Small between-year variations in nest predation rates are not related with between-year differences in predator identity
Bibliographic record
Abstract
Nest predation is one of the most important causes of nest failure in breeding birds and can vary extensively between sites and years. Different mechanisms governing predation rates may dominate in different years and this annual variation should therefore be evaluated directly. Here we document year-to-year variation in nest predation rates in two ecosystems (forest and salt meadows) within the mid-boreal forest zone to evaluate whether annual variation in nest predation rates are linked with annual variation in predator identity or the ratio between predator types. Year-to-year variation in predation rates was low in all experiments (non-significant differences in experiments 1 and 2), with a significant decrease only from 2005 (0.90%) to 2008 (0.70%), 2009 (0.65%) and 2010 (0.72%) in experiment 3. In addition, random intercept estimates indicated that two sites from experiment 1 showed higher predation rates in year 2 than in year 1. None of these differences were related with differences in apparent predator community structure or predator identity. This suggests that low between-year variation in nest predation rates may be common in areas where the predator communities are stable, and the existing variation cannot be explained by variation in predator identity alone.
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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 | 0.001 | 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".