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Record W2046135260 · doi:10.1071/wf10010

Tree mortality and snag dynamics in North American boreal tree species after a wildfire: a long-term study

2011· article· en· W2046135260 on OpenAlexafffundabout
Virginie A. Angers, Sylvie Gauthier, Pierre Drapeau, Karelle Jayen, Yves Bergeron

Bibliographic record

VenueInternational Journal of Wildland Fire · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsNatural Resources CanadaUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec à Montréal
FundersCanadian Forest ServiceNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsSnagTaigaBasal areaEcologyDeciduousBorealForestryGeographyBlack spruceForest dynamicsLoggingBiologyHabitat

Abstract

fetched live from OpenAlex

Temporal patterns of tree mortality and snag dynamics after fire were investigated over 10 years in a permanent plot design established immediately after a wildfire in an eastern boreal forest landscape of north-western Quebec, Canada. Post-fire tree mortality, snag persistence, tree fall patterns and variables influencing snag dynamics were assessed in deciduous, mixed and coniferous stands that experienced low- and moderate-severity fires. Temporal patterns of tree mortality for the three species revealed that mortality was delayed through time. Most post-fire tree mortality occurred within 2 years following fire but continued until the end of the 10-year observation period. Jack pine was the most persistent snag species, followed by trembling aspen and black spruce. Factors influencing the persistence of snags were multi-scaled and generally species-specific. Fire severity was the only common factor influencing snag persistence among all species, with snags located in severely-burned stands being less susceptible to falling. Trembling aspen snag persistence increased with basal area and diameter. Salvage logging in the vicinity affected black spruce. Fall patterns also differed among species. Bypasses of the snag stage (i.e. when a living tree falls directly to the forest floor) as well as uprooting of snags were common.

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 score0.202
Threshold uncertainty score0.808

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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

Citations61
Published2011
Admission routes3
Has abstractyes

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