Trade‐off between mating and predation risk in the marine snail, <i>Littorina plena</i>
Bibliographic record
Abstract
Abstract. We investigated the hypothesis that predation risk affects mating decisions in the intertidal snail Littorina plena in Bamfield Inlet, Northeast Pacific. First, we conducted a field tethering experiment to test the assumption that mating pairs of snails are more susceptible to predation than solitary individuals, and then performed a laboratory experiment to quantify the effect of predation threat on the propensity of snails to form mating pairs. Our results support the hypothesis, in that “mating pairs” were more frequently killed than single snails in the field, and snails were less likely to form mating pairs in the laboratory when simulated predation risk was high (chemical cues from crushed conspecifics were added to the water) than when it was low (no risk cues were added to the water). In contrast to several earlier studies, we found no effect of individual size on snail susceptibility to predation, perhaps because our two size classes were contiguous and snails within them were not dissimilar enough. The results of the behavioral experiment were consistent with this lack of individual size effect on snail vulnerability; both size classes of snails showed a significant and similar tendency to decrease mating when predation risk was high. Taken together, the results of this and recent studies indicate that predators can considerably affect the behavior of littorinid snails, including their movement patterns, feeding, and reproduction. We argue that greater consideration should be given to how marine invertebrates trade off predation risk and activities related to reproduction.
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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 | 0.000 | 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) | 0.001 | 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".