Effects of small mammal cycles on productivity of boreal ducks
Bibliographic record
Abstract
North American boreal nesting waterfowl (and their eggs and ducklings) share a number of generalist predators with small mammals and non-migratory birds that could indirectly link fluctuations in these coexisting prey. We surveyed pairs and broods to determine an index of productivity for lesser scaup Aythya affinis breeding near Yellowknife, Northwest Territories, Canada. We also calculated a mallard Anas platyrhynchos productivity index for birds from northern Saskatchewan, Canada. Small mammal abundance was estimated by snap trapping rodents and by counting pellets of snowshoe hares Lepus americanus in the Yellowknife area. Because small mammal data were not available for the same area as mallard harvest survey data, correlation with an estimate of ruffed grouse Bonasa umbellus harvest was used because small mammal abundance and grouse are known to correlate positively. We found a positive correlation between the abundance of rodents and lesser scaup productivity suggesting a prey switching relationship for predators between their main prey (rodents) and alternative prey (lesser scaup, eggs and ducklings). A negative correlation between snowshoe hare abundance and lesser scaup productivity was also found as well as a negative correlation between ruffed grouse abundance and mallard productivity. Negative correlations suggest a possible shared predation relationship, where changes in main prey abundance (hares) may cause a numerical response in predators that influences predation rates of shared alternative prey (ducks, eggs and ducklings). Although our conclusions are based on correlations, they indicate that a great deal of variation in boreal duck productivity might be explained by the indirect effects of coexisting prey abundance. Further work is needed to determine causal mechanisms contributing to these relationships, the effect of cycles in small mammal populations and the overall importance of top-down predator regulation for regulating duck productivity in boreal forest.
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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 | 0.001 | 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".