Ernst Mayr and the integration of geographic and ecological factors in speciation
Bibliographic record
Abstract
Mayr's best recognized scientific contributions include the biological species concept and the theory of geographic speciation. In the latter, reproductive isolation evolves as an incidental by-product of genetic divergence between allopatric populations. Mayr noted that divergent natural selection could accelerate speciation, but also argued that gene flow so strongly retards divergence that, even with selection, non-allopatric speciation is unlikely. However, current theory and data demonstrate that substantial divergence, and even speciation, in the face of gene flow is possible. Here, I attempt to connect some opposing views about speciation by integrating Mayr's ideas about the roles of ecology and geography in speciation with current data and theory. My central premise is that the speciation process (i.e. divergence) is often continuous, and that the opposing processes of selection and gene flow interact to determine the degree of divergence (i.e. the degree of progress towards the completion of speciation). I first establish that, in the absence of gene flow, divergent selection often promotes speciation. I then discuss how population differentiation in the face of gene flow is common when divergent selection occurs. However, such population differentiation does not always lead to the evolution of discontinuities, strong reproductive isolation, and thus speciation per se. I therefore explore the genetic and ecological circumstances that facilitate speciation in the face of gene flow. For example, particular genetic architectures or ecological niches may tip the balance between selection and gene flow strongly in favour of selection. The circumstances allowing selection to overcome gene flow to the extent that a discontinuity develops, and how often these circumstances occur, are major remaining questions in speciation research.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".