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Record W3020834941 · doi:10.1139/x05-281

Fire and the origin of Table Mountain pine pitch pine communities in the southern Appalachian Mountains, USA

2006· article· en· W3020834941 on OpenAlexvenueno aff
Patrick H. Brose, Thomas A. Waldrop

Bibliographic record

VenueCanadian Journal of Forest Research · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsCanopyPine barrensDisturbance (geology)Regeneration (biology)Fire regimeTable (database)Pinus <genus>Fire ecologyEcologyPrescribed burnGeographyEnvironmental scienceForestryCoastal plainWoody plantEcosystemBiologyBotany

Abstract

fetched live from OpenAlex

The prevalence of stand-replacing fire in the formation of Table Mountain pine – pitch pine (Pinus pungens Lamb. and Pinus rigida Mill., respectively) communities was investigated with dendrochronological techniques. Nine stands in Georgia, South Carolina, and Tennessee were analyzed for age structure, species recruitment trends, and radial growth patterns to determine whether they had originated as a result of stand-replacing fires. The oldest pines date from the late 1700s or early 1800s. Continuous or frequent episodic pine regeneration from those times to the early to mid 1900s was evident at all sites. During the first half of the 20th century, all sites experienced large surges in pine regeneration. However, no clear evidence of stand-replacing wildfires could be definitively linked to these surges. Rather, the regeneration appeared to have been caused by noncatastrophic surface fires and canopy disturbances occurring together or by the cessation of a frequent fire regime. For the past 25–50 years, there has been little pine regeneration at any of the sites. Restoring the dual disturbance regime of periodic fires and canopy disturbances should help sustain Table Mountain pine – pitch pine communities in southern Appalachian Mountains landscapes.

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)0.007
metaresearch head score (Gemma)0.000
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 score0.116
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.261
Teacher spread0.241 · 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

Citations61
Published2006
Admission routes1
Has abstractyes

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