MétaCan
Menu
Back to cohort
Record W3182638973 · doi:10.1139/cjfr-2021-0060

Biomass procurement in boreal forests affected by spruce budworm: effects on regeneration, costs, and carbon balance

2021· article· en· W3182638973 on OpenAlexafffundvenue
Daniel Gouge, Évelyne Thiffault, Nelson Thiffault

Bibliographic record

VenueCanadian Journal of Forest Research · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversité LavalNatural Resources Canada
FundersNatural Resources Canada
KeywordsBiomass (ecology)Environmental scienceForestryForest managementSilvicultureTaigaProcurementBioenergyStockingCarbon sequestrationAgroforestryAgronomyEcologyRenewable energyBiologyGeographyCarbon dioxideBusiness

Abstract

fetched live from OpenAlex

Biomass procured from forests affected by natural disturbances as a bioenergy source is increasingly considered in the context of climate change mitigation. By comparing clearcuts with and without biomass procurement, we aimed to determine the effects of biomass extraction performed alongside lumber harvesting on regeneration density, number of planting microsites, forest renewal costs, and carbon fluxes, in harvested boreal stands affected by spruce budworm. The results showed that biomass procurement increased regeneration density and number of planting microsites. Reduction of downed woody debris due to biomass procurement lowered site preparation costs by 282.07 $CAN·ha −1 , equivalent to 14.45 $CAN per oven-dry metric ton (odmt −1 ) of harvested biomass. Product value from biomass processing had to reach from 13.90 to 76.84 $CAN·odmt −1 to make biomass procurement operations profitable. Since biomass procurement significantly increased stocking and reduced the amount of decaying debris, it also reduced cumulative CO 2 emissions relative to scenarios without biomass procurement. However, ensuring forest renewal through site preparation and plantation per se, irrespective of biomass procurement, played a more important role for carbon sequestration and net balance. Integrating biomass harvesting with silviculture could have significant ecological and financial impacts on forest management while supporting mitigation efforts against climate change.

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 score0.536
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.275
Teacher spread0.260 · 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

Citations10
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicForest Management and PolicyFrench-language works237,207