A hierarchical analysis of stand structure, composition, and burn patterns as indicators of stand age in an Engelmann spruce – subalpine fir forest
Bibliographic record
Abstract
We studied the relationship between observed fire effects and stand age in a recently burned subalpine Engelmann spruce ( Picea engelmannii Parry ex. Engelm.) – subalpine fir ( Abies lasiocarpa (Hook.) Nutt.) forest in New Mexico. We installed a network of variable-radius plots to assess stand structure, and cored 379 trees to measure the spatial patterns of the stand ages with respect to fire boundaries. We found that pre-fire stand age and stand mortality were not significantly related at either of two spatial scales (p ≤ 0.33 and p ≤ 0.26). We also found that stand structure and stand composition were poor indicators of stand age. The random effects terms of a linear mixed-effects model revealed substantial heterogeneity in stand structure and composition with respect to age at fine spatial scales. Discussions of the factors contributing to stand-replacing fires in subalpine Engelmann spruce – subalpine fir forests might be improved by focusing on traits that are more reliably linked to fuel characteristics, rather than on the age of the stands.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".