Ecological turnover and megafaunal ghost ranges during the Pleistocene-Holocene transition in central Yukon, Canada as revealed by palaeoenvironmental DNA
Bibliographic record
Abstract
The multitude of factors alleged to have contributed to the late Quaternary mass extinction of some two-thirds of Earth’s megafauna is complicated by the coarse record of buried macro-fossils. In response, micro-methods such as ancient DNA have been increasingly able to augment discontinuous palaeontological records to investigate the relative timings of vegetation turnover versus megafaunal extirpations—all in the absence of biological tissues. Here, we present sedimentary ancient DNA data retrieved using the PalaeoChip Arctic-1.0 bait-set diachronically identifying fauna and flora from permafrost cores recovered from the Klondike region of central Yukon, Canada dating between 30,000–6000 calendar years BP. We observe a substantial turnover in ecosystem composition between 13,000–10,000 BP with the rise of woody shrubs and the disappearance of mammoth-steppe vegetation. We also identify a lingering signal of Equus sp. (North American horse) and Mammuthus primigenius (woolly mammoth) from multiple samples thousands of years after their last dated macro-fossils, possibly as late as the mid-Holocene.
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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 | 0.003 |
| 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".