Color Polymorphism and Genetic Structure in the Sea Star<i>Pisaster ochraceus</i>
Bibliographic record
Abstract
The sea star Pisaster ochraceus is one of the more striking species on the rocky shores of the Northeast Pacific, in part due to the dramatic color polymorphism of the adults. Along the open Pacific coast, Pisaster populations are 6%-28% orange, with a small percentage of brilliant purple stars and a large percentage of reddish-brown to dull purple ones. However, populations in the San Juan Island Archipelago (Washington, USA) and the southern Strait of Georgia (British Columbia, Canada) are almost entirely brilliant purple. The factors that maintain the color polymorphism, and those that contribute to among-site variation in color frequencies, remain unknown. We examined the relationships between color frequencies and several ecological and morphological variables, and conducted a large-scale phylogeographic survey of Pisaster populations. We found very low population genetic structure, suggesting that gene flow is high and geographic variation in color frequencies is not a vestige of Pleistocene glacial refugia. Color frequencies are also unrelated to adult size and to the frequency of injury within a population. However, there are suggestive relationships between color frequency and diet, and with areas of potentially low salinity. We propose that, although the color polymorphism may have an underlying genetic component, the regional-scale variation in color frequency is ecologically controlled.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".