SEXUAL DIMORPHISM AND SPECIATION ON TWO ECOLOGICAL COINS: PATTERNS FROM NATURE AND THEORETICAL PREDICTIONS
Bibliographic record
Abstract
Adaptive divergence of phenotypes, such as sexual dimorphism or adaptive speciation, can result from disruptive selection via competition for limited resources. Theory indicates that speciation and sexual dimorphism can result from identical ecological conditions, but co-occurrence is unlikely because whichever evolves first should dissipate the disruptive selection necessary to drive evolution of the other. Here, we consider ecological conditions in which disruptive selection can act along multiple ecological axes. Speciation in lake populations of threespine sticklebacks (Gasterosteus aculeatus) has been attributed to disruptive selection due to competition for resources. Head shape in sticklebacks is thought to reflect adaptation to different resource acquisition strategies. We measure sexual dimorphism and species variation in head shape and body size in stickleback populations in two lakes in British Columbia, Canada. We find that sexual dimorphism in head shape is greater than interspecific differences. Using a numerical simulation model that contains two axes of ecological variation, we show that speciation and sexual dimorphism can readily co-occur when the effects of loci underlying sexually dimorphic traits are orthogonal to those underlying sexually selected traits.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".