Uncovering millennia of wildfire occurrence during the Holocene at local and regional scales in the Northwest Territories, Canada
Bibliographic record
Abstract
Northern ecosystems are experiencing disproportionate impacts of climate change compared to the rest of the globe, primarily due to Arctic amplification. Ongoing climate change is projected to lead to increases in the frequency and severity of wildfires in the boreal forest. Records of past wildfires in the Northwest Territories, Canada, are spatially limited and temporally short, making it difficult to assess the impacts of wildfires on a long-term basis. Using paleolimnological techniques, including the analysis of macroscopic charcoal, pollen, temperature reconstructions and solar insolation values, local and regional scale wildfire and vegetation histories were constructed for the Northwest Territories. For the local scale study, the charcoal record produced from lake 18-YK-16 (unofficial name) recorded 36 wildfire events during the past ~9,500 years before present (BP), and from lake 18-YK-20 (unofficial name), 62 wildfire events were recorded during the past ~10,300 years BP. For both lakes, wildfire events increased in frequency ~8,000 and ~5,500 years BP, corresponding to the presence of spruce (Picea spp.) and increasing temperatures. Additionally, for 18-YK-16, a third peak in wildfire activity coincided with the Medieval Climate Anomaly 800-1200 CE. Fire occurrence declined during the middle to late Holocene (~5,500-600 years BP) which is a period of climatic cooling. For the regional scale study, wildfire activity was limited during the Late Pleistocene to early Holocene, due to receding glaciers and a lack of vegetation on the landscape. Between ~7,000 years BP and ~5,500 years BP, wildfire activity in the North Slave Region was frequent due to the expansion of fire-prone Picea and higher temperatures. Regional wildfire activity declined throughout the Neoglacial period (~4,500 years BP); however, local-scale wildfires were occurring which can be attributed to the expansion of Pinus ~4,500 years BP in addition to local scale bottom-up and top-down controls. Wildfire activity remained low up until the late 20th century, which can be correlated to increasing temperatures and anthropogenic activities. Long term implications of wildfire activity suggest that with continued warming of the climate, wildfire frequency and severity will increase.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".