Climatic and human influences on fire history in Pike National Forest, central Colorado
Bibliographic record
Abstract
We investigated interannual and multidecadal variability in fire regimes, as related to climate and human land-use in Pike National Forest, central Colorado. Short and long-term trends in fire-scar records were related to tree-ring proxy records of moisture availability and to variability in El Niño Southern Oscillation (ENSO). Fire occurrence is strongly tied to interannual drought conditions and is associated with cycles of ENSO. Fire events tend to occur in years of reduced moisture availability (La Niña years) and are often preceded by 24 years of increased moisture availability (El Niño years). A period of reduced variability in the tree-ring record from 1760 to 1820 AD, roughly corresponds to a period of reduced fire occurrence from approximately 1792 to 1842. Coincident with increased fire occurrence, variability in the climate proxies was high in the middle to late 1800s until the early 1900s. Multidecadal impacts through land use are also evident in the fire record with sharp increases during Euro-American settlement in ca. 1850 and abrupt declines with the start of active fire suppression after ca. 1920. Both humans and climatic variation appear to have interacted synergistically to create long-term trends in fire occurrence over the past two centuries.
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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 | 0.001 | 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".