Common Eider and large gull and nesting associations in coastal Labrador
Bibliographic record
Abstract
Apparent nesting associations between avian egg predators and their prey have received much interest, with gulls and waterfowl receiving considerable attention. We examined the co-occurrence of breeding large gulls (Herring Gull (Larus argentatus Pontoppidan, 1763) and Great Black-backed Gull (Larus marinus L., 1758)) and Common Eiders (Somateria mollissima L., 1758) along the coast of Labrador from 1998 to 2003. Nest counts for large gulls and eiders were undertaken by ground crews on 45–109 islands each year, counting 79–283 and 721–3424 nests annually, respectively. Gulls were more likely to nest on an island with nesting eiders (69.4%) than without nesting eiders (38.4%), and the probability and numbers of gulls nesting on an island increased as eider colony size increased. Large gulls were 1.76 times more likely to occupy islands that had nesting eiders in the previous year, while eiders were equally likely to colonize islands that did or did not have nesting gulls in the previous year. Eiders were no more likely to abandon islands that had nesting gulls in the previous year. In subarctic coastal landscapes, large gulls appear to preferentially nest in association with nesting eiders, while eiders appear not to avoid nesting islands based on the previous presence of large gulls.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".