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Record W2017191846 · doi:10.1139/x07-079

A stand-replacing fire history in upper montane forests of the southern Rocky Mountains

2007· article· en· W2017191846 on OpenAlexvenueno aff
Ellis Q. Margolis, Thomas W. Swetnam, Craig D. Allen

Bibliographic record

VenueCanadian Journal of Forest Research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersSandia National Laboratories
KeywordsDendrochronologyFire historyElevation (ballistics)LoggingForestryGeographyPhysical geographyEcosystemFire ecologySalvage loggingFire regimeMontane ecologyEcologyForest ecologyArchaeologyClimate change

Abstract

fetched live from OpenAlex

Dendroecological techniques were applied to reconstruct stand-replacing fire history in upper montane forests in northern New Mexico and southern Colorado. Fourteen stand-replacing fires were dated to 8 unique fire years (1842–1901) using four lines of evidence at each of 12 sites within the upper Rio Grande Basin. The four lines of evidence were (i) quaking aspen ( Populus tremuloides Michx.) inner-ring dates, (ii) fire-killed conifer bark-ring dates, (iii) tree-ring width changes or other morphological indicators of injury, and (iv) fire scars. The annual precision of dating allowed the identification of synchronous stand-replacing fire years among the sites, and co-occurrence with regional surface fire events previously reconstructed from a network of fire scar collections in lower elevation pine forests across the southwestern United States. Nearly all of the synchronous stand-replacing and surface fire years coincided with severe droughts, because climate variability created regional conditions where stand-replacing fires and surface fires burned across ecosystems. Reconstructed stand-replacing fires that predate substantial Anglo-American settlement in this region provide direct evidence that stand-replacing fires were a feature of high-elevation forests before extensive and intensive land-use practices (e.g., logging, railroad, and mining) began in the late 19th century.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.726
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.259
Teacher spread0.238 · 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 teacher head, 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

Citations93
Published2007
Admission routes1
Has abstractyes

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