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Record W1896772981 · doi:10.22230/jem.2015v15n1a580

Impacts and Susceptibility of Young Pine Stands to the Mountain Pine Beetle, Dendroctonus Ponderosae in British Columbia

2015· article· en· W1896772981 on OpenAlexaboutno aff
Lorraine Maclauchlan

Bibliographic record

VenueJournal of Ecosystems and Management · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMountain pine beetleDendroctonusBark beetleBroodWoody plantForestryBorealEcologyTaigaGeographyBiologyBark (sound)

Abstract

fetched live from OpenAlex

The impact of mountain pine beetle, Dendroctonus ponderosae Hopkins (Coleoptera: Scolytinae), is the most significant source of mortality of mature pine forests in western North America; however, in 2003-2004, high levels of mortality were observed in young pine stands in central British Columbia. This study investigagtes the impact of mountain pine beetle in these young pine stands. In 2005 and 2006, 24 plots were established throughout the mountain pine beetle-affected area of British Columbia. Cumulative mortality reached 83% in some plots. Secondary bark beetles and other pests contributed to overall stand mortality and decline but to a far lesser degree than mountain pine beetle. Stem deterioration and falldown was very rapid and severe in young stands following attack. Over 70% of attacked trees in the Sub-Boreal Spruce ecosystem were severely deteriorated, or had fallen less than 5 years after attack. The largest pines in young stands were attacked first, and brood production and emergence in these trees was more successful than in smaller, younger cohorts. Many attached stands had received silvicultural treatments. Once the outbreak in adjacent mature stands had subsided, very little new attack occurred in these young stands. Brood production was successful, albeit lower in young trees than in mature trees.

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 score0.726
Threshold uncertainty score0.989

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 studies0.0000.000
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 head0.221
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 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

Citations7
Published2015
Admission routes1
Has abstractyes

Explore more

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