Ecology of purple sulfur bacteria in the highly stratified meromictic Lake Shunet (Siberia, Khakassia) in 2002–2009
Bibliographic record
Abstract
Phototrophic sulfur bacteria form dense accumulations in the chemocline zones of stratified lakes where light reaches the sulfide-containing layers of water. Many works are dedicated to the ecophysiology of these microorganisms in meromictic lakes. However, the role of these microorganisms in the trophic network of these ecosystems, the ways of biomass utilization, and the contribution to the turnover of biogenic elements have so far been insufficiently understood. This work deals with the analysis of many years’ seasonal dynamics of the biomass of purple sulfur bacteria and the physicochemical conditions of their environment in Lake Shunet (Siberia, Khakassia, Russia), unraveling the causes of their anomalous development in the chemocline of this lake, as well as the comparative analysis of such type of ecosystems. Lake Shunet is characterized by markedly pronounced stratification and the high density of purple sulfur bacteria (PSB) in the chemocline, which is comparable to that of Lake Mahoney (Canada) where the number of PSB is the greatest among those known in the world. It was shown that, in the period 2002–2009, the total amount of bacterio-chlorophyll a in the water column of Lake Shunet increased and did not correlate with the seasonal variations in temperature and illumination in the chemocline. It was established that PSB cells in the purple layer experienced the effect of self-shading. The sedimentation rate of purple sulfur bacteria in Lake Shunet was low due to the pronounced density gradient in the chemocline zone. Thus, the high number of PSB in the chemocline was due to the combination of strong illumination, a high sulfide concentration, and a high water density gradient, which was responsible for stable stratification and contributed to the accumulation of the cells in a narrow layer. The data obtained could be useful for the paleoreconstruction of climatically deter-mined changes in the level of the lake and its periods of meromixis by the presence of carotenoids and bacte-riochlorophylls in the bottom sediments.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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; 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".