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Figure 1 in Evolution of litter size in bats and its influence on longevity and roosting ecology
Figure 1. Polytocous bat species richness map obtained by overlapping the International Union for Conservation of Nature species geographical ranges. Warmer colours represent higher diversity. The plot on the right represents the species richness as function of latitude. Thin lines represent the maximum and minimum species richness values recorded at each latitude, and the thick line represents the mean species richness per latitude.
Figure 10 in A revision of pipistrelle-like bats (Mammalia: Chiroptera: Vespertilionidae) in East Africa with the description of new genera and species
Figure 10. Plate showing the cranium and mandible of Pseudoromicia nyanza (FMNH 215626). Scale bar = 5 mm.
Figure 9 in A revision of pipistrelle-like bats (Mammalia: Chiroptera: Vespertilionidae) in East Africa with the description of new genera and species
Figure 9. Plate showing the cranium and mandible of Pseudoromicia kityoi (FMNH 223211). Scale bar = 5 mm.
Figure 8. A in A revision of pipistrelle-like bats (Mammalia: Chiroptera: Vespertilionidae) in East Africa with the description of new genera and species
Figure 8. A, portrait of Laephotis kirinyaga (FMNH 234558), showing bright brown upper parts and off-white under parts, with bicoloured hairs. The skin around the eye is blackish in the holotype, but distinctly pinkish in most of the paratypes. B, portrait of Pseudoromicia nyanza (FMNH 215626), showing the distinctive white wings and under parts of this species.
Figure 7 in A revision of pipistrelle-like bats (Mammalia: Chiroptera: Vespertilionidae) in East Africa with the description of new genera and species
Figure 7. Plate showing the cranium and mandible of Laephotis kirinyaga (FMNH 234558). Scale bar = 5 mm.
Figure 5 in A revision of pipistrelle-like bats (Mammalia: Chiroptera: Vespertilionidae) in East Africa with the description of new genera and species
Figure 5. Bacula of the four clades within formerly or traditionally recognized as Neoromicia: A, Laephotis kirinyaga (FMNH 234639); B, Neoromicia somalica (FMNH 215614); C, Pseudoromicia kityoi (FMNH 223211); and D, Afronycteris nana (DM 13013). Note the three-pronged tip in Neoromicia, the straight shaft with spatulate tip at an angle of 45° in Laephotis, the long, curved shaft with bilobed tip in Pseudoromicia and the deeply bilobed base and gently curved shaft in Afronycteris. Scale bars: 1 mm.
Figure 2 in A revision of pipistrelle-like bats (Mammalia: Chiroptera: Vespertilionidae) in East Africa with the description of new genera and species
Figure 2. Maximum likelihood phylogeny of intergeneric relationships of mitochondrial cytochrome b sequences of Vespertilionidae. The phylogeny was inferred in IQ-TREE, and its topology was similar to the Bayesian phylogeny calculated in MRBAYES. Bootstrap (BS) values followed by Bayesian posterior probabilities (PP) are indicated adjacent to nodes (those nodes with both BS <70% and PP <0.95 are not labelled).
Figure 6 in A revision of pipistrelle-like bats (Mammalia: Chiroptera: Vespertilionidae) in East Africa with the description of new genera and species
Figure 6. Principal components analysis of craniodental characters of the short-eared species of Laephotis as recognized in this study.
Figure 4 in A revision of pipistrelle-like bats (Mammalia: Chiroptera: Vespertilionidae) in East Africa with the description of new genera and species
Figure 4. Principal components analysis of craniodental measurements of the species traditionally allocated to the genus Neoromicia s.l.; the colours correspond to the four distinct types of bacula exhibited by these species (shown in Fig. 5). Each dot refers to the mean value of the craniodental measurements of examined specimens; see main text for further details.
Noise distracts foraging bats
<p>Predators frequently must detect and localize their prey in challenging environments. Noisy environments have been prevalent across the evolutionary history of predator-prey relationships, but now with increasing anthropogenic activities noise is becoming a more prominent feature of many landscapes. Here, we use the gleaning pallid bat, <i>Antrozous pallidus, </i>to investigate the mechanism by which noise disrupts hunting behavior. Noise can primarily function to <i>mask </i>– obscure by spectrally overlapping a cue of interest, or <i>distract </i>– occupy an animal's attentional or other cognitive resources. Using band-limited white noise treatments that either overlapped the frequencies of a prey cue or did not overlap this cue, we find evidence that distraction is a primary driver of reduced hunting efficacy in an acoustically-mediated predator. Under exposure to both noise types successful prey localization declined by half, search time nearly tripled, and bats used 25% more sonar pulses than when hunting in ambient conditions. Overall, the pallid bat does not seem capable of compensating for environmental noise. These findings have implications for mitigation strategies, specifically the importance of reducing sources of noise on the landscape rather than attempting to reduce the bandwidth of anthropogenic noise.</p>
Figure 3 in A revision of pipistrelle-like bats (Mammalia: Chiroptera: Vespertilionidae) in East Africa with the description of new genera and species
Figure 3. Maximum likelihood phylogeny of mitochondrial cytochrome b sequences of Vespertilionidae: (A) Pipistrellus, Scotoecus, Vansonia, and outgroups (B) Afronycteris, Pseudoromicia, Nycticeinops, and Hypsugo (C) Laephotis and Neoromicia. The phylogeny was inferred in IQ-TREE, and its topology was similar to the Bayesian phylogeny calculated in MRBAYES. Filled red circles on nodes denote bootstrap (BS) values ≥ 70% and Bayesian posterior probabilities (PP) ≥ 0.95. Open circles outlined in black indicate BS ≥ 70% and PP <0.95, and open circles outlined in red indicate BS <70% and PP> 0.95. Support values for most minor clades are not shown. Specimen localities include counties for Kenya. DRC refers to Democratic Republic of the Congo and CAR to Central African Republic. Museum acronyms are defined in the Material and Methods section. Sequences downloaded from GenBank are indicated by inclusion of GenBank accession numbers (Supporting Information, Table S1). Branch colours indicate individual species/clade membership.
Figure 1 in A revision of pipistrelle-like bats (Mammalia: Chiroptera: Vespertilionidae) in East Africa with the description of new genera and species
Figure 1. Type localities of taxa of African and Malagasy Vespertilionini and Pipistrellini. Valid species are denoted by filled circles, subspecies and synonyms by open circles and species described herein by stars: 1, Pipistrellus abaensis J. A. Allen, 1917; 2, N[ycticejus]. adovanus Heuglin, 1877; 3, Pipistrellus aero Heller, 1912; 4, Vespertilio pipistrellus var. africanus Rüppell, 1842; 5, Nycticeius africanus G. M. Allen, 1911; 6, Scotoecus albigula Thomas, 1909; 7, Scoteinus schlieffeni albiventer Thomas & Wroughton, 1908; 8, Scotophilus albofuscus Thomas, 1890; 9, Vesperugo anchietae Seabra, 1900; 10, Laephotis angolensis Monard, 1935; 11, Eptesicus capensis angolensis Hill, 1937; 12, Pipistrellus ariel Thomas, 1904; 13, Scotoecus artinii De Beaux, 1923; 14, Eptesicus ater J. A. Allen, 1917; 15, Pipistrellus nanus australis Roberts, 1913; 16, Scoteinus schlieffeni australis Thomas & Wroughton, 1908; 17, Scoteinus schlieffeni bedouin Thomas & Wroughton, 1908; 18, Pipistrellus eisentrauti bellieri De Vree, 1972; 19, Hypsugo bemainty Goodman et al., 2015; 20, Vesperus bicolor Bocage, 1889; 21, Laephotis botswanae Setzer, 1971; 22, Pipistrellus (Romicia) kuhlii broomi Roberts, 1948; 23, Vesperugo (Vesperus) brunneus Thomas, 1880; 24, Vespertilio capensis A. Smith, 1829; 25, Scotoecus cinnamomeus Wettstein, 1916; 26, Pipistrellus crassulus Thomas, 1904; 27, Pipistrellus culex Thomas, 1911; 28, Vesperus damarensis Noack, 1889; 29, Scotophilus darwini Tomes, 1859; 30, Pipistrellus deserti Thomas, 1902; 31, Pipistrellus eisentrauti Hill, 1968; 32, Scotoecus falabae Thomas, 1915; 33, Eptesicus faradjius J. A. Allen, 1917; 34, Scoteinus schlieffeni fitzsimonsi Roberts, 1932; 35, Pipistrellus fouriei Thomas, 1926; 36, Pipistrellus kuhlii fuscatus Thomas, 1901; 37, Pipistrellus fuscipes Thomas, 1913; 38, Eptesicus garambae J. A. Allen, 1917; 39, Vespertilio capensis gracilior Thomas & Schwann, 1905; 40, Vesperugo (Vesperus) grandidieri Dobson, 1876; 41, Vesperus guineensis Bocage, 1889; 42, Pipistrellus hanaki Hulva & Benda, 2004; 43, Parahypsugo happoldorum Hutterer, Decher, Monadjem & Astrin, 2019; 44, Pipistrellus helios Heller, 1912; 45, Vespertilio hesperida Temminck, 1840; 46, Scotoecus hindei Thomas, 1901; 47, Scotophilus hirundo de Winton, 1899; 48, Vesperus humbloti Milne-Edwards, 1881; 49, Vesperugo hypoleucus Heuglin [in Fitzinger & Heuglin], 1866; 50, Pipistrellus inexspectatus Aellen, 1959; 51, Neoromicia isabella Decher, Hutterer & Monadjem, 2016; 52, Laephotis kirinyaga Monadjem et al., this paper; 53, Pseudoromicia kityoi Monadjem et al., this paper; 54, Hypsugo lanzai Benda, Al-Jumaily, Reiter & Nasher, 2011; 55, Pipistrellus leucomelas Monard, 1932; 56, Parahypsugo macrocephalus Hutterer & Kerbis Peterhans, 2019; 57, Vesperugo maderensis Dobson, 1878; 58, Eptesicus somalicus malagasyensis Peterson, Eger & Mitchell, 1995; 59, Vespertilio marginatus Cretzschmar, 1830; 60, Pipistrellus marrensis Thomas & Hinton, 1923; 61, Vespertilio matroka Thomas & Schwann, 1905; 62, Pipistrellus africanus meesteri Kock, 2001; 63, Eptesicus melckorum Roberts, 1919; 64, Scotophilus minimus Noack, 1887; 65, Pipistrellus minusculus Miller, 1900; 66, Vespertilio minuta Temminck, 1840; 67, Pipistrella minuta Loche, 1867; 68, Pipistrellus musciculus Thomas, 1913; 69, Laephotis namibensis Setzer, 1971; 70, Pipistrellus nanulus Thomas, 1904; 71, Vespertilio nanus Peters, 1852; 72, Eptesicus capensis nkatiensis Roberts, 1932; 73, Scabrifer notius G. M. Allen, 1908; 74, Pseudoromicia nyanza Monadjem et al., this paper; 75, †Scotoecus olduvensis Gunnell, Butler, Greenwood & Simmons, 2015; 76, Vesperugo pagenstecheri Noack, 1889; 77, Pipistrellus (Pipistrellus) permixtus Aellen, 1957; 78, Eptesicus phasma G. M. Allen, 1911; 79, Vespertilio pipistrellus Schreber, 1774; 80, Vespertilio platycephalus Temminck, 1832; 81, Vesperugo pulcher Dobson, 1875; 82, Vesperugo pusillulus Peters, 1870; 83, Pipistrellus raceyi Bates et al., 2006; 84, Eptesicus rectitragus Wettstein, 1916; 85, Vesperugo (Vesperus) rendalli Thomas, 1889; 86, Neoromicia robertsi Goodman et al., 2012; 87, Neoromicia roseveari Monadjem et al., 2013; 88, V[espertilio]. rueppelii J. Fischer, 1829; 89, Scotophilus rusticus Tomes, 1861; 90, Vespertilio savii Bonaparte, 1837; 91, Nycticejus schlieffenii Peters, 1859; 92, Pipistrellus rueppelli senegalensis Dorst, 1960; 93, †Nycticeinops serengetiensis Gunnell et al., 2015; 94, Pipistrellus simandouensis Monadjem et al., 2020; 95, Vespertilio minutus somalicus Thomas, 1901; 96, Vesperugo stampflii Jentink, 1888; 97, Neoromicia stanleyi Goodman et al., 2017; 98, Vesperus tenuipinnis Peters, 1872; 99, Eptesicus ugandae Hollister, 1916; 100, Neoromicia vansoni Roberts, 1932; 101, Pipistrellus vernayi Roberts, 1932; 102, Laephotis wintoni Thomas, 1901; 103, Scotoecus woodi Thomas, 1917; 104, Eptesicus zuluensis Roberts, 1924. Not mapped: [Pipistrellus Kuhli] latastei Laurent, 1937; Vespertilio pusillus LeConte, 1857; Vesperugo subtilis Sundevall, 1846.
Data from: A test for rate-coupling of trophic and cranial evolutionary dynamics in New World bats
<p>Data supporting article Shi et al. 2021, Evolution: <a href="https://doi.org/10.1111/evo.14188">https://doi.org/10.1111/evo.14188</a></p> <p>Morphological evolution is often assumed to be causally related to underlying patterns of ecological trait evolution. However, few studies have directly tested whether evolutionary dynamics of and major shifts in ecological resource use are coupled with morphological shifts that may facilitate trophic innovation. Using diet and multivariate cranial (microCT) data, we tested whether rates of trophic and cranial evolution are coupled in the radiation of New World bats. <span>We developed a generalizable information-theoretic method for describing evolutionary rate heterogeneity across large candidate sets of multi-rate models of evolution, without relying on a single best-fitting model</span>. We found considerable variation in trophic evolutionary dynamics, in sharp contrast to a largely homogeneous cranial evolutionary process. This dichotomy is surprising given documented functional associations between overall skull morphology and trophic ecology. We suggest that assigning discrete trophic states may underestimate trophic generalism, and that this radiation could be characterized by generally labile crania that result in a homogeneous dynamic of overall high morphological rates. Overall, we discuss how trophic classification could substantively impact our interpretation of how these dynamics covary in adaptive radiations.</p>
Data from: New insights on postglacial colonisation in Western Europe: the phylogeography of the Leisler's bat (Nyctalus leisleri)
Despite recent advances in the understanding of the interplay between a dynamic physical environment and phylogeography in Europe, the origins of contemporary Irish biota remain uncertain. Current thinking is that Ireland was colonized post-glacially from southern European refugia, following the end of the last glacial maximum (LGM), some 20 000 years BP. The Leisler's bat (Nyctalus leisleri), one of the few native Irish mammal species, is widely distributed throughout Europe but, with the exception of Ireland, is generally rare and considered vulnerable. We investigate the origins and phylogeographic relationships of Irish populations in relation to those across Europe, including the closely related species N. azoreum. We use a combination of approaches, including mitochondrial and nuclear DNA markers, in addition to approximate Bayesian computation and palaeo-climatic species distribution modelling. Molecular analyses revealed two distinct and diverse European mitochondrial DNA lineages, which probably diverged in separate glacial refugia. A western lineage, restricted to Ireland, Britain and the Azores, comprises Irish and British N. leisleri and N. azoreum specimens; an eastern lineage is distributed throughout mainland Europe. Palaeo-climatic projections indicate suitable habitats during the LGM, including known glacial refugia, in addition to potential novel cryptic refugia along the western fringe of Europe. These results may be applicable to populations of many species.
Data from: Bat trait, genetic and pathogen data from large-scale investigations of African fruit bats (Eidolon helvum)
Bats, including African straw-coloured fruit bats (Eidolon helvum), have been highlighted as reservoirs of many recently emerged zoonotic viruses. This common, widespread and ecologically important species was the focus of longitudinal and continent-wide studies of the epidemiological and ecology of Lagos bat virus, henipaviruses and Achimota viruses. Here we present a spatial, morphological, demographic, genetic and serological dataset encompassing 2827 bats from nine countries over an 8-year period. Genetic data comprises cytochrome b mitochondrial sequences (n=608) and microsatellite genotypes from 18 loci (n=544). Tooth-cementum analyses (n=316) provide rare age-specific serologic data for a lyssavirus, a henipavirus and two rubulaviruses. This dataset contributes a substantial volume of data on the ecology of E. helvum and its viruses and will be valuable for a wide range of studies, including viral transmission dynamic modelling in age-structured populations, investigation of seasonal reproductive asynchrony in wide-ranging species, ecological niche modelling, inference of island colonisation history, exploration of relationships between island and body size, and various spatial analyses of demographic, morphometric or serological data.
Data from: Nathusius' bats optimize long-distance migration by flying at maximum range speed.
Metabolic rate of 12 Pipistrellus nathusii in relation to varying airspeed. We measured the metabolic rate of flying bats in a wind tunnel using the 13C labeled Na-bicarbonate method. The relationship between metabolic rate and airspeed was U-shaped in the majority of individuals. We could not find a U-shaped curve in a few individuals that engaged in flight manoeuvers, including landing. We used the shape of the U-shaped power curve to estimate minimum flight speed and maximum range speed for the study species. Further we present data on migration speed (n=37) and foraging flight speed (n=40) in wild Pipistrellus nathusii at a major miratory corridor in Latvia.
Data from: Range expansion is associated with increased survival and fecundity in a long-lived bat species
The speed and dynamics of range expansions shape species distributions and community composition. Despite the critical impact of population growth rates for range expansion, they are neglected in existing empirical studies, which focus on the investigation of selected life history traits. Here, we present an approach based on non-invasive genetic capture-mark-recapture data for the estimation of adult survival, fecundity, and juvenile survival, which determine population growth. We demonstrate the reliability of our method with simulated data, and use it to investigate life history changes associated with range expansion in 35 colonies of the bat species Rhinolophus hipposideros. Comparing the demographic parameters inferred for 19 of those colonies which belong to an expanding population with those inferred for the remaining 16 colonies from a non-expanding population reveals that range expansion is associated with higher net reproduction. Juvenile survival was the main driver of the observed reproduction increase in this long-lived bat species with low per capita annual reproductive output. The higher average growth rate in the expanding population was not associated with a trade-off between increased reproduction and survival, suggesting that the observed increase in reproduction stems from a higher resource acquisition in the expanding population. Environmental conditions in the novel habitat hence seem to have an important influence on range expansion dynamics, and warrant further investigation for the management of range expansion in both native and invasive species.
Data from: Diversity of bat astroviruses in Lao PDR and Cambodia
Astroviruses are known to infect humans and a wide range of animal species, and can cause gastroenteritis in their hosts. Recent studies have reported astroviruses in bats in Europe and in several locations in China. We sampled 1876 bats from 17 genera at 45 sites from 14 and 13 provinces in Cambodia and Lao PDR respectively, and tested them for astroviruses. Our study revealed a high diversity of astroviruses among various Yangochiroptera and Yinpterochiroptera bats. Evidence for varying degrees of host restriction for astroviruses in bats was found. Furthermore, additional Pteropodid hosts were detected. The astroviruses formed distinct phylogenetic clusters within the genus Mamastrovirus, most closely related to other known bat astroviruses. The astrovirus sequences were found to be highly saturated indicating that phylogenetic relationships should be interpreted carefully. An astrovirus clustering in a group with other viruses from diverse hosts, including from ungulates and porcupines, was found in a Rousettus bat. These findings suggest that diverse astroviruses can be found in many species of mammals, including bats.
Data from: Echolocation and roosting ecology determine sensitivity of forest-dependent bats to coffee agriculture
Species differ in vulnerability to anthropogenic landuse changes. Knowledge of the mechanisms driving differential sensitivity can inform conservation strategies but is generally lacking for species-rich taxa in the tropics. The diverse bat fauna of Southeast Asia is threatened by rapid loss of forest and expanding agricultural activities, but the associations between species, traits, vulnerability to agriculture and the underlying drivers have yet to be elucidated. We studied the responses of speciose insectivorous bat assemblages to robusta coffee cultivation in Sumatra, Indonesia. We compared abundance, species richness and assemblage structures of bats between forests and coffee farms based on trapping data and evaluated the influence of vegetation complexity on assemblage composition and species-level reactions. Bat abundance and species richness were significantly lower in coffee farms than in forests. Bat assemblage structure differed between landuses, and the overall variation can be largely explained by vegetation simplification. Species sensitive to coffee agriculture were associated with more complex vegetation structure, whereas tolerant species were associated with simpler vegetation structure. Sensitive and tolerant species differed in the type, frequency, and bandwidth of echolocation calls and roost use. Species sensitive to coffee use broadband and high-pitched frequency-modulated calls, which are efficient at detecting insects in complex vegetation, and roost in plant structures that may be lost as vegetation is simplified. In contrast, tolerant species used lower-pitched constant frequency calls and roost in caves. We advocate for greater use of trait analyses in studies seeking to clarify the influence of agriculture on diverse tropical bat faunas.
Data from: Metabarcoding for the parallel identification of several hundred predators and their preys: application to bat species diet analysis
Assessing diet variability is of main importance to better understand the biology of bats and design conservation strategies. Although the advent of metabarcoding has facilitated such analyses, this approach does not come without challenges. Biases may occur throughout the whole experiment, from fieldwork to biostatistics, resulting in the detection of false negatives, false positives or low taxonomic resolution. We detail a rigorous metabarcoding approach based on a short COI minibarcode and two-step PCR protocol enabling the 'all at once' taxonomic identification of bats and their arthropod preys for several hundreds of samples. Our study includes faecal pellets collected in France from 357 bats representing 16 species, as well as insect mock communities that mimic bat meals of known composition, negative and positive controls. All samples were analysed using three replicates. We compare the efficiency of DNA extraction methods and we evaluate the effectiveness of our protocol using identification success, taxonomic resolution, sensitivity, and amplification biases. Our parallel identification strategy of predators and preys reduces the risk of mis-assigning preys to wrong predators and decreases the number of molecular steps. Controls and replicates enable to filter the data and limit the risk of false positives, hence guaranteeing high confidence results for both prey occurrence and bat species identification. We validate 551 COI variants from arthropod including 18 orders, 117 family, 282 genus and 290 species. Our method therefore provides a rapid, resolutive and cost-effective screening tool for addressing evolutionary ecological issues or developing 'chirosurveillance' and conservation strategies.
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Allen Brain Atlas
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