Bioamplification and the Selective Depletion of Persistent Organic Pollutants in Chinook Salmon Larvae
Bibliographic record
Abstract
The maternal provisioning of yolk to eggs transfers significant quantities of persistent organic pollutants (POPs). As yolk utilization progresses via metabolic activity, there is a potential to realize further increases in POP concentrations if yolk lipids are depleted at a faster rate than POPs, a condition referred to as bioamplification. This study investigated the bioamplification of POPs in Chinook salmon ( Oncorhynchus tshawytscha ) eggs and larvae. Chinook eggs were sampled from the Credit River, ON, Canada, and brought to an aquaculture facility where they were fertilized, incubated, and maintained posthatch until maternally derived lipid reserves became depleted (approximately 168 days). The loss of chemicals having an octanol-water partition coefficient (log K(OW)) greater than 5.8 was slow to negligible from days 0-135. However, during the increase in water temperatures in early spring, K(OW)-dependent elimination of POPs was observed. Bioamplification was maximized for the highest log K(OW) POPs, with an approximate 5-fold increase in lipid equivalents concentrations in 168 day old larvae as compared to newly fertilized eggs. This study demonstrates that later yolk-sac Chinook larvae (before exogenous feeding) are exposed to higher lipid equivalents POP concentrations than predicted by maternal deposition, which could lead to underestimates in the toxicity of critical life stages.
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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 | 0.000 | 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".