Spatial segregation and the influence of habitat on the foraging behavior of northern fur seals (<i>Callorhinus ursinus</i>)
Bibliographic record
Abstract
Central place foraging by colonial breeders can lead to depleted prey resources around breeding areas. Segregation of foraging areas both within and between large colonies may act as a mechanism to reduce competition for prey resulting in increased foraging success. We reassessed horizontal (spatial) foraging habitat segregation for northern fur seals (Callorhinus ursinus (L., 1758)) within and between colonies on the Pribilof Islands, Alaska (St. Paul and St. George islands), after the population declined by approximately 40%. Additionally, we examined vertical habitat segregation, where foraging ranges overlapped, and describe the influence of different foraging habitats on northern fur seal dive behavior. Spatial habitat segregation in northern fur seal foraging areas occurred between islands but was variable within islands, which is similar to the pattern previously described. There was no evidence for vertical habitat segregation when fur seals from different rookeries on St. George Island used the same foraging area. Additionally, fur seals from St. Paul Island rookeries that foraged in similar habitats showed fewer differences in dive behavior, indicating that foraging habitat plays a significant role in shaping dive behavior. The use of multiple foraging strategies within the Pribilof Island fur seal population could indicate that a complex management and conservation strategy may be necessary to stop the continuing decline of this population.
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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 | 0.001 |
| 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".