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Record W2046534879 · doi:10.3732/ajb.1200267

Episodic recruitment of the seedling banks in balsam fir and white spruce

2012· article· en· W2046534879 on OpenAlexaffabout
Sergio Rossi, Hubert Morin, François Gionest, Danielle Laprise

Bibliographic record

VenueAmerican Journal of Botany · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsSeedlingBalsamAbies balsameaBiologyBotanyHorticultureAgronomy

Abstract

fetched live from OpenAlex

PREMISE OF THE STUDY: In ecosystems where seed production is low and masting years are sporadic, or with species that have short-lived seeds, regeneration is assured by seedling banks rather than seed banks. Seedling establishment and survival play a critical role in determining the composition of these plant communities by supplying new individuals for their maintenance. Seedling emergence and mortality were investigated to test the hypothesis that recruitment into the seedling bank is periodic. • MATERIALS AND METHODS: Seed production and seedling emergence and survival was monitored during 1994-2007 in balsam fir (Abies balsamea) and white spruce (Picea glauca) in four pristine stands of the boreal forest of Quebec, Canada. Measurements were collected twice per month by sampling one permanent plot of 20 × 20 m per stand. • KEY RESULTS: Seed-rain abundance reached 9 × 10(3) seeds m(-2) year(-1), and was characterized by synchronous sequences of low and high seed production. New seedlings appeared only during the year following a seed production of at least 1 × 10(3) and 1.5 × 10(2) seeds m(-2) year(-1) for balsam fir and white spruce, respectively. Seedlings emerged in July and survived 34-52 d on average, with balsam fir showing a longer lifespan and lower mortality, although 85-99% of seedlings died before completing one year of life. • CONCLUSIONS: The emergence of young seedlings was coupled with massive seed rains, which allowed synchronous replenishment of the seedling banks among stands and species, and generated different cohorts, yielding a discontinuous age structure.

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)0.001
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 score0.030
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.248
Teacher spread0.228 · 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

Citations12
Published2012
Admission routes2
Has abstractyes

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