Macroanatomy and compartmentalization of recent fire scars in three North American conifers
Bibliographic record
Abstract
Fire scars are initiated by cambial necrosis caused by localized lethal heating of the tree stem. Scars develop as part of the linked survival processes of compartmentalization and wound closure. The position of scars within dated tree ring series is the basis for dendrochronological reconstruction of fire history. Macroanatomical features were described for western larch (Larix occidentalis Nutt.), ponderosa pine (Pinus ponderosa Douglas ex P. Lawson & C. Lawson), and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) injured by fire in 2003 and harvested in 2011 at the Lolo National Forest near Missoula, Montana, USA. Bark scorch did not necessarily indicate the formation of a scar. Wound-initiated discoloration inward from the scar face was bounded tangentially by reaction zones. In western larch, the transition between earlywood and latewood was much less abrupt in woundwood rings than in rings formed the same year but not associated with a scar. Wood formed the year after injury contained tangential rows of resin ducts in the earlywood. Compartmentalization plays a key role in resisting the spread of infection and the loss of healthy sapwood and heartwood. Wound closure restores some degree of circumferential continuity of the vascular cambium and reinforces stem structure. The terminology presented here should facilitate communication among tree pathologists, wound anatomists, and dendrochronologists.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".