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Record W4241287743 · doi:10.24124/2019/59017

Growth release and carbon storage of residual live trees in a mountain pine beetle (MPB) attacked lodgepole pine stand in northern British Columbia

2019· dissertation· en· W4241287743 on OpenAlexafffundabout
Jesse McEwen

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Northern British Columbia
KeywordsCanopyPinus contortaResidualEnvironmental scienceEddy covarianceCarbon sinkForestryMountain pine beetleNutrientHorticultureBotanyEcosystemEcologyBiologyGeographyMathematics

Abstract

fetched live from OpenAlex

Carbon (C) storage in residual live lodgepole pine trees in northern BC at Kennedy Siding was measured 11 and 12 years after a severe mountain pine beetle (MPB) epidemic.Kennedy Siding eddy covariance (EC) measurements showed that the net ecosystem productivity (NEP) was quick to recover C sink status.In this study, measurements of heights and diameters of 160 residual live lodgepole pine trees and a subset of 60 tree cores were used to calculate residual tree stem C-storage in 2017 and 2018 (36.01 and 26.71 g C m -2 yr -1 respectively).Dendrochronology analyses indicated that residual pine trees released on average 392% in the decade following versus the decade prior to MPB-attack.Stem C-storage was strongly and positively correlated with EC-NEP measurements (R 2 =0.77) and percent downed canopy trees (R 2 =0.837), suggesting that growth release of residual trees was likely driven by improvements in resources (e.g.light, moisture, nutrient).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.361
Threshold uncertainty score0.727

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.004
GPT teacher head0.198
Teacher spread0.195 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2019
Admission routes3
Has abstractyes

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