Revisiting the phylogeography, demography and taxonomy of the frog genus Ptychadena in the Ethiopian highlands with the use of genome-wide SNP data
Bibliographic record
Abstract
Understanding the diversification of biological lineages is central to evolutionary studies. To properly study the process of speciation, it is necessary to link micro-evolutionary studies with macro-evolutionary mechanisms. Micro-evolutionary studies require proper sampling across a taxon's range to adequately infer genetic diversity. Here we use the grass frogs of the genus Ptychadena from the Ethiopian highlands as a model to study the process of lineage diversification in this unique biodiversity hotspot. We used thousands of genome-wide SNPs obtained from double digest restriction site associated DNA sequencing (ddRAD-seq) in populations of the Ptychadena neumanni species complex from the Ethiopian highlands in order to infer their phylogenetic relationships and genetic structure, as well as to study their demographic history. Our genome-wide phylogenetic study supports the existence of approximately 13 lineages clustered into 3 species groups. Our phylogenetic and phylogeographic reconstructions suggest that those endemic lineages diversified in allopatry, and subsequently specialized to different habitats and elevations. Demographic analyses point to a continuous decrease in the population size across the majority of lineages and populations during the Pleistocene, which is consistent with a continuous period of aridification that East Africa experienced since the Pliocene. We discuss the taxonomic implications of our analyses and, in particular, we warn against the recent practice to solely use Bayesian species delimitation methods when proposing taxonomic changes.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".