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Record W1968714595 · doi:10.1139/x05-124

Effects of post-thinning density and repeated fertilization on the growth and development of young lodgepole pine

2005· article· en· W1968714595 on OpenAlexvenueno aff
R. P. Brockley

Bibliographic record

VenueCanadian Journal of Forest Research · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
Fundersnot available
KeywordsThinningHuman fertilizationPinus contortaUnderstoryHectareAgronomyStand developmentNutrientBiologyFertilizerBotanyEnvironmental scienceHorticultureEcologyCanopy

Abstract

fetched live from OpenAlex

The effects of factorial combinations of post-thinning density and fertilization on the growth and development of young lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) were investigated in central British Columbia. The effects of density and fertilization (repeated every 5 years) on tree height were small relative to the effects on stem radial growth. Tree radial growth increased with thinning intensity, whereas per-hectare growth was greatest at the highest residual density. Fertilizer effects varied across the range of residual densities tested. Tree and stand volume gains following fertilization were less, in both relative and absolute terms, at 600 trees/ha than at 1100 or 1600 trees/ha. Vigorous response of understory vegetation to nutrient additions (and strong competition for water and nutrients) may have reduced the effectiveness of fertilization on tree growth at 600 trees/ha relative to higher stand densities. Results indicate that the combined positive effects of thinning and fertilization on the growth of young lodgepole pine will accelerate stand development, thereby shortening technical rotation length. Results also indicate that significant growth gains following fertilization of thinned lodgepole pine will partially compensate for stand volume losses due to thinning. However, fertilization may be less effective at low stand densities, where negative effects of thinning on harvest volume are greatest.

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)0.001
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 score0.109
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.247
Teacher spread0.231 · 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

Citations45
Published2005
Admission routes1
Has abstractyes

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