Spacing behavior and morphology predict promiscuous mating strategies in the rock-dwelling snow vole, <i>Chionomys nivalis</i>
Bibliographic record
Abstract
Adaptive models predict that variation in the spacing of microtines during reproductive periods may reflect mating strategies linked to differences in habitat characteristics. Using spatial and morphological analyses, we aimed to assess the mating system adopted by a population of rock-dwelling snow voles, Chionomys nivalis (Martins, 1842), and its functional significance within high-mountain environments. Spacing data coincided with a pattern generally associated with promiscuous mating: males had largely overlapping home ranges, whereas female home ranges showed a very reduced or absent degree of overlap. In addition, ranges overlapped considerably between sexes. Males had significantly greater body mass than females, and the magnitude of this difference resembled more a promiscuous than a polygamous or monogamous species. Also, relative testis size of males was in the range reported for promiscuous voles. Our results fit the predictions made by food abundance and distribution optimality models, suggesting that mating strategies might be related to the habitat occupied by C. nivalis. In alpine rocky formations, vegetation is sparse and patchily distributed, and competing females could benefit from defending an exclusive territory. In turn, males might be unable to monopolize widely spaced females by defending exclusive territories, which may result in extensive overlap between their spatial ranges.
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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 | 0.000 |
| 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".