Changes in plastic ingestion over the breeding season: do yellow-legged gulls (Larus michahellis) adjust foraging habits for chick provisioning?
Bibliographic record
Abstract
Abstract: Over the last few decades, anthropogenic debris, and particularly plastics, have become a major threat for the environment and biodiversity. Over 200 seabird species have been recorded to interact directly with plastics, leading to reductions in survival and/or breeding rates, and consequently representing a major conservation concern. Breeding birds are known to adjust prey quality over the breeding season in order to provide higher quality food for chick provisioning. Nevertheless, it is unclear what this means with respect to the use of anthropogenic food sources used by seabirds. Over the 2020 breeding season, regurgitated pellets, or boluses (n=143), from yellow-legged gulls (Larus michahellis) were collected from a series of nests at Carteau colony in the Gulf of Fos, Camargue, France. 85% (n=121) contained at least one plastic. The most abundant plastic type was sheet plastic, mainly composed of polyethylene and used in food packagings. There was a significant decrease in the number of boluses containing plastics between pre-hatching and post hatching (respectively 84% and 75%). The number of collected boluses also declined between these two periods (respectively n=82 and n=61). These results suggest that gulls may indeed adjust their foraging habits to provide more digestible food to chicks. However, we found high variability among the followed nests in the number of recovered boluses, and a large majority of regurgitates still contained anthropogenic items post-hatching. As yellow-legged gulls are known to specialize on particular food sources, landfill specialist birds may continue to use these food items during chick rearing despite their potential risk for chick growth and survival. More detailed surveys will now be required to test whether these birds are nonetheless able to select different types of anthropogenic items to maximize reproductive success. Authors: Florence Droguet¹, Carole Leray², Alexandra ter Halle³, Marion Vittecoq², Jennifer Provencher⁴, Karen McCoy¹ ¹University of Montpellier CNRS IRD, Centre IRD, ²Tour du Valat, Research Institute for the Conservation of Mediterranean Wetlands, ³UMR 5623 CNRS - University of Toulouse III Paul Sabatier, ⁴Environment and Climate Change Canada, National Wildlife Research Centre
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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 | 0.000 |
| 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 | 0.000 |
| 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 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".