An Assessment of the Toxicity of Pesticide Mixtures in Periphyton from Agricultural Streams to the Mayfly <i>Neocloeon triangulifer</i>
Bibliographic record
Abstract
Residual concentrations of pesticides are commonly found outside the intended area of application in Ontario's surface waters. Periphyton are a vital dietary component for grazing organisms in aquatic ecosystems but can also accumulate substantial levels of pesticides from the surrounding water. Consequently, grazing aquatic organisms are likely subjected to pesticide exposure through the consumption of pesticide-contaminated periphyton. The objectives of the present study were to determine if pesticides partition into periphyton in riverine environments across southern Ontario and, if so, to determine the toxicity of pesticides in periphyton when fed to the grazing mayfly Neocloeon triangulifer. Sites with low, medium, and high pesticide exposure based on historic water quality monitoring data were selected to incorporate a pesticide exposure gradient into the study design. Artificial substrate samplers were utilized to colonize periphyton in situ, which were then analyzed for the presence of approximately 500 pesticides. The results demonstrate that periphyton are capable of accumulating pesticides in agricultural streams. A novel 7-day toxicity test method was created to investigate the effects of pesticides partitioned into periphyton when fed to N. triangulifer. Periphyton collected from the field sites were fed to N. triangulifer and survival and biomass production recorded. Survival and biomass production significantly decreased when fed periphyton colonized in streams with catchments dominated by agricultural land use (p < 0.05). However, the relationship between pesticide concentration and survival or biomass production was not consistent. Using field-colonized periphyton allowed us to assess the dietary toxicity of environmentally relevant concentrations of pesticide mixtures; however, nutrition and taxonomic composition of the periphyton may vary between sites. Environ Toxicol Chem 2023;42:2143-2157. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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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".