Biodilution of Organic Species of Arsenic in Freshwater Food Webs
Bibliographic record
Abstract
Abstract Arsenic can accumulate in freshwater biota, sometimes reaching potentially harmful levels. However, the toxicity of arsenic strongly depends on which arsenic species are present. Although organic species are considered less harmful than inorganic ones, they have not been extensively studied in freshwater environments, and drivers of variation in arsenic speciation among sites and taxa remain unclear. We assessed concentrations of two organic arsenic species, arsenobetaine (AsB) and dimethylarsinic acid (DMA), in fish and invertebrates from three lakes near Sudbury, Ontario, Canada—a region with widespread mining impacts. Both AsB and DMA were detected in most samples (n = 212), varying across a wide range of concentrations (<0.001–30.144 and <0.006–5.262 mg/kg dry wt, respectively). The lake with the most severe mining impacts typically had the highest concentrations (designated by square brackets []) of AsB and DMA. In contrast, the percentage of total arsenic made up by AsB (%AsB) and DMA (%DMA) did not vary significantly between lakes. Arsenic speciation in fish muscle varied with fish size, selenium concentrations, and trophic elevation (inferred from nitrogen stable isotope ratios δ15N), but relationships with dietary carbon source (inferred from carbon stable isotope ratios δ13C) were more varied. Within all three lake food webs, [AsB] and [DMA] typically underwent biodilution, decreasing with trophic elevation (i.e., δ15N). Although the aforementioned factors explained some variation in arsenic speciation, there remains considerable unexplained variation. Further studies on arsenic speciation in freshwater biota should target a wider diversity of taxa to better understand drivers of variation in arsenic speciation. In addition, research emphasizing the percentage of inorganic arsenic and other organic arsenic species is needed to improve environmental and human health risk assessments. Environ Toxicol Chem 2024;43:833–846. © 2024 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".