Isotopic Fingerprints of Anthropogenic Molybdenum in Lake Sediments
Bibliographic record
Abstract
We measured the molybdenum isotope compositions (δ(98)Mo) of well-dated sediment cores from two lakes in eastern Canada in an effort to distinguish between natural and anthropogenic contributions to these freshwater aquatic systems. Previously, Chappaz et al. (1) ascribed pronounced 20th-century Mo concentration enrichments in these lakes to anthropogenic inputs. δ(98)Mo values in the deeper sediments (reflecting predominantly natural Mo sources) differ dramatically between the two lakes: -0.32 ± 0.17‰ for oxic Lake Tantare and +0.64 ± 0.09‰ for anoxic Lake Vose. Sediment layers previously identified as enriched in anthropogenic Mo, however, reveal significant δ(98)Mo shifts of ± 0.3‰, resulting in isotopically heavier values of +0.05 ± 0.18‰ in Lake Tantare and lighter values of +0.31 ± 0.03‰ in Lake Vose. We argue that anthropogenic Mo modifies the isotopic composition of the recent sediments, and we determine δ(98)Mo(anthropogenic) values of 0.1 ± 0.1‰ (Lake Vose) and 0.2 ± 0.2‰ (Lake Tantare). These calculated inputs are consistent with the δ(98)Mo of molybdenite (MoS(2)) likely delivered to the lakes via smelting of porphyry copper deposits (Lake Vose) or through combustion of coal and oil also containing Mo (Lake Tantare). Our results confirm the utility of Mo isotopes as a promising fingerprint of human impacts and perhaps the specific sources of contamination. Importantly, the magnitudes of the anthropogenic inputs are large enough, relative to the natural Mo cycles in each lake, to have an impact on the microbiological communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".