The effect of temperature on foraging activity and digestion in the American lobster Homarus americanus (Milne Edwards, 1837) (Decapoda: Nephropsidae) feeding on blue mussels Mytilus edulis (Linnaeus, 1758)
Bibliographic record
Abstract
The foraging activity and digestive processes of the American lobster Homarus americanus, feeding on blue mussels, Mytilus edulis were investigated over a temperature range of |${\rm{5 - 15}}^\circ {\rm{C}}$|. Lobsters ate more food with increasing temperature, consuming maximal levels of approximately 5% of their body mass of mussel flesh in one sitting in |${\rm{15}}^\circ {\rm{C}}$| water. When foraging behaviour was observed over 7 days, lobsters were more active outside of their shelter at 10 and |${\rm{15}}^\circ {\rm{C}}$| and consumed more mussels at these two temperatures. Although lobsters were more active during the hours of darkness, they still exited shelters and fed during the light period if food was available. The lobsters consumed at least one mussel every 15.8, 7.8, and |${\rm{4.7\, h}}$| in temperatures of 5, 10, and |${\rm{15}}^\circ {\rm{C}}$|, respectively. The passage of a mussel meal through the digestive system of lobsters was considerably slower compared with other decapod crustaceans. Transit rate decreased as the temperature was increased, with clearance times of 252, 133 and |${\rm{69\, h}}$| in temperatures of 5, 10, and |${\rm{15}}^\circ {\rm{C}}$|. Although the time between feeding bouts decreased with increasing temperature, at the time of next feeding the amount of food that had been cleared from the foregut was the same in each temperature (approximately 20%), suggesting that this proportion of stomach emptying could be the cue for next feeding. Recent work has suggested that lobster numbers increase in the presence of mussel aquaculture operations. This work gives further insight into the feeding behaviour and activity around mussel farms, and suggests that lobsters could be an effective means of removing moribund mussels that could be lost during the harvesting process.
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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".