Disruptive selection in a bimodal population of Darwin's finches
Bibliographic record
Abstract
A key part of the ecological theory of adaptive radiation is disruptive selection during periods of sympatry. Some insight into this process might be gained by studying populations that are bimodal for dual-context traits, i.e. those showing adaptive divergence and also contributing to reproductive isolation. A population meeting these criteria is the medium ground finch (Geospiza fortis) of El Garrapatero, Santa Cruz Island, Galápagos. We examined patterns of selection in this population by relating individual beak sizes to interannual recaptures during a prolonged drought. Supporting the theory, disruptive selection was strong between the two beak size modes. We also found some evidence of selection against individuals with the largest and smallest beak sizes, perhaps owing to competition with other species or to gaps in the underlying resource distribution. Selection may thus simultaneously maintain the current bimodality while also constraining further divergence. Spatial and temporal variation in G. fortis bimodality suggests a dynamic tug of war among factors such as selection and assortative mating, which may alternatively promote or constrain divergence during adaptive radiation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".