Chemoautotrophy and anoxygenic photosynthesis within the water column of a large meromictic tropical lake (Lake Kivu, East Africa)
Bibliographic record
Abstract
Abstract We quantified chemoautotrophic and anoxygenic photosynthetic microbial production in the water column of Lake Kivu, a permanently stratified tropical lake situated amidst volcanic activity, and aimed to identify the microorganisms involved in these processes through the analysis of their phospholipid fatty acid (PLFA) content and stable isotope (13C) labelling of PLFA in a set of incubation experiments. Data demonstrate the existence of a biogeochemically active chemoautotrophic bacterial community in the redoxcline of Lake Kivu (50–70 m). PLFA data indicate that the bacterial communities are structured vertically in the water column, with a large dissimilarity between the oxic and anoxic waters. Maximum volumetric dark CO2 fixation rates measured in Lake Kivu were in the same range as values reported from H2S‐rich marine redoxclines, such as the Black and Baltic Seas, and the Cariaco Basin. Similarly, maximal chemoautotrophic activities in Lake Kivu were observed in sulfidic waters, just below the oxycline. Anoxygenic photosynthetic production was never observed in the main basin of Lake Kivu. However, anoxygenic phototrophs largely dominated CO2 fixation in the illuminated redoxcline of Kabuno Bay, a shallower ferruginous sub‐basin. Overall, this study supports the idea that chemoautotrophs and/or anoxygenic photoautotrophs might play an important role in the flow of carbon and energy in permanently stratified tropical ecosystems. In Lake Kivu, these processes significantly contribute to organic matter biosynthesis and exert an indirect control on oxygenic photoautotrophs by shortcircuiting the vertical transport of nutrients to the illuminated and oxygenated surface waters.
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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 | 0.000 | 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 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".