Freshwater Bivalve Shells as Archival Indicators of Metal Pollution from a Copper−Uranium Mine in Tropical Northern Australia
Bibliographic record
Abstract
Freshwater bivalves (Velesunio angasi) were sampled in 1996 from the Finniss River in tropical northern Australia at 10 sites a priori exposed and nonexposed to acid rock drainage (ARD), containing elevated metal concentrations, from the rehabilitated Rum Jungle copper-uranium mine. Secondary ion mass spectrometry (SIMS) was used to measure Cu, Mn, Zn, U, Ni, Co, Pb, and Fe/Ca ratios across the annual shell laminations of the longest-lived bivalves found at each site, with the aim of evaluating the ability of the shells to archive measured annual metal inputs and their temporal patterns. At sites not contaminated by ARD, relatively constant and similar (baseline) SIMS signals were found for all metals in the shell laminations of V. angasi, dating as far back as 1965. At sites contaminated by ARD, relatively constant, but variably elevated, SIMS signals were evident for Cu, Mn, Zn, Ni, and Co in the shell, which extended back to the end of rehabilitation (1986) only. Since rehabilitation, the temporal patterns of Cu, Zn, and Mn observed in the shells at the most contaminated sites reflected those of the measured annual dissolved loads in the surface waters. The average concentrations of Cu, Mn, Zn, Ni, and Co in the shells decreased (3-13-fold) with increasing distance downstream of the mine site, until concentrations characteristic of the noncontaminated sites were reached. This geographic pattern of decline in pollution signal in the shell with increasing distance downstream of the pollution input is consistent with the pattern established for water and sediment chemistry. Overall, the SIMS results support the proposition that the shells of V. angasi can be used as archival indicators of metal pollution in surface waters of the Finniss River over their lifetime.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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; both teacher heads agree on what is shown here.
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".