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Record W2014557777 · doi:10.1139/b09-103

Interspecific covariation between stomatal density and other functional leaf traits in a local flora

2010· article· en· W2014557777 on OpenAlexafffundvenueabout
Jessy Loranger, Bill Shipley

Bibliographic record

VenueBotany · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyInterspecific competitionStomatal densitySpecific leaf areaBotanyContext (archaeology)HerbariumDeciduousTraitLaminaEvergreenEcologyPhotosynthesis

Abstract

fetched live from OpenAlex

Despite the importance of stomata in leaf functioning, and despite the recent interest in interspecific leaf trait covariation in functional ecology, little is known about how stomatal density relates to other leaf traits in a broad interspecific context. This is especially important because stomatal density has been widely used to deduce temporal variation in atmospheric CO2 concentrations [CO2atm] from fossilized or herbarium leaves. We therefore measured stomatal density, specific leaf area (SLA) and its components, leaf thickness, and leaf chlorophyll content in both sun and shade leaves of 169 individuals from 52 angiosperm species in southwestern Quebec. Using mixed models, we show that stomatal density decreases allometrically with increasing SLA and chlorophyll content, and increases allometrically with increasing lamina thickness. The sun–shade contrast changes the intercepts, but not the slopes, of these relationships. It is important to take into consideration these relations when correlating stomatal density with [CO2], to avoid spurious interpretations.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.211
Teacher spread0.190 · 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

Citations46
Published2010
Admission routes4
Has abstractyes

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