A test of frequency dependent selection in the evolution of a generalist phenotype
Bibliographic record
Abstract
A solitary population of consumers frequently evolves to the middle of a resource gradient and an intermediate mean phenotype compared to a sympatric pair of competing species that diverge to either side via character displacement. The forces governing the distribution of phenotypes in these allopatric populations, however, are little investigated. Theory predicts that the intermediate mean phenotype of the generalist should be maintained by negative frequency dependent selection, whereby alternate extreme phenotypes are favored because they experience reduced competition for resources when rare. However, the theory makes assumptions that are not always met, and alternative explanations for an intermediate phenotype are possible. We provide a test of this prediction in a mesocosm experiment using threespine stickleback that are ecologically and phenotypically intermediate between the more specialized stickleback species that occur in pairs. We manipulated the frequency distribution of phenotypes in two treatments and then measured effects on a focal intermediate population. We found a slight frequency-dependent effect on survival in the predicted direction but not on individual growth rates. This result suggests that frequency dependent selection might be a relatively weak force across the range of phenotypes within an intermediate population and we suggest several general reasons why this might be so. We propose that allopatric populations might often be maintained at an intermediate phenotype instead by stabilizing or fluctuating directional selection.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.017 | 0.004 |
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".