Informing the Exposure Landscape: The Fate of Microplastics in a Large Pelagic In-Lake Mesocosm Experiment
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Understanding microplastic exposure and effects is critical to understanding risk. Here, we used large, in-lake closed-bottom mesocosms to investigate exposure and effects on pelagic freshwater ecosystems. This article provides details about the experimental design and results on the transport of microplastics and exposure to pelagic organisms. Our experiment included three polymers of microplastics (PE, PS, and PET) ranging in density and size. Nominal concentrations ranged from 0 to 29,240 microplastics per liter on a log scale. Mesocosms enclosed natural microbial, phytoplankton, and zooplankton communities and yellow perch ( Perca flavescens ). We quantified and characterized microplastics in the water column and in components of the food web (biofilm on the walls, zooplankton, and fish). The microplastics in the water stratified vertically according to size and density. After 10 weeks, about 1% of the microplastics added were in the water column, 0.4% attached to biofilm on the walls, 0.01% within zooplankton, and 0.0001% in fish. Visual observations suggest the remaining >98% were in a surface slick and on the bottom. Our study suggests organisms that feed at the surface and in the benthos are likely most at risk, and demonstrates the value of measuring exposure and transport to inform experimental designs and achieve target concentrations in different matrices within toxicity tests.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".