Life‐history trade‐offs promote the evolution of dioecy
Bibliographic record
Abstract
Most dioecious plants are perennial and subject to trade-offs between sexual reproduction and vegetative performance. However, these broader life-history trade-offs have not usually been incorporated into theoretical analyses of the evolution of separate sexes. One such analysis has indicated that hermaphroditism is favoured over unisexuality when female and male sex functions involve the allocation of nonoverlapping types of resources to each sex function (e.g. allocations of carbon to female function vs. allocations of nitrogen to male function). However, some dioecious plants appear to conform to this pattern of resource allocation, with different resource types allocated to female vs. male sex functions. Using an evolutionarily stable strategy approach, we show that life-history trade-offs between sexual reproduction and vegetative performance enable the evolution of unisexual phenotypes even when there are no direct resource-based trade-offs between female and male sex functions. This result might help explain the preponderance of perennial life histories among dioecious plants and why many dioecious plants with annual life histories have indeterminate growth with ongoing trade-offs between sexual reproduction and vegetative growth.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".