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Record W2912030839 · doi:10.1093/treephys/tpy151

Contrasting strategies of xylem formation between black spruce and balsam fir in Quebec, Canada

2018· article· en· W2912030839 on OpenAlexafffundabout
Lei Chen, Sergio Rossi, Annie Deslauriers, Jianquan Liu

Bibliographic record

VenueTree Physiology · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsBalsamAbies balsameaXylemBlack spruceBiologyBotanyTaigaEcology

Abstract

fetched live from OpenAlex

Present-day global warming is occurring faster at higher elevations. Although there is much information regarding the divergent responses of tree growth to climate change, the altitudinal patterns of species-specific xylogenesis remains poorly understood. We investigated the xylogenesis of balsam fir (Abies balsamea Mill.) and black spruce (Picea mariana Mill. B.S.P.) at two elevations in Quebec (Canada). The number of enlarging and mature cells of the developing tree ring were counted on microcores collected weekly between 2011 and 2014. At the lower site, the growth pattern and duration of xylogenesis were similar between species. No difference in responses to temperature and solar radiation between species was observed. At the higher site, however, cell production was higher and lasted longer in balsam fir than black spruce. Furthermore, the xylem growth of balsam fir had a stronger response to temperature and solar radiation than black spruce. These findings demonstrate the contrasting strategies of wood formation of the two species, with black spruce being more conservative than balsam fir. Our study provides evidence that sympatric species can have species-specific growth dynamics and site-specific responses to the local environment. Predictions of tree growth under a changing environment require the incorporation of species-specific growth strategies.

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 score0.140
Threshold uncertainty score0.288

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 head0.019
GPT teacher head0.234
Teacher spread0.216 · 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
Published2018
Admission routes3
Has abstractyes

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