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Record W2439427016 · doi:10.1126/science.aaf4951

Northeastern North America as a potential refugium for boreal forests in a warming climate

2016· article· en· W2439427016 on OpenAlexaffabout
Loïc D’Orangeville, Louis Duchesne, Daniel Houle, Daniel Kneeshaw, Benoît Côté, Neil Pederson

Bibliographic record

VenueScience · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsMcGill UniversityMinistère des Ressources naturelles et des ForêtsOuranosUniversité du Québec à Montréal
Fundersnot available
KeywordsTaigaBorealRefugium (fishkeeping)Climate changePrecipitationDendroclimatologyDendrochronologyEnvironmental scienceLatitudeGlobal warmingGeographyEcologyPhysical geographyClimatologyForestryGeologyBiology

Abstract

fetched live from OpenAlex

High precipitation in boreal northeastern North America could help forests withstand the expected temperature-driven increase in evaporative demand, but definitive evidence is lacking. Using a network of tree-ring collections from 16,450 stands across 583,000 km(2) of boreal forests in Québec, Canada, we observe a latitudinal shift in the correlation of black spruce growth with temperature and reduced precipitation, from negative south of 49°N to largely positive to the north of that latitude. Our results suggest that the positive effect of a warmer climate on growth rates and growing season length north of 49°N outweighs the potential negative effect of lower water availability. Unlike the central and western portions of the continent's boreal forest, northeastern North America may act as a climatic refugium in a warmer climate.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.812
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.251
Teacher spread0.239 · 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

Citations185
Published2016
Admission routes2
Has abstractyes

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