Experimental predator removal: a response in small mammal communities and relations to duck nest success
Bibliographic record
Abstract
Reducing predator populations in the prairie pothole region can greatly increase nest success of both over water and upland nesting ducks. However, little is understood about impacts of predator removal on other wildlife within the same area. I conducted a field experiment to test whether small mammals, primarily mice (Peromyscus sp.) and voles (Microtus sp.), responded to seasonally reduced predator abundance. I compared small mammal abundance on 10 experimental (259 ha) sites in North Dakota during 2001 and 2002 with intensive, seasonal predator trapping with 10 control sites (259 ha) also monitored in both years. Small mammals were more abundant on sites where predators had been removed (F3,132= 44.45, P<0.001), suggesting that small mammals responded numerically to an absence of medium-sized carnivores. However, levels of small mammals were comparable in both springs, suggesting that enlarged populations of rodents in summer and early fall were not sustained through winter. I also observed a strong positive relationship between small mammal abundance and duck nest success (r = 0.84, P = 0.002 in 2001; r= 0.82, P = 0.004 in 2002), suggesting a possible buffer effect small mammals may have on predation of waterfowl nest.
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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 | 0.001 |
| 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 | 0.001 |
| 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".