Consistent differences among individuals more influential than energetic trade-offs in life history variation in grey seals ( <i>Halichoerus grypus</i> )
Bibliographic record
Abstract
Abstract Life history variation is thought to be mainly a result of energetic trade-offs among fitness components; however, detecting these trade-offs in natural populations has yielded mixed results. Individual quality and environmental variation may mask expected relationships among fitness components because some higher quality individuals may be able to acquire more resources and invest more in all functions. Thus, life history variation may be more affected by variation in individual quality than varying strategies to resolve energetic trade-offs, e.g. costs of reproduction. Here, we investigated whether variation in female quality or costs of reproduction is a larger factor in shaping differences in life history trajectories by assessing the relationship between survival and individual reproductive performance using a 32-year longitudinal data set of repeated reproductive measurements from 273 individually marked, known-aged female grey seals ( Halichoerus grypus ) from the Sable Island breeding colony. We defined individual reproductive performance using two traits: reproductive frequency (a female’s probability of breeding) and provisioning performance (provisions given to young measured by offspring mass), computed using mixed effects models separately for (1) all reproductive events, and (2) an age-class specific reproductive investment. Individual differences contributed a large portion of the variance in reproductive traits, with individuals displaying a range in individual reproductive frequencies from 0.45 to 0.94, and a range of average pup weaning masses from 34.9 kg to 61.8 kg across their lifetime. We used a Cormack-Jolly-Seber open-population model to estimate the effect of these reproductive performance traits on adult survival probability. Our approach estimated a positive relationship between reproductive performance and survival, where individuals that consistently invest well in their offspring survive longer. The best supported model estimated survival as a function of age-class specific provisioning performance, where late-life performance was quite variable and had the greatest impact on survival, possibly indicating individual variation in senescence. There was no evidence to support a trade-off in reproductive performance and survival at the individual level. These results suggest that in grey seals, individual quality is a stronger driver in life history variation than varying strategies to mitigate trade-offs among fitness components.
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 | 0.001 | 0.001 |
| 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 | 0.000 | 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".