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Record W1997742462 · doi:10.1126/science.1113977

Carbon Flux and Growth in Mature Deciduous Forest Trees Exposed to Elevated CO <sub>2</sub>

2005· article· en· W1997742462 on OpenAlexaff
Christian Körner, Roman Asshoff, Olivier Bignucolo, Stephan Hättenschwiler, Sonja G. Keel, Susanna Pelaez‐Riedl, Steeve Pépin, Rolf Siegwolf, Gerhard Zotz

Bibliographic record

VenueScience · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsUniversité LavalMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
Fundersnot available
KeywordsDeciduousCanopyCarbon dioxideBiomass (ecology)Carbon fibersEnvironmental scienceCarbon dioxide in Earth's atmospherePhotosynthesisFlux (metallurgy)Temperate climateCarbon cyclePlant litterCarbon sequestrationLitterTemperate forestBotanyHorticultureAgronomyBiologyChemistryEcologyEcosystemMathematics

Abstract

fetched live from OpenAlex

Whether rising atmospheric carbon dioxide (CO2) concentrations will cause forests to grow faster and store more carbon is an open question. Using free air CO2 release in combination with a canopy crane, we found an immediate and sustained enhancement of carbon flux through 35-meter-tall temperate forest trees when exposed to elevated CO2. However, there was no overall stimulation in stem growth and leaf litter production after 4 years. Photosynthetic capacity was not reduced, leaf chemistry changes were minor, and tree species differed in their responses. Although growing vigorously, these trees did not accrete more biomass carbon in stems in response to elevated CO2, thus challenging projections of growth responses derived from tests with smaller trees.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), 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

Citations559
Published2005
Admission routes1
Has abstractyes

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