Recent speciation associated with range expansion and a shift to self-fertilization in North American Arabidopsis
Bibliographic record
Abstract
The main processes classically evoked for promoting reproductive isolation and speciation are geographic separation reducing gene flow among populations, divergent selection, and chance genomic change. In a case study, we present evidence that the additional factors of climate change, range expansion and a shift in mating towards inbreeding can initiate the processes leading to parapatric speciation. At the end of the last Pleistocene glaciation cycle, the North American plant Arabidopsis lyrata expanded its range and concomitantly lost its reproductive mode of outcrossing multiple times. We show that in one of the newly colonized areas, the self-fertilizing recolonization lineage of A. lyrata gave rise to selfing A. arenicola, which expanded its range to subarctic and arctic Canada and Greenland, while the parental species remained restricted to temperate North America. Despite the vast range expansion by the new species, mutational load did not increase, probably because of selfing and quasi-clonal selection. We conclude that such peripheral parapatric speciation combined with range expansion and inbreeding may be an important but so far overlooked mode of speciation.
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 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".