Phenotypic plasticity in mating-system traits in the annual <i>Collinsia verna</i>
Bibliographic record
Abstract
Variation in abiotic factors can influence the selective advantage of selfing and expression of the mating system if mating-system modifier traits are phenotypically plastic. However, relative to biotic factors, the role of abiotic conditions in driving variation in and evolution of plant mating systems is rarely addressed. We use an experimental approach to evaluate the extent to which genetic and environmental variation influence the expression of mating-system traits in the annual Collinsia verna. We subjected families to two environmental treatments in the greenhouse that varied in light and water availability, simulating natural and short flowering-season conditions, and examined the following: autonomous fruit set, flower number, flower size, rate of anther dehiscence, floral longevity, and timing of selfing. Our results demonstrate plasticity in nearly all traits examined. Compared with natural-season conditions, plants under short-season conditions produced fewer, smaller flowers and selfed approximately one day later due to slower anther dehiscence rates. Autonomous fruit set was similar across treatments, but there was genetic variation for plasticity in this important trait. Further, we show genetic variation in autonomous fruit set, timing of selfing, and flower number and size. Given the effects of global climate change on the duration of growing season, our results suggest that plasticity in mating-system traits will affect mating-system variation and, thus, opportunities for selection.
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 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 | 0.000 | 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) | 0.001 | 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".