Ocean climate and El Niño impacts on survival of Cassin's Auklets from upwelling and downwelling domains of British Columbia
Bibliographic record
Abstract
We report on the survival of populations of Cassin's Auklet (Ptychoramphus aleuticus) that breed on two oceanic colonies in British Columbia: Triangle Island, near the northern end of the California Current Ecosystem, and Frederick Island to the north in the Alaska Current Ecosystem. We captured and banded birds at both colonies from 1994 to 2000 and analyzed the recovery data with the computer program MARK. Average local adult annual survival (± standard error) was significantly lower (p = 0.0001) on Triangle Island (0.71 ± 0.02) than that on Frederick Island (0.80 ± 0.02), likely a result of poor production in the California Current Ecosystem during the 1990s. Coincident with a strong El Niño event, survival in 1997-1998 fell in unison to the lowest values observed for both colonies (to 0.54 ± 0.05 and 0.64 ± 0.04, respectively, for adults). A common winter environment in the California Current Ecosystem could explain the unified mortality response of both British Columbia populations to an exceptionally poor food period. The seabird colonies in this study occupy key positions in relation to major oceanographic domains and hence provide unique platforms for investigations of marine ecosystem response to ocean climate variability in the Northeast Pacific Ocean.
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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 | 0.001 | 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".