There has been little research comprehensively documenting wildlife species in Harenna Forest within the Bale Mountains National Park of Ethiopia. This area is one of the few remaining afro-alpine biodiversity hotspots and is home to numerous endemic plants and animals and offers socio-economic benefits to the neighboring communities. Human population pressure, weak land protection policies, and uncertain land tenure rights have led to increases in farmland for subsistence and coffee farming, livestock grazing, and reduction of afro-alpine, shrubland and grassland habitats. Given these challenges, I used 48 camera trap stations to produce an inventory of wildlife species and to determine factors influencing occupancy (i.e., habitat use), detection, and temporal activity and overlap. I recorded 26 terrestrial and arboreal mammalian species and I had sufficient data to model occupancy for 13 species and temporal activity for 14 species. Occupancy and detection were generally higher for herbivores and omnivores (occupancy: 0.28-0.97; detection: 0.1-0.54) than carnivores (occupancy: 0.31-0.80; detection: 0.04-0.18). I found more evidence of positive anthropogenic impacts on herbivore and omnivore occupancy than negative, while detection was influenced by habitat or landscape features, rather than by humans. Carnivore occupancy was largely unaffected by anthropogenic or habitat variables, but detection was strongly, and mostly positively, influenced by anthropogenic impacts. Temporal activity analyses revealed that, for herbivores and omnivores, only tree hyraxes (Dendrohyrax arboreus) and crested porcupines (Hystrix cristata) were nocturnal, Menelik bushbucks (Tragelaphus scriptus meneliki) were crepuscular, and the remaining species ranged from diurnal to cathemeral. Neither similar body size nor similar diet affected overlap between species pairs. However, overlap with human temporal activity was low for Menelik bushbucks (Δ=0.45) and common duikers (Sylvicapra grimmia) appeared to become less active at stations with high human use. For carnivores, leopards (Panthera pardus) and honey badgers (Mellivora capensis) were crepuscular, and the remaining species were nocturnal. I found evidence that carnivores overlapped less when they were more similar in body size to other carnivores (average Δ=0.67-0.71) compared to species more dissimilar in body size (average Δ=0.75), although there was variation across species. In general, carnivores overlapped much less with humans (average Δ=0.20) than did herbivores (average Δ=0.52) and omnivores (average Δ=0.43). Spotted hyenas (Crocuta crocuta), in particular, appeared to alter activity to reduce overlap with humans. This study provides baseline information on presence, distribution, and activity of large- and medium-sized terrestrial and arboreal mammals in an understudied biodiversity hotspot. My findings are concerning for biodiversity conservation as rare and endangered species (e.g., mountain nyalas (Tragelaphus buxtoni), Ethiopian wolves (Canis simensis)) were rarely or never photographed, and larger carnivores (e.g., lions (Panthera leo), leopards, jackals), generally had low capture rates. The species with higher capture rates, occupancy, and activity tended to be those that can tolerate or take advantage of human activity and disturbance. Species sensitive to human disturbance eventually may be lost unless measures can be put in place to reduce human impacts. This baseline knowledge is important for future studies examining trends in mammalian wildlife populations, such as site extinction and colonization, or changes in overlap with humans, in a landscape that is continuing to experience human-caused, landscape change. / Master of Science / Harenna forest, which is located in Bale Mountains National Park, Ethiopia is an important habitat to both wildlife and people. However, it faces a number of challenges as a result of population growth leading to increased coffee farming and livestock grazing resulting in reduced habitat for wildlife species. I used 48 cameras located across the forest to record presence of terrestrial mammals and document their distribution and daily activity across the landscape. I also used data such as vegetation indices, elevation, and distances to human-disturbed areas to determine what influenced wildlife species. Cameras recorded 26 species of mammals. I had enough data to determine distribution for 13 species and daily activity for 14 species. I found that presence across the landscape and activity of herbivores and omnivores was generally higher than that of carnivores. Additionally, I found that human activity or disturbance often had a positive influence on herbivore and omnivore distribution, but my ability to detect species in camera traps was primarily influenced by habitat or landscape features. Carnivore distribution on the landscape was not influenced much by humans or habitat, but their detectability was often positively influenced by presence of humans. In addition to daily activity, I also analyzed overlap in activity between species pairs and between species and humans, to determine whether wildlife changed their temporal activity to overlap less with similar sized competitors or in response to high human use. For herbivores and omnivores, I found that tree hyraxes and crested porcupines were active at night, Menelik's bushbucks were active at sunrise and sunset, and cape bushbucks, common duiker, olive baboon, bushpig, and giant forest hogs were active either during the day or throughout the day and night. I found little evidence that the herbivores or omnivores avoided each other temporally and only the Menelik bushbuck and duiker appeared to avoid humans. For carnivores, I found that leopards and honey badgers were active early morning and evening, and the common genet, African civet, white-tailed mongoose, and spotted hyenas were all active at night only. Carnivores generally overlapped less with humans than herbivores and omnivores. I found some evidence that carnivores more similar in body size had lower temporal overlap with each other and that spotted hyaenas appeared to avoid activity during times of day when humans were active. My study not only provides baseline information on terrestrial and arboreal mammals present in Harenna forest, Ethiopia, but is also necessary for understanding how wildlife species use the landscape and particularly how presence of humans influences wild animal behavior. My findings are concerning for biodiversity conservation because I had few to no photographs, respectively, of the endangered mountain nyala and Ethiopian wolf. In fact, most of the species with a wide distribution on the landscape, or with high activity, were common or smaller species that are tolerant of, or could take advantage of, human disturbance. Without concerted effort to curtail the current landscape change caused by humans, the area is likely to lose species less tolerant of humans, and biodiversity will ultimately decline.

Yes / This paper presents a new control strategy for stochastic distribution shape tracking regarding non-Gaussian stochastic non-linear systems. The objective can be summarised as adjusting the probability density function (PDF) of the system output to any given desired distribution. In order to achieve this objective, the system output PDF has first been formulated analytically, which is time-variant. Then, the PDF vectorisation has been implemented to simplify the model description. Using the vector-based representation, the system identification and control design have been performed to achieve the PDF tracking. In practice, the PDF evolution is difficult to implement in real-time, thus a data-driven extension has also been discussed in this paper, where the vector-based model can be obtained using kernel density estimation (KDE) with the real-time data. Furthermore, the stability of the presented control design has been analysed, which is validated by a numerical example. As an extension, the multi-output stochastic systems have also been discussed for joint PDF tracking using the proposed algorithm, and the perspectives of advanced controller have been discussed. The main contribution of this paper is to propose: (1) a new sampling-based PDF transformation to reduce the modelling complexity, (2) a data-driven approach for online implementation without model pre-training, and (3) a feasible framework to integrate the existing control methods. / This paper is partly supported by National Science Foundation of China under Grants (61603262 and 62073226), Liaoning Province Natural Science Joint Foundation in Key Areas (2019- KF-03-08), Natural Science Foundation of Liaoning Province (20180550418), Liaoning BaiQianWan Talents Program, i5 Intelligent Manufacturing Institute Fund of Shenyang Institute of Technology (i5201701), Central Government Guides Local Science and Technology Development Funds of Liaoning Province (2021JH6/10500137).

Abstract: Road traffic accidents claim more than 1,500 lives each year in Canada and affect society adversely, so transport authorities must reduce their impact. This is a major concern in Quebec, where the traffic-accident risks increase year by year proportionally to provincial population growth. In reality, the occurrence of traffic crashes is rarely random in space-time; they tend to cluster in specific areas such as intersections, ramps, and work zones. Moreover, weather stands out as an environmental risk factor that affects the crash rate. Therefore, traffic-safety engineers need to accurately identify the location and time of traffic accidents. The occurrence of such accidents actually is determined by some important factors, including traffic volume, weather conditions, and geometric design. This study aimed at identifying hotspot locations based on a historical crash data set and spatiotemporal patterns of traffic accidents with a view to improving road safety. This thesis proposes two new methods for identifying hotspot locations on a road network. The first method could be used to identify and rank hotspot locations in cases in which the value of traffic volume is available, while the second method is useful in cases in which the value of traffic volume is not. These methods were examined with three years of traffic-accident data (2011–2013) in Sherbrooke. The first method proposes a two-step integrated approach for identifying traffic-accident hotspots on a road network. The first step included a spatial-analysis method called network kernel-density estimation. The second step involved a network-screening method using the critical crash rate, which is described in the Highway Safety Manual. Once the traffic-accident density had been estimated using the network kernel-density estimation method, the selected potential hotspot locations were then tested with the critical-crash-rate method. The second method offers an integrated approach to analyzing spatial and temporal (spatiotemporal) patterns of traffic accidents and organizes them according to their level of significance. The spatiotemporal seasonal patterns of traffic accidents were analyzed using the kernel-density estimation; it was then applied as the attribute for a significance test using the local Moran’s I index value. The results of the first method demonstrated that over 90% of hotspot locations in Sherbrooke were located at intersections and in a downtown area with significant conflicts between road users. It also showed that signalized intersections were more dangerous than unsignalized ones; over half (58%) of the hotspot locations were located at four-leg signalized intersections. The results of the second method show that crash patterns varied according to season and during certain time periods. Total seasonal patterns revealed denser trends and patterns during the summer, fall, and winter, then a steady trend and pattern during the spring. Our findings also illustrated that crash patterns that applied accident severity were denser than the results that only involved the observed crash counts. The results clearly show that the proposed methods could assist transport authorities in quickly identifying the most hazardous sites in a road network, prioritizing hotspot locations in a decreasing order more efficiently, and assessing the relationship between traffic accidents and seasons. / Les accidents de la route sont responsables de plus de 1500 décès par année au Canada et ont des effets néfastes sur la société. Aux yeux des autorités en transport, il devient impératif d’en réduire les impacts. Il s’agit d’une préoccupation majeure au Québec depuis que les risques d’accidents augmentent chaque année au rythme de la population. En réalité, les accidents routiers se produisent rarement de façon aléatoire dans l’espace-temps. Ils surviennent généralement à des endroits spécifiques notamment aux intersections, dans les bretelles d’accès, sur les chantiers routiers, etc. De plus, les conditions climatiques associées aux saisons constituent l’un des facteurs environnementaux à risque affectant les taux d’accidents. Par conséquent, il devient impératif pour les ingénieurs en sécurité routière de localiser ces accidents de façon plus précise dans le temps (moment) et dans l’espace (endroit). Cependant, les accidents routiers sont influencés par d’importants facteurs comme le volume de circulation, les conditions climatiques, la géométrie de la route, etc. Le but de cette étude consiste donc à identifier les points chauds au moyen d’un historique des données d’accidents et de leurs répartitions spatiotemporelles en vue d’améliorer la sécurité routière. Cette thèse propose deux nouvelles méthodes permettant d’identifier les points chauds à l’intérieur d’un réseau routier. La première méthode peut être utilisée afin d’identifier et de prioriser les points chauds dans les cas où les données sur le volume de circulation sont disponibles alors que la deuxième méthode est utile dans les cas où ces informations sont absentes. Ces méthodes ont été conçues en utilisant des données d’accidents sur trois ans (2011-2013) survenus à Sherbrooke. La première méthode propose une approche intégrée en deux étapes afin d’identifier les points chauds au sein du réseau routier. La première étape s’appuie sur une méthode d’analyse spatiale connue sous le nom d’estimation par noyau. La deuxième étape repose sur une méthode de balayage du réseau routier en utilisant les taux critiques d’accidents, une démarche éprouvée et décrite dans le manuel de sécurité routière. Lorsque la densité des accidents routiers a été calculée au moyen de l’estimation par noyau, les points chauds potentiels sont ensuite testés à l’aide des taux critiques. La seconde méthode propose une approche intégrée destinée à analyser les distributions spatiales et temporelles des accidents et à les classer selon leur niveau de signification. La répartition des accidents selon les saisons a été analysée à l’aide de l’estimation par noyau, puis ces valeurs ont été assignées comme attributs dans le test de signification de Moran. Les résultats de la première méthode démontrent que plus de 90 % des points chauds à Sherbrooke sont concentrés aux intersections et au centre-ville où les conflits entre les usagers de la route sont élevés. Ils révèlent aussi que les intersections contrôlées sont plus à risque par comparaison aux intersections non contrôlées et que plus de la moitié des points chauds (58 %) sont situés aux intersections à quatre branches (en croix). Les résultats de la deuxième méthode montrent que les distributions d’accidents varient selon les saisons et à certains moments de l’année. Les répartitions saisonnières montrent des tendances à la densification durant l’été, l’automne et l’hiver alors que les distributions sont plus dispersées au cours du printemps. Nos observations indiquent aussi que les répartitions ayant considéré la sévérité des accidents sont plus denses que les résultats ayant recours au simple cumul des accidents. Les résultats démontrent clairement que les méthodes proposées peuvent: premièrement, aider les autorités en transport en identifiant rapidement les sites les plus à risque à l’intérieur du réseau routier; deuxièmement, prioriser les points chauds en ordre décroissant plus efficacement et de manière significative; troisièmement, estimer l’interrelation entre les accidents routiers et les saisons.

Increased demands on water supplies caused by population expansion, saltwater intrusion, and drought have led to water shortages which may be addressed by use of recycled water as recycled water products. Study I investigated recycled water production in Florida and California during 2009 to detect gaps in distribution and identify areas for expansion. Gaps were detected along the panhandle and Miami, Florida, as well as the northern and southwestern regions in California. Study II examined gaps in distribution, identified temporal change, and located areas for expansion for Florida in 2009 and 2015. Production increased in the northern and southern regions of Florida but decreased in Southwest Florida. Recycled water is an essential component water management a broader adoption of recycled water will increase water conservation in water-stressed coastal communities by allocating recycled water for purposes that once used potable freshwater.