Experimental Evidence from the Field that Naturally Weathered Microplastics Accumulate Cyanobacterial Toxins in Eutrophic Lakes
Bibliographic record
Abstract
Freshwater ecosystems with recurring harmful algal blooms can also be polluted with plastics. Thus the two environmental problems may interact. To test whether microplastics influence the partitioning of microcystins in freshwater lakes, we examined the sorption of four microcystin congeners to different polymers of commercially available plastics (low-density polyethylene, polyethylene terephthalate, polyvinyl chloride, and polypropylene). We conducted three experiments: a batch sorption experiment in the laboratory with pristine microplastics of four different polymers, a second batch sorption experiment in the laboratory to compare pristine and naturally weathered microplastics of a single polymer, and a 2-month sorption experiment in the field with three different polymers experiencing natural weathering in a eutrophic lake. This series of experiments led to a surprising result: microcystins sorbed poorly to all polymers tested under laboratory conditions (<0.01% of the initial amount added), irrespective of weathering, yet in the field experiment, all polymers accumulated microcystins under ambient conditions in a eutrophic lake (range: 0-84.1 ng/g). Furthermore, we found that the sorption capacity for microcystins differed among polymers in the laboratory experiment yet were largely the same in the field. We also found that the affinity for plastic varied among microcystin congeners, namely, more polar congeners demonstrated a greater affinity for plastic than less polar congeners. Our study improves our understanding of the role of polymer and congener type in microplastic-microcystin sorption and provides novel evidence from the field, showing that naturally weathered microplastics in freshwater lakes can accumulate microcystins. Consequently, we caution that microplastics may alter the persistence, transport, and bioavailability of microcystins in freshwaters, which could have implications for human and wildlife health. Environ Toxicol Chem 2022;41:3017-3028. © 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 | 0.001 |
| 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 | 0.001 |
| 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".