Robin, Least Flycatcher and Ovenbird nest survival did not appear to be related to arthropod biomasses. Through bottom-up relationships, predicted climate change-induced reductions in snowpack may cause food resource declines and negatively affect some forest breeding bird populations.

Author Keywords: Arthropod biomass, Bottom-up, Forest birds, Nest survival, Path analysis, Precipitation

ABSTRACT

Development of Forest Degradation Indicators from Long-term Trajectories of Multispectral Satellite Images, and their Projections into the Future under Climate Change, in Ontario, Canada

Md. Mozammel Hoque

Ontario forests are affected by natural and anthropogenic disturbances leading to forest degradation, which significantly impact local ecosystems, health, safety, and economy. This thesis develops a methodology for the continuous assessment, mapping, and monitoring of present and historic (1972–2020) forest disturbances, and future forest degradation trends and projections, using remote sensing data, ground measurements, and predictive models in an Ontario forested area. After testing four supervised classification algorithms, support vector machine was found to be the most robust, consistent, and effective for land cover classification. Seven vegetation indices derived from Landsat and MODIS platforms were used to derive forest degradation indicators (FDIs), which were combined into one composite forest degradation indicator (CFDI) for each year, using the principal component analysis image fusion approach. The CFDI was the most informative indicator. The computed FDIs from available large multispectral image stacks were statistically related to historical climate variables. These relationships were used to project future FDIs related to climate variables derived from General Circulation Models through multiple linear regression models. Spatially-explicit maps of relevant climatic variables and of long-term historical forest degradation were developed from the LandTrendr trajectory analysis. Climate variables P, MA1, MA2, and CFDI were strongly correlated, allowing for the development of a model with a high coefficient of determination, R2 (0.93), and low RMSE (0.28) to predict future values. Forest disturbances (as CFDI) were also monitored from 1972–2020. Overall, these relationships allowed for to the creation of spatially-explicit, long-term historical forest degradation maps derived from the Landtrendr trajectory analysis. Historical and future forest degradation maps identified the areas with projected high vulnerability to climate change, as well as the actual and potential changes in forest cover under climate change. The results indicated 2050 will experience an average temperature increase of 3.0°C, projected yearly decrease in precipitation of 109.5 mm, evapotranspiration increase of 73.0 mm, and moisture deficits of 28.47 mm (MA1) and 37.60 mm (MA2), leading to increased forest degradation.

Author Keywords: Climate change impacts, Forest degradation indicators, Forest disturbance and degradation, Land cover classification, Projections of 2050 forest degradation under climate change, Remote sensing technology