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Record W2112679593 · doi:10.2980/20-2-3588

Effects of a forest tent caterpillar outbreak on the dynamics of mixedwood boreal forests of eastern Canada

2013· article· en· W2112679593 on OpenAlexaffvenueabout
Julien Moulinier, François Lorenzetti, Yves Bergeron

Bibliographic record

VenueEcoscience · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsUniversité du Québec en OutaouaisUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec à Montréal
Fundersnot available
KeywordsForestryAbies balsameaCanopyEcological successionDominance (genetics)UnderstoryTaigaGeographyEcologyBorealBalsamBiologyForest dynamicsBotany

Abstract

fetched live from OpenAlex

Abstract: In boreal mixedwood stands dominated by trembling aspen (Populus tremuloides), forest tent caterpillar (Malacosoma disstria, FTC) outbreaks are recurrent events whose effects on stand dynamics are poorly documented. To describe and characterize the effects of FTC outbreaks, we assessed canopy opening, gap size, and understory tree recruitment in 12 stands dominated by trembling aspen that had experienced different levels of defoliation (in terms of severity and duration) during the last outbreak in northwestern Quebec (1999–2002). The study showed a significant increase in canopy opening and gap size with defoliation intensity. Furthermore, the proportion of large gaps and aspen mortality increased with defoliation intensity. Balsam fir (Abies balsamea) regeneration benefited from changes in canopy structure caused by the FTC, while aspen did not. Forest succession in mixedwood stands that had been defoliated for 1 y was not profoundly affected, while multiple years of defoliation likely caused more rapid canopy transition from aspen to fir. By creating a variety of gaps, FTC outbreaks modify stand structure in ways that differ from succession to coniferous dominance controlled by single-stem exclusion.

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)0.000
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 score0.514
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.006
GPT teacher head0.159
Teacher spread0.153 · 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

Citations23
Published2013
Admission routes3
Has abstractyes

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