Fine‐scale biogeographical and temporal diversification processes of peacock swallowtails (<i>Papilio</i> subgenus <i>Achillides</i>) in the Indo‐Australian Archipelago
Bibliographic record
Abstract
© The Willi Hennig Society 2012. ABSTRACT: Explanations for the high species diversity of the Indo-Australian Archipelago are often challenged by the region's complex climatic and geological histories. Here, we investigated the evolutionary history of swallowtail butterflies of the Papilio subgenus Achillides, comprising up to 25 recognized species and about 100 subspecies distributed across the Indo-Australian Archipelago. To estimate the relative contributions of factors influencing their biodiversity, we used DNA sequences to infer the phylogeny and species limits of 22 species including most of their subspecies. We recovered a highly resolved and well-supported phylogeny for the subgenus, and clarified some taxonomic ambiguities at the species level. The corresponding DNA-based species phylogeny was then employed to reconstruct their historical biogeography using relaxed-clock and parametric-based analyses. Molecular dating and biogeographical analyses showed that Achillides originated around 19 Ma in Sunda + Wallacea. Biogeographical reconstructions indicated that geological vicariance shaped the early evolutionary history of Achillides whereas dispersal influenced late diversification. Birth-death likelihood analyses allowed exploration of their tempo and mode of diversification. We detected several shifts in diversification rates that are attributable to past climate-induced biogeographical events. By assessing both regional and fine-scale biodiversity patterns, this study brings new findings to a biogeographical understanding of the Indo-Australian Archipelago.
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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 | 0.000 |
| 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".