Brian Klinkenberg

Illicit opioid overdose deaths in British Columbia have increased five folds since 2012. Previous studies have identified potential factors that may affect the distribution of fatal and nonfatal overdose risks, such as socioeconomic status, stigma, and access to health care services. Most of these factors affect rural and urban areas differently, and I hypothesize that fatal/nonfatal overdose risks could be higher in rural areas than in urban areas because rural communities are often disadvantaged concerning these factors. The presence of rural-urban differences in overdose risks was confirmed by modelling the recurrent overdose rate and odds of fatal overdose per event for British Columbians who had at least one overdose between Jan 2015 and Dec 2018 with Poisson and logistic regression methods. Spatial variations in these two measures were then estimated using Generalized Additive Models; the results are mapped to identify communities and regions with the highest risk of fatal overdose. Long-term survival after a first overdose event was also investigated using Cox proportional hazard models under a multi-state framework that conceptualized overdose risk relative to Opioid Agonist Therapy (OAT) event history. On the one hand, the results suggest that the hypothesis was verified in terms of fatal risk per event; healthcare access, namely living close to harm reduction sites, seemed to reduce the likelihood of overdose death, which is consistent with previous findings. However, communities or regions without harm reduction sites had higher fatal risks than other places. On the other hand, the hypothesis was not justified (i.e., the risk of fatal overdose did not vary spatially) in the long term. Overdose survival was highly related to receiving OAT. Even though service access is limited in rural communities, people in these areas were more likely to have received OAT resulting in no significant difference in survival probability over space.

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Canada has some of the highest rates of pediatric Inflammatory Bowel Diseases (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), in the world. Environmental factors are known to be important for disease development but are not well understood. This study used two forms of analysis to examine the epidemiology and potential causes of IBD diagnosed before age 17 in the Canadian province of British Columbia from 2001 to 2016. A spatial cluster detection methodology was used to locate disease clusters of high and low incidence rates, the presence of which would highlight potential environmental risk and protective factors. Logistic regression models of case-control data were used to measure the relationship between IBD diagnosis and NO₂ air pollution, density of residential and neighborhood vegetation greenness (green spaces), vitamin D adjusted ultraviolet solar radiation, area South Asian and Jewish ethnicity, area self-identification as Aboriginal, and area social and material deprivation. The spatial distributions of IBD, CD, and UC were significantly clustered, with consistent IBD hot spots identified near the main urban centre of the province and cold spots identified in rural areas of south-eastern British Columbia. CD and UC had similar and different hot and cold spots, suggesting both shared and distinct environmental determinants. Most measured associations between variables of interest and IBD were moderate or small; as IBD is a multifactorial disease, these variables may still have a population-level effect on disease risk or interact with other risk factors and should be studied further. NO₂ air pollution was a significant risk factor for UC. Area South Asian ethnicity was only a significant risk factor in the univariate analysis, though a small and similar effect was observed in the multivariate analysis which included social and material deprivation. Ultraviolet vitamin D exposure was a protective factor for UC and IBD, especially in winter months. Area Aboriginal identity and area material deprivation (areas with lower socioeconomic status) were significant protective factors for CD, though Aboriginal identity was not significant in a multivariate analysis that included social and material deprivation. No reliable relationship was observed for greenness or area Jewish ethnicity.

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Bed material within gravel-bed rivers, which consists of gravel and other sediment coarser than 2mm, determines channel morphology and provides important benthic habitat. The impacts of flooding and anthropogenic activity on bed material are often examined to determine their effect on the morphology and ecology of gravel-bed rivers. To truly characterize this relationship, bed material must be discriminated from sand and sediment finer than 2mm at reach-scale over time. The current remote sensing routines that are used to synoptically characterize fluvial sediment did not emerge until the early 2000s, and as a result, reach-scale assessments of sand and gravel, extending beyond the 2000s, are absent for most gravel-bed rivers. Fortunately, archived aerial photographs, can be used to analyze past landscapes. Traditionally, these analyses are carried out, manually, by photo interpreters, but multiple studies have shown that image processing techniques can be used to extract meaningful information from scanned aerial photographs. This study provides an exploration of semi-automated and automated image classification routines and their ability to replace manual interpretation for delineating patches of sand and gravel within scanned archived aerial photographs. Results indicate that patches of sand and gravel within contemporary digital aerial imagery that has been degraded to mimic the characteristics of analog aerial photography can be consistently classified with overall accuracy above ~93% using automated object- and pixel-based classification routines. However, these same classifications only agree with manual interpretations of archived aerial photographs between ~45-70%. In contrast, the semi-automated routine provides measures of agreement that range almost entirely between ~75-85% when compared to the manual interpretations as well as the automated routines. Together, this demonstrates that a semi-automated routine should be used to classify scanned archived aerial photographs into sand and gravel.

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For decades, leaders in environmental governance have been directing the attention of their peers towards co-management frameworks. These participatory approaches to land management connect local communities and governments through power-sharing, and enhanced stakeholder engagement. Adaptive co-management is a distinct approach within this tradition that encourages flexibility and adaptability within environmental management through participatory governance, and an iterative, trial-by-error approach to understanding social-ecological systems. However, while the conceptual understanding of adaptive co-management has grown considerably over the years, critics have highlighted that the knowledge and representation of how this process occurs is lacking. This is particularly true regarding parkland. To begin addressing this concern, I conducted a multiple ethnographic case-study of four community-based organizations in Vancouver, British Columbia that are engaged in the adaptive co-management of parkland alongside their regional land manager. Specifically, I aimed to: (1) explore barriers to adaptive co-management related to citizen monitoring, institutional culture, and stakeholder engagement; (2) highlight the lived experience of participants to provide a thicker description for understanding the adaptive co-management process; and (3) suggest solutions and avenues for future research. A broad array of barriers existed for participants in this study. First, a lack of understanding regarding the quality of citizen data has led to funding shortages for citizen monitoring programs, and a regional disparity in their utilization. Second, rigid communication and information technology policies have resulted from unequal organizational growth, and an institutional fear of decentralized technology. Finally, stakeholder engagement has been reduced due to the marginalization of “outsider organizations,” and a lack of actor-level diversity on community boards. In response to these findings, I conclude this thesis with a series of five best practices that are based on suggestions emerging from the literature and my participants: These include: (1) Increased internal funding for citizen monitoring programs; (2) the use of a holistic data quality assessment framework; (3) the adoption of more flexible and transparent communication policies; (4) the adoption of an Agile information technology framework; and (5) the formalization of community-led bridging organizations to support stakeholder mediation.

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Conservation biology emerged as an activist discipline in the 1980s in response to increasing evidence that Earth is undergoing a biodiversity crisis. Building on foundations of biological science and applied resource management methods, this new discipline called upon its practitioners to both undertake scientific research to improve understanding of all species and ecosystems, and to take social and political action to protect and enhance endangered biodiversity. In the current era of declining budgets for biodiversity research and management, volunteer citizen science is gaining recognition as an important strategy for expanding and extending the work of embattled professional conservation biologists. New technologies such as handheld computers, GPS, GIS, interactive map services, and the internet, and the wide-spread availability, adoption and adaptation of these technologies by the general public, have created an environment where citizens can be rapidly mobilized to gather, process, and communicate data in support of conservation biology’s twin goals. In this thesis I explore citizen science within conservation biology and within the concept of the GeoWeb. I trace the history of citizen science in biology since the late 1800s to the current day, to better understand the practice and its contribution to conservation science. I find that citizen science is often employed to undertake research at large spatial scales, and that often location is a key attribute of the data citizens gather; as a result, the infrastructure and methods of the GeoWeb are fundamental to many citizen science projects. In the spirit of conservation biology, I pair my research of citizen science with the assembly of a set of best practices for increasing the impact of the practice on the conservation agenda, and then evaluate twelve current citizen science projects currently underway in British Columbia against these practices. I conclude that citizen participation in biological science furthers both of conservation biology’s goals: it both increases our body of knowledge about biodiversity, and helps to develop an informed and empowered constituency for conservation action and ecologically sustainable stewardship.

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Yellow-cedar (Chamaecyparis nootkatensis) is currently undergoing a dramatic decline in western North America, with concentrated areas of decline located in southeast Alaska and coastal British Columbia. Recent research suggests that a shift in climate is responsible for the decline and a working hypothesis concerning the role of climate and site specific factors has been proposed. The main objective of this research was to contribute to the understanding of the yellow-cedar decline phenomenon by examining the spatial pattern of the decline and assessing the relations with topographic variables in coastal British Columbia.The research questions were addressed through a combination of remote sensing and Geographic Information System (GIS) techniques. Sample points were distributed across the landscape according to a stratified sampling scheme and the presence/absence of decline at each point was determined using a forest cover dataset and aerial photograph interpretation. Spatial patterns of topographic factors (e.g. elevation, slope, aspect) were derived from a 25 m digital elevation model of the province. To assess the strength of relations between the distribution of decline and the various environmental predictors, logistic regression and decision-tree models were applied. The lasso technique was used to select a significant set of coefficients and the selection was then validated through bootstrap analysis. Model results indicated that low elevation sites close to the coast, which are more exposed and have more variation in elevation, are more likely to show evidence of decline. The logistic model fit the data well (Nagelkerke R² = 0.846, Hosmer-Le Cessie omnibus test failed to find any evidence of lack of fit) and had high predictive accuracy (AUC = 0.98).The topographic variables identified by the model influence degree of soil saturation, temperatures and snowpack presence in a forest stand, supporting the proposed associations in the current decline hypothesis. The analysis also highlighted the utility of the lasso logistic model for selecting significant variables and mapping high risk areas for decline. Knowledge of the determinants of the spatial pattern of decline will improve predictability and provide critical information for the conservation and management of yellow-cedar.

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