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Record W4312918214 · doi:10.22230/jem.2007v8n1a359

Growing trembling aspen and white spruce intimate mixtures: Early results (13—17 years) and future projections

2007· article· en· W4312918214 on OpenAlexaff
Richard Kabzems, Amanda Linnell Nemec, Craig Farnden

Bibliographic record

VenueJournal of Ecosystems and Management · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsGovernment of British Columbia
Fundersnot available
KeywordsHectareBlack spruceTaigaBorealProductivityEnvironmental scienceForestrySilvicultureRange (aeronautics)HorticultureAgronomyMathematicsGeographyAgroforestryBiologyEcologyEngineering

Abstract

fetched live from OpenAlex

Controlled mixtures of trembling aspen (Populus tremuloides Michx.) and white spruce (Picea glauca [Moench] Voss) were established in 1989 at two locations in the Boreal White and Black Spruce (BWBS) biogeoclimatic zone in northeastern British Columbia. The initial study design of three aspen treatment densities of 0, 5000, and 10000 stems per hectare was expanded by reducing existing densities of aspen on a subset of plots to 1000 and 2000 stems per hectare. A random-coefficients regression model was used to analyze height and diameter growth trends for aspen and spruce 13–17 years after establishment. White spruce grown without aspen had significantly greater rates of height and diameter growth. There were no significant differences in spruce growth between the 5000 and 10000 aspen stems per hectare treatments. Differences in spruce height and diameter growth did not consistently display a pattern of declining growth as aspen density increased from 1000 to 10000 stems per hectare. Aspen responded to aspen density reduction by increased diameter growth of the remaining stems.The Mixedwood Growth Model was used to predict future growth of the experimental stands. Yield projections indicated that a total productivity gain of 21% may be achieved for mixtures compared to a pure spruce scenario. Over the range of conditions studied, spruce comprised approximately 40% of the total volume in mixed stands. These initial results will improve the assessments of the relative contributions that pure- and mixed-species management regimes may offer to achieving forest-level objectives.

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 score0.224
Threshold uncertainty score0.471

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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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