Impacts of microplastics on terrestrial plants: A critical review
Bibliographic record
Abstract
Abstract Microplastic (MP) pollution is an important environmental problem owing to its widespread use, long residence time, and overall persistence. MPs threaten the health of humans, animals, and plants. However, studies on the effects of MPs on terrestrial plants are less common compared to those conducted in aquatic systems. This review discusses the sources of MPs in terrestrial ecosystems, their effects on C and N cycling in soils, and the impact of MPs on terrestrial plants, and focuses on plant growth and the potential risks to human health. MPs affect plants and their performance by altering soil structure, microbial activity, nutrient immobilization, transporting contaminants, and causing direct toxicity. Chemicals, such as plasticizers, additives, and colorants, in MPs may negatively affect ecosystems and their inhabitants, and MPs may interact with a wide array of pollutants, including pesticides, heavy metals, and antibiotics. These impacts vary as a function of soil type, plant species, and MP type. Future research efforts should focus on interaction complexity, uptake mechanisms, and impacts on plants at multiple spatiotemporal scales, while concurrently considering their effects on food chains and human health.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".