REPRODUCTIVE ISOLATION CAUSED BY NATURAL SELECTION AGAINST IMMIGRANTS FROM DIVERGENT HABITATS
Bibliographic record
Abstract
The classification of reproductive isolating barriers laid out by Dobzhansky and Mayr has motivated and structured decades of research on speciation. We argue, however, that this classification is incomplete and that the unique contributions of a major source of reproductive isolation have often been overlooked. Here, we describe reproductive barriers that derive from the reduced survival of immigrants upon reaching foreign habitats that are ecologically divergent from their native habitat. This selection against immigrants reduces encounters and thus mating opportunities between individuals from divergently adapted populations. It also reduces the likelihood that successfully mated immigrant females will survive long enough to produce their hybrid offspring. Thus, natural selection against immigrants results in distinctive elements of premating and postmating reproductive isolation that we hereby dub “immigrant inviability”. We quantify the contributions of immigrant inviability to total reproductive isolation by examining study systems where multiple components of reproductive isolation have been measured and demonstrate that these contributions are frequently greater than those of traditionally recognized reproductive barriers. The relevance of immigrant inviability is further illustrated by a consideration of population‐genetic theory, a review of selection against immigrant alleles in hybrid zone studies, and an examination of its participation in feedback loops that influence the evolution of additional reproductive barriers. Because some degree of immigrant inviability will commonly exist between populations that exhibit adaptive ecological divergence, we emphasize that these barriers play critical roles in ecological modes of speciation. We hope that the formal recognition of immigrant inviability and our demonstration of its evolutionary importance will stimulate more explicit empirical studies of its contributions to speciation.
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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".