Intra-annual consistent diet of lanternfish and krill in adult female southern elephant seals Mirounga leonina from the South Georgia population
Bibliographic record
Abstract
Southern elephant seals Mirounga leonina are top predators in the Southern Ocean and significant consumers of mesopelagic mid-trophic level prey while spending most of the year foraging out at sea. Yet, there is still considerable uncertainty regarding variability in the dietary composition between individuals and over time. We ran a suite of mixing models using carbon and nitrogen stable isotope ratios from the vibrissae of 54 adult female southern elephant seals from the South Georgia population (2005-2009) and potential fish, squid, and krill prey. Our goals were to (1) estimate the dietary composition of this population as a whole, (2) compare the dietary composition of individuals between previously identified foraging strategies, and (3) quantify the degree of dietary consistency at the individual level throughout a long foraging migration. Models indicate that myctophid fish were the dominant prey item consumed (mean 45% of diet), followed by Antarctic krill and Antarctic jonasfish. However, there was considerable variability within and among groups of seals regarding specific prey items consumed and the degree of individual dietary specialization, possibly as a means of reducing intraspecific competition. Finally, our models provide evidence of most seals displaying dietary consistency throughout a foraging migration. These findings have important management implications for the South Georgia population in an uncertain future and highlight the need for more effective krill management along the western Antarctic Peninsula.
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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) | 0.000 | 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".