Climate change and the initiation of spring breeding by deer mice in the Kananaskis Valley, 1985–2003
Bibliographic record
Abstract
Deer mice (Peromyscus maniculatus (Wagner, 1845)) in the Kananaskis Valley were monitored from 1985 to 2003 by livetrapping, and first parturition dates were compared among years and examined in relation to spring weather. On average, first litters were conceived on 2 May, well after the winter snowpack melted (19 March) and just before average temperatures reached 0 °C (8 May). First parturitions took place on 26 May, when average temperatures were above freezing. The average temperature at the time of conceptions (late April – early May) declined by approximately 2 °C, and the date that the average temperatures reached 0 °C was 11 days later, between 1985 and 2003, with potential effects for summer phenology. Spring temperatures, but not snowfall, were related to the El Niño Southern Oscillation index. The initiation of breeding by deer mice was variable among years, but was not related to snowfall or temperature and did not change, on average, between 1985 and 2003. The decrease in spring temperatures had no noticeable effects on breeding success. We conclude that photoperiod may be a primary cue for the initiation of spring breeding and that food resources over winter may explain the among-year variation in the initiation of breeding.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".