The Disadvantage of Having a Big Mouth: The Relationship between Insect Body Size and Microplastic Ingestion
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Plastic pollution is ubiquitous. When plastics enter natural environments, they break down into microplastics (MPs; <5 mm), becoming more accessible to smaller animals. Insects ingesting plastics in the wild can physically degrade larger MPs into smaller MPs and nanoplastics. While particle size and body size undoubtedly impact plastic ingestion and degradation, we have no predictive understanding of how these factors interact. We studied how a model cricket species ( Gryllodes sigillatus ) interacts with plastics of differing sizes throughout a 20-fold change in body mass during growth and development. We fed crickets differently sized polyethylene MPs to first investigate whether crickets would avoid MPs when given a choice. We found that they do not. Instead, they gradually began to consume more of the plastic diet over time. Crickets would only consume beads when their mouth size was larger than the MP. While small MPs (e.g., 38 μm) were more likely to be excreted whole, larger MPs (e.g., 425 μm) were more extensively biofragmented if ingested. These effects of insect behavior and body size on the likelihood of plastic ingestion and the degree to which MPs are degraded have important implications for how and when we should regulate size classes of plastic particles entering natural environments.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".