Widespread ingestion of synthetic micro-particles by geese across Great Britain and Ireland
Bibliographic record
Abstract
Scant consideration has been given to the ingestion of synthetic micro-particles (e.g. plastic particles such as micro-fibres and micro-fragments 0.5–5 mm in size) by non-marine waterbirds, such as geese, residing in coastal and inland areas. In the present study, we therefore assessed the occurrence of micro-particle ingestion for five goose species across multiple locations throughout the United Kingdom and Ireland. Micro-particle recovery was inclusive of synthetic micro-fibres and micro-fragments, as well as treated textile micro-fibres such as dyed cotton fibres. Goose faecal samples were collected opportunistically between May 2018 and October 2019. At least one micro-particle was detected in 46.5% of the samples (n = 809 samples in total; 0–21 micro-particles per sample), which were collected from Greater White-fronted Geese Anser albifrons (n = 31 samples; 41.9% yielded micro-particles), Greylag Geese A. anser (n = 256; 58.6%), Pink-footed Geese A. brachyrhynchus (n = 66; 42.4%), Canada Geese Branta canadensis (n = 298; 36.6%) and Barnacle Geese B. leucopsis (n = 158; 48.1%). Time of year and distance from the coast had significant partial effects on the abundance of micro-particles recovered, with fewer micro-particles recovered during winter months and from locations > 70 km from the coast. Overall, it appears that the ingestion of synthetic micro-particles is a widespread and frequent occurrence, albeit in low quantities, in different goose species. Further research is however needed to ascertain the extent of absorption and subsequent impacts of chemical contaminants derived from synthetic micro-particles and textile fibres, especially in relation to bird health and developmental life stages.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".