Data from: Arctic and boreal paleofire records reveal drivers of fire activity and departures from Holocene variability
Bibliographic record
Abstract
Boreal forest and tundra biomes are key components of the Earth system because the mobilization of large carbon stocks and changes in energy balance could act as positive feedbacks to ongoing climate change. In Alaska, wildfire is a primary driver of ecosystem structure and function, and a key mechanism coupling high-latitude ecosystems to global climate. Paleoecological records reveal sensitivity of fire regimes to climatic and vegetation change over centennial-millennial time scales, highlighting increased burning concurrent with warming or elevated landscape flammability. To quantify spatiotemporal patterns in fire-regime variability, we synthesized 27 published sediment-charcoal records from four Alaskan ecoregions, and compared patterns to paleoclimate and paleovegetation records. Biomass burning and fire frequency increased significantly in boreal forest ecoregions with the expansion of black spruce, ca. 6-4 thousand years before present (yr BP). Biomass burning also increased during warm periods, particularly in the Yukon Flats ecoregion from ca. 1000-500 yr BP. Increases in biomass burning concurrent with constant fire return intervals suggest increases in average fire severity (i.e., more biomass burning per fire) during warm periods. Results also indicate increases in biomass burning over the last century across much of Alaska that exceed Holocene maxima, providing important context for ongoing change. Our analysis documents the sensitivity of fire activity to broad-scale environmental change, including climate warming and biome-scale shifts in vegetation. The lack of widespread, prolonged fire synchrony suggests regional heterogeneity limited simultaneous fire-regime change across our study areas during the Holocene. This finding implies broad-scale resilience of the boreal forest to extensive fire activity, but does not preclude novel responses to 21-century changes. If projected increases in fire activity over the 21st century are realized, they would be unprecedented in the context of the last 8,000 years or more.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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 | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".