EXPERIMENTAL ANALYSIS OF BIPARENTAL INBREEDING IN A SELF-FERTILIZING PLANT
Bibliographic record
Abstract
Localized dispersal and mating may genetically structure plant populations, resulting in matings among related individuals. This biparental inbreeding has significant consequences for the evolution of mating systems, yet is difficult to estimate in natural populations. We estimated biparental inbreeding in two populations of the largely self-fertilizing plant Aquilegia canadensis using standard inference as well as a novel experiment comparing apparent selfing between plants that were randomly relocated within populations to experimental control plants. Using two allozyme markers, biparental inbreeding (b) inferred from the difference between single-locus and multilocus estimates of selfing (b = s(s) - s(m)) was low. Less than 3% of matings involved close relatives (mean b = 0.029). In contrast, randomly relocating plants greatly reduced apparent selfing (mean s(s) = 0.674) compared to control plants that had been dug up and replanted in their original locations (s(s) = 0.953, P = 0.002). Based on this difference in s(s), we estimated that approximately 30% of all matings involved close relatives (mean b = 0.279, 95% CL = 0.072-0.428). Inference from s(s) - s(m) underestimated b in these populations by more than an order of magnitude. Biparental inbreeding is thought to influence the evolution of self-fertilization primarily through reducing the genetic cost of outcrossing. This is unlikely to be of much significance in A. canadensis because inbreeding depression (a major cost of selfing) is much stronger than the cost of outcrossing. However, biparental inbreeding combined with strong inbreeding depression may influence selection on dispersal.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".