The association between female reproductive performance and leukocyte telomere length in wild Soay sheep
Bibliographic record
Abstract
Telomere length (TL), typically measured across a sample of blood cells, has emerged as an exciting potential marker of physiological state and of the costs of investment in growth and reproduction within evolutionary ecology. While there is mounting evidence from studies of wild vertebrates that short TL predicts raised subsequent mortality risk, the relationship between reproductive investment and TL is less clear cut, and previous studies report both negative and positive associations. In this study, we examined the relationship between TL and different aspects of maternal reproductive performance in a free-living population of Soay sheep. We find evidence for shorter TL in females that bred, and thus paid any costs of gestation, compared to females that did not breed. However, we found no evidence for any association between TL and litter size. Furthermore, females that invested in gestation and lactation actually had longer TL than females who only invested in gestation because their offspring died shortly after birth. We used multivariate models to decompose these associations into among- and within-individual effects, and discovered that within-individual effects were driving both the negative association between TL and gestation, and the positive association between TL and lactation. This suggests that telomere dynamics may reflect recent physiologically costly investment or variation in physiological condition, depending on the aspect of reproduction being investigated. Our results highlight the physiological complexity of vertebrate reproduction, and the need to better understand how and why different aspects of physiological variation underpinning life histories impact blood cell TL.
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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 | 0.000 | 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) | 0.001 | 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".