SELECTION ON HERITABLE SEASONAL PHENOTYPIC PLASTICITY OF BODY MASS
Bibliographic record
Abstract
The ability to cope with environmental change is fundamental to a species' evolution. Organisms can respond to seasonal environmental variation through phenotypic plasticity. The substantial plasticity in body mass of temperate species has often been considered a simple consequence of change in environmental quality, but could also have evolved as an adaptation to seasonality. We investigated the genetic basis of, and selection acting on, seasonal plasticity in body mass for wild bighorn sheep ewes (Ovis canadensis) at Ram Mountain, Alberta, under two contrasting environmental conditions. Heritability of plasticity, estimated as mass-specific summer and winter mass changes, was low but significant. The additive genetic variance component of relative summer mass change was greater under good environmental conditions (characterized by a population increase and high juvenile survival) than under poor conditions (population decrease and low juvenile survival). Additive genetic variance of relative winter mass change appeared independent of environmental conditions. We found evidence of selection on summer (relative) and winter (relative and absolute) mass change. For a given mass, more plastic individuals (with greater seasonal mass changes) achieve greater fitness through reproduction in the following year. However, genetic correlations between mass parameters were positive. Our study supports the hypothesis that seasonal plasticity in body mass in vertebrates is an adaptation that evolved under natural selection to cope with environmental variation but genetic correlations with other traits might limit its evolutionary potential.
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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 | 0.001 |
| 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".