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Record W2133867103 · doi:10.1093/treephys/27.11.1635

Seasonal patterns of cytokinins and microclimate and the mediation of gas exchange among canopy layers of mature Acer saccharum trees

2007· article· en· W2133867103 on OpenAlexafffund
Ian Reeves, R. J. Neil Emery

Bibliographic record

VenueTree Physiology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCanopyMicroclimateSaccharumBotanyTree canopyBiologyEcology

Abstract

fetched live from OpenAlex

Seasonal patterns of cytokinins (CKs) and microclimate were examined in the upper, middle and lower canopy layers of mature Acer saccharum Marsh. (sugar maple) trees to elucidate the potential role of CKs in the mediation of gas exchange. The upper canopy showed a distinctly dissimilar microclimate from the middle and lower canopy layers with higher photosynthetically active radiation and wind speed, but showed no corresponding differences in transpiration (E) or stomatal conductance (g(s)). Although E and g(s) tended to be higher in the upper canopy than in the middle and lower canopies, the differences were not significant, indicating regulation beyond the passive response to changes in microclimate. The upper canopy accumulated significantly higher concentrations of CKs, predominantly as ribosides, and all canopy layers showed distinct seasonal patterns in CK profiles. Multiple regression models showed significant relationships between both g(s) and E and foliar CK concentration, although these relationships varied among canopy layers. The relationships were strongest in the middle and lower canopy layers where there was less fluctuation in leaf water status and less variability in abiotic variables. The relationships between gas exchange parameters and leaf CK concentration began to decouple near the end of the growing season as foliar phytohormone concentrations changed with the approach of dormancy.

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 score0.375
Threshold uncertainty score0.176

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 head0.005
GPT teacher head0.199
Teacher spread0.194 · 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

Citations8
Published2007
Admission routes2
Has abstractyes

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