Tundra fire and vegetation change along a hillslope on the Seward Peninsula
Bibliographic record
Abstract
A 1977 tundra fire burned a hillslope where prefire soils and vegetation ranged from poorly drained moist tussock-shrub tundra on the lower slopes to well-drained dwarf shrub tundra on the back slope and very poorly drained wet sedge meadow on the flat crest. We sampled the vegetation on this slope before the fire and at 8 sites following the fire at irregular intervals from 1 yr to 25 yr. During the first decade after the fire, shortterm recovery was dominated by bryophytes, sedges, and grasses from both regrowing sedge tussocks and seedlings. However, during the second and third decade, and by 24 yr after the fire, evergreen (Ledum palustre) and deciduous shrubs (mainly Salix pulchra willow) expanded dramatically so that shrub cover was generally higher than before the fire. Labrador tea has increased by vegetative means on the poorly drained lowest 3 tussock-shrub tundra sites. Upslope on the better-drained and more severely burned tussock-shrub and dwarf shrub tundra sites, willows became established from seed mainly during the first 10 yr after the fire and, based on their relatively large size (0.5–1 m tall) and cover, have grown rapidly during the past 15 to 20 yr. There has been very little or no recovery of Sphagnum moss and fruticose lichens after 24 yr at any site, except for Sphagnum moss in the wet meadow site. The permafrost active layer thickness has diminished to prefire levels at the lower slope tussock-shrub tundra sites but is much greater or degraded completely on the steeper slope, corresponding with the distribution of willow shrub colonization. These changes in tundra vegetation and permafrost following fire suggest that such fires could accelerate the predicted effects of climate warming on ecosystems in the Arctic.
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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) | 0.002 | 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".