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Record W1985468023 · doi:10.1155/2011/108529

Silvicultural Attempts to Induce Browse Resistance in Conifer Seedlings

2011· article· en· W1985468023 on OpenAlexaff
Bruce A. Kimball, Fred Pfund, Mark F. Gourley, Doreen L. Griffin, John H. Russell

Bibliographic record

VenueInternational Journal of Forestry Research · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsGovernment of British Columbia
Fundersnot available
KeywordsThujaSeedlingResistance (ecology)FertilizerHuman fertilizationAmendmentHerbivoreSulfurBiologyBotanyAgronomyHorticultureChemistry

Abstract

fetched live from OpenAlex

A multiyear study was conducted to determine if soil amendment combined with topical application of elemental sulfur could be employed to reduce deer browse damage to four conifer species. Fertilizer and sulfur were applied to conifer seedlings at seven sites near Corvallis, OR. Growth and browse damage data were collected for all seedlings over a period of 17 months. Additionally, foliar concentrations of monoterpenes and simple carbohydrates were assessed in western redcedar ( Thuja plicata ) seedlings over a period of three years. Fertilization and sulfur treatments had a moderate impact on growth and no influence on browse damage or the chemical responses. Over the course of the study, browse damage diminished while foliar monoterpene concentrations increased in redcedar. It appears that silvicultural manipulation via sulfur application and/or soil amendment cannot accelerate or alter the ontogenetical changes that may naturally defend seedlings against mammalian herbivores. In a brief trial with captive deer, redcedar browse resistance was influenced by seedling maturation, but not monoterpene content. Other maturation effects may yield significant browse protection to young seedlings.

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)0.001
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 score0.022
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.080
GPT teacher head0.364
Teacher spread0.284 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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