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Record W7161768820 · doi:10.82308/21439

The effects of alternative harvesting practices on saproxylic beetles in eastern mixedwood boreal forest of Quebec /

2006· dissertation· en· W7161768820 on OpenAlexaboutno aff
Annie. Webb

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiodiversitySpecies richnessSilvicultureEcological successionTaigaBorealClearcuttingForest managementNatural forest

Abstract

fetched live from OpenAlex

I examined saproxylic beetle responses in two silvicultural systems of the eastern mixedwood boreal forest of Quebec. I first investigated habitat-use and aspen-host use of saproxylic and bark and wood-boring beetles in remnant forest patches (cut-bock separators and small patches) left after harvest, theorized to resemble natural post-fire residual trees and snags. A second study focused on effects of partial cutting, a method that may serve to imitate natural succession dynamics. Remnant forest patches had the highest saproxylic and bark and woodboring beetle species richness and relative abundance. Although non-significant, higher larval densities were also collected from remnant forest patches. In the second study, partial cut patches had an intermediate saproxylic beetle assemblage compared to uncut forest and clearcuts. This research has brought new information on the effects of alternative harvesting practices on saproxylic beetles, supporting the hypothesis that biodiversity is best preserved based on forest management that is diversified and based on natural disturbance dynamics.

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 score0.068
Threshold uncertainty score0.136

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.243
Teacher spread0.227 · 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
Published2006
Admission routes1
Has abstractyes

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