Assessing plastic debris in aquatic food webs: what we know and don’t know about uptake and trophic transfer
Bibliographic record
Abstract
Plastic pollution is now recognized as a global environmental issue that can affect the health of biota and ecosystems. Now that a growing number of species and taxa are known to ingest a diverse range of sizes and types of plastics and retain the plastics in their guts, there are increasing questions relating to the movement of plastics through food webs, and how biota may directly and indirectly ingest plastics. Here, we synthesize what is known from the published, peer-reviewed literature about plastic ingestion by animals and identify critical gaps in our knowledge. We systematically reviewed and examined the literature for studies that reported ingested plastics in marine and freshwater biota at a global scale. Our objective was to inform discussions and future studies regarding what we know about plastic ingestion and fate in food webs. We assessed what regions, ecosystems, and food webs have been studied to date and whether potential information may already be available to assess if trophic transfer of plastics may be occurring. We found 160 relevant publications through 2016. Most studies were concentrated in specific regions and in specific ecosystem types, with freshwater studies being the most limited. Moreover, most studies examined one species at a time with only a handful of regions with multiple taxa examined across multiple studies. Twenty-one percent of the regions have no published data on plastic ingestion to date. Although some studies have measured ingestion in multiple species across trophic levels, few have tested the hypothesis that plastics are transferred across trophic levels. Moreover, none have addressed questions related to biomagnification. While our review suggests that numerous papers have recorded the ingestion of plastics by biota across many trophic levels, habitats, and geographic regions, many questions regarding how or whether biota retain, bioaccumulate, biomagnify, and trophically transfer plastics still need to be addressed.
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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 | 0.016 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".