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Record W2789667261 · doi:10.1111/nph.14987

Living on next to nothing: tree seedlings can survive weeks with very low carbohydrate concentrations

2018· article· en· W2789667261 on OpenAlexaff
Raphael Weber, Andrea Schwendener, Sandra Schmid, Savoyane Lambert, Erin Wiley, Simon M. Landhäusser, Henrik Hartmann, Günter Hoch

Bibliographic record

VenueNew Phytologist · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of Alberta
FundersNational Science CouncilSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungUniversität Basel
KeywordsSeedlingEvergreenStarchFructoseDarknessSugarSucroseBiologyDeciduousBotanyCarbohydrateDry matterHorticultureFood scienceBiochemistry

Abstract

fetched live from OpenAlex

The usage of nonstructural carbohydrates (NSCs) to indicate carbon (C) limitation in trees requires knowledge of the minimum tissue NSC concentrations at lethal C starvation, and the NSC dynamics during and after severe C limitation. We completely darkened and subsequently released seedlings of two deciduous and two evergreen temperate tree species for varying periods. NSCs were measured in all major organs, allowing assessment of whole-seedling NSC balances. NSCs decreased fast in darkness, but seedlings survived species-specific whole-seedling starch concentrations as low as 0.4-0.8% per dry matter (DM), and sugar (sucrose, glucose and fructose) concentrations as low as 0.5-2.0% DM. After re-illumination, the refilling of NSC pools began within 3 wk, while the resumption of growth was delayed or restricted. All seedlings had died after 12 wk of darkness, and starch and sugar concentrations in most tissues were lower than 1% DM. We conclude that under the applied conditions, tree seedlings can survive several weeks with very low NSC reserves probably also using alternative C sources like lipids, proteins or hemicelluloses; lethal C starvation cannot be assumed, if NSC concentrations are higher than the minimum concentrations found in surviving seedlings; and NSC reformation after re-illumination occurs preferentially over growth.

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 score0.059
Threshold uncertainty score0.993

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 head0.013
GPT teacher head0.216
Teacher spread0.203 · 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

Citations96
Published2018
Admission routes1
Has abstractyes

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