Nest Attributes, Aggression, and Breeding Success of Gulls in Single and Mixed Species Subcolonies
Bibliographic record
Abstract
We investigated attributes of nests, aggressive interactions, and reproductive success in mixed and single species subcolonies of Great Black-backed Gulls (Larus marinus) and Herring Gulls (L. argentatus) on Appledore Island, Maine. Distances to the nearest neighboring nest were smaller for L. argentatus than L. marinus, with greatest distances between nests at edges of subcolonies in both species. More L. argentatus nests had natural screens (vegetation or rock >30 cm tall) adjacent to them than did L. marinus nests, but screen presence did not differ among nest positions within the colony. Clutch size did not differ between species; however, hatching success (number of chicks hatched per nest) was higher in L. argentatus than L. marinus. Fledging success (number of chicks fledged per nest) of L. marinus was greater at nests with heterospecific neighbors, whereas the opposite was true for L. argentatus. For both species, the frequency of aggressive interactions was lower at nests with L. argentatus neighbors. Overall, L. marinus nesting near L. argentatus experienced less aggression and greater reproductive success than those nesting among conspecifics, where intraspecific aggression was relatively high. L. argentatus nesting near L. marinus experienced more aggression and lower reproductive success than those nesting among conspecifics, where intraspecific aggression was relatively low. The costs and benefits of nesting in mixed species colonies may depend on the relative size and aggressiveness of the heterospecifics. Interactions with L. marinus in mixed species colonies may be contributing to the current declines of L. argentatus throughout New England.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".