Heavy metal concentrations in Canada geese, snow geese, mallards, and American coots from the northern Rocky Mountains in Montana
Bibliographic record
Abstract
Abstract The presence of metals in migratory bird tissues is well established and mining as an anthropogenic source of exposure to metals is well reported in the scientific literature. Determining the difference between what are hypothesized as normal metal levels and those associated with acute mining toxicity is challenging as spatial and temporal overlap of migratory birds with anthropogenic point sources can be highly variable at individual, population, and species levels. We examined the concentrations of 5 geologically prominent metals and metalloids in the region (arsenic, cadmium, copper, manganese, and zinc) in tissues (kidney, n = 64; liver, n = 65; and muscle, n = 65) from 4 species common to the northern Rocky Mountains in western Montana (Canada goose, Branta canadensis, n = 12; snow goose, Anser caerulescens, n = 15; mallard, Anas platyrhynchos, n = 32; and American coot, Fulica americana, n = 6), to identify metal concentrations for comparison to acute mining‐associated mortalities. Metal levels were highly variable across tissue types for all species. For example, the highest concentrations of copper, manganese, and zinc were measured in the liver (18,300, 3,960, and 38,200, respectively; ug/kg), while cadmium levels were highest in the kidney (973 ug/kg). Among species and tissue types, metal levels were also highly variable. For example, copper levels in mallards were highest in the kidney (6,700 ug/kg) and lowest in muscle (2,780 ug/kg). In contrast, copper levels in American coots were highest in muscle (14,400 ug/kg) and lowest in the kidney (5,060 ug/kg). While the wide variation in metal concentrations among species and tissue types measured in our study can make for difficult comparisons, the results are similar to control cases from other peer‐reviewed publications, and several times lower than dose‐response experiments and incidents in which mining‐associated mortality was known. Our results provide metal concentrations in migratory bird species that utilize the northern Rocky Mountains through Montana, which are essential data for assessing exposure, risk, and mortality associated with anthropogenic activities in the region.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".