Early‐life seasonal, weather and social effects on telomere length in a wild mammal
Bibliographic record
Abstract
Early-life environmental conditions can provide a source of individual variation in life-history strategies and senescence patterns. Conditions experienced in early life can be quantified by measuring telomere length, which can act as a biomarker of survival probability in some species. Here, we investigate whether seasonal changes, weather conditions and group size are associated with early-life and/or early-adulthood telomere length in a wild population of European badgers (Meles meles). We found substantial intra-annual changes in telomere length during the first 3 years of life, where within-individual effects showed shorter telomere lengths in the winter following the first spring and a trend for longer telomere lengths in the second spring compared to the first winter. In terms of weather conditions, cubs born in warmer, wetter springs with low rainfall variability had longer early-life (3-12 months old) telomeres. Additionally, cubs born in groups with more cubs had marginally longer early-life telomeres, providing no evidence of resource constraint from cub competition. We also found that the positive association between early-life telomere length and cub survival probability remained when social and weather variables were included. Finally, after sexual maturity, in early adulthood (i.e., 12-36 months) we found no significant association between same-sex adult group size and telomere length (i.e., no effect of intrasexual competition). Overall, we show that controlling for seasonal effects, which are linked to food availability, is important in telomere length analyses, and that variation in telomere length in badgers reflects early-life conditions and also predicts first year cub survival.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".