Low S-allele numbers limit mate availability, reduce seed set and skew fitness in small populations of a self-incompatible plant
Bibliographic record
Abstract
1. The role of genetic factors in species decline and extinction is the subject of a long-running controversy, with demographical factors often seen as more important for the immediate persistence of populations and species. One gene system that directly links genetic diversity with reproduction, through its influence on fertilization success, is the self-incompatibility (SI) locus in angiosperm plants. Despite the potential importance of SI allele diversity for demographical function, there are few direct measures of S-allele numbers in multiple populations, and no studies have simultaneously measured reproductive output, mate availability, S-allele diversity and pollinator service. 2. We used diallel crosses to estimate S-allele number and mate availability in seven populations of the forb Rutidosis leptorrhynchoides ranging in size from 5 to 100 000 plants. Seed set and correlated paternity were assessed from open-pollinated inflorescences to examine reproductive output and variance in female and male fitness. To assess whether populations were receiving adequate pollinator service, the amount of pollen deposited on open-pollinated stigmas was quantified. 3. We found that small populations (<100 plants) of R. leptorrhynchoides have low S-allele diversity and mate availability and exhibit significant reductions in seed set relative to large populations (>1000 plants) with higher numbers of S-alleles, despite the maintenance of pollinator service. Greater variance in seed set among plants and higher correlated paternity in small populations suggest that low S-allele numbers are directly limiting mate availability and causing the observed reproductive failure. 4. Synthesis and applications. Our work demonstrates that the loss of genetic diversity at the SI locus can have immediate detrimental effects on reproductive performance, despite the maintenance of pollinator service. These results highlight the importance of genetic factors in determining demographical outcomes when clear links between genotype and individual fitness exist, even when populations are not ecologically constrained. This result is important for the conservation and management of many plant species as approximately half of all angiosperm families contain species with genetically controlled SI and the loss of genetic diversity through habitat loss and fragmentation is an ever-increasing reality for plant species worldwide.
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 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".