Hydrothermal inputs drive dynamic shifts in microbial communities in Lake Magadi, Kenya Rift Valley
Bibliographic record
Abstract
Abstract. The Methane Index (MI) is an organic geochemical index that uses isoprenoid glycerol dialkyl glycerol tetraethers (GDGTs) as a proxy for methane cycling. Here, we report results from core spanning > 700 ka in Lake Magadi, Kenya, which shows abrupt shifts between high and low MI values in the core. These shifts coincide with interbedded tuffaceous silt. Where tuffaceous silts are present, MI “switches off” (MI < 0.2); in contrast, where these silts are absent in the core, the MI increases (MI > 0.5). Bulk organic matter is enriched in 13C in Magadi during “MI-off” periods, with values of ~ −18 ‰ in the upper part of the core and −22 to −25 ‰ in the lower portion. Evidence from n-alkanes and fatty acid methyl esters (FAMEs) support previous interpretations of an arid environment with a shallower lake where Thermoproteotal (formerly Crenarchaeota) archaea thrive in a hot spring rich environment over Euryarchaeota. Sediments deposited when the MI switches “on” showed δ13COM values as low as −89.4 ‰, but most were within the range of −28 to −30 ‰, which is consistent with contributions from methanogens rather than methanotrophs. Thus, the likely source of these high MI values in Lake Magadi is methanogenic archaea. Our results show that hydrothermal inputs of bicarbonate-rich waters into Lake Magadi cause a shift in the dominant archaeal communities, alternating between two stable states.
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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".