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    Assessment of ERA5-Land Lake Ice Related Variables from Satellite Observations
    (University of Waterloo, 2025-12-19) Mansingh, Ariana
    Lake ice is an important climatic indicator because it responds to and alters surface energy fluxes, which in turn influence weather and climate (e.g., precipitation, air temperature). Therefore, accurately representing lake-atmosphere interactions within climate and weather models has been shown to reduce forecast errors. Despite the recognized importance of lake ice processes within models, few studies have evaluated the quality of the lake ice-related variables available from ERA5-Land, a widely used reanalysis product. To address this gap, this thesis evaluates ERA5-Land’s lake ice estimates against satellite-derived observations from NOAA, CIS, IMS and MODIS. It assesses biases in lake ice fraction, timing and surface temperature across seven Canadian lakes over 20 years (2004-2023). The study lakes are grouped into northern lakes (Great Bear, Great Slave, Athabasca and Winnipeg) and the Laurentian Great Lakes (Superior, Huron and Erie). The biases were quantified using mean bias error (MBE) and mean absolute error (MAE), with ERA5-Land treated as “predicted” values and satellite-derived products as “observed” values. This thesis provides one of the first spatial and temporally extensive evaluations of ERA5-Land’s lake ice estimates. The overall findings show that ERA5-Land consistently overestimated lake ice fraction during freeze-up and break-up. Across all lakes, ERA5-Land generally produced earlier freeze-up timing, earlier break-up start, and later break-up end than observations. While timing bias followed similar patterns across lakes, distinct patterns emerged between the northern lakes and the Laurentian Great Lakes. These patterns indicate broader weaknesses of ERA5-Land, which uses the Freshwater Lake model (FLake) as its lake parameterization scheme, notably the omission of snow cover over lake ice and the tendency of the product to form a full ice cover on the Laurentian Great Lakes, which typically experience 40-80% ice fraction at winter maximum. As a result, high MAE was observed during both freeze-up (max=47%) and break-up (max=62%). Consequently, this overestimation of ice cover in ERA5-Land typically led to a daytime cold bias in surface temperatures during the ice-covered period. Additionally, it contributed to ice timing biases, notably the freeze-up end (~22 days earlier on average) and the break-up start (~25-28 days later on average). The lack of consideration of snow cover on ice in FLake/ERA5-Land prevents accounting for its effects on ice growth, heat absorption, and surface temperature. It is well known that snow slows ice growth by reducing downward heat transfer. Thus, ERA5-Land overestimates lake ice thickness across all lakes, which in turn contributes to the delay in break-up start. The early break-up end timing is likely linked to ERA5-Land neglecting the cooling effect of snow’s high albedo, which would otherwise slow melt by reflecting solar radiation. Additionally, during months of high snowfall, ERA5-Land produced a larger warm surface temperature bias, most notable among the northern lakes. Overall, this thesis quantified the biases arising from two notable weaknesses in ERA5-Land’s parameterization: the omission of snow cover on ice and the inability to account for partial ice coverage in the large lakes examined in this research. The quantification of biases provides insight into how these weaknesses skew ERA5-Land estimates. This thesis provides new insights into the limitations of ERA5-Land regarding lake ice, which should be considered leading to for future product releases.
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    Love, Resilience, and the Past: The Role of Positive Emotion Regulation in Overcoming Childhood Maltreatment and Building Strong Romantic Relationships
    (University of Waterloo, 2025-12-19) McNeil, Julia
    Experiences of childhood maltreatment (CM) are associated with relationship and sexual difficulties in adulthood (Vaillancourt-Morel, et al., 2024). Research has shown that these issues are partially explained by difficulties regulating negative emotions (DiLillo et al., 2009). However, the effect CM has on the regulation of positive emotions has received considerably less attention. In this thesis I examined how CM is related to fear of positive and negative emotional states (Studies 1-3), using online-self report questionnaires, I tested if this anxiety mediates the association between CM and difficulties in relationships (Studies 2 & 3), and finally, I examined how CM is related to an individuals’ ability to regulate their positive and negative emotions in response to images that evoke positive and negative emotions. My results consistently showed that CM is related to fear of positive and negative emotional states (Studies 1-3). Consistently I found an association between the intensity of CM experienced and decreased satisfaction with communication in adult long-term relationships (Studies 2 & 3). This association was mediated by fear of emotions (Study 2), with Study 3 showing unique effects for both fear of positive and negative emotions. Finally, my results showed that CM was associated with difficulty enhancing positive emotions and improved performance when asked to decrease positive emotions (Study 3). These results provide evidence that CM affects individuals’ ability to tolerate and regulate their positive emotions. Furthermore, my results suggest that difficulties with positive emotions play a role in long-term relationship difficulties reported by survivors of CM. The present research suggests that clinicians should focus on improving tolerance for positive emotions and teaching tools for capitalizing on positive experiences when working with survivors of CM.
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    Revivifying, Repurposing, Reimagining: From Commodification to Kinship in 21st-Century De-Extinction and Xenotransplantation Narratives
    (University of Waterloo, 2025-12-19) Sanderson, Jerika
    De-extinction and xenotransplantation represent two key 21st-century biotechnological developments, both of which aim to use genetic engineering to address ecological and medical crises. This dissertation investigates the representation of de-extinction and xenotransplantation by scientific corporations, in the media, and in fiction. In particular, I draw on critical posthumanist theory to investigate how techno-optimistic and transhumanist rhetoric has influenced de-extinction and xenotransplantation narratives; how narratives respond to key issues in bioethics and environmental ethics; the implications that these narratives suggest for how biotechnology is shaping human and nonhuman identity; and the way that they explore possibilities for multispecies care, kinship, and entanglement. My analysis in Part I shows that de-extinction is frequently framed in terms of the biomedical and human health benefits that it can offer. While this biomedical framing is reflected in the Jurassic World films (2015, 2018, 2022) and the novels Ghost Species (2020) and The Neanderthal’s Aunt (2014), these narratives focus on the risks arising from the exploitation and commodification of genetic material. In my analysis of xenotransplantation narratives in Part II, I observed that pigs are frequently framed as an abundant supply of organs that can solve the organ shortage crisis. In contrast, the novel Pig-Heart Boy (1997) and the film We Ate the Children Last (2011) focus on the bioethical risks faced by the first patients to undergo xenotransplantation, such as their vulnerability and the risk of discrimination, while the novels Oryx and Crake (2003) and Chromosome 6 (1998) counter the frame of abundance by depicting the potential for detrimental environmental, political, and economic impacts. Lastly, my analysis in Part III of the short story “The Birdsong Fossil” (2021) and the novel Pighearted (2021) reveals that these narratives prioritize care, kinship, and entanglement, providing possibilities for reimagining the animals created by biotechnology beyond the hype of charismatic megafauna and the spare parts metaphor in de-extinction and xenotransplantation discourse. By drawing on multispecies environmental ethics and posthumanist bioethics, I conclude that these narratives can allow us to envision more ethical applications of biotechnology, which can thereby shape the future of de-extinction and xenotransplantation.
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    Challenges and Opportunities for Sustainable Nitrogen Management in Dairy Systems
    (University of Waterloo, 2025-12-19) Lakhanpal, Garima
    Nitrogen (N) is central to agricultural productivity, yet its mismanagement drives water and air pollution across the world. Ireland’s grass-based dairy systems are among the most N-intensive in the European Union (EU), with high inorganic and organic fertilizer sustaining productivity but creating persistent surpluses that threaten groundwater and surface water quality. Despite major policy efforts, Ireland continues to struggle to meet EU Water Framework Directive (WFD) chemical targets for good water status. However, Ireland is still seeking the renewal of its Nitrates Derogation, which allows exceptionally high stocking rates up to 220 kg N ha⁻¹ yr⁻¹. This tension between economic needs and environmental compliance defines one of the country’s greatest agri-environmental challenges. The EU is moving toward tighter nutrient limits and nature restoration objectives, making it essential to understand whether sustainable dairy production can coexist with future regulatory expectations. One of the main obstacles to achieving water-quality goals is the temporal disconnect between management interventions and measurable improvements, which can erode stakeholder confidence and obscure the true impact of mitigation policies. In Ireland, the EU WFD program of measures (PoMs) is carried out under the Nitrates Directive, which include nutrient management, land management and farmyard management strategies to protect water quality. These lags are increasingly attributed to legacy N i.e., reactive N accumulated in soils and subsoils from past surpluses that continue to leach long after inputs decline. While groundwater legacy effects are recognized (i.e., the time it takes water to travel through the soil termed hydrologic time lag), few studies worldwide have directly quantified soil legacy N (i.e., biogeochemical time lags), and none had done so in Ireland prior to this research. Understanding the scale, distribution, and persistence of these soil pools is critical for designing realistic mitigation timelines and adaptive policies. The overarching aim of my research was therefore to assess N dynamics and environmental outcomes in Irish dairy systems by evaluating mitigation scenarios and quantifying legacy soil N accumulation to understand how current and historical management, drainage class, and hydrogeological setting influence both near-term losses and the pace of environmental recovery. I combined process-based modelling, multi-decadal farm data, deep soil coring, and groundwater monitoring to connect farm management decisions with both short- and long-term system responses. Together, these studies form the first integrated assessment of soil N legacies in Irish dairy systems. In Chapter 2, I used the €riN-MDSM model to simulate N flows, surpluses, and losses in a well-drained dairy farm operating under derogation conditions. This model, developed to represent N cycling in Irish grass-based systems, quantifies losses of nitrate (NO₃⁻), ammonia (NH₃), nitrous oxide (N₂O), and dinitrogen (N₂) from urine, dung, slurry, dairy soiled water, and fertilizer. I simulated a range of management scenarios, including reduced inorganic N rates (200–225 kg N ha⁻¹) and organic rates (170–430 kg N ha⁻¹), substitution of calcium ammonium nitrate (CAN) with protected urea, and restrictive grazing during vulnerable winter–spring months. Results showed that integrated approaches combining restrictive grazing, protected urea, and reduced fertilizer inputs lowered NO₃⁻ leaching by up to 44 % and NH₃ volatilization by 31 %, bringing water losses close to the 30 kg N ha⁻¹ threshold for good groundwater quality. These findings demonstrated that substantial environmental gains are possible through system-level optimization, but that even under improved management, N surpluses remain high, implying persistent risks to water and air quality. This modelling work provided a critical benchmark for assessing what levels of mitigation might be achievable within the derogation framework and highlighted the need to understand how historical surpluses continue to affect recovery, setting the stage for the legacy N analyses that followed in the next phase of this research study. In Chapter 3, I conducted a 24-year investigation (2001–2024) at Moorepark Teagasc Research Farm (known as Curtins Research Farm locally) in southern Ireland, a well-drained, karstic site with low denitrification potential. I reconstructed multi-decadal N budgets from detailed farm records and collected 75 soil cores across 15 paddocks, 1m deep profiles representing a gradient of historical management intensity. Annual N surpluses frequently exceeded 200 kg N ha⁻¹ yr⁻¹, leading to cumulative soil N accumulation of 4,000–5,500 kg N ha⁻¹ in the top 50 cm. Groundwater NO₃⁻ loads declined from over 70 kg N ha⁻¹ in the early 2000s to under 30 kg N ha⁻¹ by 2024, yet concentrations have plateaued rather than continuing to fall. This persistent signal alludes that subsoil N stored from past decades continues to mineralize and leach, sustaining groundwater nitrate levels despite reduced inputs. These findings provide the first direct quantification of legacy soil N in Irish dairy systems, showing that deep soil stores act as long-term sources of reactive N, constraining the pace of water quality recovery even when surface management improves. In Chapter 4, I expanded the investigation to include the Johnstown Castle Teagasc Dairy Research Farm, a variably drained site in the southeast with finer-textured soils and higher denitrification potential. I analyzed 45 soil cores from 9 paddocks, 1 m deep profiles covering an 18-year management period and compared results to those from Curtins. Despite lower annual surpluses (~100–150 kg N ha⁻¹ yr⁻¹), Johnstown Castle soils contained 4,000–11,000 kg N ha⁻¹ in the upper 50 cm, substantially higher than the well-drained Curtins profiles. The difference reflected higher clay and silt content, which enhanced N retention through adsorption and organic-mineral associations, as well as shallower water tables and moderate denitrification that reduced nitrate transport to groundwater but trapped nitrogen in the soil profile. These results revealed a clear trade-off: well-drained systems potentially act as “fast transmitters,” showing rapid leaching but quicker recovery when management improves, whereas variably drained systems are possibly “slow retainers,” buffering groundwater in the short term but accumulating persistent legacy N stores that prolong recovery. By linking long-term management records, soil data, and investigating groundwater trends across these contrasting systems, I demonstrated that N accumulation is governed by the interaction of soil texture, soil drainage class, hydrology, denitrification potential, and historical management intensity. Across both sites, total soil N accumulation exceeded 3,000–11,000 kg N ha⁻¹, far higher than values reported for most temperate cropland systems, confirming the exceptional capacity of Irish grassland soils to store reactive N from decades of intensive management. This thesis makes several novel contributions. It provides the first empirical evidence of soil legacy N magnitudes in temperate dairy grasslands, quantifies their long-term influence on water quality and nitrate dynamics, and develops a conceptual framework concerning drainage, soil texture, and hydrology to N retention and release. It also demonstrates how soil legacy N can be reframed as both a risk and a resource—a potential nutrient reservoir that, if managed strategically, could offset fertilizer needs during the transition to lower-input systems. These findings have direct implications for Ireland’s compliance with the EU Nitrates and WFD. Current six-year reporting cycles are too short to capture recovery in legacy-affected catchments, creating the perception of policy failure. Integrating soil monitoring to 1 m depth alongside existing high-resolution catchment and groundwater networks would enable more accurate assessment of progress and support realistic, site-specific mitigation timelines. Legacy N must be explicitly incorporated into nutrient models, regulatory assessments, and PoMs to ensure that both soil and water systems are managed as coupled components of the nitrogen cycle. Ultimately, this research underscores that Ireland’s path to sustainable dairy production requires addressing both current N surpluses and historical legacies. The methods and evidence developed here — combining modelling, deep soil sampling, and long-term monitoring offer a blueprint for future national assessments and international comparisons. As EU policy evolves toward stricter nutrient limits and nature restoration goals, understanding and managing legacy N will be fundamental to aligning agricultural productivity with environmental resilience.
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    Exploring intersectoral collaboration in a community-based climate adaptation initiative: A qualitative case study of the Waterloo Region Heat, Cold and Air Quality Network (WRHCAN)
    (University of Waterloo, 2025-12-19) Abbas, Sabeen
    Background: An increase in the frequency and severity of extreme weather and poor air quality events due to anthropogenic climate change has resulted in negative implications for human and planetary health. Understanding the role of local public health units in the development and implementation of community-based climate change adaptation initiatives can minimize the health impacts of climate change and enhance community resilience. This study aimed to explore the facilitators and barriers to intersectoral collaboration for Network partners of the Waterloo Region Heat, Cold and Air Quality Network (WRHCAN), a public health led climate adaptation initiative. Methods: A community engaged research approach informed the study design and community-academic partnership between the University of Waterloo and Region of Waterloo Public Health (ROWPH). A case study methodology was applied to explore the processes of intersectoral collaboration in the context of the WRHCAN. Data sources included a focus group with ROWPH, 13 semi-structured interviews with Network partners, participant observation of two Network meetings, and a document review of selected WRHCAN internal documents. Recruitment was facilitated by ROWPH, and data collection and analysis were guided by the Bergen Model of Collaborative Functioning, a theoretical framework for intersectoral collaboration. All interviews were audio-recorded using Teams and transcribed verbatim. Interview data were thematically analyzed using a hybrid inductive-deductive approach. Results: Network partners identified several facilitators and barriers, as well as contextual factors influencing intersectoral collaboration in the WRHCAN. For Network partners, facilitators included alignment with WRHCAN objectives, coordination by ROWPH, usefulness of communication products, and information and resource sharing with other Network partners. Barriers included accessibility of information and resources for vulnerable populations, and the need for more tailored training and response by frontline staff. Contextual factors included the housing and affordability crisis impacting Waterloo Region and the need to address the specific challenges of those experiencing substance use challenges, mental health concerns, and/or homelessness. Conclusion: This study highlighted intersectoral collaboration as an approach that can be leveraged by local public health units in the design and implementation of community-based climate change adaptation initiatives. This study provides insights into the facilitators and barriers experienced by WRHCAN Network partners. The findings from this study can inform future climate change adaptation efforts that utilize intersectoral collaboration.