Ancient DNA sequences point to a large loss of mitochondrial genetic diversity in the saiga antelope (<i>Saiga tatarica</i>) since the Pleistocene
Bibliographic record
Abstract
Prior to the Holocene, the range of the saiga antelope (Saiga tatarica) spanned from France to the Northwest Territories of Canada. Although its distribution subsequently contracted to the steppes of Central Asia, historical records indicate that it remained extremely abundant until the end of the Soviet Union, after which its populations were reduced by over 95%. We have analysed the mitochondrial control region sequence variation of 27 ancient and 38 modern specimens, to assay how the species' genetic diversity has changed since the Pleistocene. Phylogenetic analyses reveal the existence of two well-supported, and clearly distinct, clades of saiga. The first, spanning a time range from >49,500 (14) C ybp to the present, comprises all the modern specimens and ancient samples from the Northern Urals, Middle Urals and Northeast Yakutia. The second clade is exclusive to the Northern Urals and includes samples dating from between 40,400 to 10,250 (14) C ybp. Current genetic diversity is much lower than that present during the Pleistocene, an observation that data modelling using serial coalescent indicates cannot be explained by genetic drift in a population of constant size. Approximate Bayesian Computation analyses show the observed data is more compatible with a drastic population size reduction (c. 66-77%) following either a demographic bottleneck in the course of the Holocene or late Pleistocene, or a geographic fragmentation (followed by local extinction of one subpopulation) at the Holocene/Pleistocene transition.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".