MétaCan
Menu
← Back to cohort
Record W2038531732 · doi:10.1139/cjfr-2014-0322

Sugar maple (<i>Acer saccharum</i>) forests at their northern distribution limit are recurrently impacted by fire

2014· article· en· W2038531732 on OpenAlexaffvenueabout
Vanessa Pilon, Serge Payette

Bibliographic record

VenueCanadian Journal of Forest Research · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversité LavalCenter for Northern Studies
Fundersnot available
KeywordsMapleAceraceaeTemperate forestTemperate rainforestEcologyYellow birchSugarTemperate climateForestryEnvironmental scienceGeographyEcosystemBiology

Abstract

fetched live from OpenAlex

The sugar maple (Acer saccharum Marsh.) forest is a widespread temperate forest prevailing south of 48°N in Quebec. Windthrows are the principal disturbance maintaining the old-growth status of the forest supposedly since its postglacial establishment. Nonetheless, the presence of wood charcoal buried in several sugar maple forest soils attests to the occurrence of fire during the Holocene. In this study, we aimed to elucidate the long-term fire dynamics and species composition of three sites (Témiscamingue, Saguenay, and Gaspé peninsula) currently dominated by sugar maple situated at its northern range limit. The botanical identification and 14C dating of charcoal fragments extracted from the soil surface and the mineral soil indicate that the development of the sugar maple sites was influenced by recurrent fires at least over the last 1000 to 3500 years. Two of the studied sugar maple stands are of recent origin, with the Témiscamingue forest being established after the most recent fire in the late 18th to early 19th centuries. Our data highlight the resilience of sugar maple forests in a disturbance regime dominated by frequent fires and suggest that the northernmost sugar maple forests are young ecosystems at the Holocene timescale.

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 score0.618
Threshold uncertainty score0.759

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.249
Teacher spread0.232 · 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

Citations19
Published2014
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Forest Research→Same topicFire effects on ecosystems→French-language works237,207→