Increased nest defence of upland‐nesting ducks in response to experimentally reduced risk of nest predation
Bibliographic record
Abstract
Parent birds should take greater risks defending nests that have a higher probability of success. Given high rates of mammalian nest predation, therefore, parents should risk more for nests in areas with a lower risk of mammalian predation. We tested this hypothesis using nest defence data from over 1300 nests of six species of dabbling ducks studied in an area where predation risk had been reduced through removal of mammalian predators. When predator removal reduced nest predation, the ducks increased risk taking as predicted. Also as predicted, risk taking varied inversely with body size, an index of annual survival, among species. For ducks to vary nest defence in response to variation in predation risk they must be able to assess the risk of nest predation. Because ducks modified nest defence in the breeding season immediately following predator removal, ducks may be able to assess predator abundance indirectly (e.g. by UV reflection from urine) rather than by seeing or interacting directly with the predators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".