Temperature-controlled tundra fire severity and frequency during the last millennium in the Yukon-Kuskokwim Delta, Alaska
Bibliographic record
Abstract
Wildfire is an important disturbance to Arctic tundra ecosystems. In the coming decades, tundra fire frequency, intensity, and extent are projected to increase because of anthropogenic climate change. To more accurately predict the effects of climate change on tundra fire regimes, it is critical to have detailed knowledge of the natural frequency and extent of past wildfires and how they responded to past climate variability. We present analyses of fire frequency and temperature from a lake sediment core from the Yukon-Kuskokwim (YK) Delta. Our ca. 1000 macroscopic charcoal record shows more frequent but possibly less severe tundra fires during the first half of the last millennium, whereas less frequent, possibly more severe fires characterize the latter half. Our temperature reconstruction, based on distributional changes of branched glycerol dialkyl glycerol tetraethers (brGDGTs), shows slightly warmer conditions from ca. AD 1000 to 1500, and cooler conditions thereafter (ca. AD 1500 to 2000), suggesting that fire frequency increases when climate is relatively warmer in this region. When wildfires occur more frequently, fire severity may decrease because of limited biomass (fuel source) accumulating between fires. The data suggest that tundra ecosystems are highly sensitive to climate change, and that a warmer climate, which is predicted to develop in the near future, will result in more frequent tundra wildfires.
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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 | 0.001 | 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 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".