Across mountains and ocean: species delimitation and historical connectivity in Holarctic and Arctic-Alpine wolf spiders (Lycosidae, <i>Pardosa</i>)
Bibliographic record
Abstract
Abstract Holarctic species offer great opportunities to study biogeography, phylogenetics, taxonomy, and local adaptation. Species that are considered conspecific between the Palearctic and the Nearctic realms are often split into 2 or more species when denser sampling and molecular markers are applied. Similar in complexity but at a finer geographical scale are species groups having Arctic-Alpine distributions where lineages have complicated demographic histories due to glacial dynamics. In both cases, allopatric speciation might not result in fast differentiation of morphological characters if environmental conditions in isolated areas are similar and the main driver of variability is genetic drift. Here, we study the Holarctic Pardosa hyperborea (Thorell, 1872) and its closest European relatives to assess their taxonomic status and patterns of genetic variability. Based on DNA barcodes and genomic data from double-digest restriction site associated sequencing, we propose that the North American populations should be regarded as a distinct species (P. luteola Emerton,1894, stat. resurr.), possibly consisting of several independent lineages. With the help of D-statistics, population genetic simulations and phylogenetic networks analysis, we demonstrate historical introgression among European species of the group and a likely explanation for shared DNA barcodes among allopatric and fully differentiated species. Our study exposes a promising model for studying speciation processes and demographic history in parallel on both sides of the Atlantic Ocean and demonstrates the usefulness of genomic tools in elucidating the taxonomy and biogeography of taxa across broad geographic scales.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 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".