A re‐evaluation of the role of killer whales <i>Orcinus orca</i> in a population decline of sea otters <i>Enhydra lutris</i> in the Aleutian Islands and a review of alternative hypotheses
Bibliographic record
Abstract
ABSTRACT During the past 15–20 years, sea otters Enhydra lutris in the Aleutian Islands, Alaska, USA, experienced a drastic decrease in population size. It has been hypothesized that an increase in killer whale Orcinus orca predation was the primary cause of this decline. Causation of the decline by increased killer whale predation is now considered a textbook case of top‐down predator control. The purpose of this review is to re‐evaluate the evidence for killer whale predation and to review evidence for alternative causes. The killer whale predation hypothesis is based on three lines of evidence: (i) there was an increase in the number of observed killer whale attacks on sea otters during the 1990s, coincident with a decline in sea otters, (ii) sea otter populations did not decline in areas considered inaccessible to killer whales, while they declined in adjacent areas considered accessible to killer whales, and (iii) the estimated number of attacks necessary to account for the rate of decline is similar to the observed number of attacks. Our re‐evaluation indicates that although the killer whale hypothesis is by no means disproved, the supporting data are limited and inconclusive. Increases in shark populations in the Aleutian Islands concurrent with the sea otter population declines indicate the need for further research into the role of alternative marine predators in the population decline. High contaminant levels observed in sea otters in the Aleutian Islands warrant further investigation into the impact of these toxins on sea otter health and vital rates, and their possible role on the population decline. Disease has not been ruled out as a significant contributor to the population decline, particularly in the early stages of the decline.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Re-evaluation of ecological evidence about sea otter decline; the object is an ecological hypothesis, not research practice.
The review evaluates ecological explanations for sea-otter population decline.
Ecological re-evaluation of killer whale predation on sea otters; domain wildlife ecology.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".