Ingestion of polyethylene microplastics impacts cichlid behaviour despite having low retention time
Bibliographic record
Abstract
• Exposing juvenile cichlids to polyethylene microplastics through their prey. • Microplastic exposure does not affect growth, foraging behaviour or satiation rate. • Plastic-exposed fish show initial deficit in mazes but exhibit larger improvement. • Juvenile cichlids readily egest microplastics; retention time < 24 h. Microplastics, particles between 0.001 and 5 mm in diameter, are ubiquitous in the environment and their consumption by aquatic organisms is known to lead to a variety of adverse effects. However, studies on the effects of microplastics on prey fish have not shown consistent trends, with results varying across species and plastic type used. Here, we manipulated the levels of microplastic (MP) exposure among juvenile convict cichlids ( Archocentrus nigrofasciatus ) by feeding them brine shrimp ( Artemia spp .) exposed to 0, 10, or 100 MP ml -1 of virgin polyethylene microspheres (10–20 μm) for a 10-day period. We then tested groups of 3 cichlids in a 2-day maze trial, in which we measured the latency to explore and time to complete a novel maze. We found no impacts of microplastic exposure on foraging rate, growth, or competitive aggression. However, our results demonstrate that microplastics exposure shaped exploratory behaviour and maze performance. Despite these effects, we found very little microplastics remaining in the fish's bodies after the experiment. A companion experiment demonstrates that most plastic particles were egested within 24 h. Our current results show that pristine microplastics at non-lethal levels have consequences on cichlid behaviour and decision-making but not growth.
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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 | 0.000 | 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".