Microplastics in the digestive tract of Gryllus pennsylvanicus crickets in a biosolid – treated agricultural field
Bibliographic record
Abstract
Microplastic ubiquity, its general toxicology, and its suitability for ingestion by biota are leading ecological and human health concerns. Microplastics are abundant in terrestrial environments including agricultural settings where municipal biosolids applied as fertilizers show high levels of microplastics. Microplastic ingestion by omnivorous insects in the environment is not well explored. To determine whether crickets eat microplastics in the wild, we examined the digestive tracts of 50 crickets collected from a research site in Ontario, Canada. Crickets were caught in three locations: a crop field amended with dewatered municipal biosolids, along the untreated edge of the field, and along a nearby tree line. Over half of the dissected crickets contained microplastics. A total of 87 microplastics (31-2548 μm) were found (60 microfragments; 27 microfibers). Using FTIR, we determined 66% of the microfragments were plastic polymers although match quality was low, likely due to exposure to multiple degradation processes (e.g. laundry, wastewater processing, ingestion by animals). Trap location did not influence the number of crickets ingesting microplastics. We present evidence that lab-reared crickets of the same species break down ingested microplastics into smaller fragments using manufactured polyethylene spheres, and discuss the possibility that generalist ground dwelling insects like crickets contribute to the active transport and biotransformation of microplastics, with potential cascading effects on microplastic movement through the food webs.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".