Characterizing Contaminant Concentrations in Priority Chinook Salmon Stocks Consumed by Resident Killer Whales in the Northeastern Pacific Ocean
Bibliographic record
Abstract
The critically endangered, transboundary Southern Resident Killer Whale (SRKW) (Orcinus orca) population faces significant threats including a reduced abundance of their primary prey (Chinook salmon, Oncorhynchus tshawytscha), physical and acoustic disturbance, and high levels of endocrine disrupting contaminants. However, the sympatric Northern Resident Killer Whales (NRKW) that also primarily consume Chinook salmon have had continued population growth and have lower contaminant burdens. Studies have reported adverse health effects from contaminant burdens in transient killer whales and NRKWs. Contaminant exposure modeling has predicted protracted health risks for both resident killer whale populations. Despite Chinook salmon from the Fraser River watershed in British Columbia, Canada compromising up to 90% of the SRKW diet during the summer months, little contaminant information exists for these priority stocks, as well as other priority Chinook stocks from other Canadian rivers. Characterizing contaminant concentrations in SRKWs is exceedingly difficult due to their small population size, endangered status, and long-range habitat movements. Chinook salmon can be used as a proxy for helping to characterize contaminants and their risks to SRKWs. In the current study, muscle tissue from nine priority Chinook stocks consumed by SRKWs and NRKWs were assessed for concentrations of five priority contaminants classes (PCBs, PBDEs, OCPs, Dioxin Furans, and Chlorinated paraffins) and stable isotope (d13C, d15N, d34S) profiles. This enabled the characterization of contaminants in priority Chinook stocks and allowed for a preliminary assessment of exposure between two sympatric resident killer whale populations. Collections were done via partnerships with First Nations, recreational and commercial anglers, and the Albion test fishery. Stable isotopes and stock migrations were used to investigate variables affecting differences in the accumulation of contaminants. This evaluation of contaminants found in resident killer whale priority Chinook stocks will help to deliver refined guidance to support the wider conservation agenda for these at risk species.
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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 | 0.001 | 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) | 0.000 | 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".