Differential temperature adaptation mechanisms in the High Arctic-adapted <i>Cerastium regelii</i> Ostenf. and the widespread <i>Stellaria longipes</i> Goldie
Bibliographic record
Abstract
Summary Climate change impacts arctic latitudes more acutely than other latitudes, resulting in arctic shrubification. How individual species in these climes respond to warming temperature is poorly understood. Understanding species resiliency to climate change will help us conserve plant species at risk. We performed a survey of plants in a permafrost anomaly in Resolute (Qausuittuq), Nunavut, Canada. Two identified species, Stellaria longipes Goldie and Cerastium regelii Ostenf., were investigated through modelled niche suitability under future climate scenarios, phenological analysis, and in vitro warming experiments to investigate growth and phytochemical profiles. 10 species including Stellaria longipes and Cerastium regelii were identified in the anomaly. Predicted niche suitability increased under SSP126 for C. regelii , with compressed and later flowering period since 1850 . In vitro, S. longipes maximized growth at 24 °C with greater abundance of cytokinins than C. regelii , which increased growth at 28 °C. Stellaria longipes is self-limiting at higher temperatures, and is less temperature-dependent for its success, while C. regelii is more affected by warming temperatures, showing increases in growth and predicted niche suitability. Our work increases understanding of plant resiliency and vulnerability in Canada’s High Arctic, and sheds light on the biology of an understudied arctic specialist in C. regelii .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".