Phylogeography and palaeodistribution modelling of <i>Nassauvia</i> subgenus <i>Strongyloma</i> (Asteraceae): exploring phylogeographical scenarios in the Patagonian steppe
Bibliographic record
Abstract
The Patagonian steppe is an immense, cold, arid region, yet phylogeographically understudied. Nassauvia subgen. Strongyloma is a characteristic element of the steppe, exhibiting a continuum of morphological variation. This taxon provides a relevant phylogeographical model not only to understand how past environmental changes shaped the genetic structure of its populations, but also to explore phylogeographical scenarios at the large geographical scale of the Patagonian steppe. Here, we (1) assess demographic processes and historical events that shaped current geographic patterns of haplotypic diversity; (2) analyze hypotheses of isolation in refugia, fragmentation of populations, and/or colonization of available areas during Pleistocene glaciations; and (3) model extant and palaeoclimatic distributions to support inferred phylogeographical patterns. Chloroplast intergenic spacers, rpl32-trnL and trnQ-5'rps16, were sequenced for 372 individuals from 63 populations. Nested clade analysis, analyses of molecular variance, and neutrality tests were performed to assess genetic structure and range expansion. The present potential distribution was modelled and projected onto a last glacial maximum (LGM) model. Of 41 haplotypes observed, ten were shared among populations associated with different morphological variants. Populations with highest haplotype diversity and private haplotypes were found in central-western and south-eastern Patagonia, consistent with long-term persistence in refugia during Pleistocene. Palaeomodelling suggested a shift toward the palaeoseashore during LGM; new available areas over the exposed Atlantic submarine platform were colonized during glaciations with postglacial retraction of populations. A scenario of fragmentation and posterior range expansion may explain the observed patterns in the center of the steppe, which is supported by palaeomodelling. Northern Patagonian populations were isolated from southern populations by the Chubut and the Deseado river basins during glaciations. Pleistocene glaciations indirectly impacted the distribution, demography, and diversification of subgen. Strongyloma through decreased winter temperatures and water availability in different areas of its range.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".