Genomic and Morphological Evidence Support Contemporary Three‐Way Interspecific Hybridization in Ranid Frogs
Bibliographic record
Abstract
ABSTRACT Hybridization is increasingly understood as common throughout and beyond the speciation process, rather than an anomaly. Sympatric taxa are expected to exhibit strong reproductive isolation, and although hybridization may occur, it often results in inviable offspring. We investigated hybridization among three ranid frogs ( Rana areolata , R. palustris , and R. sphenocephala ) in eastern Oklahoma, where their distributions and breeding phenology overlap. Using micro‐CT scans of cranial morphology, genomic SNP data, and phenological records, we confirmed two putative hybrids collected in the field—remarkable given the phylogenetic distance between these non‐sister taxa. Genomic data show split ancestry from parental populations, representing one R. areolata × R. palustris and one R. areolata × R. sphenocephala . Cranial morphology indicates hybrids exhibit intermediate phenotypes, and our assessment identified a third likely hybrid, a specimen collected two decades earlier from the same area. Both confirmed hybrids were R. areolata backcrosses, but minimal introgression throughout the dataset suggests hybrid fitness may be lower than that of parental populations. Hybridization appears facilitated by overlapping breeding strategies and ecological factors leading to misdirected amplexus. This study provides the first documentation of natural hybridization in R. areolata , a species of conservation concern throughout its range. Our findings emphasize the utility of high‐resolution morphological data (micro‐CT) in complementing genomic approaches for hybrid diagnosis and suggest cranial morphology may be an effective method for hybrid identification in similar systems. Understanding this atypical three‐species hybridization has important implications for conservation, as hybrid fitness and introgression can influence population dynamics and genetic integrity.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".