Long-term evaluation of pup growth and preweaning survival rates in subantarctic fur seals,<i>Arctocephalus tropicalis</i>, on Amsterdam Island
Bibliographic record
Abstract
This study is the first to investigate pup preweaning growth and survival rates over seven consecutive breeding seasons in subantarctic fur seals, Arctocephalus tropicalis, on Amsterdam Island, southern Indian Ocean. Growth and survival were studied in relation to year and pup sex, birth date, birth mass, and growth rate at 60 days of age. The pup growth rate decreased over the 7-year study period and was the lowest ever found in otariids, which suggests that lactating females experience constant low food availability. Male and female pups grew and survived at similar rates. Pups that were heavier at birth grew faster and exhibited better early survival (i.e., the first 2 months of life) than pups that were lighter at birth. However, no such relationship was detected for late survival (i.e., from 2 months to weaning) in this long-lactating species. No relationship was found between pup growth rate, pup survival rate, and sea-surface temperature (SST) gradient during the study period, especially during the later years of good trophic conditions (i.e., a high SST gradient). Such dissociations suggest that variation in food availability may not be the only factor influencing pup performance until weaning. We therefore propose that the subantarctic fur seal population is reaching its carrying capacity and that a density-dependent effect is occurring on Amsterdam Island.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".