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FIG. 18 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 18. — Ventral view of the skull of Molossus pretiosus Miller, 1902. Note the crest between the occipital and the basisphenoid pits. Scale bar: 1 mm.
FIG. 13 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 13. — Molossus molossus (Pallas, 1766) skull: A, dorsal view; B, frontal view; C, ventral view; D, posterior view; E, lateral view. Scale bar: 1 mm.
FIG. 14 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 14. — Molossus molossus (Pallas, 1766). Photo courtesy of Dr Marco A. R. Mello (https://marcoarmello.wordpress.com).
FIG. 12 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 12. — Geographic range of Molossus rufus (E. Geoffroy, 1805) in Brasil. The numbers represent the localities described in Appendix 1.
FIG. 10 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 10. — Molossus rufus (E. Geoffroy, 1805). Photo courtesy of Dr Marco A. R. Mello (https://marcoarmello.wordpress.com).
FIG. 11 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 11. — Skull of Molossus rufus E. Geoffroy, 1805: A, dorsal view; B, posterior view; C, lateral view; D, frontal view. Scale bar: 1 mm.
FIG. 2 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 2. — Variable characters in skull morphology within Molossus E. Geoffroy, 1805 (Pallas, 1766): A, B, lateral views; C, D, ventral views; E, F, posterior view; H, G, frontal view. Numbers represents characters described in the text: 1, skull robustness; 2, sagittal crest; 3, basioccipital pits; 4, projection of the canines; 5, lambdoidal crest and occipital complex; 6, mastoid process; 7, rostrum shape; 8, infraorbital foramen; 9, upper incisors; 10, nasal process. Not to scale.
FIG. 8 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 8. — Ventral view of skull of Molossus coibensis Allen, 1904. The arrow shows the absence of the basioccipital pits.
FIG. 6 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 6. — Molossus aztecus Saussure, 1860 skull: A, ventral view; B, posterior view; C, lateral view; D, frontal view. Scale bar: 1 mm.
FIG. 5. — Strict consensus tree from eight most parsimonious trees recovered for Molossus E. Geoffroy, 1805 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 5. — Strict consensus tree from eight most parsimonious trees recovered for Molossus E. Geoffroy, 1805. Numbers above the branches indicate Bootstrap values and bottom numbers indicate Bremer support values.
FIG. 3 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 3. — Principal Components Analysis plot of PC1 and PC2 based on 13 cranial and external variables of Molossus E. Geoffroy, 1805: A, females, B, males. Symbols: ■, M. pretiosus Miller, 1902; ■, M. rufus (E. Geoffroy, 1805); ▲, M. currentium Thomas, 1901; +, M. molossus (Pallas, 1766); X, M. coibensis Allen, 1904; ▲, M. aztecus Saussure, 1860;, M. sinaloae Allen, 1906; *, and Molossus sp.
FIG. 1 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 1. — Definition of skull measurements used in this study of Molossus E. Geoffroy, 1805. Abbreviations: see Material & Methods. Reprinted from Loureiro
FIG. 7 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 7. — Geographic range of Molossus aztecus Saussure, 1860 in Brazil (Gregorin et al. 2011). -, represents new records for the country, the numbers represent the localities described in Appendix 1.
FIG. 4 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 4. — Principal component analysis of the first two main components (PC1 and PC2) based on 13 cranial and external variables of Molossus molossus: A, males,B, females.Symbols:■, Rio de Janeiro; ▲, Ceará; ▼, Pará; +, Rio Grande do Sul; ▲, Piauí; ●, Mato Grosso do Sul; O, Minas Gerais; *, Bahia; ◆, Amazonas; ●, Paraíba;, São Paulo; ❚, Mato Grosso; x, Paraiba, ▼, Acre; ●, Piaui.
FIG. 19 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 19. — Geographic range of Molossus pretiosus Miller, 1902 in Brasil. The numbers represent the localities described in Appendix 1.
FIG. 17 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 17. — Geographic range of Molossus currentium Thomas, 1901 in Brasil: -, represents new records for the country. The numbers represent the locality described in Appendix 1.
FIG. 9 in Diversity, morphological phylogeny, and distribution of bats of the genus Molossus E. Geoffroy, 1805 (Chiroptera, Molossidae) in Brazil
FIG. 9. — Geographic range of Molossus coibensis Allen, 1904 in Brazil: -, Represents new records for the country. The numbers represent the localities described in Appendix 1.
Sex-based population structure of ectoparasites from Neotropical bats
<p>The structure and composition of populations may be molded by multiple evolutionary and ecological mechanisms, with natural selection affecting sex ratios, as well as the distributions of each sex throughout the environment. To address sex-based aspects of population structure, I evaluated sex ratios, co-occurrence of the sexes, correlations of abundance of the sexes, and dispersion of individuals of each sex for each of 34 host-ectoparasite associations from Paraguayan bats. Of the 34 host-ectoparasite associations, 23 exhibited positive co-occurrence, 27 exhibited positive correlation of abundances, 4 exhibited male sex bias, 1 exhibited female sex bias, 27 had clumped distributions of males, and 26 had clumped distributions of females. No associations exhibited negative co-occurrence, negative correlation of abundance, or hyper-dispersed males or females. There was no evidence for sexual segregation, sex-based niche partitioning, or intrasexual selection in any host-ectoparasite association. Previously proposed mechanisms (e.g. pre-partum sex bias, local mate competition, or mortality from host grooming) fail to explain observed patterns of sex bias. For ectoparasites of hosts that occupy permanent roost sites, sex-specific behaviour related to reproduction may make females more susceptible to off-host predation and less likely to be present in samples from bats captured away from the roost.</p>
Data from: Neural representation of bat predation risk and evasive flight in moths: a modelling approach
<p>Most animals are at risk from multiple predators and can vary anti-predator behaviour based on the level of threat posed by each predator. Animals use sensory systems to detect predator cues, but the relationship between the tuning of sensory systems and the sensory cues related to predator threat are not well-studied at the community level. Noctuid moths have ultrasound-sensitive ears to detect the echolocation calls of predatory bats. Here, combining empirical data and mathematical modelling, we show that moth hearing is adapted to provide information about the threat posed by different sympatric bat species. First, we found that multiple characteristics related to the threat posed by bats to moths correlate with bat echolocation call frequency. Second, the frequency tuning of the most sensitive auditory receptor in noctuid moth ears provides information allowing moths to escape detection by all sympatric bats with similar safety margin distances. Third, the least sensitive auditory receptor usually responds to bat echolocation calls at a similar distance across all moth species for a given bat species. If this neuron triggers last-ditch evasive flight, it suggests that there is an ideal reaction distance for each bat species, regardless of moth size. This study shows that even a very simple sensory system can adapt to deliver information suitable for triggering appropriate defensive reactions to each predator in a multiple predator community.</p>
Data from: Diversification rates have no effect on the convergent evolution of foraging strategies in the most speciose genus of bats, Myotis
<p>Adaptive radiations are defined as rapid diversification with phenotypic innovation led by colonization to new environments. Notably, adaptive radiations can occur in parallel when habitats with similar selective pressures are accessible promoting convergent adaptions. While convergent evolution appears to be a common process, it is unclear what are the main drivers leading the reappearance of morphologies or ecological roles. We explore this question in <i>Myotis</i> bats, the only Chiropteran genus with a worldwide distribution. Three foraging strategies –gleaning, trawling, and aerial netting– repeatedly evolved in several regions of the world, each linked to characteristic morphologies recognized as ecomorphs. Phylogenomic, morphometric, and comparative approaches were adopted to investigate convergence of such foraging strategies and skull morphology as well as factors that explain diversification rates. Genomic and morphometric data were analyzed from ~80% extant taxa. Results confirm that the ecomorphs evolved multiple times, with trawling evolving more often and foliage gleaning most recently. Skull morphology does not reflect common ancestry, evolves convergently with foraging strategy. While diversification rates have been roughly constant across the genus, speciation rates are area-dependent in taxa with temperate distributions. Results suggest that in this species-rich group of bats, first, stochastic processes have led divergence into multiple lineages. Then, natural selection in similar niches has promoted repeated adaptation of phenotypes and foraging strategies. <i>Myotis</i> bats are thus a remarkable case of ecomorphological convergence and an emerging model system for investigating the genomic basis of parallel adaptive radiation.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.