Are spatial and temporal patterns in Lynn Canal overwintering Pacific herring related to top predator activity?
Bibliographic record
Abstract
In Southeast Alaska, overwintering Pacific herring (Clupea pallasii) form large conspicuous schools that are preyed upon by an abundance of mammalian and avian predators, thus leading to the question of why herring adopt a strategy that appears counterproductive to predator avoidance during these periods. We examined the spatial and temporal dynamics of overwintering Pacific herring and associations with predators through monthly hydroacoustic surveys during two consecutive winters. Large variation was observed through the winter season in herring distribution, school morphology, and density. Herring school characteristics and biomass estimates were negatively correlated with humpback whale (Megaptera novaeangliae) abundance patterns during both winters, and as whales departed towards the end of winter, herring distributions shifted from dispersed schools in the water column toward deep, dense schools. We postulate that the schooling patterns observed in Lynn Canal overwintering herring are likely to be mediated by predation threat rather than energetics or feeding activities. An additional consequence of humpback whales dispersing herring in the water column may be an increased threat of predation by other surface-oriented predators.
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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 | 0.000 |
| 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".