Detection of a marine to terrestrial transition in lake sediment from Baffin Island, Arctic Canada, using sedimentary DNA
Bibliographic record
Abstract
The recent development and refinement of the molecular toolkit to detect ancient DNA in sediment samples (sedaDNA) has allowed the high-resolution reconstruction of ancient ecological communities dating back thousands of years. Specifically, DNA from lake sediment has been used to derive continuous records of ecological community changes through variable paleoenvironmental conditions. These paleoecological reconstructions can be an important tool for understanding how ecosystems may respond to current and future warming, but reliable methods for taxonomic detection are needed in order make optimal use of these bioarchives. In this study, metabarcoding assays targeting mammal, bird, and marine fauna have been carried out across a sediment core collected from Lake Qaupat, Baffin Island, Arctic Canada. While Lake Qaupat is currently ~30 m above sea level, it is located below the local marine limit related to isostatic adjustment after deglaciation. Consequently, initial sediment accumulation is in a marine environment, Combined results from the DNA assays indicate a transitional period over which marine-based fauna are systematically replaced by more terrestrial-based fauna. This transition occurs at a predicted age of 7.4 ± 0.2 ka. This research builds on previous studies to develop Baffin Island paleorecords in an effort to inform future changes to the Arctic system in the context of a rapidly warming world. Ultimately these data will be useful in better informing climate models and how taxa may move, adapt or be extirpated from arctic regions[GHM1] [SC2] .[SC3]
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 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".