Face à l’augmentation observée des accidents de régénération en forêt boréale et leur impact sur la productivité et la résilience des peuplements denses d’épinette noire, une meilleure compréhension des mécanismes de résilience et une surveillance des risques d’accident de régénération sont nécessaires. L’objectif principal de cette étude visait donc le développement de modèles prédictifs et spatialement explicites de la régénération de l’épinette noire. Plus particulièrement, deux modèles ont été développés soit (1) un modèle théorique, développé à l’aide de données in situ et de données spatiales et (2) un modèle cartographique, utilisant uniquement des données spatiales accessibles telles que les inventaires forestiers provinciaux et l’indice spectral de sévérité des feux « differenced Normalized Burn Ratio » (dNBR). Les résultats obtenus ont permis de constater que la succession rapprochée (< 55 ans) d’une coupe et d’un feu n’entraîne pas automatiquement une ouverture des peuplements d’épinette noire. Tout d’abord, les peuplements affectés par la coupe de récupération de brûlis (1963), immatures lors du feu de 2005, sont caractérisés par une faible régénération. En contrepartie, la régénération à la suite du feu de 2005, observé dans les peuplements coupés entre 1948 et 1967, est similaire à celle observée dans les peuplements non perturbés dans les 60 années précédant le feu. Le modèle théorique sélectionné à l’aide des critères d’information d’Akaike a, quant à lui, permis d'identifier trois variables déterminantes dans le succès ou l’échec de la régénération de l’épinette noire soit (1) la végétation potentielle, (2) le pourcentage de recouvrement du sol par les sphaignes et (3) la sévérité du feu évaluée à l’aide du dNBR. Des validations bootstrap et croisée ont permis de mettre en évidence qu’un modèle utilisant ces trois variables explique 59 % de la variabilité de la régénération observée dans le territoire d’étude., Quant à lui, le modèle cartographique qui utilise uniquement les variables végétation potentielle et dNBR explique 32 % de la variabilité. Finalement ce modèle a permis la création d’une carte de risque d’accident de régénération. Basée sur la précision du modèle, cette carte offre un potentiel intéressant afin de cibler les secteurs les plus à risque et ainsi appuyer les décisions relatives aux reboisements dans les zones incendiées.

This master’s thesis deals with boiling crisis and with departure from nucleate boiling ratio. This thesis explains terms like the boiling crisis in nuclear reactors and the thesis deals with individual parameters of the reactor core, which have an impact on departure from nucleate boiling ratio. After that, the thesis deals with subchannel analysis and describes basic mathematical and physical models of the chosen subchannel program. The thesis then processes, with the ALTHAMC12 subchannel program, the chosen parameters and their impact on departure from nucleate boiling ratio. The conclusion of the diploma thesis deals with the evaluation of the best and worst calculated combination.

The advent of industrial, fertilizer-intensive agriculture during the 20th century has promoted export of anthropogenic nutrients, spurring degradation of ecosystem biodiversity and water quality. Exported nitrogen and phosphorus are recognized drivers of this deterioration, and require management. In the mid-1990s, denitrifying bioreactors (DNBRs), a subsurface, edge-of-field best management practice (BMP) that intercepts and treats agricultural drainage by supporting nitrate-attenuating denitrification with a saturated, carbon-filled substrate, were developed. Since then, their utility has expanded, and recent studies have unearthed biochar's capability to stimulate simultaneous nitrate (NO3--N) and phosphate (PO43--P) removal in DNBRs. This study investigated biochar's potential as an amendment to the traditional woodchip media by conducting nine, five-day trials on twelve laboratory-scale, horizontal flow-through DNBR columns. Three media types were tested: woodchips (W), 90% woodchips and 10% biochar (B10), and 70% woodchips and 30% biochar (B30). Simulated agricultural drainage with four unique concentration combinations of 16.1 and 4.5 mg L-1 NO3--N and 1.9 and 0.6 mg L-1 PO43--P was delivered at hydraulic retention times (HRTs) of 3, 6, and 12 h. Mean NO3--N removal efficiencies ranged from 16.9%-93.7%, and media type was insignificant at low influent NO3--N concentrations, but B30 was the most effective at high influent NO3--N concentrations. Mean PO43--P removal efficiencies ranged from -122.0%-74.9%, with B10 and B30 significantly worse than W at removing PO43--P. These findings corroborate previous work indicating boosted NO3--N removal with biochar, but contradict studies upholding PO43--P-removing capabilities. / Master of Science

Nitrous oxide (N2O) is a greenhouse gas (GHG) with 300 times the radiative forcing in the atmosphere of carbon dioxide (CO2), and has recently become a subject of great concern because the nitrogen (N) fertilizers which have been necessary to increase agricultural productivity have also dramatically increased N2O emissions from agroecosystems. Many N control practices have been suggested and implemented in agroecosystems, but their ability to simultaneously remove reactive N from the environment and prevent the production of N2O is, at best poorly understood. The goal of this work is to characterize environmental controls on production of N2O in denitrifying bioreactors. The review portion of this work first discusses the geologic history of the N cycle, how its past and present processes differ, and how it is being affected by human activity. It then explores the N cycle's biochemical pathways, reviews the controls for each of its steps, and discusses the environmental drivers of these controls. The review closes with a discussion of environmental N management strategies. The experimental portion of this work further explores these concepts by observing how biochar amendment and the modification of pH affect N2O production in the denitrification pathway in denitrifying bioreactors. Both pH and biochar have previously been shown to affect N2O production and many N management practices utilize biochar or manipulate pH to increase N retention. The objectives of the experiment were to: 1) Examine headspace N2O concentration in sealed, biochar-amended, denitrifying bioreactors; 2) Determine if the effects of pH on N2O production differ in biochar-amended systems versus controls (under acidic, unbuffered, and buffered conditions); 3) Quantify key denitrification genes (nirK, nirS, nosZ) in each treatment combination. Experimental results showed biochar treatment to significantly increase N2O emissions, a result which runs contrary to most, but not all studies regarding its effects on N2O production. Differences between treatments decreased with increasing pH levels. Biochar did not exhibit significant effects on individual denitrification genes, but it did show influence on the ratios of their populations. On the other hand, pH was found to have significant effects on nirS and nosZ populations. Differences in N2O production between biochar and controls were thus explained by biochar's chemical effects, likely its ability to increase denitrification activity. Developing an understanding of the mechanisms behind these differences will require using a combination of isotope tracing, enzyme assays, and mass balance approaches. Future microbial work in biochar-amended systems should attempt to characterize differences in gene expression, overall community structure, and long-term population trends in the genes of interest. The combination of these approaches should allow researchers to better predict where N2O production will occur and develop strategies to mitigate it while simultaneously increasing food production to meet the demands of a growing population. / Master of Science

When a devastating event such as a forest fire occurs, multiple actions have to be taken. The first priority is to ensure people's safety during the fire, then the fire has to be kept under control and finally extinguished. After all of this, what remains is a damaged area in the forest. The objective of this thesis is to evaluate medium and high-resolution satellite imagery for the classification of different burn severities in a wildfire damaged forest. The classification can then be used to plan where to focus restoration efforts after the fire to achieve a safe and economically beneficial usage of the affected area. Trängslet fire in Dalarna and Lillhärdal fire in Härjedalen, the two of the 2018 forest fire sites in Sweden were chosen for this study. Satellite imagery over both study areas at medium spatial resolution from Sentinel-2 were acquired pre-fire in early July, 2018 and post-fire on October 2, 2018 while imagery at high spatial resolution from Pleiades were acquired on September 13, 2018. Image processing, analysis and classification were performed using Google Earth Engine (GEE) and PCI Geomatica. To ensure the quality of the classifications, field data were collected during a field trip to the Lillhärdal area using Open Data Kit (ODK). ODK was used since it is an application that can collect/store georeferenced information and images. The result that this thesis found is that while both the medium and high-resolution classifications achieved accurate results, the Sentinel-2 classification is the most suited method in most cases since it is an easy and automated classification using differential Normalized Burn Ratio (dNBR) compared to the Pleiades classification where a lot of manual work has to be put in. There are however cases where the Pleiades classification would be preferable, such as when the affected area usually is obscured by clouds and Sentinel-2 thus finds it hard to achieve good images and when a good spatial resolution is required to more easily display the classification with the original image. The most accurate result according to the data collected at the site in Lillhärdal also showed that the Pleiades classification had a precise match of 61.54% and a plausible match of 92.31%. This can be compared to the Sentinel-2 classification that had a precise match of 48.72% and a plausible match of 94.87%. These percentages are based on the visual analysis of collected images at the Lillhärdal site compared to the classifications. This thesis could have been improved if more information regarding the groundwork that had been done after the fire, but before the acquiring of the satellite imagery, were available. The result would also most likely be better if a satellite with better spatial resolution than Sentinel-2 but still with near infrared and short-wave infrared bands would have been used. The reason being that dNBR, which gave a good result, only needs those two bands.

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