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Fire-induced decrease in forest cover on a small rock outcrop in the Abitibi region of Québec, Canada

2003· article· en· W2543854234 on OpenAlexafffundvenueabout
Isabelle Larocque, Yves Bergeron, Ian Campbell, Richard Bradshaw

Bibliographic record

VenueEcoscience · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsCanadian Forest ServiceUniversité du Québec à Montréal
FundersCanadian Forest Service
KeywordsBlack spruceOutcropEdaphicVegetation (pathology)Fire regimeBorealTaigaPalynologyForestryEnvironmental scienceFire ecologyWoodlandEcologyGeologyGeographyEcosystemSoil waterGeomorphologyBiology

Abstract

fetched live from OpenAlex

Rocky outcrops represent about 30% of the boreal forest of Abitibi, Québec, Canada. Although these outcrops have similar edaphic and climatic conditions, their vegetation can vary. Some are composed of a closed forest of black spruce (Picea mariana) and eastern white cedar (Thuja occidentalis), while others support open Pinus-dominated stands. A long-term study using palynology and charcoal analysis was used to determine the processes involved in creating the open vegetation observed on one outcrop located at Roquemaure. Changes in the fire regime through time seem to be the explanatory factor. Vegetation on this outcrop started 3,775 calibrated years ago as a closed Picea mariana-dominated stand. Increase in fire frequency ca 1,465 calibrated years ago led to the replacement of the Picea mariana-dominated stand by the more open Pinus woodland observed today. Changes in climate from wet to dry might explain this increase in fire frequency. Dry soils and exposed bedrock created by climate change and increased fire frequency limited the regeneration of Picea mariana. For future landscape management, long-term studies should be taken into consideration to determine the natural variability of ecosystems.

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)0.001
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 score0.039
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.012
GPT teacher head0.194
Teacher spread0.182 · 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

Citations11
Published2003
Admission routes4
Has abstractyes

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