The response of flowering time to global warming in a high-altitude plant: the impact of genetics and the environment
Bibliographic record
Abstract
In high-altitude habitats, an increase in temperature and greater precipitation in the form of rain represent climate changes typically associated with global warming. We determined whether phenotypic plasticity and genetic changes in the mean phenotype could affect the adaptation of flowering time to changes in the environment resulting from global warming in a montane plant species, Aquilegia coerulea James. We collected seeds from 17 plants from each of three natural populations. For each of these 51 families, we assigned 3–4 individuals to each of four water and temperature treatments. We observed phenotypic plasticity in flowering time in response to both temperature and water availability but no genetic variance or genetic differentiation in phenotypic plasticity. These results indicate that phenotypic plasticity could provide a quick response to environmental changes but provides little evolutionary potential. In contrast to phenotypic plasticity in flowering time, the mean flowering time did vary among families and among populations, suggesting a genetic basis to flowering time and adaptation in the different populations. The most likely scenario for the adaptation of this plant species to climate change is a rapid response via phenotypic plasticity followed by selection and micro-evolutionary changes in the mean phenotype.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".