The seasonality of reproduction in photoperiod responsive and nonresponsive northern red-backed voles (Myodes rutilus) in Alaska
Bibliographic record
Abstract
High-latitude arvicoline rodents usually reproduce in warmer months, but winter breeding has been documented in several species, including the northern red-backed vole ( Myodes rutilus (Pallas, 1779) Wilson and Reader, 2005; formerly Clethrionomys rutilus (Pallas, 1779)). We tested whether the reproductive condition of the species is linked to changes in environmental parameters or its body condition, and we tested the frequencies at which different reproductive phenotypes are exhibited under field and laboratory conditions. Free-living voles in south-central Alaska reached peak reproductive organ masses in spring (females) and early summer (males). Between-subject comparisons showed an effect of body mass, photoperiod, percent fat, temperature, and snow depth on reproductive organ masses, depending on the sex and breeding period (p < 0.05). One instance of late-summer photoperiod nonresponsiveness was observed, but we detected no winter breeding. Captive male voles given food ad libitum and housed at room temperature exhibited strong phenotypic variation in testis mass in response to short photoperiods. The percentage of nonresponders was 28.2% and was within the known range of nonresponsiveness for lower latitude species (20%–40%). Thus, photoperiod nonresponsive morphs are conserved in at least one arctic and subarctic species at frequencies comparable to lower latitude voles despite no observance of winter breeding in the field. Voles exhibit reproductive elasticity and may breed in winter if environmental conditions enable them.
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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 | 0.000 |
| 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".