Risks of carbamate and organophosphate pesticide mixtures to salmon in the Pacific Northwest
Bibliographic record
Abstract
Salmon populations in the Pacific Northwest are being affected by a variety of environmental stressors including intense fishing pressure, parasites and disease, climatic variability and change, land development, hatchery production, hydropower operations, stormwater runoff, and exposure to toxic contaminants. In recent years, there has been much concern that mixtures of pesticides are causing toxic effects to Pacific salmon. In this study, we compared measured stream water concentrations from 2 monitoring studies conducted in the Pacific Northwest with concentration-response curves derived for inhibition of brain acetylcholinesterase activity in juvenile coho salmon (Oncorhynchus kisutch) for mixtures of organophosphate (OPs) and carbamate (CBs) pesticides. In the first monitoring study, samples were collected from 2003 to 2007 in salmonid-bearing waters of 5 urban or agricultural watersheds in Washington State. This study was targeted to areas of high pesticide use and generally involved weekly sampling during the pesticide use season. The second monitoring study was the United States Geological Survey National Water Quality Assessment that included samples taken from 2003 to 2010 in California, Idaho, Oregon, and Washington. OPs and CBs were frequently detected in both studies. The available monitoring data collected since 2003, however, demonstrates that mixtures of OPs and CBs in surface waters rarely occur at levels capable of producing significant physiological and behavioral effects in Pacific salmon. The observed mixtures never reached concentrations capable of causing mortality. We conclude that mixtures of organophosphates and carbamates do not pose a significant direct risk to Pacific salmon.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.001 | 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 teacher head, 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".