NOAA/WDS Paleoclimatology - Kelly fire data from Granger Lake, Yukon Flats, Alaska - IMPD USGAL008
Bibliographic record
Abstract
Wildfire activity in boreal forests is anticipated to increase dramatically, with far-reaching ecological and socioeconomic consequences. Paleorecords are indispensible for elucidating boreal fire regime dynamics under changing climate, because fire return intervals and successional cycles in these ecosystems occur over decadal to centennial timescales. We present charcoal records from 14 lakes in the Yukon Flats of interior Alaska, one of the most flammable ecoregions of the boreal forest biome, to infer causes and consequences of fire regime change over the past 10,000 y. Strong correspondence between charcoal-inferred and observational fire records shows the fidelity of sedimentary charcoal records as archives of past fire regimes. Fire frequency and area burned increased ~6,000–3,000 y ago, probably as a result of elevated landscape flammability associated with increased Picea mariana in the regional vegetation. During the Medieval Climate Anomaly (MCA; ~1,000–500 cal B.P.), the period most similar to recent decades, warm and dry climatic conditions resulted in peak biomass burning, but severe fires favored less-flammable deciduous vegetation, such that fire frequency remained relatively stationary. These results suggest that boreal forests can sustain high severity fire regimes for centuries under warm and dry conditions, with vegetation feedbacks modulating climate–fire linkages. The apparent limit to MCA burning has been surpassed by the regional fire regime of recent decades, which is characterized by exceptionally high fire frequency and biomass burning. This extreme combination suggests a transition to a unique regime of unprecedented fire activity. However, vegetation dynamics similar to feedbacks that occurred during the MCA may stabilize the fire regime, despite additional warming.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 0.001 |
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".