Impact of Climate Change on Winter Road Systems in Ontario's Far North: First Nations' and Climatological Perspectives on the Changing Viability and Longevity of Winter Roads
Bibliographic record
Abstract
Climate change is already being experienced in Ontario’s Far North with implications for First Nations communities that are reliant on winter road systems. The first study of this thesis examined how winter road seasons have been affected historically by particular climate conditions by focusing on the timing of opening dates of the James Bay Winter Road (JBWR). This study established a minimum threshold of 380 freezing degree-days (FDDs) below 0°C, a threshold subsequently used to assess the impacts of climate change on winter road systems in the future using climate change projections. The second study explored the current vulnerability of the Fort Albany First Nation community regarding physical, social/cultural, economic impacts associated with changing winter roads and its seasons, as well as river ice regimes. Through the analysis of key informant interviews and winter road user surveys on the changes in winter roads and river ice regimes, the six major themes were identified. As a result, the JBWR has now become a critical seasonal lifeline for not only providing a relatively inexpensive land transport of essential goods and supplies, but also reconnecting coastal remote communities by physical, social, and cultural activities during winter. The third study focused on the viability and longevity of winter road systems in Ontario’s Far North for the next century using recent climate model projections using three Representative Concentration Pathway (RCP) scenarios. Using FDD threshold established in the first study as the main metric, climate conditions are expected to remain favourable in Big Trout Lake and Lansdowne House during winter road construction through the end of 2100. However, climate conditions would possibly be unfavourable for winter road construction at Moosonee, Kapuskasing, and Red Lake by 2041−2070. These studies demonstrate that there is an immediate need to develop adaptation strategies in response to impacts of climate change on winter roads in Ontario’s Far North.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".