The origin and fate of organic matter in circum-Arctic subglacial ecosystems
Bibliographic record
Abstract
Glacier and ice sheet beds represent important yet underresearched cryospheric ecosystems. Life in the subglacial environment is mostly dependent on organic matter (OM) overridden by ice during times of glacier advance, and the nature of subglacial OM is, therefore, likely to drive the ecosystem functionality. Here we describe the origin, degradation stage and environmental context of OM present underneath glaciers in the circum-Arctic, and their effects on the resident microbial communities. In total, 19 glaciers from Alaska, Greenland, Iceland, Svalbard, and Norway were sampled for subglacial sediments. Biomarker analysis of the sediment samples was conducted using total solvent extraction, and copper (II) oxide (CuO) oxidation techniques yielding lipids and lignin-derived phenols. The extracts were analyzed by GC-MS to characterize the molecular-level composition of OM present. The biomarker data were then placed in the context of other environmental data, such as radiocarbon age, nutrient contents, and microbial community composition. The majority of OM in the samples was plant-derived, suggested by the dominance of long-chain n-alkanols over the microbial-specific short-chain n-alkanols. The composition of long-chain n-alkanes (≥C20), used as biomarkers for vascular plant waxes, in the solvent extracts suggested grass sources for samples from most Greenland glaciers and conifer sources for some glaciers from Norway, Alaska, and Disko Island (Qeqertarsuaq) in West Greenland. The rest of the OM in the subglacial samples was identified to have more general tree sources. The carbon preference index (CPI) of long-chain n-alkanes suggested a high degradation stage in most samples and was correlated with the radiocarbon age of the sediments’ OC (r = -0.68). Sediments containing older and more degraded OM were found to host less diverse microbial communities compared to those of the younger sites. In a rapidly warming climate, previously glacier-covered areas are being exposed as a consequence of glacier recession. This new land is standing at the onset of ecological succession and pedogenesis. Our results contribute to the understanding of the potential ecological function of subglacial OM as an important source of carbon and driver of microbial community development after deglaciation in the circum-Arctic region.
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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 | 0.000 |
| 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".