Data from: Population genomic signatures of founding events in autonomously self-fertilizing plants: A test with <em>Impatiens capensis</em>
Bibliographic record
Abstract
Autonomously self-fertilising plants possess disproportionate abilities to found populations. Viewed from the metapopulation perspective, founding events should be frequent in such plants, but the intensity and timing of bottlenecks and recovery should vary among populations. We tested the hypothesis that variation in these demographic characteristics in one such species helps to explain variation in levels of genetic diversity and population genomic signatures of inbreeding, relative recombination, and microscale spatial genetic structure. We used reduced-representation sequence data from eleven populations of the dimorphic cleistogamous species Impatiens capensis, a species that has figured prominently in evolutionary studies. The populations occur in a landscape where suitable habitat is fragmented. Population genomic analyses revealed significant among-population variation in demographic history, genetic diversity, inbreeding, relative recombination rate, tracts of homozygosity by descent, and spatial autocorrelation of genotypes at micro-geographic scales. Our findings support the hypothesis that variation in the intensity of bottlenecks and length of the post-bottleneck recovery phase in autonomously self-fertilising plants lead to variation in genetic diversity and a suite of associated population genomic signatures of inbreeding. We suggest that these findings have consequences for understanding evolutionary processes and guiding conservation strategies in fragmented habitats for dimorphic
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".