Relationship between dissolved organic matter quality and microbial community composition across polar glacial environments
Bibliographic record
Abstract
Vast expanses of Earth's surface are covered by ice, with microorganisms in these systems affecting local and global biogeochemical cycles. We examined microbial assemblages from habitats fed by glacial meltwater within the McMurdo Dry Valleys, Antarctica and on the west Greenland Ice Sheet (GrIS), evaluating potential physicochemical factors explaining trends in community structure. Microbial assemblages present in the different Antarctic dry valley habitats were dominated by Sphingobacteria andFlavobacteria, while Gammaproteobacteria and Sphingobacteria prevailed in west GrIS supraglacial environments. Microbial assemblages clustered by location (Canada Glacier, Cotton Glacier and west GrIS) and were separated by habitat type (i.e. ice, cryoconite holes, supraglacial lakes, sediment and stream water). Community dissimilarities were strongly correlated with dissolved organic matter (DOM) quality. Microbial meltwater assemblages were most closely associated with different protein-like components of the DOM pool. Microbes in environments with mineral particles (i.e. stream sediments and cryoconite holes) were linked to DOM containing more humic-like fluorescence. Our results demonstrate the establishment of distinct microbial communities within ephemeral glacial meltwater habitats, with DOM-microbe interactions playing an integral role in shaping communities on local and polar spatial scales.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".