Permafrost microbial communities follow shifts in vegetation, soils, and megafauna extinctions in Late Pleistocene NW North America
Bibliographic record
Abstract
Abstract We analyzed the microbial constituent of sedimentary ancient DNA sequence data recovered from subarctic loessal permafrost sediments dating between 30,000 and 4000 years ago. These data were originally studied for paleo‐ecological shifts in plants and animals associated with the Pleistocene–Holocene transition. Here, we explore whether there were changes in microbial communities paralleling the transition from distinctive cold‐adapted Ice Age megafauna and vegetation communities—the mammoth steppe ecosystem—toward the expansion of woody shrubs, extirpation of grazing megaherbivores, and development of the boreal forest. We observe a clear shift in the relative proportions of prokaryotic taxa after ca. 13,300 years ago associated with the collapse of the mammoth steppe. These data are consistent among study sites and between replicates processed with different methodologies (shotgun sequencing and targeted capture), which highlights that the “off‐target” fraction of metagenomic data used to study macro‐ecosystems can also be used to investigate synchronous changes in microbial communities. Functional analyses were performed with SEED and KEGG databases where we observed a shift in methane metabolism pathways after ~13,100 years ago, which suggests that there was a shift in methanogenesis away from animal gut microflora at the end of the Pleistocene. There does not appear to be a significant shift in the overall diversity of microbial communities despite the observed taxonomic and functional changes.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".