Colour vision variation in leaf‐nosed bats (Phyllostomidae): Links to cave roosting and dietary specialization
Bibliographic record
Abstract
Bats are a diverse radiation of mammals of enduring interest for understanding the evolution of sensory specialization. Colour vision variation among species has previously been linked to roosting preferences and echolocation form in the suborder Yinpterochiroptera, yet questions remain about the roles of diet and habitat in shaping bat visual ecology. We sequenced OPN1SW and OPN1LW opsin genes for 20 species of leaf-nosed bats (family Phyllostomidae; suborder Yangochiroptera) with diverse roosting and dietary ecologies, along with one vespertilionid species (Myotis lavali). OPN1LW genes appear intact for all species, and predicted spectral tuning of long-wavelength opsins varied among lineages. OPN1SW genes appear intact and under purifying selection for Myotis lavali and most phyllostomid bats, with two exceptions: (a) We found evidence of ancient OPN1SW pseudogenization in the vampire bat lineage, and loss-of-function mutations in all three species of extant vampire bats; (b) we additionally found a recent, independently derived OPN1SW pseudogene in Lonchophylla mordax, a cave-roosting species. These mutations in leaf-nosed bats are independent of the OPN1SW pseudogenization events previously reported in Yinpterochiropterans. Therefore, the evolution of monochromacy (complete colour blindness) has occurred in both suborders of bats and under various evolutionary drivers; we find independent support for the hypothesis that obligate cave roosting drives colour vision loss. We additionally suggest that haematophagous dietary specialization and corresponding selection on nonvisual senses led to loss of colour vision through evolutionary sensory trade-off. Our results underscore the evolutionary plasticity of opsins among nocturnal mammals.
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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 | 0.000 |
| 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".