MétaCan
Menu
Back to cohort
Record W1853775253 · doi:10.1139/b2012-091

Controls on bud activation and tiller initiation in C<sub>3</sub>and C<sub>4</sub>tallgrass prairie grasses: the role of light and nitrogen

2012· article· en· W1853775253 on OpenAlexvenueno aff
Melinda M. Williamson, Gail W. T. Wilson, David C. Hartnett

Bibliographic record

VenueBotany · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsnot available
FundersOklahoma State UniversityU.S. Department of Agriculture
KeywordsTiller (botany)Perennial plantBiologyNitrogenDormancyGrazingEcosystemPopulationBotanyAgronomyDarknessEcologyChemistry

Abstract

fetched live from OpenAlex

Population dynamics of perennial grasses in tallgrass prairie ecosystems are strongly influenced by vegetative outgrowth from their belowground bud banks. We examined the role of light and nitrogen in regulating tiller initiation and tested an integrated model of controls on bud dormancy and activation in several C 3 and C 4 grasses. In addition, we assessed the interaction of nitrogen and light quantity and red – far red spectral composition on tiller initiation. Belowground perennating organs of three C 3 and three C 4 species were grown under full light or dark conditions, amended with one of four nitrogen concentrations (0 to 350 ppm N). Dormant buds were also subjected to full light under different spectral compositions or to continuous darkness. Our results among C 3 grasses support the integrated model as light and nitrogen played important and interacting roles in the regulation of bud banks. However, differences in responses among C 4 grasses and a lack of light × nitrogen interactions suggest that an alternative model may be necessary for this functional group. Our results provide predictions of responses to nitrogen enrichment or light imitations in prairie ecosystems due to interacting disturbances such as reduction in fire frequencies, alterations in grazing intensities, or climate change.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.184

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 head0.215
Teacher spread0.202 · 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 designBench or experimental
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

Citations24
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueBotanySame topicRuminant Nutrition and Digestive PhysiologyFrench-language works237,207