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Record W2095488286 · doi:10.1139/x03-117

Influences of paper birch competition on growth of understory white spruce and subalpine fir following spacing

2003· article· en· W2095488286 on OpenAlexvenueno aff
Philip G. Comeau, Jian R. Wang, Tony Letchford

Bibliographic record

VenueCanadian Journal of Forest Research · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
Fundersnot available
KeywordsUnderstoryAbies lasiocarpaBasal areaMontane ecologyBotanySubalpine forestCompetition (biology)BiologyBetulaceaeEnvironmental scienceHorticultureCanopyEcology

Abstract

fetched live from OpenAlex

Five years after spacing a young, 11 m tall paper birch (Betula papyrifera Marsh.) stand, we examine relationships between growth of understory white spruce (Picea glauca (Moench) Voss), subalpine fir (Abies lasiocarpa (Hook.) Nutt.), and level of birch retention. Our objectives were to evaluate the effectiveness of selected measures of competition for estimating the effects of the residual birch and to evaluate the influence of residual birch densities on growth responses of naturally regenerated subalpine fir and white spruce. Basal area of Scouler willow (Salix scouler iana Barratt) and birch were found to effectively predict light transmittance (diffuse noninterceptance). The best models for predicting 4-year volume growth of subalpine fir and white spruce incorporate initial crown volume of the subject trees and transmittance as independent variables. Lorimer's index and Hegyi's index gave similar results to those obtained using basal area and transmittance, suggesting that there is little benefit in including measurements of proximity in a competition index. For both species, the correlation between basal area increment and light was substantially stronger than observed for volume increment. However, height increment of both subalpine fir and spruce was only weakly correlated with measured light levels. The ratio of height increment to volume increment decreased with both increasing initial height and transmittance for subalpine fir and white spruce.

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)0.002
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 score0.115
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.024
GPT teacher head0.263
Teacher spread0.240 · 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

Citations48
Published2003
Admission routes1
Has abstractyes

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