The interaction of fire, climate and vegetation in the boreal forest of Alaska-Yukon during the Holocene
Bibliographic record
Abstract
Using radiocarbon-dated sedimentary records with the temporal focus on two key vegetative transitions (deciduous-Picea and Picea-Pinus) and a climatic transition (cold and dry to moister), high resolution time series of charcoal-peak frequencies form lake sediments are used as a proxy of the local fire regime. The regional vegetation transition from deciduous- to coniferous-dominated forest at ~10ka BP displays a clear sequence where the climate shift precedes the alteration in vegetation composition, to which the fire regime responds. The deciduous vegetation experienced low levels of burning, with a lower fire frequency than when Picea became dominant on the landscape, suggesting that Picea was excluded from the landscape due to moisture limitations rather than high fire return frequencies. In the Yukon Territory, Pinus contorta (lodgepole pine) is migrating northwards and westwards towards Alaska, and is considered a potential invasive species to the northern boreal forest of Alaska under global warming. Lodgepole pine is a fire-dependent species that appears to thrive and spread when fires are intense and frequent. Analysis of stomata reveals lodgepole pine was present in the Southern Yukon forests, at least in low numbers, by ~6 ka BP, much earlier than conventional pollen records suggest. The main population expansion (represented by increased Pinus pollen from <5 to >15%) was regionally asynchronous, and occurred over 3 ka after the first appearance of Pinus. Contrary to expectations derived from flammability estimates and modern observations that pine stands burn particularly frequently, there is no clear, sustained increase in charcoal peak frequency in the late-Holocene Pinus zone; Pinus-Picea forests appear to have burned under a regime similar to that of the preceding Picea-dominated forests.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".