BSc, PhD, RPBio
Brendan Wilson is an instructor and research scientist in Selkirk College's School of Environment & Geomatics and Selkirk Innovates, where he has taught since 2001.
Originally from the Bow Valley in Alberta, Brendan has had a life-long interest in subalpine and timberline forest communities. He completed a B.Sc. Hons. in Applied Environmental Biology at the University of Technology in Sydney, where he examined the effect of selective harvesting on understory plant communities in an Australian subalpine forest. Upon his return to Canada in the mid-1990’s, he completed his PhD at the University of Alberta, studying regeneration dynamics of alpine larch.
Over the past 20 years Brendan and his students have worked on whitebark pine conservation, species at risk assessment, white pine blister rust monitoring, species distribution modelling, prescribed fire and forest fuel treatment work, and using remotely sensed imagery to aid with these projects.
Brendan currently teaches Ecosystem Management, Systems Ecology, Applied Research Methods, and Spatial Statistics. He also is on the board of directors for the Columbia Mountains Institute of Applied Ecology.
Recent student theses:
Lognon, E. 2024. Exploring the Use of UAV Thermal Imagery to Map Thermal Refugia in the West Kootenays. BGIS Thesis, Selkirk College, BC.
Deas, M. 2024. Using spatial analysis to identify if greenspaces are equally accessible across differing economic dissemination areas within New Westminster. BGIS Thesis, Selkirk College, BC.
Ernst, T.M. 2023. Species distribution modeling to inform seed provenance approaches that create climate change resilience in Camassia quamash (common camas) populations located throughout the Lower Columbia region of the West Kootenays in British Columbia. BGIS Thesis, Selkirk College, BC.
Block, S. 2023. High spatial resolution RGB imagery and subalpine coniferous tree species identification: pixel-based and object-based analyses: whitebark pine in Southeastern British Columbia. BGIS Thesis, Selkirk College, BC.
Nutley, P. 2022. Use of landcover classification, burn severity mapping, and analysis of covariance (ANCOVA) to examine the impact of burn severity on regrowth of herbaceous and shrubland vegetation. BGIS Thesis, Selkirk College, BC.
Stolyarov, V. 2022. Using a deep learning model and data augmentation to classify tree species from high-resolution multispectral data. BGIS Thesis, Selkirk College, BC.
Jouvet, S. 2022. Subalpine tree species classification using remote sensing methods and techniques. BGIS Thesis, Selkirk College, BC.
Recent publications:
Freisen M, Albino J, Cahill J, Grieves D, Wilson B. 2023. Can we use drones to remotely identify whitebark pine in mature forests? In: Annual Researchers’ Forum. Nelson, British Columbia: The Columbia Mountains Institute of Applied Ecology.
Wilson B, Cameron H, Griffith C, Ernst T. 2023. Examining blister rust incidence in whitebark pine: why is Banff so different? In: People and Pines: Human Impacts on 5 -Needle Pines. Revelstoke, BC: Whitebark Pine Ecosystem Foundation, Canada.
Jouvet S and Wilson B. 2022. Subalpine tree species classification using remote sensing methods and techniques. Research and Management of High-Elevation Five-Needle Pines in Western North America. 15.
Wilson B, Jouvet S, Stuart-Smith GJ, and Walker RC. 2022. Forest structure twenty years after the first whitebark pine prescribed burn in Banff Nation Park. Research and Management of High-Elevation Five-Needle Pines in Western North America. 4.