Sea-Surface Slicks and Their Effect on the Concentration of Plastics and Zooplankton in the Coastal Waters of Rapa Nui (Easter Island)
Bibliographic record
Abstract
The abundance and distribution of plastic debris at the sea surface shows considerable variability over different spatial scales. Some of the oceanographic processes at small (<1 km) and submeso (1–10 km) scales manifest themselves as slicks at the sea surface, which might have the potential to concentrate organisms and particles (such as positively buoyant plastics), putting species that feed in these areas at risk of ingesting plastics. Slicks can be filaments, lines, meanders, or patches, which are lighter in color and smoother in surface roughness compared to the surrounding area. Here we tested the hypothesis that passive particles (including plastics) and organisms are aggregated in the surface waters within these slicks. According to their main features (orientation to coast and/or wind), the studied slicks were most likely generated by oceanographic processes such as topographically controlled fronts, other types of fronts and internal waves. Neuston samples were collected from the sea surface inside and outside of slicks ( n = 11 sites with slicks) in the coastal waters of Rapa Nui (Easter Island) during two campaigns in austral summer (January 2018) and autumn (April 2019). In general, passive particles, including plastics, exuviae, eggs and foraminiferans, were found more frequently inside than outside the slicks. In some cases, motile zooplankton organisms such as chaetognaths, vertically migrating crustaceans and early developmental stages (EDS) of fish were also more common within the slicks. In addition, a positive relationship was found between plastics and planktonic organisms such as foraminiferans, snails and jellyfish (e.g., Velella velella ), although a strong correlation was also found with fish EDS and chaetognaths. These results suggest that surface slicks are areas of aggregation for both passive particles and active organisms, thus playing an important ecological role in food retention and particle concentration where the risk of plastic ingestion by fish and seabirds is enhanced.
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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) | 0.000 | 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".