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67 results for “Insectivorous bats”
FIG. 3 in Species richness, functional diversity and assemblage structure of insectivorous bats along an elevational gradient in tropical West Africa
FIG. 3. Dendrogram of bat functional groups present on Mount Nimba. Eight functional groups were identified, each represented by a different colour. See Supplementary Table S1 for full species names
FIG. 1 in Species richness, functional diversity and assemblage structure of insectivorous bats along an elevational gradient in tropical West Africa
FIG. 1. Study sites in Liberia and Guinea (Google Earth, 2015) and their assignment to the eight elevation belts. Key for site colours: red: <500 m; green: 500–600 m; yellow: 601–800 m; blue: 801–900 m; purple: 901–1100 m; black: 1101–1200 m; orange: 1201– 1400 m; white: 1401–1600 m
Data from: Insectivorous bat occupancy is mediated by drought and agricultural land use in a highly modified ecoregion
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Data from: Functional responses of insectivorous bats to increasing housing density support 'land-sparing' rather than ‘land-sharing’ urban growth strategies
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Data from: Insectivorous bat pollinates columnar cactus more effectively per visit than specialized nectar bat
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Data from: Insectivorous bats respond to vegetation complexity in urban green spaces
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Data from: Molecular diet analysis finds an insectivorous desert bat community dominated by resource sharing despite diverse echolocation and foraging strategies
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Data from: Separating the effects of water quality and urbanization on temperate insectivorous bats at the landscape scale
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Data from: Illuminating the physiological implications of artificial light on an insectivorous bat community
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Data from: Resource availability and roosting ecology shape reproductive phenology of rain forest insectivorous bats
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Data from: Resource partitioning by insectivorous bats in Jamaica
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Data from: Insectivorous bats integrate social information about species identity, conspecific activity, and prey abundance to estimate cost-benefit ratio of interactions
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Urban tolerance data for African insectivorous bats
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Data from: Beyond size – morphological predictors of bite force in a diverse insectivorous bat assemblage from Malaysia
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Data from: Responses of aerial insectivorous bats to local and landscape-level features of coffee agroforestry systems in Western Ghats, India
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Coarse-scale online data reveals habitat similarities but weak cross-taxa congruence between insectivorous bats and birds in the eastern U.S.
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Data from: Estimating population density of insectivorous bats based on stationary acoustic detectors: a case study
<p>1. Automated recording units are commonly used by consultants to assess environmental impacts and to monitor animal populations. Although estimating population density of bats using stationary acoustic detectors is key for evaluating environmental impacts, estimating densities from call activity data is only possible through recently developed numerical methods, as the recognition of calling individuals is impossible.<br> 2. We tested the applicability of generalized random encounter models (gREMs) for determining population densities of three bat species (Common pipistrelle <em>Pipistrellus pipistrellus</em>, Northern bat Eptesicus nilssonii,, and Natterer's bat Myotis nattereri) based on passively collected acoustical data. To validate the results, we compared them to (i) density estimates from the literature and to (ii) Royle-Nichols (RN) models of detection/non-detection data.<br> 3. Our estimates for M. nattereri matched both the published data and RN-model results. For E. nilssonii, the gREM yielded similar estimates to the RN-models, but the published estimates were more than twice as high. This discrepancy might be because the high-altitude flight of E. nilssonii is not accounted for in gREMs. Results of gREMs for P. pipistrellus were supported by published data but were approximately 10 times higher than those of RN-models. RN-models use detection/non-detection data and this loss of information probably affected population estimates of very active species like P. pipistrellus.<br> 4. gREM models provided realistic estimates of bat population densities based on automatically recorded call activity data. However, the average flight altitude of species should be accounted for in future analyses. We suggest including flight altitude in the calculation of the detection range to assess the detection sphere more accurately and to obtain more precise density estimates.</p>
Data from: Loss of sweet taste despite the conservation of sweet receptor genes in insectivorous bats
<p>The evolution of taste perception is usually associated with the ecology and dietary changes of organisms. However, mismatches between feeding ecology and taste receptor evolution have been identified in some vertebrate animals. One example is the sweet taste receptor gene <em>Tas1r2</em>. Previous analysis of partial sequences has revealed that <em>Tas1r2</em> has undergone equally strong purifying selection between insectivorous and frugivorous bats. To test whether the sweet taste function is also important in bats with contrasting diets, we examined the complete coding sequences of both sweet taste receptor genes (<em>Tas1r2</em> and <em>Tas1r3</em>) in 34 representative bat species. Although these two genes are highly conserved between frugivorous and insectivorous bats at the sequence level, our behavioral experiments revealed that an insectivorous bat (<em>Myotis ricketti</em>) showed no preference for natural sugars, whereas the frugivorous species (<em>Rousettus leschenaultii</em>) showed strong preferences for sucrose and fructose. Furthermore, while both sweet taste receptor genes are expressed in the taste tissue of insectivorous and frugivorous bats, our cell-based assays revealed striking functional divergence: the sweet taste receptors of frugivorous bats are able to respond to natural sugars whereas those of insectivorous bats are not, which is consistent with the behavioral preference tests, suggesting that functional evolution of sweet taste receptors is closely related to diet. This comprehensive study suggests that using sequence conservation alone could be misleading in inferring protein and physiological function, and highlights the power of combining behavioral experiments, expression analysis, and functional assays in molecular evolutionary studies. </p>
Data from: Illuminating prey selection in an insectivorous bat community, exposed to artificial light at night
1.Light pollution has been increasing around the globe and threatens to disturb natural rhythms of wildlife species. Artificial light impacts the behaviour of insectivorous bats in numerous ways, including foraging behaviour, which may in turn lead to altered prey selection. 2.In a manipulative field experiment, we collected faecal samples from six species of insectivorous bats in naturally dark and artificially lit conditions, and identified prey items using molecular methods to investigate effects of light pollution on prey selection. 3.Proportional differences of identified prey were not consistent and appeared to be species specific. Red bats, little brown bats, and gray bats exhibited expected increases in moths at lit sites. Beetle-specialist big brown bats had a sizeable increase in beetle consumption around lights, while tri-colored bats and evening bats showed little change in moth consumption between experimental conditions. Dietary overlap was high between experimental conditions within each species, and dietary breadth only changed significantly between experimental conditions in one species, the little brown bat. 4.Policy implications. Our results, building on others, demonstrate that bat-insect interactions may be more nuanced than the common assertion that moth consumption increases around lights. They highlight the need for a greater mechanistic understanding of bat-light interactions to predict which species will be most affected by light pollution. Given differences in bat and insect communities, we advocate biologists, land stewards, and civil planners work collaboratively to determine lighting solutions that minimize changes in foraging behaviour of species in the local bat community. Such efforts may allow stakeholders to more effectively craft management strategies to minimize unnatural shifts in prey selection caused by artificial lights.
Data from: Diet of the insectivorous bat Pipistrellus nathusii during autumn migration and summer residence
Migration is widespread among vertebrates. Yet bat migration has received little attention and only in the recent decades knowledge of it has been gained. Migration can cause significant changes in behaviour and physiology, due to increasing energy demands and aerodynamic constraints. Dietary shifts, for examples, have been shown to occur in birds before onset of migration. For bats it is not known if a change in diet occurs during migration, although especially breeding season related dietary preference has been documented. It is known that fat-rich diets, and subsequent accumulation of high fat deposits, do increase the flight range of migratory bats. Some bat species can be regarded as long-distance migrants, covering up to 2,000 km on their way between summer and winter roosting areas. Pipistrellus nathusii (Vespertilionidae), a European long-distant migrant, travels each year along the Baltic Sea from north-eastern Europe to hibernate in central and southern Europe. This study presents data on the dietary habits of migrating Pipistrellus nathusii compared with dietary habits during the breeding season. We analysed faecal samples from bats on fall migration caught at the Ornithological Field Station in Pape, Latvia and from samples collected in North-Latvian summer roosts. We applied both morphological identification and molecular methods, as morphological methods also recognize life stages of prey and can contribute frequency data. The diets of bats on migration and breeding bats were similar, with Diptera and Lepidoptera comprising the major prey categories. However certain prey groups could be explained by the different hunting habitats used during migration vs. summer residence.
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Allen Brain Atlas
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