Environmental influence on primary sex ratio in a dioecious plant
Bibliographic record
Abstract
The proximity of mates can influence mating opportunities and the quantity and quality of offspring, especially in dioecious plant species. Progeny sex ratios modulated by environmental conditions is one of the most radical ways in which offspring quality may be influenced, yet it has rarely been reported in plants. A mechanism proposed to influence progeny sex ratios in dioecious plants involves competition between female- and male-determining microgametophytes (certation) as a result of variation in pollination intensity. However, the role of selective fertilization in dioecious plants is controversial and has not been demonstrated under field conditions. Here we investigate whether natural variation in the spatial arrangement of females and males influences pollination intensity and progeny sex ratios in the wind-pollinated herb Rumex nivalis. Based on previous experimental manipulation of pollination intensity in this species, we predicted that maternal parents in close proximity to males would produce more strongly female-biased progeny sex ratios. We tested this prediction in six alpine populations in Switzerland by measuring the distance between focal females and neighboring males and assessing pollen loads and seed sex ratios of maternal parents. In four of the six populations, females positioned in close proximity to males captured more pollen and exhibited more female-biased sex ratios. Our results demonstrate that demographic aspects of the maternal mating environment can influence progeny sex ratios. The most probable explanation for biased primary sex ratios in Rumex is selective fertilization resulting from pollen tube competition.
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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 | 0.000 | 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".