Recording of climate and diagenesis through fossil pigments and sedimentary DNA at Laguna Potrok Aike, Argentina
Bibliographic record
Abstract
Abstract. Aquatic sediments record past climatic conditions while providing a wide range of ecological niches for microorganisms. Although marine sedimentary microbial assemblages are often defined by their surrounding geochemical conditions, the influence of environmental features upon microbial development and post-depositional survival remains largely unknown in the lacustrine realm. Due to long-term microbial activity, the composition of environmental DNA can be expected to evolve with sediment depth and over time and therefore should reflect both ancient and extant microbial populations, but this hypothesis has rarely been tested using a multiproxy approach. Here geomicrobiological and phylogenetic analyses of a Patagonian maar lake were used to indicate that the different sedimentary microbial assemblages derive from specific lacustrine regimes during defined climatic periods. Two well defined climatic intervals whose sediments harboured active microbial populations and measurable ATP were sampled for a comparative environmental study based on fossil pigments and 16S rRNA gene sequences. Bacterial and archaeal 16S rRNA gene sequences recovered from the Holocene record revealed a microbial community adapted to subsaline conditions actively producing methane during organic matter degradation. These characteristics were associated with sediments resulting from endorheic lake conditions with high evaporative stress and concomitant high algal productivity. Moreover, archaeal clone libraries established throughout the Holocene record indicate an age-related stratification of these populations, consistent with a gradual use of organic substrates after deposition. In contrast, sulphate-reducing bacteria and lithotrophic Archaea were predominant in sediments dated from the Last Glacial Maximum, in which pelagic clays alternated with fine volcanic material characteristic of a lake level highstand and freshwater conditions, but reduced water column productivity. These patterns reveal that microbial assemblages identified from environmental DNA stemmed from a variety of sedimentary niches associated with climate-dependent factors (catchment inflows, water column conditions, productivity), but that initial assemblages underwent structural changes and selective preservation during early diagenesis to result in the final composition entombed in the sediments. We conclude that environmental DNA obtained from lacustrine sediments provides essential genetic information to complement paleoenvironmental indicators and trace climate change and post-depositional diagenetic processes over tens of millennia.
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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) | 0.001 | 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".