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Record W2588150398 · doi:10.1139/cjb-2016-0317

Late canopy closure delays senescence and promotes growth of the spring ephemeral wild leek (<i>Allium tricoccum</i>)

2017· article· en· W2588150398 on OpenAlexafffundvenueabout
Pierre‐Paul Dion, Julie Bussières, Line Lapointe

Bibliographic record

VenueBotany · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsUniversité Laval
FundersAgriculture and Agri-Food CanadaMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsBiologyPhenologyCanopyGrowing seasonAgronomyBotany

Abstract

fetched live from OpenAlex

Spring ephemerals take advantage of the high light conditions in spring to accumulate carbon reserves through photosynthesis before tree leaves unfold. Recent work has reported delayed leaf senescence under constant light availability in some spring ephemerals, such as wild leek (Allium tricoccum). This paper aims to establish whether tree canopy composition and phenology can influence the growth of spring ephemerals through changes in their phenology. Wild leek bulbs were planted in 31 plots in southern Quebec, Canada, under canopies varying in composition and densities. Light availability and tree phenology were measured, along with other environmental conditions, and their effect on the growth of wild leeks was assessed with a redundancy analysis. Higher light availability resulted in better growth of wild leeks. The plants postponed their senescence under trees with late bud-burst, and thus better bulb growth and seed production were achieved. The tree litter and temperature and moisture levels of the soil also influenced the growth and survival of wild leeks. Thus, tree leaf phenology appears to have a strong impact on the growth of spring ephemerals by modulating the length of their growing season and their photosynthetic capacity. This underlines the importance of considering the variation of light availability throughout the growing season in the study of spring ephemerals.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.596

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.027
GPT teacher head0.251
Teacher spread0.224 · 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

Citations21
Published2017
Admission routes4
Has abstractyes

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