Eurasian Dipper Eggs Indicate Elevated Organohalogenated Contaminants in Urban Rivers
Bibliographic record
Abstract
Many urban European streams are recovering from industrial, mining, and sewage pollution during the 20th century. However, associated recolonization by clean water organisms can potentially result in exposure to legacy or novel toxic pollutants that persist in the environment. Between 2008 and 2010, we sampled eggs of a river passerine, the Eurasian dipper (Cinclus cinclus), from 33 rivers in South Wales and the English borders (UK) which varied in catchment land use from rural to highly urbanized. Dipper egg δ(15)N and δ(13)C stable isotopes were enriched from urban rivers while δ(34)S was strongly depleted, effectively discriminating their urban or rural origins at thresholds of 10% urban land cover or 1000 people/km(2). Concentrations of total polychlorinated biphenyls (PCBs) and polybrominated biphenyl ethers (PBDEs) were positively related to urban land cover and human population density while legacy organochlorine pesticides such as p,p'-DDE, lindane, and hexachlorobenzene were found in higher concentrations at rural sites. Levels of PBDEs in urban dipper eggs (range of 136-9299 ng/g lw) were among the highest ever reported in passerines, and some egg contaminants were at or approaching levels sufficient for adverse effects on avian development. With the exception of dieldrin, our data shows PCBs and other organochlorine pesticides have remained stable or increased in the past 20 years in dipper eggs, despite discontinued use.
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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".