Virus-driven nitrogen cycling enhances phytoplankton growth
Bibliographic record
Abstract
Viruses have been implicated as major players in aquatic nutrient cycling, yet few data exist to quantify their significance.To determine the effect of viruses on ammonium regeneration by bacteria, experiments were carried out in the oligotrophic Indian Ocean and productive False Creek, Vancouver, Canada.Bacteria were concentrated and then diluted with virus-free water to reduce virus abundance, or with virus-replete water to restore natural virus abundances.Virus-replete treatments showed increased ammonium concentrations compared to treatments with viruses removed (differences of 0.287 ± 0.14 and 1.44 ± 0.73 µmol l -1 , mean ± SD, in the Indian Ocean and False Creek, respectively).Bacterial abundances were lower, while phytoplankton abundances and chlorophyll a (chl a) concentrations were greater in the virus-replete treatments, consistent with the increased availability of ammonium in the presence of viruses.These data demonstrate that viral lysis leads to ammonium production, likely through the liberation of dissolved organic N that is remineralised by uninfected bacteria.In turn, the released ammonium fuels primary production.These results show that viruses play a critical role in the marine N cycle, and suggest that viral lysis likely supplies a significant portion of the global N requirements of phytoplankton.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".