Source Environments of the Microbiome in Perennially Ice-Covered Lake Untersee, Antarctica
Bibliographic record
Abstract
Ultra-oligotrophic Lake Untersee is among the largest and deepest surface lakes of Central Queen Maud Land in East Antarctica. It is dammed at its north end by the Anuchin Glacier and the ice-cover dynamics are controlled by sublimation — not melt — as the dominating ablation process and therefore surface melt during austral summer does not provide significant amounts of water for recharge compared to subsurface melt of the Anuchin Glacier. Several studies have already described the structure and function of the microbial communities within the water column and benthic environments of Lake Untersee, however, thus far there have been no studies that examine the linkages between the lake ecosystem with that of the surrounding soils or the Anuchin Glacier. The glacier may also play an important role as a major contributor of nutrients and biota into the lake ecosystem. Based on microbial 16S rRNA amplicon sequencing, we showed that the dominant bacterial signatures in Lake Untersee, the Anuchin Glacier and its surrounding soils were affiliated with Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, and Proteobacteria. Aerosol and local soil depositions on the glacier surface resulted in distinct microbial communities developing in glacier ice and cryoconite holes. Based on a source tracking algorithm, we found that cryoconite microbial assemblages were a potential source of organisms, explaining up to 36% of benthic microbial mat communities in the lake. However, the major biotic sources for the lake ecosystem are still unknown, illustrating the possible importance of englacial and subglacial zones. The Anuchin Glacier may be considered as a vector in a biological sense for the bacterial colonization of the perennially ice-covered Lake Untersee. However, despite a thick perennial ice cover, observed “lift-off” microbial mats escaping the lake make a bidirectional transfer of biota plausible. Hence, there is an exchange of biota between Lake Untersee and connective habitats possible despite the apparent sealing by a perennial ice cover and the absence of moat areas during austral summer.
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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".