Growth and condition in harp seals: evidence of density-dependent and density-independent influences
Bibliographic record
Abstract
Abstract Life history theory predicts that resource competition increases as a population increases, leading to changes in life history traits such as growth, survival, and reproduction. The Northwest Atlantic (NWA) harp seal population has increased from a low of 1.1 million animals in 1971 to over 7 million animals in 2014. Given this 7-fold increase in abundance, we hypothesized that density-dependent regulation might be reflected by changes in body growth. Gompertz curves fitted to size at age data for harp seals collected in the Gulf of St Lawrence over a 40 year period show a decline in female asymptotic length and mass. Body mass and condition were negatively related to reproductive rates the previous year, while a quadratic relationship (‘inverse u’) was observed between body measures and the ratio of the March:April first year ice cover, a measure of ice breakup. Condition was also negatively related to January ice cover. At high densities, reproduction is likely to be relatively more expensive for Northwest Atlantic harp seals, underlining the importance of females being able to access high energy food during the winter foraging period to build-up condition prior to pupping. A complex relationship between condition and the timing of ice-breakup likely reflects the influence of the timing of ice retreat on food resources and hence female ability to rebuild energy stores prior to moulting.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".