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Record W4220716715 · doi:10.3390/f13040533

Emulating Succession of Boreal Mixedwood Forests in Alberta Using Understory Protection Harvesting

2022· article· en· W4220716715 on OpenAlexaffabout
Ivan Bjelanovic, Philip G. Comeau, Sharon Meredith, Brian E. Roth

Bibliographic record

VenueForests · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsWest Fraser (Canada)University of Alberta
Fundersnot available
KeywordsUnderstoryForestryBorealTaigaWindthrowEcological successionDiameter at breast heightEnvironmental scienceClearcuttingCanopyBlack spruceAgronomyBiologyBotanyGeographyEcology

Abstract

fetched live from OpenAlex

Understory protection harvesting is a form of partial cutting that can be used in aspen (Populus tremuloides Michx.)-dominated stands that have understories of white spruce (Picea glauca (Moench) Voss). This practice involves removing 75% to 85% of the merchantable aspen while minimizing damage to the advance spruce regeneration, in addition to leaving 15% to 25% of the aspen standing to reduce potential windthrow of the spruce understory. In this paper, we summarize results from 18 stands measured 10 to 12 years after understory protection harvest. Diameter growth of spruce increased during the first five years after harvest while height growth increased during the second five-year period (5 to 10 or 7 to 12 years after release). Consistent with other studies, mortality rates of aspen trees ≥7.1 cm DBH (diameter breast height, 1.3 m) averaged 45.0% over the 10–12 year period following harvesting. Spruce mortality averaged 27.5% over the same 10–12 year period. Substantial aspen regeneration was evident across most harvested blocks, with aspen sapling densities 10–12 years from harvest being higher in removal (14,637 stems⋅ha−1) than in buffer areas (6686 stems⋅ha−1) and in extraction trails (7654 stems⋅ha−1). Spruce sapling (>1.3 m height and <4 cm DBH) densities averaged 1140 stems⋅ha−1 in removal areas at ages 10–12, with these trees likely being present as seedlings at the time of harvest. Mixedwood Growth Model projections indicate merchantable volumes averaging 168 m3⋅ha−1 (conifer) and 106 m3⋅ha−1 (deciduous) 70 years from harvest, resulting in MAI (mean annual increment) for this period averaging 2.0 m3⋅ha−1⋅y−1 with MAI for a full 150-year rotation of approximately 2.5 m3⋅ha−1⋅y−1.

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 score0.278
Threshold uncertainty score0.909

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 head0.019
GPT teacher head0.239
Teacher spread0.220 · 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

Citations4
Published2022
Admission routes2
Has abstractyes

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