Bibliographic record
Abstract
Abstract Genetic divergence among allopatric populations builds reproductive isolation over time and is thought to be the major mechanism underlying the formation of new species. This process is accelerated when populations face a changing environment, but abrupt change also places populations at risk of extinction. Here we use simulations of Fisher’s geometric model with explicit population dynamics to explore the genetic changes that occur in the face of extreme environmental changes to which populations must adapt or go extinct. We show that evolutionary rescue leads to the fixation of mutations whose effects are larger on average and that these mutations are more likely to lead to reproductive isolation, compared with populations not at risk of extinction. We refer to the formation of new species from the ashes of populations in decline as the phoenix hypothesis of speciation. The phoenix hypothesis predicts more substantial hybrid fitness breakdown among populations surviving a higher extinction risk. The hypothesis was supported when many loci underlie adaptation. When, however, there was only a small number of potential rescue mutations, we found that mutations fixed in different populations were more likely to be identical, with parallel changes reducing isolation. With a limited genomic potential for adaptation, we find support for a modified version of the phoenix hypothesis where reproductive isolation builds fastest in populations subject to an intermediate extinction risk. While processes driving extinction lead to the loss of lineages with deep evolutionary histories, they may also generate new taxa, albeit taxa with minimal genetic differences.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".