Selection against migrants contributes to the rapid evolution of ecologically dependent reproductive isolation
Bibliographic record
Abstract
Ecologically dependent reproductive isolation (EDRI) is the decrease in gene flow that occurs when adaptive divergence reduces the fitness of individuals that move between ecological environments. A particularly simple and perhaps almost universal mechanism contributing to EDRI is natural selection against migrants themselves (i.e. before any selection against their offspring). Here I use single-locus and quantitative-genetic models to examine how quickly this mechanism can contribute to EDRI after the founding of a new population. I find that as long as divergent selection is relatively strong, selection against migrants can make a substantial contribution to EDRI in less than 30 generations. This mechanism is only one of several that might influence EDRI. The addition of other mechanisms, such as habitat choice or selection against hybrids, would presumably accelerate the accumulation of EDRI. Although EDRI is neither complete (some gene flow may still occur) nor unconditional (it depends on the ecological context), it may reduce gene flow to the point that absolute and unconditional reproductive isolation can evolve through other mechanisms. Whenever organisms colonize new ecological environments, selection against migrants may contribute to rapid reductions in gene flow. Future studies of ecological speciation may profit from particular attention to this mechanism of reproductive isolation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".