Contrasting Winter Versus Summer Microbial Communities and Metabolic Functions in a Permafrost Thaw Lake
Bibliographic record
Abstract
Permafrost thawing results in the formation of thermokarst lakes, which are biogeochemical hotspots in northern landscapes and strong emitters of greenhouse gasses to the atmosphere. Most studies of thermokarst lakes have been in summer, despite the predominance of winter and ice-cover over much of the year, and the microbial ecology of these waters under ice remains poorly understood. Here we first compared the summer versus winter microbiomes of a subarctic thermokarst lake using DNA- and RNA-based 16S rRNA amplicon sequencing and qPCR. We then applied comparative metagenomics and used genomic bin reconstruction to compare the two seasons for changes in potential metabolic functions in the thermokarst lake microbiome. In summer, the microbial community was dominated by Actinobacteria and Betaproteobacteria, with phototrophic and aerobic pathways consistent with the utilization of labile and photodegraded substrates. The microbial community was strikingly different in winter, with dominance of methanogens, Planctomycetes, Chloroflexi and Deltaproteobacteria, along with various taxa of the Patescibacteria/Candidate Phyla Radiation (Parcubacteria, Microgenomates, Omnitrophica, Aminicenantes). The latter group was underestimated or absent in the amplicon survey, but accounted for about a third of the metagenomic reads. The winter lineages were associated with multiple reductive metabolic processes, fermentations and pathways for the mobilization and degradation of complex organic matter, along with a strong potential for syntrophy or cross-feeding. The results imply that the summer community represents a transient stage of the annual cycle, and that carbon dioxide and methane production continue through the prolonged season of ice cover via a taxonomically distinct winter community and diverse mechanisms of permafrost carbon transformation.
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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".