A quantitative genetic analysis of hibernation emergence date in a wild population of Columbian ground squirrels
Bibliographic record
Abstract
The life history schedules of wild organisms have long attracted scientific interest, and, in light of ongoing climate change, an understanding of their genetic and environmental underpinnings is increasingly becoming of applied concern. We used a multi-generation pedigree and detailed phenotypic records, spanning 18 years, to estimate the quantitative genetic influences on the timing of hibernation emergence in a wild population of Columbian ground squirrels (Urocitellus columbianus). Emergence date was significantly heritable [h(2) = 0.22 ± 0.05 (in females) and 0.34 ± 0.14 (in males)], and there was a positive genetic correlation (r(G) = 0.76 ± 0.22) between male and female emergence dates. In adult females, the heritabilities of body mass at emergence and oestrous date were h(2) = 0.23 ± 0.09 and h(2) = 0.18 ± 0.12, respectively. The date of hibernation emergence has been hypothesized to have evolved so as to synchronize subsequent reproduction with upcoming peaks in vegetation abundance. In support of this hypothesis, although levels of phenotypic variance in emergence date were higher than oestrous date, there was a highly significant genetic correlation between the two (r(G) = 0.98 ± 0.01). Hibernation is a prominent feature in the annual cycle of many small mammals, but our understanding of its influences lags behind that for phenological traits in many other taxa. Our results provide the first insight into its quantitative genetic influences and thus help contribute to a more general understanding of its evolutionary significance.
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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 | 0.001 |
| 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) | 0.000 | 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".