Sex‐dependent habitat selection modulates risk management by meadow voles
Bibliographic record
Abstract
Abstract Foraging involves a trade‐off between food and safety. Most research into the trade‐off invokes safety from predation. But danger and its associated risk arise from multiple causes that cannot be assessed solely with reference to predators. A more complete assessment of risk management requires experimental designs that attempt to modify and measure risks, regardless of the source of danger. I aimed to do so by adding shelter (mulched straw) and time‐varying supplemental food (rabbit chow), while measuring foraging behavior and habitat use by a seminatural population of meadow voles. Voles foraged more intensely under safety, recognized least risk when given access to both food and shelter, but altered their risk management through time: management included a novel form of sex‐dependent habitat selection in which male–male pairs occupied risky areas without shelter while female–female pairs occupied habitats sheltered by straw. The pattern is consistent with a sex‐dependent evolutionary game in which female territoriality and tolerance of other females limit conflict with, and space use by, males. Voles' array of interacting strategies demonstrates that ecologists must be wary of ascribing risk only to predation, and particularly so if experiments are blind to other dangers and processes that alter foraging behavior and habitat selection.
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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) | 0.001 | 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".