Does evolution of echolocation calls and morphology in Molossus result from convergence or stasis?
Bibliographic record
Abstract
Although many processes of diversification have been described to explain variation of morphological traits within clades that have obvious differentiation among taxa, not much is known about these patterns in complexes of cryptic species. Molossus is a genus of bats that is mainly Neotropical, occurring from the southeastern United States to southern Argentina, including the Caribbean islands. Molossus comprises some groups of species that are morphologically similar but phylogenetically divergent, and other groups of species that are genetically similar but morphologically distinct. This contrast allows investigation of unequal trait diversification and the evolution of morphological and behavioural characters. In this study, we assessed the role of phylogenetic history in a genus of bat with three cryptic species complexes, and evaluated if morphology and behavior are evolving concertedly. The Genotype by Sequence genomic approach was used to build a species-level phylogenetic tree for Molossus and to estimate the ancestral states of morphological and echolocation call characters. We measured the correlation of phylogenetic distances to morphological and echolocation distances, and tested the relationship between morphology and behavior when the effect of phylogeny is removed. Morphology evolved via a mosaic of convergence and stasis, whereas call design was influenced exclusively through local adaptation and convergent evolution. Furthermore, the frequency of echolocation calls is negatively correlated with the size of the bat, but other characters do not seem to be evolving in concert. We hypothesize that slight variation in both morphology and behaviour among species of the genus might result from niche specialization, and that traits evolve to avoid competition for resources in similar environments.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".