Triple sulfur isotope constraints on the sulfur cycling in Lake Sevan, Armenia
Bibliographic record
Abstract
Lake Sevan is a meso-eutrophic water body, which was severely impacted by anthropogenic level decrease, pollution and eutrophication during the last century. Starting in the 1970s, a decrease in the water level and an increase in dissolved inorganic nitrogen concentrations resulted in oxygen depletion in the hypolimnion of the lake during summer–autumn thermal stratification of the water column. Our work shows that in October 2019, the redox conditions in the hypolimnion progressed not only to full depletion of oxygen and nitrate, but to the formation of a hydrogen sulfide-rich deep-water layer, which covers 66% of lake’s bottom and accounts for 19% of its water volume. Concentrations of hydrogen sulfide in the hypolimnion of Major and Minor Sevan in October were as high as 9 and 39 μM, respectively.Triple sulfur isotope composition of sulfate and hydrogen sulfide in the water column of the lake provides further constraints on the biogeochemical processes which result in the formation of hydrogen-sulfide hypolimnion. Values of δ34S for hypolimnetic sulfide are lower by only 7–12 ‰ compared to epilimnetic sulfate, while δ33S values of sulfide are similar to the δ33S values of sulfate. These isotopic fingerprints are not consistent either with microbial sulfate reduction in the water column or with its combination with re-oxidative sulfur cycle as the sources of hydrogen sulfide in the hypolimnion. We attribute the formation of a sulfidic deep-water layer to a combination of microbial sulfate reduction in the water column and diffusion of hydrogen sulfide from the sediments.
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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 | 0.001 | 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".