Kin selection in Columbian ground squirrels: direct and indirect fitness benefits
Bibliographic record
Abstract
Empirical and theoretical studies have supported kin selection by demonstrating nepotism or modelling its conditions and consequences. As an alternative, we previously found that female Columbian ground squirrels had greater direct fitness when more close kin were present. Extending those results, we used population matrix methods to calculate minimum estimates of individual fitness, estimated direct and indirect components of fitness, estimated inclusive fitness by adding the direct fitness (stripped of estimated influences of the social environment) and indirect fitness components together, and finally looked for inclusive fitness benefits of associations with close kin who seem to be 'genial neighbours'. We examined the estimated fitness of a sample of 35 females for which complete lifetimes were known for themselves, their mothers and their littermate sisters. Six of these females had no cosurviving adult close kin, and their direct fitness was significantly lower than 29 females with such kin (λ = 0.66 vs. λ = 1.23). The net fitness benefit of the presence of close kin was thus 0.57. The estimated indirect component of fitness through benefits to the direct fitness of close kin was 0.43. Thus, estimated inclusive fitness for females with cosurviving close kin (λ = 1.09) was significantly greater than that for females without surviving close kin (viz., λ = 0.66). The presence of closely related and philopatric female kin appeared to result in considerable fitness benefits for female ground squirrels, perhaps through the behavioural mechanisms of lowered aggression and other forms of behavioural cooperation.
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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 | 0.000 |
| 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".