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Record W4389786411 · doi:10.3389/fevo.2023.1320745

Inland populations of sugar maple manifest higher phenological plasticity than coastal populations

2023· article· en· W4389786411 on OpenAlexaffabout
Yongzhi Zhou, Chunmei Bai, Xiali Guo, Vasyl Mohytych, Marcin Klisz, Sylvain Delagrange, Sergio Rossi

Bibliographic record

VenueFrontiers in Ecology and Evolution · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversité du Québec à ChicoutimiUniversité du Québec en Outaouais
Fundersnot available
KeywordsPhenologyMapleBiologyClimate changeSugarFrost (temperature)Context (archaeology)Phenotypic plasticityEcologyGrowing seasonGeography

Abstract

fetched live from OpenAlex

Plasticity is vital for plants to rapidly acclimate to environmental changes, especially under the climate change. Global warming could advance bud break and extend the growing season, but it also increases the risk of frost damage to developing leaves. In this study, we explored the phenological plasticity of bud burst of half-sib family sugar maple ( Acer saccharum Marsh.) seedlings from 11 seed origins in two common gardens at the center and the northern edge of the species distribution in Quebec, Canada. Results showed that the phenological plasticity of sugar maple originating from inland was significantly higher than those from coastal areas at the beginning of leaf development. This discrepancy may result from the long-term frost change frequency of seed origins. Our study suggests that in the context of climate warming, the higher plasticity observed in sugar maple originating from inland areas may benefit from the phenological adaptation of sugar maple and the survival of local populations. It also suggests that inland populations may have a higher potential regarding to assisted migration, but this needs to be confirmed for other functional traits than phenology.

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 score0.066
Threshold uncertainty score0.268

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 head0.015
GPT teacher head0.216
Teacher spread0.200 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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