Experimental addition of cover lowers the perception of danger and increases reproduction in meadow voles (<i>Microtus</i> <i>pennsylvanicus</i>)
Bibliographic record
Abstract
Predation danger is pervasive for small mammals and is expected to select strongly for behavioural tactics that reduce the risk. In particular, since it may be considered a cost of reproduction, predation danger is expected to affect the level of reproductive effort. We test this hypothesis in a population of meadow voles (Microtus pennsylvanicus (Ord, 1815)) under seminatural conditions in field enclosures. We manipulated the voles’ perception of predation danger by adjusting the available cover and measured giving up density (GUD) in food patches to verify that the perception of danger differed between high- and low-cover treatments. Treatments did not differ in actual predation rate, in vole density, or in the quantity or quality of food. During the experiments, we measured indices of vole reproductive effort including activity (electronic detectors), foraging intensity (fecal plates), and the number of young produced (livetrapping). Voles in the high-cover (lower danger) treatments were more active, foraged more, and produced 85% more young per female per trap period than voles in the low-cover (higher danger) treatment. We briefly discuss the population consequences of this adaptive behavioural flexibility.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".