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Record W2238367711 · doi:10.1139/cjfr-2015-0377

Macroanatomy and compartmentalization of recent fire scars in three North American conifers

2016· article· en· W2238367711 on OpenAlexaffvenue
Kevin T. Smith, Estelle Arbellay, Donald A. Falk, Elaine Kennedy Sutherland

Bibliographic record

VenueCanadian Journal of Forest Research · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of British Columbia
FundersRocky Mountain Research StationNorthern Research StationU.S. Forest Service
KeywordsCambiumLarchScarsPinus <genus>Vascular cambiumBiologyBotanyMedicineXylemSurgery

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.969
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.026
GPT teacher head0.285
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations45
Published2016
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Forest ResearchSame topicFire effects on ecosystemsFrench-language works237,207