Variation in predator diet and prey size affects perceived impacts to salmon species of high conservation concern
Bibliographic record
Abstract
Management of protected species is difficult when objectives include the recovery of both predator and its prey. Ideally, identifying trade-offs between competing objectives involves evaluating management alternatives with a quantitative model that integrates information on both species, but data are often limited. We used new predator diet data and simulation modeling to update our understanding of seal predation on juvenile Chinook (Oncorhynchus tshawytscha) and coho salmon (Oncorhynchus kisutch) in the Puget Sound. Under prey size assumptions used by previous studies, estimates suggest predation could be a significant source of mortality for Chinook salmon (mean: 37% of ocean age-0 juveniles), but varied considerably among years (range of median estimates: 22%–49%). However, when we estimated prey size from otoliths recovered from seal scats, the impact (numbers of fish consumed) decreased by 71%. Predation on coho salmon was estimated to be relatively low under both scenarios (6%–8% of ocean age-0 juveniles) with a 21% decrease in consumption using otolith-derived prey size. Our analysis highlights the importance of updating model inputs and re-evaluating assumptions of multi-species models used for ecosystem-based fisheries management.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 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".