Microplastics and phagotrophic soil protists: evidence of ingestion
Bibliographic record
Abstract
Microplastics (MPs) can now be found in all the Earth's biomes, thereby representing a global change phenomenon with largely unknown consequences for biodiversity and ecosystem functioning. Soil protists are eukaryotic, primarily single celled organisms that play important roles in the soil food web. Microplastics have been shown to affect protist populations in freshwater and marine environments, yet the interactions between soil protists and MPs remains largely unknown. Here we examined whether phagotrophic soil protists can ingest MPs and experience declines in abundance. We exposed protists to soil treatments with different concentrations of MPs using commercial polymer fluorescent microspheres and used fluorescence microscopy to find evidence of MP ingestion. In addition, we quantified the total number of active phagotrophic protists over time. We show that most soil protists (>75% individuals) can readily ingest and keep MP within their food vacuoles, even at relatively small MP concentrations (0.1% w/w). There was a trend for higher prevalence of ingestion and for declines in protist abundance at the highest concentration of MPs (1% w/w). However, more data are necessary to further ascertain cause-effect relationships. This is the first report indicating that soil protists can play an important role in the transport and uptake of MPs in the soil food web.
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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 | 0.001 | 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".