When can stress facilitate divergence by altering time to flowering?
Bibliographic record
Abstract
Stressors and heterogeneity are ubiquitous features of natural environments, and theory suggests that when environmental qualities alter flowering schedules through phenotypic plasticity, assortative mating can result that promotes evolutionary divergence. Therefore, it is important to determine whether common ecological stressors induce similar changes in flowering time. We review previous studies to determine whether two important stressors, water restriction and herbivory, induce consistent flowering time responses among species; for example, how often do water restriction and herbivory both delay flowering? We focus on the direction of change in flowering time, which affects the potential for divergence in heterogeneous environments. We also tested whether these stressors influenced time to flowering and nonphenology traits using Mimulus guttatus. The literature review suggests that water restriction has variable effects on flowering time, whereas herbivory delays flowering with exceptional consistency. In the Mimulus experiment, low water and herbivory advanced and delayed flowering, respectively. Overall, our results temper theoretical predictions for evolutionary divergence due to habitat-induced changes in flowering time; in particular, we discuss how accounting for variation in the direction of change in flowering time can either increase or decrease the potential for divergence. In addition, we caution against adaptive interpretations of stress-induced phenology shifts.
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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".