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Record W2208223968 · doi:10.1111/nph.13782

How fresh is maple syrup? Sugar maple trees mobilize carbon stored several years previously during early springtime sap‐ascent

2015· article· en· W2208223968 on OpenAlexaff
Jan Muhr, Christian Messier, Sylvain Delagrange, Susan Trumbore, Xiaomei Xu, Henrik Hartmann

Bibliographic record

VenueNew Phytologist · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversité du Québec en OutaouaisUniversité du Québec à Montréal
Fundersnot available
KeywordsMapleSugarBotanyAceraceaeCarbon fibersHorticultureChemistryBiologyFood scienceMathematics

Abstract

fetched live from OpenAlex

While trees store substantial amounts of nonstructural carbon (NSC) for later use, storage regulation and mobilization of stored NSC in long-lived organisms like trees are still not well understood. At two different sites with sugar maple (Acer saccharum), we investigated ascending sap (sugar concentration, δ(13) C, Δ(14) C) as the mobilized component of stored stem NSC during early springtime. Using the bomb-spike radiocarbon approach we were able to estimate the average time elapsed since the mobilized carbon (C) was originally fixed from the atmosphere and to infer the turnover time of stem storage. Sites differed in concentration dynamics and overall δ(13) C, indicating different growing conditions. The absence of temporal trends for δ(13) C and Δ(14) C indicated sugar mobilization from a well-mixed pool with average Δ(14) C consistent with a mean turnover time (TT) of three to five years for this pool, with only minor differences between the sites. Sugar maple trees hence appear well buffered against single or even several years of negative plant C balance from environmental stress such as drought or repeated defoliation by insects. Manipulative investigations (e.g. starvation via girdling) combined with Δ(14) C measurements of this mobilized storage pool will provide further new insights into tree storage regulation and functioning.

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 score0.048
Threshold uncertainty score0.896

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 head0.015
GPT teacher head0.209
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

Citations74
Published2015
Admission routes1
Has abstractyes

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