Adult Chinook salmon diets delineate regions with distinct forage assemblages in the Salish Sea
Bibliographic record
Abstract
Forage fish are an important link between zooplankton and higher trophic levels, including marine mammals and economically valuable predatory fish. However, forage fish are often difficult to assess using traditional fishery-independent surveys, resulting in major data gaps for both commercially important and non-exploited species. In the Salish Sea, there are many data gaps about the distribution and regional importance of forage fish and other forage species (e.g., juvenile Gadiformes, euphausiids, crustacean larvae). We used the diet composition of adult Chinook salmon (Oncorhynchus tshawytscha), a generalist predator, to examine the spatial structure of forage assemblages in the Canadian Salish Sea from 2017 – 2021. Stomach contents analysis of >1700 stomachs revealed that the importance of forage species such as Pacific herring (Clupea pallasii), northern anchovy (Engraulis mordax), and Pacific sand lance (Ammodytes personatus) varied spatially and seasonally. Cluster analysis of Chinook salmon diet composition identified regions of the Salish Sea with distinct forage assemblages. The spatial structure identified here has implications for efforts to model and protect the food web supporting Chinook salmon, their marine mammal predators, and other economically and ecologically important species in the Salish Sea. This study demonstrates the utility of predator diet sampling to provide important data on forage species at spatial and temporal scales difficult to achieve using traditional fishery-independent surveys.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".