Lovers, not fighters: docility influences reproductive fitness, but not survival, in male Cape ground squirrels, Xerus inauris
Bibliographic record
Abstract
Over their lifetime, individuals may use different behavioural strategies to maximize their fitness. Some behavioural traits may be consistent among individuals over time (i.e., 'personality' traits) resulting in an individual behavioural phenotype with different associated costs and benefits. Understanding how behavioural traits are linked to lifetime fitness requires tracking individuals over their lifetime. Here, we leverage a long-term study on a multi-year living species (maximum lifespan ~ 10 years) to examine how docility (an individual's reaction to trapping and handling) may contribute to how males are able to maximize their lifetime fitness. Cape ground squirrels are burrowing mammals that live in social groups, and although males lack physical aggression and territoriality, they vary in docility. Males face high predation risk and high reproductive competition and employ either of two reproductive tactics ('natal' or 'band') which are not associated with different docility personalities. We found that although more docile individuals sired more offspring on an annual basis, docility did not affect an individual's long-term (lifetime) reproductive output. Survival was not associated with docility or body condition, but annual survival was influenced by rainfall. Our findings suggest that although docility may represent a behavioural strategy to maximize fitness by possibly playing a role in female-male associations or female mate-choice, variations in docility within our study population is likely maintained by other environmental drivers. However, individual variations in behaviours may still contribute as part of the 'tool kit' individuals use to maximize their lifetime fitness. Supplementary Information: The online version contains supplementary material available at 10.1007/s00265-023-03421-8.
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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 | 0.000 | 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".