A spatially variable scarcity of floating microplastics in the eastern North Pacific Ocean
Bibliographic record
Abstract
Abstract Plastic waste accumulating in the global ocean is an increasingly threatening environmental issue. To date, the floating and thus most visible fraction of ocean plastic pollution has been mapped at global scale. Yet, large knowledge gaps exist in our current understanding of the transport and transformation processes of positively buoyant plastic debris at the sea surface. Observations at sea typically report an apparent scarcity of microplastics (<5 mm) relative to the expected abundance-size distribution based on fragmentation of larger plastic objects. Here, we provide a comprehensive study on the relative abundance of microplastics (>500 µ m) and mesoplastics (0.5–5 cm) in the surface waters of the eastern North Pacific Ocean using data from 1136 040 plastic fragments collected by 679 neuston trawl deployments between 2015 and 2019. Our results reveal that the apparent microplastic scarcity is not uniformly distributed across the region. Instead, we show that the relative abundance of floating microplastics increases from the outside to the inside of the North Pacific Garbage Patch. We hypothesize that this observation could be explained by (i) a spatially variable microplastic removal due to spatial differences in ocean productivity, (ii) a differential dispersal of micro- vs. mesoplastics with a preferential accumulation of microplastics in the subtropical gyre, and/or (iii) the timescales associated with transport and fragmentation of plastic objects at the ocean surface with older, more degraded, floating plastic accumulation in subtropical gyres. The results presented here highlight that global estimates of the accumulation and removal of positively buoyant microplastics need to consider spatial aspects such as variations in ocean productivity, the dominant physical transport processes in a given area, as well as the time needed for a plastic object to reach the specific offshore location.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".