Review on the ecotoxicological impacts of plastic pollution on the freshwater invertebrate Daphnia
Bibliographic record
Abstract
The environmental impacts of plastic pollution have recently attracted universal attention, especially in the aquatic environment. However, research has mostly been focused on marine ecosystems, even though freshwater ecosystems are equally if not more polluted by plastics. In addition, the mechanism and extent to which plastic pollution affects aquatic biota and the rates of transfer to organisms through food webs eventually reaching humans are poorly understood, especially considering leaching hazardous chemicals. Several studies have demonstrated extreme toxicity in freshwater organisms such Daphnia. When such keystone species are affected by ambient pollution, entire food webs are destabilized and biodiversity is threatened. The unremitting increase in plastic contaminants in freshwater environments would cause impairments in ecosystem functions and structure, leading to various kinds of negative ecological consequences. As various studies have reported the effects on daphnids, a consolidation of this literature is critical to discuss the limitations and knowledge gaps and to evaluate the risk posed to the aquatic environment. This review was undertaken due to the evident need to evaluate this threat. The aims were to provide a meaningful overview of the literature relevant to the potential impact of plastic pollution and associated contaminants on freshwater daphnids as primary consumers. A critical evaluation of research gaps and perspectives is conducted to provide a comprehensive risk assessment of microplastic as a hazard to aquatic environments. We outlined the challenges and limitations to microplastic research in hampering better-focused investigations that could support the development of new plastic materials and/or establishment of new regulations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".