Steller sea lions (<i>Eumetopias jubatus</i>) have greater blood volumes, higher diving metabolic rates and a longer aerobic dive limit when nutritionally stressed
Bibliographic record
Abstract
Marine mammal foraging behaviour inherently depends on diving ability. Declining populations of Steller sea lions may be facing nutritional stress that could affect their diving ability through changes in body composition or metabolism. Our objective was to determine whether nutritional stress (restricted food intake resulting in a 10% decrease in body mass) altered the calculated aerobic dive limit (cADL) of four captive sea lions diving in the open ocean, and how this related to changes in observed dive behaviour. We measured diving metabolic rate (DMR), blood O2 stores, body composition and dive behaviour prior to and while under nutritional restriction. We found that nutritionally stressed sea lions increased the duration of their single long dives, and the proportion of time they spent at the surface during a cycle of four dives. Nutritionally stressed sea lions lost both lipid and lean mass, resulting in potentially lower muscle O2 stores. However, total body O2 stores increased due to rises in blood O2 stores associated with having higher blood volumes. Nutritionally stressed sea lions also had higher mass-specific metabolic rates. The greater rise in O2 stores relative to the increase in mass-specific DMR resulted in the sea lions having a longer cADL when nutritionally stressed. We conclude that there was no negative effect of nutritional stress on the diving ability of sea lions. However, nutritional stress did lower foraging efficiency and require more foraging time to meet energy requirements due to increases in diving metabolic rates and surface recovery times.
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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) | 0.002 | 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".