The chemical limnology of two meromictic lakes with emphasis on pyrite formation
Bibliographic record
Abstract
Powell and Sakinaw Lakes are stably stratified ex-fjords, which became isolated from the Strait of Georgia approximately 11000 years ago by emerged sills due to postglacial isostatic rebound. Although both lakes contain highly sulphidic relict seawater (Powell 3.0 mM; Sakinaw 5.5 mM), they have distinct chemical differences, which may be due to Sakinaw receiving occasional inputs of seawater over the barely-emerged sill when strong onshore winds are coincident with spring tides. Powell Lake, now 50 m above sea level, has not received additional seawater since the sill originally emerged. Sakinaw has a very sharp chemocline located just below the oxic/anoxic interface, whereas in Powell, the interface is spread out over 200 m of the water column. Although both lakes have freshened, the ratios of major ion concentrations relative to chloride in the bottom saline waters are similar to those of present-day seawater. There are some differences, however, and these can be explained, in part, by the difference in molecular diffusivities for each of the ions. The bottom waters of Powell and Sakinaw Lakes are chemically similar to anoxic sediment porewaters. containing high concentrations of nutrients, DOC and alkalinity. Unlike Sakinaw, however, Powell Lake has very low concentrations of phosphate in its bottom waters, in spite of both lakes having similar particulate organic N:P ratios in their upper oxic waters. This may be attributable to more recent addition of sulphate to Sakinaw, allowing greater mineralization of phosphorus compared to the relatively oxidant-starved Powell Lake. High concentrations of reduced iron, hydrogen sulphide, and polysulphides result in formation of iron monosulphides and pyrite in the anoxic water columns of both lakes. The presence of these two minerals correlates well with their calculated saturation states. Pyrite precipitates directly with no monosulphide precursor at depths where sulphide concentrations are low; thus monosulphide phases are undersaturated. As sulphide levels increase with depth, iron monosulphides become saturated and are detected in the water column. Pyrite can then form via the slower reaction of elemental sulphur with monosulphide. The large separation of the oxic/anoxic interface and the chemocline in Sakinaw (∼10 m) and especially in Powell Lake (∼100 m) relative to that of sediment pore waters allows excellent resolution of these processes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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 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".