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Effects of elevated CO <sub>2</sub> on intra‐specific competition in <i>Sinapis alba</i> : an examination of the role of growth responses to red:far‐red ratio

2008· article· en· W2128231265 on OpenAlexaff
J. E. Cowan, E. G. Reekie

Bibliographic record

VenuePlant Biology · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsAcadia University
Fundersnot available
KeywordsSinapisBiologyCompetition (biology)PhotosynthesisFar-redAnimal scienceCanopyBiomass (ecology)Growth rateShade avoidanceBotanyRelative growth rateAgronomyEcologyRed lightBiochemistry

Abstract

fetched live from OpenAlex

Response of plants to elevated CO2 differs markedly between individually- and competitively-grown plants, both in terms of mean size and variation about the mean. Using Sinapis alba, we explored whether these contrasting effects are a consequence of the effect of competition on the red:far red (R:FR) light ratio. Plants were grown at both ambient and elevated (700 microl.l(-1)) CO2 in competitive stands, and as individuals at either a low (0.7) or high (1.25) R:FR ratio at a constant photosynthetic photon fluence rate. Elevated CO2 increased stand biomass by enhancing the growth of canopy dominants, but not the subordinates. As a consequence, elevated CO2 increased the coefficient of variation in size within the stands. Elevated CO2 did not enhance the growth of individually-grown plants at the low R:FR ratio, but did at the high R:FR ratio. Both the poor response of subordinate plants to elevated CO2 and the increased size inequalities of individuals within the stand can be explained in terms of the effect of the R:FR ratio on CO2 responsiveness. The effect of the R:FR ratio on CO2 response may be related to its effect on allocation patterns and nutrient uptake.

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 score0.007
Threshold uncertainty score0.015

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 integrity0.0000.001
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 head0.012
GPT teacher head0.196
Teacher spread0.184 · 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

Citations12
Published2008
Admission routes1
Has abstractyes

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