Hybridization in leopard frogs (<i>Rana pipiens</i> complex): terrestrial performance of newly metamorphosed hybrid and parental genotypes in field enclosures
Bibliographic record
Abstract
Terrestrial ecology has been largely neglected in the study of amphibian life histories because it is difficult to manipulate most species during the terrestrial stage. I examined the terrestrial performance of Rana blairi, Rana sphenocephala, and four hybrid (two F1 and two advanced generation) genotypes in replicated experimental enclosures to test for differences in traits related to juvenile terrestrial fitness. I produced all genotypes by means of artificial fertilizations using frogs collected from natural populations in central Missouri, and juvenile frogs were obtained from larvae reared in experimental ponds. Following metamorphosis, froglets were raised in single-genotype groups in terrestrial enclosures through the first overwintering. The proportion surviving did not vary among genotypes, but the power to detect significant differences was low. F1 hybrid genotypes BS and SB demonstrated significantly higher growth rates than either parental species or advanced-generation hybrid genotypes. Observation of growth rates of advanced-generation hybrids equal to those of the parental species, and heterosis in F1 hybrids for growth rate, suggests that natural hybridization between R. blairi and R. sphenocephala can produce novel and relatively fit hybrid genotypes. Direct measurement of multiple fitness components for hybrid and parental genotypes is critical for assessing the evolutionary potential of natural hybridization in organisms with complex life cycles.
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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 | 0.000 |
| 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".