Ecological context and metapopulation dynamics affect sex-ratio variation among dioecious plant populations
Bibliographic record
Abstract
BACKGROUND AND AIMS: Populations of dioecious flowering plants commonly exhibit heterogeneity in sex ratios and deviations from the equilibrium expectation of equal numbers of females and males. Yet the role of ecological and demographic factors in contributing towards biased sex ratios is currently not well understood. METHODS: Species-level studies from the literature were analysed to investigate ecological correlates of among-population sex-ratio variation and metapopulation models and empirical data were used to explore the influence of demography and non-equilibrium conditions on flowering sex ratios. KEY RESULTS: The survey revealed significant among-population heterogeneity in sex ratios and this was related to the degree of sampling effort. For some species, sex-ratio bias was associated with the proportion of non-reproductive individuals, with greater male bias in populations with a lower proportion of individuals that were flowering. Male-biased ratios were also found at higher altitudes and latitudes, and in more xeric sites. Simulations and empirical data indicated that clonal species exhibited greater heterogeneity in sex ratios than non-clonal species as a result of their slower approach to equilibrium. The simulations also indicated the importance of interactions between reproductive mode and founder effects, with greater departures from equilibrium in clonal populations with fewer founding individuals. CONCLUSIONS: The results indicate that sex-based differences in costs of reproduction and non-equilibrium conditions can each play important roles in affecting flowering sex ratios in populations of dioecious plants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".