Gulls foraging in landfills: Does atmospheric exposure to halogenated flame retardants result in bioaccumulation?
Bibliographic record
Abstract
Several bird species have adapted to foraging in landfills, although these sites are known to represent significant sources of emissions of toxic semi-volatile chemicals including the halogenated flame retardants (HFRs) (e.g., polybrominated diphenyl ethers (PBDEs) and emerging compounds). The objective of this study was to investigate the association between atmospheric exposure to PBDEs and selected emerging HFRs and their bioaccumulation in landfill-foraging birds. We determined HFR concentrations in liver of 58 GPS-tagged ring-billed gulls (Larus delawarensis) breeding in a colony near Montreal (Canada) as well as their atmospheric exposure determined using a miniature bird-borne passive air sampler. PBDE mixtures were the most abundant HFRs determined in passive air samplers (daily exposure rates of ∑9PentaBDE: 47.4 ± 6.5 pg/day; DecaBDE: 36.0 ± 6.3 pg/day, and ∑3OctaBDE: 3.4 ± 0.5 pg/day) and liver (∑9PentaBDE: 68.1 ± 8.9 ng/g ww; DecaBDE: 52.3 ± 8.1 ng/g ww, and ∑3OctaBDE: 12.8 ± 2.1 ng/g ww), and their concentrations increased with the presence probability of gulls in landfills. We found a spatial relationship between the local sources of atmospheric exposure to PBDEs and the sites associated with greatest PBDE concentrations in liver. Specifically, the atmospheric exposure index was correlated with the bioaccumulation index (Pearson r for ∑9PentaBDE: r = 0.63, p < 0.001; DecaBDE: r = 0.66, p < 0.001, and ∑3OctaBDE: r = 0.42, p < 0.001). However, we found no correlation at the individual level between daily exposure rates of HFRs in passive air samplers and their liver concentrations. This suggests that complex exposure pathways combined with toxicokinetic factors shaped HFR profiles in gull liver, potentially confounding the relationships with atmospheric exposure.
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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".