Stable Isotope Values in South American Fur Seal Pup Whiskers as Proxies of Year-round Maternal Foraging Ecology
Bibliographic record
Abstract
Abstract Natural selection should favour strategies that maximise reproductive success. Females may use different resources during progressive stages of reproduction according to energetic demands, behavioural constraints and prey availability. We used South American fur seal,Arctocephalus australis australis, pup whisker isotope values as proxies for maternal diet and habitat use to determine how resource use (1) changes throughout pup development from in utero growth to mid-end of lactation and (2) how it differs among individuals. The longest whisker was cut from 5 male and 5 female fur seal pups (of approximately 8 months of age) at Bird Island, Falkland Islands, in 2018, andδ15N values andδ13C values were analysed every 5 mm along the length of each whisker. Patterns inδ13C values indicated that mothers used different habitats during the annual cycle, likely coinciding with seasonal shifts in prey availability or distribution. The individual specialisation index based onδ13C values was 0.34, indicating that adult females used different habitats, which could reduce intra-specific competition and ultimately enhance pup growth and survival. An increase inδ15N values occurred along every pup whisker from pup birth to mid-end of lactation, which likely reflected trophic enrichment related to suckling and fasting by pups, overriding the maternal isotopic signature. Pup whisker stable isotopes are useful proxies of maternal foraging ecology. However, physiological processes complicate interpretations by alteringδ15N values. Interpreting these values therefore requires additional knowledge of the species’ ecology and physiology.
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 | 0.001 | 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".