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Record W2185990921 · doi:10.1139/cjb-2015-0181

Effects of winter warming on cold hardiness and spring budbreak of four boreal conifers

2015· article· en· W2185990921 on OpenAlexafffundvenue
Rongzhou Man, Steve Colombo, Pengxin Lu, Qing‐Lai Dang

Bibliographic record

VenueBotany · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsLakehead UniversityOntario Forest Research InstituteMinistry of Natural Resources and Forestry
FundersNatural Resources CanadaOntario Ministry of Natural Resources and ForestryMinistry of Natural Resources
KeywordsPinus contortaBlack spruceHardiness (plants)Frost (temperature)BiologyDormancyTaigaJack pinePhenologyBotanyBorealGrowing seasonHorticultureSeedlingGerminationEcologyPinus <genus>Cultivar

Abstract

fetched live from OpenAlex

Compared with the effects of spring frosts on opening buds or newly flushed tissues, winter freezing damage to conifers, owing to temperature fluctuations prior to budbreak, is rare and less known. In this study, changes in cold hardiness (measured based on electrolyte leakage and needle damage) and spring budbreak were assessed to examine the responses of four boreal conifer species — black spruce (Picea mariana (Mill.) B.S.P.), white spruce (Picea glauca) (Moench) Voss), jack pine (Pinus banksiana Lamb.), and lodgepole pine (Pinus contorta Dougl. ex. Loud.) — to different durations of experimental warming (16 °C day to –2 °C night with a 10 h photoperiod, except for night temperatures during November warming (+2 °C)). Seedlings showed increased responses to warming from November to March, while the capacity to regain the cold hardiness lost to warming decreased during the same period. This suggests an increasing vulnerability of conifers to temperature fluctuations and freezing damage with the progress of chilling and dormancy release from fall to spring. Both lodgepole pine and jack pine initiated spring growth earlier and had greater responses to experimental warming in bud phenology than black spruce and white spruce, suggesting a greater potential risk of frost/freezing damage to pine trees in the spring.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.008
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.227
Teacher spread0.207 · 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

Citations20
Published2015
Admission routes3
Has abstractyes

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