Effects of extreme climate events on adult survival of three Pacific auks
Bibliographic record
Abstract
Climate change is predicted to increase the frequency and severity of extreme climate events, and it is important that we understand how this might affect natural systems. We examined the effects of extreme climate events on adult survival rates in three species of auks breeding on Triangle Island, British Columbia: Cassin's Auklet (Ptychoramphus aleuticus), Rhinoceros Auklet (Cerorhinca monocerata), and Tufted Puffin (Fratercula cirrhata). Our 15-year study period (1994–2008) included two extreme climate events: a strong El Niño event in 1997–1998 and an atmospheric blocking event in 2005. Neither event had any detectable effect on the annual adult survival rate (± 95% confidence interval) of either Tufted Puffins (females: 0.96 ± 0.05; males: 0.91 ± 0.06) or Rhinoceros Auklets (0.86 ± 0.02 in both sexes). By contrast, the adult survival of female Cassin's Auklets was halved during both extreme climate events (from a background rate of 0.84 ± 0.05 to 0.44 ± 0.10), whereas survival of males was low, but constant through time (0.75 ± 0.03). Our results, combined with those of previous studies, suggest that the major ongoing decline in the Cassin's Auklet population on Triangle Island is driven by negative effects of climatic variation on both reproductive success and the survival of adult females. Climate change may result in continued Cassin's Auklet population declines at this and more southerly colonies. By contrast, the relative stability of Rhinoceros Auklet and Tufted Puffin populations is likely attributable to the resiliency of adult survival rates to climatic conditions.
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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 | 0.000 | 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".