Shooting blanks: extreme climate event promotes phenological mismatch between sexes in hibernating ground squirrels
Bibliographic record
Abstract
Abstract Hibernating ground squirrels rely on a short active period for breeding and mass accrual, and are thus vulnerable to extreme climate events that affect key periods in their annual cycle. Here, we observed how a heatwave in March 2012 led to a phenological mismatch between sexes in Richardson’s ground squirrels (Urocitellus richardsonii). Females emerged from hibernation and commenced breeding earlier in 2012 relative to average female emergence. Despite external indicators suggesting that males were prepared for breeding, it appeared that not all males were physiologically prepared since 58.6% of males had non-motile sperm when breeding commenced. We found that males with non-motile sperm had smaller accessory glands than males with motile sperm. Body condition, relative testes size, and the relative size of accessory glands were significant predictors of sperm motility. There was no difference in litter size among years, nor a decrease in the number of juveniles emerged in 2012 or female yearlings recruited in 2013. The impact of this heatwave on male ground squirrels emphasizes the importance of assessing the consequences of climate change on breeding success of hibernating species in both sexes, since the different cues for emergence led to a mismatch in timing under this event.
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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 | 0.000 |
| 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) | 0.002 | 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".