Online appendix for: Hybridization and transgressive evolution as drivers of adaptive radiations: Reticulate evolution generates diversity in the Puerto Rican Anolis lizards
Bibliographic record
Abstract
Interspecific hybridization may act as a major force contributing to the evolution of biodiversity. Although generally thought to reduce or constrain divergence between two species, hybridization can, paradoxically, promote divergence by increasing genetic variation or providing novel combinations of alleles that selection can act upon to move lineages toward new adaptive peaks. Hybridization may, then, play a key role in adaptive radiation by allowing lineages to diversify into new ecological space. Here, we test for signatures of historical hybridization in the Anolis lizards of Puerto Rico and evaluate two hypotheses for the role of hybridization in facilitating adaptive radiation – the hybrid swarm origins hypothesis and the syngameon hypothesis. Using whole genome sequences from all ten species of Puerto Rican anoles, we calculated D and f-statistics (from ABBA-BABA tests) to test for introgression across the radiation and employed multispecies network coalescent methods to reconstruct phylogenetic networks that allow for hybridization. We then analyzed morphological data for these species to test for patterns consistent with transgressive evolution, a phenomenon in which the trait of a hybrid lineage is found outside of the range of its two parents. Our analyses uncovered strong evidence for introgression at multiple stages of the radiation, including support for an ancient hybrid origin of a clade comprising half of the extant Puerto Rican anole species. Moreover, we detected significant signals of transgressive evolution for two ecologically-important traits, head length and toepad width, the latter of which has been described as a key innovation in Anolis.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.805 | 0.362 |
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".