The decline of <scp>S</scp>teller sea lions (<i><scp>E</scp>umetopias jubatus</i>) in the <scp>N</scp>orth <scp>P</scp>acific: insights from indigenous people, ethnohistoric records and archaeological data
Bibliographic record
Abstract
Abstract A number of hypotheses have been proposed to explain the most recent decline (1977–2012) of Steller sea lions (SSL; Eumetopias jubatus) in the Gulf of Alaska and Aleutian Islands. We examined hypotheses about fisheries competition, environmental change, predation, anthropogenic effects and disease using observations of modern Aleut and archaeological, ethnohistoric and ethnographic data from the western Gulf of Alaska and Aleutian Islands. These data indicate that Steller sea lion numbers have declined and recovered repeatedly over the past 4500 years and were last at critically low numbers during the 1870s–1930s. Steller sea lions appear to have been more abundant during the cool periods – and lower during the warmer periods. Observations by local peoples, explorers, early government surveyors and biologists since the late 1800s suggest that low populations of SSL have been associated with high populations of Gadidae fishes (Pacific cod – Gadus macrocephalus and walleye pollock – Theragra chalcogramma) and are consistent with the ocean climate hypothesis to explain the decline of sea lions. They suggest that removals by people and killer whales (Orcinus orca) did not cause the sea lion declines, but could have compounded the magnitude of the decline as sea lion numbers approached low densities. Archaeological, anthropological and ethnohistorical analyses demonstrate that fluctuations have occurred in the North Pacific over hundreds to thousands of years and provide context for understanding the changes that occur today and the changes that will continue to occur in the future.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".