Are goose nesting success and lemming cycles linked? Interplay between nest density and predators
Bibliographic record
Abstract
The suggested link between lemming cycles and reproductive success of arctic birds is caused by potential effects of varying predation pressure (the Alternative Prey Hypothesis, APH) and protective association with birds of prey (the Nesting Association Hypothesis, NAH). We used data collected over two complete lemming cycles to investigate how fluctuations in lemming density were associated with nesting success of greater snow geese ( Anser caerulescens atlanticus ) in the Canadian High Arctic. We tested predictions of the APH and NAH for geese breeding at low and high densities. Goose nesting success varied from 22% to 91% between years and the main egg predator was the arctic fox ( Alopex lagopus ). Nesting associations with snowy owls ( Nyctea scandiaca ) were observed but only during peak lemming years for geese nesting at low density. Goose nesting success declined as distance from owls increased and reached a plateau at 550 m. Artificial nest experiments indicated that owls can exclude predators from the vicinity of their nests and thus reduce goose egg predation rate. Annual nest failure rate was negatively associated with rodent abundance and was generally highest in low lemming years. This relationship was present even after excluding goose nests under the protective influence of owls. However, nest failure was inversely density‐dependent at high breeding density. Thus, annual variations in nest density influenced the synchrony between lemming cycles and oscillations in nesting success. Our results suggest that APH is the main mechanism linking lemming cycles and goose nesting success and that nesting associations during peak lemming years (NAH) can enhance this positive link at the local level. The study also shows that breeding strategies used by birds (the alternative prey) could affect the synchrony between oscillations in avian reproductive success and rodent cycles.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".