Deciphering the evolution of birdwing butterflies 150 years after Alfred Russel Wallace
Bibliographic record
Abstract
One hundred and fifty years after Alfred Wallace studied the geographical variation and species diversity of butterflies in the Indomalayan-Australasian Archipelago, the processes responsible for their biogeographical pattern remain equivocal. We analysed the macroevolutionary mechanisms accounting for the temporal and geographical diversification of the charismatic birdwing butterflies (Papilionidae), a major focus of Wallace's pioneering work. Bayesian phylogenetics and dating analyses of the birdwings were conducted using mitochondrial and nuclear genes. The combination of maximum likelihood analyses to estimate biogeographical history and diversification rates reveals that diversity-dependence processes drove the radiation of birdwings, and that speciation was often associated with founder-events colonizing new islands, especially in Wallacea. Palaeo-environment diversification models also suggest that high extinction rates occurred during periods of elevated sea level and global warming. We demonstrated a pattern of spatio-temporal habitat dynamics that continuously created or erased habitats suitable for birdwing biodiversity. Since birdwings were extinction-prone during the Miocene (warmer temperatures and elevated sea levels), the cooling period after the mid-Miocene climatic optimum fostered birdwing diversification due to the release of extinction. This also suggests that current global changes may represent a serious conservation threat to this flagship group.
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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 | 0.000 |
| 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".