Is the risk of nest predation heterospecifically density-dependent in precocial species belonging to different nesting guilds?
Bibliographic record
Abstract
Nest predation is a key source of mortality and variation in fitness, but the effect co-occurring species belonging to different nesting guilds have on each other’s nest success is poorly understood. By using artificial nests, we tested if predation on cavity nests of Common Goldeneyes ( Bucephala clangula (L., 1758)) is increased in the presence of ground nests of Mallards ( Anas platyrhynchos L., 1758) and vice versa. Specifically, by adding ground nests in the vicinity of cavity nests, we tested the hypothesis that predation on cavity nests is heterospecifically density-dependent. A shared predator, the pine marten ( Martes martes (L., 1758)), was intensively hunted in one of the study areas, but not in the other, leading to most individuals in the former being naïve immigrants. Cavity-nest fate was not affected by addition of ground nests. Similarly, ground-nest survival did not decrease when nearby cavity nests were depredated. Fate of nests in a given nest cavity was highly predictable between years in the study area with minimal removal of pine martens, but not in the one with intensive removal. Predation rate was higher on cavity nests than on ground nests. Predation on ground nests was lower in the study area with intensive removal of pine martens. We conclude there was neither apparent competition between guilds nor heterospecific density-dependence in predation risk.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".