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Record W1517691976 · doi:10.1002/jqs.2685

Long-term dynamics of fire refuges in boreal mixedwood forests

2014· article· en· W1517691976 on OpenAlexaff
Samira Ouarmim, Hugo Asselin, Christelle Hély, Yves Bergeron, Adam A. Ali

Bibliographic record

VenueJournal of Quaternary Science · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsCentre de Recherche Industrielle du QuébecUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec à MontréalNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsMicrositeLarchDominance (genetics)Environmental scienceBorealEcologyTaigaForest dynamicsBiodiversityFire ecologyGeographyEcosystemBiologyAgronomy

Abstract

fetched live from OpenAlex

Burned areas in boreal mixedwood forests usually include tree patches that partially or entirely escaped fire. Some of these post-fire residual stands – called fire refuges – can escape several consecutive fires due to particular microsite conditions. Despite their potential importance as biodiversity hotspots, the long-term forest dynamics of fire refuges is unknown. High-resolution analysis of plant macroremains retrieved from forest organic matter profiles sampled in five fire refuges allowed us to describe up to 8000 years of forest dynamics. Our results display the importance of local conditions in forest dynamics. Wildfire was probably prevented by high moisture, as indicated by the presence of aquatic taxa and moisture-tolerant tree species. Lack of stand-replacing fire, coupled with organic matter accumulation, favored the millennial persistence of late-successional tree species. Shifts from spruce/larch dominance to fir/cedar dominance were noted at different occasions during the Holocene, probably resulting from endogenous processes.

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)0.002
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 score0.064
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.007
GPT teacher head0.242
Teacher spread0.235 · 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

Citations14
Published2014
Admission routes1
Has abstractyes

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