Subcolony Variation in Breeding Success in the Tufted Puffin (Fratercula Cirrhata): Association With Foraging Ecology and Implications
Bibliographic record
Abstract
Abstract Large-scale oceanographic processes are the main drivers of seabird breeding success, but small-scale processes, though not as well understood, can also be important. We compared the success of Tufted Puffins (Fratercula cirrhata) breeding at two subcolonies only 1.5 km apart on Triangle Island, British Columbia, Canada, 2002–2005. In addition, we used stable-isotope analysis to test the hypothesis that parental foraging strategies differed between the two subcolonies, potentially underlying the variation in breeding success. Success was concordant across years at the two sites but, overall, Tufted Puffins bred more successfully at Strata Rock than at Puffin Rock. They raised chicks in all four years at Strata Rock, but in only three years at Puffin Rock; in two of those three years, Strata Rock chicks were, on average, 60 g and 100 g heavier than Puffin Rock chicks just before fledging. Discriminant analysis of carbon and nitrogen stable-isotope ratios in egg yolk and chick blood in 2004 and 2005 indicated that parental foraging differed between the two subcolonies, with both spatial (δ13C) and trophic-level (δ15N) differences involved. Thus, our study demonstrates the existence of foraging asymmetries in a pelagic seabird at a small spatial scale (between subcolonies), complementing patterns found at larger scales (between colonies). Moreover, the foraging asymmetries were associated with inequalities in fitness measures. We conclude that small-scale processes—in this case, systematic differences in the foraging ecology of local groups—can interact with large-scale oceanographic processes to determine seabird breeding success. Variation sous-coloniale du succès de reproduction de Fratercula cirrhata: Association avec l'écologie de la quête alimentaire et implications
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".