PDO Dynamics Shape the Fire Regime of Boreal Subarctic Landscapes in the Northwest Territories, Canada
Bibliographic record
Abstract
Abstract Spatially explicit reconstructions of fire activity in northwestern boreal Canada are rare, despite their importance for modeling current and future disturbance regimes and forest dynamics. We provide a dendrochronological reconstruction of historical fire activity along Highway 3 in the Northwest Territories (NWT), Canada, within the boreal subarctic zone. We dated 129 fires that occurred between 1202 and 2015 CE, using samples from 479 fire‐scarred living and dead jack pine trees ( Pinus banksiana Lamb.). Three distinct periods can be distinguished in terms of historical fire cycle (FC) and fire occurrence. Initially (1340–1440 CE), fire activity was low (FC = 572 years; 1 fire/decade), before increasing notably between 1460 and 1840 (FC = 171 years; 4.45 fires/decade), and even more in recent times (1860–2015 CE; FC = 95 years; 7.63 fires/decade). Climate has been an important factor controlling changes in fire frequency and FC in the NWT since the 1300s. The 1440s and 1850s correspond with periods of increased fire activity synchronized with shifts from negative to positive Pacific Decadal Oscillation (PDO) phases. Since the mid‐1800s, human activities may have contributed to the increase in fire activity, but climate remained the leading factor. During the 20th century, years with increased area burned corresponded to periods with drier‐than‐average conditions associated with positive PDO, suggesting fire activity in the study region is still influenced by climate. Spatial teleconnection patterns among PDO, drought, and large fire years (LFYs) in the NWT reveal persistent relationships between ocean‐atmosphere circulation patterns and fire activity. PDO dynamics hold strong potential for predicting regional fire hazards across northwestern North America.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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 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".