Geographic and Seasonal Variation in Mercury Exposure of the Declining Rusty Blackbird
Bibliographic record
Abstract
Recent evidence suggests that mercury exposure has negative effects on the health of songbirds, and species that forage in wetlands may be at a greater risk of bioaccumulation of mercury than are those of other habitats. We examined mercury concentrations in blood and feathers from the wetland obligate and rapidly declining Rusty Blackbird (Euphagus carolinus) from five regions across North America: three wintering areas in the contiguous United States and breeding areas in the western boreal forests of Alaska and the Acadian forests of northeastern North America. In blood, mercury concentrations in Rusty Blackbirds from the Acadian forest (geometric mean 0.94 µg g-1; n = 59) were >3× than in those from Alaska (0.26 µg g-1; 107). Wintering birds had blood mercury levels approximately an order of magnitude lower than those of breeding birds (0.07 µg g-1; 332). In feathers, mercury concentrations in samples from the Acadian forests exceeded published minimum levels for adverse effects on birds (8.26 µg g-1; 45) and were 3× to 7× those observed from the other regions. The mercury concentrations we report in blood and feathers of the Acadian forest population of the Rusty Blackbird are among the highest reported for wild populations of passerines at sites without a known local source of mercury. Mercury should be considered as a potential contributor to the species' dramatic population decline in New England and the Maritime provinces and in other areas where bioavailability of mercury is high.
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 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".