Reconstructing the interactions between climate, fire, and vegetation dynamics during the Holocene, North Slave Region, Northwest Territories, Canada
Bibliographic record
Abstract
Local-scale fire regimes are controlled by climate, fuel availability, and topography. Research on long-term (i.e., Holocene timescales) fire activity in the Northwest Territories has focused on local fire dynamics, with fewer studies examining regional patterns. To investigate the impacts of climate variability on wildfire activity during the Holocene, 13 macroscopic charcoal and 3 pollen records, as well as insolation values, reconstructed temperatures, and precipitation data were analyzed to understand the interactions of climate, regional fire regimes and vegetation during the Holocene in the North Slave Region, Northwest Territories, Canada. Following deglaciation , wildfire activity across the region was low, due to lack of fuels, relatively low temperatures, and dry conditions. By ∼8200 cal yrs. BP, wildfire activity increased across the region as Picea expanded on the landscape increasing fuel availability and summer temperatures increased and peaked during the Holocene Thermal Maximum . Wildfire activity continued to increase throughout the mid-Holocene until cooler and wetter conditions developed with the onset of Neoglacial cooling around 4200 cal yrs. BP. With the onset of cooler and wetter conditions, wildfires declined regionally across the North Slave Region. The decline in wildfire activity following Neoglacial cooling can be attributed to a general decline in temperatures and changes in vegetations types and density. During the 20th century, wildfire activity increased in response to warming temperatures. With further increases in global mean temperature, it is expected that wildfire activity in the North Slave Region will increase during the 21st century.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".