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Record W1965426785 · doi:10.1139/x02-104

How long do trees take to reach breast height after fire in northeastern Ontario?

2002· article· en· W1965426785 on OpenAlexvenueaboutno aff
S. A. Vasiliauskas, Han Y. H. Chen

Bibliographic record

VenueCanadian Journal of Forest Research · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsDiameter at breast heightBlack spruceForestryMarshJack pineGeographyEnvironmental sciencePinus <genus>TaigaBiologyEcologyBotanyWetland

Abstract

fetched live from OpenAlex

Accurate determination of stand establishment ages is important in developing growth and yield models and in studying stand dynamics of fire-origin stands. The study objective was to determine time to reach breast height for black spruce (Picea mariana (Mill.) BSP), jack pine (Pinus banksiana Lamb.), trembling aspen (Populus tremuloides Michx.), and white birch (Betula papyrifera Marsh.) from fire origin stands under different site conditions in northeastern Ontario. Stands were randomly selected from burns with known fire dates. In each stand, three to six dominant and codominant trees of a selected species were cored at breast height (1.3 m above the ground level) to determine time to reach breast height. Trembling aspen and white birch did not differ for time to reach breast height after fire, taking 6 or 7 years, jack pine took marginally longer (8 years), whereas black spruce took the longest (18 years). While time to reach breast height did not vary among site conditions as described by soil texture and moisture regime, it was positively related to time since fire. The results of this study indicate that stand establishment dates and total tree ages can be substantially underestimated if breast height age is used as the stand age, resulting in misinterpretations of growth and yield and forest succession.

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)0.001
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 score0.060
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.021
GPT teacher head0.232
Teacher spread0.211 · 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

Citations60
Published2002
Admission routes2
Has abstractyes

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