Exploring species distribution modelling as a tool to support knowledge of country food access & availability: vaccinium vitis-idaea in the Gwich’in Settlement Area
| dc.contributor.author | Hare, Karl | |
| dc.contributor.supervisor | Boulanger-Lapointe, Noémie | |
| dc.date.accessioned | 2025-08-27T20:52:01Z | |
| dc.date.available | 2025-08-27T20:52:01Z | |
| dc.date.issued | 2025 | |
| dc.degree.department | Department of Geography | |
| dc.degree.level | Master of Science MSc | |
| dc.description.abstract | In the Canadian North berries are essential, being used extensively as a food source, for medicines, and for dyes. In the Gwich'in Settlement Area alone, it is estimated that more than 5,000 liters of berries are harvested per year. Unfortunately, climate change poses a serious threat to berry harvests and has led to a noticeable decline in the condition and yield of harvestable berries throughout Northern Canada. Berries have been a staple food source for generations of northern residents and are equally important to northern animals, particularly birds, small mammals, bears, pollinators and caribou. This work follows my collaboration with the Gwich’in Tribal Council to work towards creating a species distribution model of Vaccinium vitis-idaea (mountain cranberry) with Indigenous Knowledge in the forms of participatory mapping data and quotes from interviews. During this process, I explored two separate methodological frameworks in species distribution modeling, both of which include Indigenous Knowledge in different ways. The first is a presence-only model, where harvest locations are assumed to correspond to the presence of a high abundance of berries. The second is a random forest approach which uses field data to generate an abundance model of predicted harvestable yield of mountain cranberry fruit, validated with the help of Indigenous Knowledge. This work aims to showcase methodological frameworks that could help Indigenous Governments and ecologists investigate biology throughout their land. The results of this research highlight that species distribution modeling must be navigated with caution and context, especially when applied to Indigenous Knowledge systems, as this methodology has the potential to lead to misrepresentations of this knowledge. Additionally, this research suggests that abundance predictions from random forest modeling, especially when validated with Indigenous Knowledge, offer a promising path forward for improving access to country foods. | |
| dc.description.scholarlevel | Graduate | |
| dc.identifier.uri | https://hdl.handle.net/1828/22657 | |
| dc.language | English | eng |
| dc.language.iso | en | |
| dc.rights | Available to the World Wide Web | |
| dc.subject | Random forest | |
| dc.subject | Species distribution modelling | |
| dc.subject | Gwich’in | |
| dc.subject | Indigneous Knowledge | |
| dc.subject | Country food | |
| dc.subject | Maxent | |
| dc.subject | Vaccinium vitis-idaea | |
| dc.subject | Food security | |
| dc.title | Exploring species distribution modelling as a tool to support knowledge of country food access & availability: vaccinium vitis-idaea in the Gwich’in Settlement Area | |
| dc.type | Thesis |