Does Removal of Duck Nest Predators Affect the Temporal Patterns of Predation for Simulated Nests of Grassland Songbirds?
Bibliographic record
Abstract
We tested whether the temporal patterns of songbird nest predation changed following removal of predators of duck nests in North Dakota, USA, 1995-1996. Overall, 2286 simulated nests were deployed of which 951 were equipped with depredation timing devices that recorded the time of day of nest destruction. Predators destroyed 242 timer nests, and 155 depredation events were recorded. Temporal distribution of predation events was uniform over a 24-h period. However, predator groups, identified by using marks left on modeling clay eggs, depredated nests at different times. Mean times of depredation were 07h41, 12h57, 17h50, and 22h47 for small mammals, ground squirrels, birds, and medium-sized mammals, respectively. Daily depredation events occurred earlier on removal versus non-removal sites. However, within each predator group, there was no difference in depredation times between removal and non-removal sites. We suggest that the difference in time of depredation is caused by the differential importance of each predator group on removal versus removal sites, and thus conclude that removing duck nest predators does not affect temporal foraging patterns of smaller predators.
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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 | 0.002 |
| 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) | 0.000 | 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".