Evolution of self‐fertilization at geographical range margins? A comparison of demographic, floral, and mating system variables in central vs. peripheral populations of <i>Aquilegia canadensis</i> (Ranunculaceae)
Bibliographic record
Abstract
Biogeographic models predict that geographically peripheral populations should be smaller, more sparsely distributed, and have a lower per-capita reproductive rate than populations near the center of a species' range. Plants in peripheral populations may, therefore, receive less pollinator visitation and outcross pollination, which may select for self-fertilization to provide reproductive assurance. We tested these predictions by comparing population size, plant density, seed production, floral traits, and mating system parameters between 10 populations of Aquilegia canadensis near the northern margin of the range with 10 near the range center. Contrary to predictions, peripheral populations were not smaller, less dense, nor less productive than central populations. Nevertheless, we detected substantial regional differences in key floral traits. Plants in central populations produced larger flowers with 68% greater herkogamy and had 30% more flowers open simultaneously than plants in northern populations. However, there was no regional difference in the mating system. In northern populations, 73% (range = 60-88%) of seeds were self-fertilized compared to 76% (51-100%) in central populations. In both regions, adult inbreeding coefficients were near zero, indicating very strong inbreeding depression despite high selfing. Marked geographic variation in key floral traits does not reflect evolutionary differentiation in the mating system.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".