Maternal effects and the response to selection in red squirrels
Bibliographic record
Abstract
Mothers often provide much of the early environment for their offspring. These maternal effects are predicted to result in unusual evolutionary dynamics in offspring traits if they are themselves heritable, but these important predictions have not previously, to our knowledge, been tested in the wild. Here, we quantified the responses of red squirrels (Tamiasciurus hudsonicus) to documented episodes of natural selection and found support for both of the fundamental predictions of models that describe maternal effect evolution. First, changes in juvenile growth rates across one generation of selection were five times greater than predicted by heritability (h2) alone, but were consistent with the additional contribution of maternal genetic effects. Second, responses to selection were influenced not only by the strength of selection in the current generation, but also by selection in the previous generation, indicating the presence of evolutionary momentum. These results were in agreement with predictions of a simple model including litter size as the only maternal effect, and provide, to our knowledge, the first empirical evidence for the importance of maternal effects to evolutionary dynamics in a natural population.
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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".