Quantifying gull predation in a declining Leach’s Storm-petrel ( Hydrobates leucorhous ) colony
Bibliographic record
Abstract
The effect of gull predation on sympatric seabirds has garnered much attention and management action in recent decades. In Witless Bay, Newfoundland, Canada, gulls depredate significant numbers of Leach’s Storm-petrels (Hydrobates leucorhous) annually. We quantified this predation on Gull Island in Witless Bay, and its effects on the storm-petrel population, by estimating the annual gull predation rate using strip transects to count storm-petrel carcasses and predicting storm-petrels’ population growth rate by repeating an island-wide breeding census. Using methods that account for island topography, we found that the Leach’s Storm-petrel breeding population on Gull Island declined to roughly 180,000 pairs in 2012 (95% CI: 130,000–230,000), a decrease of 6% per year since the last census in 2001 (352,000 pairs). Based on carcass counts, gulls, mostly American Herring Gulls (Larus argentatus smithsonianus), depredated 118,000–143,000 Leach’s Storm-petrels in 2012. Studies of storm-petrel recruitment, the contribution of the large non-breeding component of the population to gulls’ diets, and the consequences of gulls’ storm-petrel diet on the gulls themselves are needed to better predict the trajectory of both species into the future.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".