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Record W4391519622 · doi:10.1080/11956860.2023.2292352

Décalage temporel dans l’établissement des érables en forêt boréale révélé par une population marginale à la limite nordique de l’érable à sucre

2024· article· fr· W4391519622 on OpenAlexafffundvenue
Laurianne Dumont, Todor S. Minchev, Pierre‐Yves Mondou Laperrière, Pierre Grondin, Guillaume de Lafontaine

Bibliographic record

VenueEcoscience · 2024
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsCenter for Northern StudiesMinistère des Ressources naturelles et des Forêts (Québec)Université du Québec à Rimouski
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPhysicsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Given their position at the limit of a species’ bioclimatic tolerance envelope, range-edge populations are particularly sensitive to variations in environmental conditions. Understanding ecological history of such peripheral populations provides key insights about ecosystem responses and resilience to global change. Here, we rely on soil macrofossil charcoal analysis to infer the origin and dynamics of a marginal sugar maple stand located within the boreal forest, at the leading edge of the species range. Radiocarbon dating of sugar maple and red maple charcoal particles indicates a late origin of the sugar maple stand at c. 600 cal yr BP, compared to red maple, which was established in the early Neoglacial period c. 4000 years ago. The earlier presence of red maple may have facilitated a later establishment of sugar maple in the boreal environment, most likely by altering edaphic conditions. The relatively recent establishment of a disjunct stand of maple at its current leading edge suggests that models predicting a northward migration of temperate species to the boreal biome in response to contemporary climate change are empirically plausible.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.013
GPT teacher head0.235
Teacher spread0.223 · 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.

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

Citations2
Published2024
Admission routes3
Has abstractyes

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