Fire history of a central Nevada pinyon–juniper woodland
Bibliographic record
Abstract
Our study reconstructed fire history (1445–2006) from tree rings for a Great Basin single-needle pinyon pine ( Pinus monophylla Torr & Frém.) – Utah juniper ( Juniperus osteosperma (Torr.) Little) woodland. Information from multiple lines of evidence, including dateable fire scars (n = 83), tree demography, and charred coarse woody debris, was used to quantify fire frequency, severity, and extent. Fire cycle models were developed using survivorship analysis of time-since-fire estimates. We investigated the spatial and temporal variation in historical fire regime, addressing the plausibility of postsettlement fire exclusion as an explanation for increased woodland area and density since the late 1800s. Historical fire regime was characterized by infrequent, small, high-severity fires. Estimated fire cycle (1570–1880) was 427 years, with no evidence of postsettlement stand-replacing fires. Topographic analyses indicated that in this drought-prone landscape, more mesic conditions favor continuous fuels that lead to more frequent or extensive fire. Superposed epoch analysis showed increased fire occurrence during drought years but with no influence of antecedent climatic conditions. More frequent grassland and shrubland fires were recorded by fire scars near valley floors. Thus, anthropogenic fire exclusion in adjacent, shrub-dominated communities presents a plausible mechanism for woodland expansion in the study area. However, there is little ecological justification for reintroducing fire to areas of historic woodland, where effects of fire exclusion have been minimal.
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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 | 0.001 | 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) | 0.000 | 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".