EFFECTS OF PREDATOR REMOVAL ON MALLARD DUCKLING SURVIVAL
Bibliographic record
Abstract
We experimentally evaluated the effect of predator removal on mallard (Anas platyrhynchos) duckling survival in south-central Saskatchewan, Canada, in 2000 and 2001. Previous predator-removal research has focused on nest success, but our study was the first to document an effect on duckling survival. We compared 4 control sites (no predator removal) with 4 treatment sites where professional trappers removed common nest predators. Survival of 686 ducklings from 78 broods was determined using radiotelemetry and periodic counts of ducklings. Duckling survival was higher on predator-removal sites relative to control sites in 2000 and 2001 and negatively correlated with hatch date in 2000. Results of analyses including and excluding hatch date as a covariate suggest that hatch date was confounded with predator removal (i.e., predator removal influenced hatch dates). Based on these results, we concluded that duckling survival was affected by predator removal in 2 ways. First, predator removal increased duckling survival by removing predators that likely caused total brood loss. Second, in-the-year hatch date was negatively correlated with duckling survival, earlier average hatch dates on predator-removal areas contributed to increased duckling survival. Combining the 2 effects and averaging over years, 30-day duckling survival was 0.573 (90% CI: 0.492 to 0.657) on predator-removal sites and 0.357 (90% CI: 0.275 to 0.456) on control sites. We concluded that predator-removal efforts conducted primarily to increase nest success of upland-nesting ducks also increased survival of mallard ducklings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".