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How phenology influences physiology in deciduous forest spring ephemerals

2001· article· en· W2145710698 on OpenAlexaff
Line Lapointe

Bibliographic record

VenuePhysiologia Plantarum · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPhenologyDormancyBiologyDeciduousShootAgronomyNutrientPerennial plantPhotosynthesisAnnual growth cycle of grapevinesBotanyEcologyGermination

Abstract

fetched live from OpenAlex

Spring ephemerals of deciduous forest are adapted to take advantage of the high-light period available in early spring. They appear shortly after snow melt and complete their aboveground growth, including fruit production, within 2 months. After they produce new buds, they senesce and enter dormancy. Dormancy is not very deep in spring ephemerals and during summer differentiation occurs in the bud of the apparently resting organ. Low soil temperatures release dormancy, and the shoots and roots then grow slowly over autumn and winter. The goal of this paper is to show how this characteristic phenology influences many aspects of spring ephemerals' physiology, and the influences these different physiological parameters have on each other. Spring ephemerals have high photosynthetic rates that allow them to rapidly accumulate carbohydrates and complete their aboveground growth in a few weeks. To sustain high photosynthetic rates in early spring, the plants must be able to absorb water efficiently at low soil temperatures and to allocate large amounts of nutrients to the shoot to compensate for lower enzymatic activity at low temperatures. Nutrients are mainly absorbed in spring, although the root system is established in autumn. This means that a large amount of both carbohydrates and nutrients is translocated from the perennial organ to the developing shoot starting in autumn through early spring. Spring ephemerals have low nutrient absorption rates, but high resorption efficiency during leaf senescence. Nevertheless, their high nutrient needs restrict them to rich forest soils. The annual growth rate of spring ephemerals is very slow and this is more likely related to the inherent slow growth rate of the perennial organ than to their short leaf life. As soon as carbohydrate reserves are replenished in spring, sink limitation apparently builds up and induces leaf senescence. A better understanding of the factors controlling the growth rate of spring ephemerals is needed before we can predict these plants' response to climatic changes.

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 score0.797
Threshold uncertainty score0.465

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 head0.031
GPT teacher head0.224
Teacher spread0.193 · 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

Citations197
Published2001
Admission routes1
Has abstractyes

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