Faculty Opinions recommendation of Contribution of Archaea to total prokaryotic production in the deep Atlantic Ocean.
Bibliographic record
Abstract
Fluorescence in situ hybridization (FISH) in combination with polynucleotide probes revealed that the two major groups of planktonic Archaea (Crenarchaeota and Euryarchaeota) exhibit a different distribution pattern in the water column of the Pacific subtropical gyre and in the Antarctic Circumpolar Current system.While Euryarchaeota were found to be more dominant in nearsurface waters, Crenarchaeota were relatively more abundant in the mesopelagic and bathypelagic waters.We determined the abundance of archaea in the mesopelagic and bathypelagic North Atlantic along a south-north transect of more than 4,000 km.Using an improved catalyzed reporter deposition-FISH (CARD-FISH) method and specific oligonucleotide probes, we found that archaea were consistently more abundant than bacteria below a 100-m depth.Combining microautoradiography with CARD-FISH revealed a high fraction of metabolically active cells in the deep ocean.Even at a 3,000-m depth, about 16% of the bacteria were taking up leucine.The percentage of Euryarchaeota and Crenarchaeaota taking up leucine did not follow a specific trend, with depths ranging from 6 to 35% and 3 to 18%, respectively.The fraction of Crenarchaeota taking up inorganic carbon increased with depth, while Euryarchaeota taking up inorganic carbon decreased from 200 m to 3,000 m in depth.The ability of archaea to take up inorganic carbon was used as a proxy to estimate archaeal cell production and to compare this archaeal production with total prokaryotic production measured via leucine incorporation.We estimate that archaeal production in the mesopelagic and bathypelagic North Atlantic contributes between 13 to 27% to the total prokaryotic production in the oxygen minimum layer and 41 to 84% in the Labrador Sea Water, declining to 10 to 20% in the North Atlantic Deep Water.Thus, planktonic archaea are actively growing in the dark ocean although at lower growth rates than bacteria and might play a significant role in the oceanic carbon cycle.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.120 | 0.042 |
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".