Effects of Large‐Scale Predator Reduction on Nest Success of Upland Nesting Ducks
Bibliographic record
Abstract
ABSTRACT Population growth for mallards ( Anas platyrhynchos ), and presumably other upland nesting ducks, in the Prairie Pothole Region of the United States and Canada is most sensitive to nest success, and nest success is most strongly influenced by predation. We evaluated the efficacy of reducing predator populations to improve nest success of upland nesting ducks on township‐sized (93.2 km 2 ) management units in eastern North Dakota, USA, during 2005–2007. We monitored 7,489 nests on 7 trapped and 5 nontrapped sites. Trappers annually removed an average of 245 predators per trapped site, and we found nest success to be 1.4–1.9 times greater on trapped sites than nontrapped sites, depending on year. Nest success was greater on both trapped and nontrapped sites when compared with a study conducted in the same areas in the mid‐1990s, likely because of changes in red fox ( Vulpes vulpes ) and coyote ( Canis latrans ) population dynamics. Nests initiated midseason had higher daily survival rates (DSR) than those initiated earlier or later in the season. Daily survival rates for nests in the middle of the nesting cycle were higher than for nests that were early in laying or late in incubation. Nests near the periphery of trapped sites had slightly higher DSRs than nests in the center of trapped sites. Predator reduction at the township scale provides managers with an effective tool to improve nest success at large spatial scales.
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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 | 0.000 | 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) | 0.000 | 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 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".