Fire history in high elevation subalpine forests in the Colorado Front Range
Bibliographic record
Abstract
Resource managers rely on knowledge of fire history to guide management decisions, but for the subalpine zone of the Colorado Front Range little information exists on fire history documenting changes in fire regimes over the past several centuries. We examined fire history at 13 high elevation sites in the Colorado Front Range to detect long-term trends that may be related to changes in land use and/or to climatic variability. There is a high degree of spatial and temporal variation in fire regimes across sites; however, most sites exhibit an increase in fire frequency during the 20th century compared to the 19th century. We did not find any evidence that fire suppression after the creation of National Forests and Rocky Mountain National Park in the early 1900s decreased fire frequency at the highest elevations of forest cover in the Front Range. Human influences over the last 200 years have played less of a role in these high elevation subalpine forests than in the lower elevation forests of the Colorado Front Range. In the absence of effective fire exclusion in these high elevation forests, there is no basis for assuming that forest structure and fuel conditions are outside of the historic range of variability for this habitat. Fire occurrence in these high elevation sites is highly dependent on drought, which often results from La Niña events. In comparison with lower elevation ponderosa pine forests of the Front Range, fire is less dependent on increased fuel production following wet El Niño events.
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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 | 0.001 |
| 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) | 0.001 | 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".