Slow life-history strategies are associated with negligible actuarial senescence in western Palaearctic salamanders
Bibliographic record
Abstract
Actuarial senescence has been viewed for a long time as an inevitable and uniform process. However, the work on senescence has mainly focused on endotherms with deterministic growth and low regeneration capacity during the adult stage, leading to a strong taxonomic bias in the study of ageing. Recent studies have highlighted that senescence could indeed display highly variable trajectories that correlate with species life-history traits. Slow life histories and indeterminate growth seem to be associated with weak and late senescence. Furthermore, high regenerative abilities could lead to negligible senescence in ectotherms. However, demographic data for species that would allow testing of these hypotheses are scarce. Here, we investigated senescence patterns in 'true salamanders' from the western Palaearctic. Our results showed that salamanders have slow life histories and that they experience negligible senescence. This pattern was consistent at both intra- and interspecific levels, suggesting that the absence of senescence may be a phylogenetically conserved trait. The regenerative capacities of salamanders, in combination with other physiological and developmental features such as an indeterminate growth and a low metabolic rate, probably explain why these small ectotherms have lifespans similar to that of large endotherms and, in contrast with most amniotes, undergo negligible senescence. Our study seriously challenges the idea that senescence is a ubiquitous phenomenon in the tree of life.
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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 | 0.000 | 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".