Avermectin Toxicity to Benthic Invertebrates is Modified by Sediment Organic Carbon and Chemical Residence Time
Bibliographic record
Abstract
Chemicals used in sea lice management strategies in salmonid aquaculture include the avermectin class of compounds that can accumulate and persist in the sediments underneath salmon farms and directly impact nontarget benthic fauna. The effects of sediment organic carbon content and chemical residence time (CRT) on the lethal and sublethal toxicity of emamectin benzoate (EB; formulation: Slice®) and ivermectin (purified) and a combination of both were examined in two benthic invertebrates, the amphipod Eohaustorius estuarius and the polychaete Neanthes virens. In both species, increased sediment organic carbon content significantly reduced lethal toxicity, a modulation that was more pronounced for ivermectin and combination exposures. At a CRT of 4 months, lethal toxicity was reduced in E. estuarius but was unaffected in N. virens. Sublethal toxicity in N. virens (burrowing behavior) was modulated by sediment organic carbon and CRT in a similar manner to the trend in lethal toxicity. Inconsistencies in behavior (phototaxis) in E. estuarius made conclusions regarding toxicity modification by sediment organic carbon or CRT inconclusive. Our results indicate that environmental factors including sediment organic carbon content and the time compounds reside in sediments are important modifiers of chemotherapeutant toxicity in nontarget benthic species and should be considered when regulatory decisions regarding their use are made. Environ Toxicol Chem 2022;41:1918-1936. © 2022 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) | 0.001 | 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".