Phenological associations of within‐ and among‐plant variation in gender with floral morphology and integration in protandrous <i>Delphinium glaucum</i>
Bibliographic record
Abstract
Summary 1. Flowering‐time differences within and among protandrous, hermaphroditic plants shift the floral sex ratio from male‐ to female‐dominated during a population’s flowering season. This dynamic should induce negative frequency‐dependent selection favouring relatively greater investment of resources and time in female function by early flowers and early‐flowering plants than by late flowers and late‐flowering individuals. In contrast, selection for floral integration to facilitate pollen export and import should limit floral variation. 2. We assessed these contrasting expectations for the protandrous Delphinium glaucum by considering the relation of variation and covariation in the lengths of perianth segments, anther and ovule number, and male‐ and female‐phase duration for flowers at three positions within inflorescences to the first flowering date, mean gender and size of 34 plants. 3. Reproductive phenotypes varied among and within plants in association with a shift in population floral sex ratio from male‐ to female‐biased, but not with plant size. Early‐flowering plants had female‐biased phenotypic gender and smaller flowers with fewer anthers per ovule and shorter male phases than late‐flowering plants. Within individuals, earlier (lower) flowers were larger with higher female effort, in terms of both the relative production of ovules and anthers and the relative durations of female and male phases, than later (upper) flowers. Overall, these results are more consistent with the expectations of negative frequency‐dependent selection than with proximate resource allocation. 4. Correlations among floral traits indicated significant floral integration. However, these correlations weakened from lower to upper flowers, suggesting that the patterns of intra‐individual variation limit the extent of integration. 5. Synthesis . Reproductive phenotypes that incorporate systematic among‐flower variation and vary consistently among individuals with flowering time, such as those exhibited by D. glaucum , may be typical of dichogamous species with multi‐flowered inflorescences. Such diversity within and among plants should result from a combination of density‐dependent selection against simultaneous flowering of individuals and frequency‐dependent selection favouring emphasis on the least common sex role during specific stages of the flowering season, both facilitated by the positive assortative mating that accompanies asynchronous flowering among individuals.
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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".