Experimental investigation of short-term warming on arsenic flux from contaminated sediments of two well-oxygenated subarctic lakes
Bibliographic record
Abstract
Legacy arsenic (As) contamination from past mining operations remains an environmental concern in lakes of the Yellowknife area (Northwest Territories, Canada) due to its post-depositional mobility in sediment and potential for continued remobilization to surface waters. Warmer temperatures associated with climate change in this subarctic region may impact As internal loading from lake sediments either by a direct effect on sediment porewater diffusion rate or indirect effects on microbial metabolism and sediment redox conditions. This study assessed the influence of warmer temperatures on As diffusion from contaminated sediment of two lakes with contrasting sediment characteristics using an experimental incubation approach. Sediments from Yellowknife Bay (on Great Slave Lake) contained predominately clay and silt with low organic matter (10%) and high As content (1675 μg/g) while sediments of Lower Martin Lake had high organic matter content (~70%) and approximately half the As (822 μg/g). Duplicate sediment batches from each lake were incubated in a temperature-controlled chamber, and overlying water was kept well-oxygenated while As flux from sediment was measured during four weekly temperature treatments (7°C to 21°C, at ~5°C intervals). During the experiment, As diffused from sediment to overlying water in all cores and temperature treatments, with As fluxes ranging from 48-956 μg/m2/day. Arsenic fluxes were greater from Yellowknife Bay sediments, which had higher solid-phase As concentrations, compared to those of Lower Martin Lake. Short-term warming did not stimulate As flux from duplicate cores of either sediment type, in contrast with reported temperature enhancement in other published studies. We conclude that warmer temperatures were insufficient to strongly enhance sediment As diffusion into overlying oxic waters. These observations are relevant for evaluating climate-warming effects on sediment As mobility in subarctic lakes with little or no thermal stratification and a well-oxygenated water column.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".