The disadvantage of having a big mouth: the relationship between insect body size and microplastic ingestion
Bibliographic record
Abstract
Abstract Plastic pollution is ubiquitous, and animals are exposed to diverse plastic shapes and sizes. When plastics enter natural environments, they break down into microplastics (MPs; <5 mm) and likely become more accessible to smaller animals. Insects play critical environmental and economic roles, ingest plastics in the wild, and can physically degrade ingested MPs into smaller and more harmful nanoplastics. While particle size and body size undoubtedly impact plastic ingestion, we have no predictive understanding of how these factors interact to influence which plastics are a threat to which animals. To uncover these potential interactions, we studied how a model cricket species ( Gryllodes sigillatus ) interacts with plastics of differing sizes throughout a twentyfold change in body size during growth and development. We fed crickets a range of MP sizes of 38 to 500 µm with clearly defined particle size thresholds. We investigated whether crickets would avoid MPs when given a choice and found that they do not; instead they gradually began to consume more of the plastic diet over time. We then studied how MP ingestion is influenced by body size and mouth size, and the extent of breakdown that occurs once MPs are ingested. We found that crickets would only consume whole beads when their mouth size was larger than the MP. While small MPs were more likely to be excreted whole, larger MPs were more extensively broken down as crickets grew. We conclude that crickets do not exhibit avoidance behaviour towards plastic and ingest it once a particle can be consumed whole. These effects of insect behaviour and body size on the likelihood of plastic ingestion and the degree to which MPs are degraded have important implications for regulating the size classes of plastic particles entering natural environments and how plastics move through those environments once discarded.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".