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Record W2621163041 · doi:10.1139/er-2017-0009

The boreal–temperate forest ecotone response to climate change

2017· article· en· W2621163041 on OpenAlexaffvenue
P. Evans, Carissa D. Brown

Bibliographic record

VenueEnvironmental Reviews · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsEcotoneBiomeClimate changeEcologyAbiotic componentTaigaBorealTemperate climateGlobal warmingGlobal changeTemperate forestBiotic componentEnvironmental scienceGeographyEcosystemBiologyHabitat

Abstract

fetched live from OpenAlex

A warming global climate will elicit changes in the distribution of plant species around the planet, and this will become most apparent where biomes converge. Climate exerts the strongest control over the geographic location of ecotones at the continental scale and many, including the boreal forest – temperate forest ecotone (BTE), are expected to shift to higher latitudes under climate change. Fine-scale drivers that define biome boundaries at the sub-continental scale are less well understood for many ecotones. We assembled studies addressing whether a modern distributional shift is occurring at the BTE and what biotic and abiotic factors are driving such a shift. Current research suggests a northward shift is occurring; yet, scant data are available to identify the processes involved. Abiotic and biotic factors are repeatedly identified as key drivers of change, though not all claims are evidence-supported and the interacting effects of these non-climatic factors are poorly understood.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.288
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations99
Published2017
Admission routes2
Has abstractyes

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