Drying Spring Accelerates Transitions Toward Pyrogenic Vegetation in Eastern Boreal North America
Bibliographic record
Abstract
The ongoing climate change increases vegetation flammability in the boreal forests of eastern North America, leading to more intense and severe wildfires. Using palaeoecological data-including charcoal, pollen, chironomids and testate amoebae-and climate model simulations of vapour pressure deficit (VPD) and available soil water (ASW), we analysed fire dynamics over the past 8000 years in boreal eastern North America. Over the last 4000 years, and particularly in the last 250 years, increasing spring drought has led to fewer, but more severe fires. This shift in the fire regime has favoured the spread of fire-adapted conifer species, particularly jack pine (Pinus banksiana), across the landscape. We infer that the predicted increase in VPD and decrease in ASW triggered by climate change will alter the fire regime and amplify the transition toward more pyrogenic vegetation within the boreal forest of eastern North America, with ecological and socio-economic consequences.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".