The Effects of Age and Sex on the Energy Intake of Captive Sea Otters (Enhydra lutris): Implications for Captive Management and Species Conservation
Bibliographic record
Abstract
Sea otters (Enhydra lutris) are known ecosystem engineers that have significant impacts on their kelp forest and rocky intertidal communities due to their high levels of food intake. Quantifying sea otter food biomass and energy intake is a valuable way to understand potential ecological impacts of sea otter populations on ecosystems and for predicting future population trends and potential for expansion. While detailed, fine-scale, age-specific food intake is difficult to quantify in wild sea otters, there is a wealth of potential information available from otters under human care. This study used food and energy intake data from husbandry records of 10 sea otters collected over three decades at the Vancouver Aquarium. Within these husbandry records, daily food biomass intake and body mass measurements were recorded and converted to annual average food mass and gross energy intake (GEI). Age-, sex-, and mass-specific trends were also observed. Young sea otters had the highest relative ingested food mass, equivalent to ~26% of body mass, which decreased to ~20% in adult otters. Young otters similarly had the highest mass-specific GEI, where measures from near birth to year 1 were ~40% higher than at year 3, the age of sexual and physical maturity. There were also key differences in trends between sexes. Captive adult male sea otters were 25 to 42% larger than females and their GEI was 23 to 58% higher, although mass-specific GEI was almost identical for male and non-reproductive female otters at all ages, plateauing at ~650 kJ kg-1 d-1. Despite high levels of ingested food mass, GEI was only 5 to 15% higher than for other captive marine mammals and was comparable to previous estimates for wild sea otters. These estimates of ingested food mass and energy intake requirements are valuable when modelling the ecological impact of sea otter populations and for considering the potential effects of future environmental changes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".