Brian Klinkenberg

Professor

Research Classification

Geomatics
Biogeography
Bioinformatics
Environmental Health

Research Interests

Geographic Information Science
Environmental Remote Sensing
Spatial Analysis
Volunteered Geographic Information (VGI) and Citizen Science Initiatives

Relevant Degree Programs

 
 

Recruitment

Master's students
Any time / year round

Please view my home page for a listing of current projects.

I support public scholarship, e.g. through the Public Scholars Initiative, and am available to supervise students and Postdocs interested in collaborating with external partners as part of their research.
I support experiential learning experiences, such as internships and work placements, for my graduate students and Postdocs.
I am open to hosting Visiting International Research Students (non-degree, up to 12 months).

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Great Supervisor Week Mentions

Each year graduate students are encouraged to give kudos to their supervisors through social media and our website as part of #GreatSupervisorWeek. Below are students who mentioned this supervisor since the initiative was started in 2017.

 

Brian Klinkenberg gives all of his time and attention to his students. He has never given me the impression that he doesn't want to help, whether it's advice for a presentation, edits for a paper, or a meeting to move a group project forward. Even on the busiest days, he balances working with his graduate students, teaching courses, attending meetings, and still makes time to guide his undergrads. And bonus: he always brings in cookies!

Emily Acheson (2018)

 

Graduate Student Supervision

Doctoral Student Supervision (Jan 2008 - May 2021)
Exploring the ecological factors behind the 1999 outbreak of Cryptococcus gattii sensu lato on Vancouver Island (2021)

Cryptococcus gattii sensu lato, a species complex of fungi that causes life-threatening infections in humans and other animals, was responsible for an outbreak of infections on Vancouver Island beginning around 1999. The possible ecological triggers for this outbreak, the first ever recorded in Canada, remain unknown. In this thesis, I apply a geospatial lens to explore the ecology of C. gattii s.l.. I aim to better understand the biophysical factors upon which C. gattii s.l. is most dependent and, through this, which factors may have led to the outbreak. Through a review of the C. gattii s.l. literature, I show that no studies directly tested the potential effects of climatic changes on C. gattii s.l., while only one study directly assessed those of land use change. I then use geographic information systems (GIS) and remote sensing to map global environmental isolations of C. gattii s.l. and challenge the long-held hypothesis that this fungus was only previously found in tropical and subtropical areas. I further demonstrate that GIS can provide a systematic method to classify the climates of disease emergence areas for public health research. In my studies of the potential effects of forest disturbance and climate on C. gattii s.l. occurrence on Vancouver Island, I found weak or no effects of forest disturbance on C. gattii s.l. occurrence. However, I found significant effects of the number of frost-free days in the year prior to, and the mean precipitation in the summer preceding, fungal sampling. These findings support previous studies that also found C. gattii s.l. has an increased survival in areas of Vancouver Island that have average winter temperatures above freezing, as well as warm, dry summers that may support aerosolization of spores. This research is also the first to examine the potential effects of forest disturbance, as well as possible interactions with climate, on C. gattii s.l.. Beyond exploring the ecology of C. gattii s.l., I propose geospatial methods to deal with spatiotemporal biases in secondary-use GIS data as well as to quantify the effects of ecological disturbance on infectious disease emergence in the natural environment.

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Modeling place attachment using GIS (2017)

The PlaceInGIS project is a comprehensive examination of how places can be represented using modern Geographic Information System (GIS). After decades of research, geographers now understand that places are dynamic features, whose fuzzy boundaries change over time, subject to internal and external forces. The long-term goal of the PlaceInGIS project is to make people's understanding of place visible, comparable and amenable to analysis.Place attachment is a theoretical construct that permits the quantification, visualization and analysis of the importance of place. The method described makes use of two significant sub-components of place attachment, place dependence and place identity, to create fuzzy surfaces in a GIS.After conducting a detailed GPS mapping exercise of the Colliery Dam Park study area in Nanaimo, British Columbia, Canada, 302 study participants were presented with a survey questionnaire between 2011 and 2012. The place attachment and place dependence components for each feature described were used to create "feature surfaces." These were then combined using a Fuzzy OR operator to generate a single "place attachment surface" for each individual, which can be compared against each other or summed to show the overall opinions of groups.In the short term, we are developing an application called the Place Analysis System (PAS), which enables places to be adequately represented. There are numerous applications for the PAS, as it creates a foundation for the comparative study of place. For the first time, it is possible to visualize, take measurements and analyze place attachment. What was once an ephemeral concept has been made concrete and amenable to study. The PAS can analyze fuzzy boundaries, or the fuzzy boundaries can be defuzzified to be more compatible with traditional representations of data in a GIS. We examine two applications of the PAS, one as a tool for site planning, and the other for the geographical analysis of core and periphery. These applications demonstrate the utility of the PAS, and we conclude by considering further applications and modifications to make the method easier to employ in future studies.

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Geospatial analysis of African elephant movement (Loxodonta africana and L. cyclotis) (2015)

African elephants (Loxodonta africana and L. cyclotis) are important species for geospatial study given their ecological role as megaherbivores, their large home ranges which pose challenges for conservation, and the ongoing ivory crisis. Using GPS tracking data, I address five research topics that contribute new information to the geospatial analysis of tracking data, to elephant movement ecology, and conservation :1. What is an appropriate method to collect, store, disseminate, visualize and analyze elephant tracking data? I present a system (Loxobase) designed to provide an efficient and scientific basis for the treatment of wildlife tracking data. I demonstrate its utility by analyzing tracking datasets collected from 247 elephants (Chapter 2). 2. Can we leverage real-time tracking data for management and conservation? I present a monitoring system that implements continuous analysis of elephant GPS tracking data streams to identify positional and movement-based geospatial alert conditions. Four algorithms identify when wildlife slow or stop moving or cross into or near to spatial objects (Chapter 3).3. Can we estimate wildlife space-use from tracking data? I develop the Elliptical Time-Density model to estimate an animal's utilization distribution from tracking data where parameters are directly linked to species biology. I demonstrate its performance in relation to other space-use estimators (Chapter 4).4. What does tracking data tell us about the movement patterns of the Sahelian elephants in Mali? I use GPS tracking to study elephants in the Gourma, Mali to understand this unique and important population. The Gourma elephant's range was found to exceed those reported elsewhere in Africa and movements were correlated with patterns of rainfall and vegetation phenology. I also identified corridors and core areas of conservation priority (Chapter 5).5. What does tracking data tell us about the factors influencing elephant range size across Africa? I present a comparative analysis of elephant range area measured in West, Central, East and Southern Africa. Using mixed effects models, I test hypotheses about elephant range size in relation to sex, species, region, vegetation phenology and quantity, protected areas, human footprint and terrain (Chapter 6).

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Master's Student Supervision (2010 - 2020)
Exploring spatio-temporal patterns and environmental determinants of pediatric Inflammatory Bowel Disease in British Columbia (2020)

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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An exploration of computational methods for classifying sediment patches within archived aerial photographs of gravel-bed rivers (2019)

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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Exploring barriers to success for community-based organizations engaged in the adaptive co-management of parkland (2019)

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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Citizen science in conservation biology: Best practices in the GeoWeb era (2013)

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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A landscape level analysis of yellow-cedar decline in coastal British Columbia (2010)

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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