Sea ice protists in arctic marine sedaDNA records: origins, diversity, and vertical export of DNA from the sea surface to the seafloor 
Bibliographic record
Abstract
Arctic sea ice is declining at an unprecedented pace as the Arctic Ocean heads towards ice-free summers within the next few decades. Because of the role of sea ice in the Earth System such as ocean circulation and ecosystem functioning, reconstructing its past variability is of great importance providing insight into past climate patterns and future climate scenarios. Today, much of our knowledge of past sea-ice variability derives from a relatively few microfossil and biogeochemical tracers, which have limitations, such as preservation biases and low taxonomic resolution. Marine sedimentary ancient DNA (marine sedaDNA) has the potential to capture more of the arctic marine biodiversity compared to other approaches. However, little is known about how well past communities are represented in marine sedaDNA. The transport and fate of DNA derived from sea-ice associated organisms, from surface waters to the seafloor and its eventual incorporation into marine sediment records is poorly understood. Here, we present results from a study applying a combination of methods to examine modern and ancient DNA to material collected along the Northeast Greenland Shelf. We characterized the vertical export of genetic material by amplicon sequencing the hyper-variable V4 region of the 18S rDNA at three water depths, in surface sediments, and in a dated sediment core. The amplicon sequencing approach, as currently applied, includes some limitations for quantitative reconstructions of past changes such as primer competition, PCR errors, and variation of gene copy numbers across different taxa. For these reasons we quantified amplicons from a single species, the circum-polar sea ice dinoflagellate Polarella glacialis in the marine sedaDNA, using digital droplet PCR. The results will increase our understanding on the taphonomy of DNA in sea ice environments, how sedimentation differs among taxonomic groups, and provide indications to potentially useful marine sedaDNA-based proxies for climate and environmental reconstructions.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".