Viral Induced Microbial Mortality in Arctic Hypersaline Spring Sediments
Bibliographic record
Abstract
Viruses are a primary influence on microbial mortality in the global ocean. The impacts of viruses on their microbial hosts in low-energy environments are poorly explored and are the focus of this study. To investigate the role of viruses in mediating mortality in low-energy environments where contacts between viruses and microbes are infrequent, we conducted a set of in situ time series incubations in the outlet and channel sediments of two cold, hypersaline springs of the Canadian High Arctic. We found microbial and viral populations in dynamic equilibrium, indicating approximately equal birth and death rates for each population. In situ rates of microbial growth were low (0.5 to 50 x 103 cells cm−3 h−1) as were rates of viral decay (0.09 to 170 x 104 virions cm−3 h−1). A large fraction of the springs’ viral communities (49 to 100%) were refractory to decay over the timescales of our experiments. Microcosms amended with lactate or acetate exhibited increased microbial growth rates (up to three-fold) indicating organic carbon as one limiting resource for the microbial communities in these environments. A substantial fraction (15 to 71%) of the microbial populations contained inducible proviruses that were released- occasionally in multiple pulses- over the eight monitored days following chemical induction. Our findings indicate that viruses in low-energy systems maintain low rates of production and activity, have a small but notable impact on microbial mortality (8 to 29% attenuation of growth) and that successful viral replication may primarily proceed by non-lethal strategies. In cold, low biomass marine systems of similar character (e.g. subsurface sediments), viruses may be a relatively minor driver of community mortality compared to less energy-limited environments such as the marine water column or surface sediments.
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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 | 0.001 | 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) | 0.000 | 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".