Denitrification, anaerobic ammonium oxidation, and dissimilatory nitrate reduction to ammonium in an East African Great Lake (Lake Kivu)
Bibliographic record
Abstract
Abstract We investigated anaerobic nitrogen (N) cycling in the water column of Lake Kivu, a deep meromictic tropical lake in East Africa. Data were collected at one station in the Northern Basin and one in the Southern Basin, during two sampling campaigns (June 2011—dry season, and February 2012—rainy season). Short‐term incubations of sulfide‐free water with 15 N‐labeled substrates revealed high potential denitrification and dissimilatory nitrate reduction to ammonium (DNRA) rates (up to 350 and 36 nmol N produced L −1 h −1 , respectively), while anaerobic ammonium oxidation (anammox) was lower (up to 3.3 nmol N produced L −1 h −1 ). However, anammox rates were 15 nmol N produced L −1 h −1 when 15 was added at depths where concentrations were very low (< 1 μmol L −1 ). With the addition of 5 μmol L −1 of 15 and 10 μmol L −1 of H 2 S, denitrification and anammox were stimulated in the Northern Basin, while the increase of DNRA rates was less notable. In the Southern Basin, the addition of H 2 S decreased denitrification rates, probably because of competition with DNRA, which increased, while no effect was observed on anammox. This study puts into evidence the co‐occurrence of denitrification, anammox and DNRA, for the first time in a great tropical lake, and underlines the spatial heterogeneity of these processes. Contrary to numerous reports in literature, we show that anammox can significantly occur in presence of H 2 S, suggesting that the contribution of anammox in the N cycle may be underestimated.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".