Mercury, lead and lead isotope ratios in the teeth of moose (Alces alces) from Isle Royale, U.S. Upper Midwest, from 1952 to 2002
Bibliographic record
Abstract
Assessing the effect of recent reductions in atmospheric pollution on metal concentrations in wildlife in North America has been difficult because of the sparse availability of historical samples with which to establish a "pre-regulation" baseline, and because many ecosystems may be affected by local point sources which could obscure broader-scale trends. Here we report a recent 50 yr annual record of Hg, Pb and Pb isotope ratios in the teeth of a resident population of moose (Alces alces) in Isle Royale National Park, a relatively remote island in Lake Superior, Michigan, USA. During the early 1980s, concentrations of tooth Hg abruptly declined by approximately 65% compared to the previous 30 years (p<0.001), similar to a previous study of Hg in herring gull eggs in the Great Lakes region. Lead declined at the same time, and by 2002 Pb in adult moose teeth was approximately 80% lower than it had been prior to the early 1980s (p<0.001). These trends were unaffected by normalization against the geogenic elements La and Sr, which indicates that the trends in Hg and Pb had an anthropogenic cause. Temporal patterns of Pb isotope ratios suggested that the primary sources of Pb at different times in the moose were combustion of U.S. coal and leaded gasoline. Reductions in emissions from coal combustion might explain the co-incident reductions of Hg and Pb in Isle Royale moose, with elimination of alkyl Pb additives also playing a role in the continued tooth Pb reductions after 1983.
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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 | 0.000 | 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".