Assessing western gull predation on purple sea urchins in the rocky intertidal using optimal foraging theory
Bibliographic record
Abstract
Purple sea urchins ( Strongylocentrotus purpuratus (Stimpson, 1857)) are abundant grazing invertebrates that can have a major impact on the rocky intertidal community. Predators can control the urchin population and indirectly reduce grazing activity. We determined the effects of western gull ( Larus occidentalis Audubon, 1839) predation on purple sea urchins in the rocky intertidal using the framework of optimal foraging theory and taking into account different prey-handling techniques. We recorded the foraging behavior of gulls, measured urchin availability, and estimated prey caloric content with bomb calorimetry. Western gulls selected purple sea urchins significantly more than other prey items (snails (genus Tegula Lesson, 1835), limpets (genus Collisella Dall, 1871), sea stars ( Pisaster giganteus (Stimpson, 1857) and Pisaster ochraceus (Brandt, 1835))). Larger urchins contained relatively more calories. Gulls foraged optimally when pecking by frequently selecting the most profitable size class. However, gulls chose smaller urchins than expected when air-dropping, which could have been influenced by group size and age. Gulls selected smaller purple sea urchins when foraging in larger groups likely owing to the risk of kleptoparasitism. Adults chose larger, and juveniles smaller, urchins when air-dropping, suggesting that juveniles are less experienced in foraging techniques. We estimated that gull predation could affect up to one third of the sea urchin populations locally, which could increase species diversity in the rocky intertidal community.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".