Passing plastic: traces of plastic in the fecal samples of a high Arctic seabird in Tunu (East Greenland)
Bibliographic record
Abstract
Arctic seabirds are key bio-indicators of marine plastic pollution due to their transient movement and large populations. Although many studies have quantified the ingestion of microplastic particles (<5 mm in size) through necropsy or regurgitation sampling methods, little is known about post-digestive particle excretion. Due to the logistical challenges of non-lethally sampling feces from Arctic seabirds, this pathway remains largely understudied. We non-lethally collected 110 fecal samples from little auks ( Alle alle) during the 2014 breeding season in Ukaleqarteq, Tunu (Kap Höegh, East Greenland). We identified 25 potential microplastic particles (>100 µm in size), 19 of which were analyzed for material composition using Fourier Transform Infrared Spectroscopy and Raman micro-spectroscopy. Of these, 13 particles were successfully matched to materials, with five as plastic. This produced an average concentration of 0.08 ± 0.28 microplastic particles per fecal sample, with no difference of occurrence between chicks and adults. Particle lengths ranged from 113 to 751 µm. The presence of microplastics larger than our lower limit of detectability of 100 µm suggests a need for analysis of smaller particles and microfibers in this species. We contribute to understanding how microplastics pass through little auks and characterize how this species interacts with the plastic pathways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".