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Record W1981601492 · doi:10.1139/cjb-2015-0004

Does increased air humidity affect stomatal morphology and functioning in hybrid aspen?

2015· article· en· W1981601492 on OpenAlexvenueno aff
Aigar Niglas, Meeli Alber, Kristi Suur, Anna K. Jasiñska, Priit Kupper, Arne Sellin

Bibliographic record

VenueBotany · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsStomatal densityVapour Pressure DeficitBiologyHumidityBotanyRelative humidityHorticultureAgronomyTranspirationPhotosynthesis

Abstract

fetched live from OpenAlex

The study investigated the effects of exposure to increased relative air humidity (RH) on stomatal morphology and sensitivity to stomata closure inducing stimulus (low RH) in hybrid aspen (Populus tremula L. × P. tremuloides Michx.) coppice growing in field conditions. Artificially elevated RH reduced air vapour pressure deficit by 5%–10% and altered stomatal sensitivity; trees grown under high RH exhibited stronger stomatal response to decreasing air humidity. We found no difference in mean stomatal pore length between treatments and a small decline in stomatal density under humidification. The lack of correlation between stomatal sensitivity and morphological traits suggests that stomatal sensitivity was unaffected by stomatal morphology. In light of rising atmospheric humidity predicted for high latitudes, strict stomatal control over water loss might be beneficial for trees if drought events become more frequent in the future. However, our experiment revealed that about two-thirds of the leaf-to-air vapour pressure difference (VPD L ) response curves demonstrated the opposite pattern, i.e., stomatal opening in response to increasing VPD L . Strict stomatal regulation is probably not beneficial to fast-growing aspen coppice under low RH, as this trait may restrict their carbon gain and growth rate.

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 score0.027
Threshold uncertainty score0.207

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 head0.009
GPT teacher head0.207
Teacher spread0.197 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

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