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67 results for “Insectivorous bats”
Figure 3 in Bats (Mammalia, Chiroptera) from Yuscarán in Eastern Honduras: Conservation and acoustic characterization for the insectivorous species
Figure 3. Part of the bat species captured with mist nets, in the Yuscarán Biological Reserve and Municipality of Yuscarán, Department of El Paraíso, Honduras, Central America. (A) M. megalophylla; (B) D. rotundus; (C) L. aurita; (D) P. discolor; (E) A. geoffroyi; (F) G. leachii; (G) G. mutica; (H) C. perspicillata; (I) A. jamaicensis; (J) A. lituratus; (K) C. salvini; (L) D. azteca; (M) D. phaeotis; (N) S. hondurensis; (O) S. parvidens; (P) E. fuscus. Photos: (C) D.J.M.Q.; (A-P) W.N.G.C.
Figure 2 in Bats (Mammalia, Chiroptera) from Yuscarán in Eastern Honduras: Conservation and acoustic characterization for the insectivorous species
Figure 2. Species accumulation curve using mist nets, in the Yuscarán Biological Reserve and Municipality of Yuscarán, Department of El Paraíso, Honduras, Central America.
Data from: Insectivorous birds and bats outperform ants in the top-down regulation of arthropods across strata of a Japanese temperate forest
<p>Birds, bats, and ants are recognized as significant arthropod predators. However, empirical studies reveal inconsistent trends in their relative roles in top-down control across strata. Here, we describe the differences between forest strata in the separate effects of birds, bats, and ants on arthropod densities and their cascading effects on plant damage. We implemented a factorial design to exclude vertebrates and ants in both the canopy and understory. Additionally, we separately excluded birds and bats from the understory using diurnal and nocturnal exclosures. At the end of the experiments, we collected all arthropods and assessed herbivory damage. Arthropods responded similarly to predator exclusion across forest strata, with a density increase of 81% on trees without vertebrates and 53% without both vertebrates and ants. Additionally, bird exclusion alone led to an 89% increase in arthropod density, while bat exclusion resulted in a 63% increase. Herbivory increased by 42% when vertebrates were excluded and by 35% when both vertebrates and ants were excluded. Bird exclusion alone increased herbivory damage by 28%, while the exclusion of bats showed a detectable but non-significant increase (by 22%). In contrast, ant exclusion had no significant effect on arthropod density or herbivory damage across strata. Our results reveal that the effects of birds and bats on arthropod density and herbivory damage are similar between the forest canopy and understory in this temperate forest. In addition, ants were not found to be significant predators in our system. Furthermore, birds, bats, and ants appeared to exhibit antagonistic relationships in influencing arthropod density. These findings highlight, unprecedentedly, the equal importance of birds and bats in maintaining ecological balance across different strata of a temperate forest.</p>
Figure 1 in Effects of agroecosystems on insect and insectivorous bat activity: a preliminary finding based on light trap and mist net captures
Figure 1. Map of Sekyere Central District showing study area (Kwamang) in Ghana.
Benign effects of logging on aerial insectivorous bats in Southeast Asia revealed by remote sensing technologies
<b>Description: </b><p>Number of bat calls recorded by SongMeter bat 2 detectors set to record continuously on a trigger. Counts are classified into 21 acoustic call types, including 13 species.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/101"><b>Impacts of forest modification on bats</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>UK Natural Environment Research Council (NERC) (Human Modified Tropical Forests programme & a PhD scholarship jointly funded by University of Kent & NERC & EnvEast DTP scholarship, NE/L002582/1)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Economic Planning Unit of the Malaysian Government and the Sabah Biodiversity Council (Research licence UPE: 40/200/19/2723)</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=7740421">here</a></p><p><b>Files: </b>This consists of 1 file: SAFE_data_archive_Yoh2.xlsx</p><p><b>SAFE_data_archive_Yoh2.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>All data </b> (described in worksheet MasterData)</p><p>Description: All auto and manual identifications for bat passes across a disturbance gradient, identified to functional group or species when possible</p><p>Number of fields: 13</p><p>Number of data rows: 134920</p><p>Fields: </p><ul><li><b>LOCATION</b>: Where the data was collected (Field type: location)</li><li><b>DATE</b>: Date surveyed (Field type: date)</li><li><b>TIME</b>: Time of recording (Field type: time)</li><li><b>AUTO_ID</b>: Taxa as identified using the automatic classifier (Field type: taxa)</li><li><b>ACCURACY</b>: Confidence value for auto identification results (Field type: numeric)</li><li><b>THRESLEVEL</b>: Whether the data met the desired auto-identification confidence value (Field type: categorical)</li><li><b>MANUAL_ID_CLEAN</b>: Taxa as identified manually (Field type: taxa)</li><li><b>FINAL_ID</b>: Final taxa label considering both the auto and manual ID (Field type: taxa)</li><li><b>TREATMENT</b>: Habitat type (Field type: categorical)</li><li><b>fc_100m</b>: Forest extent within 100m buffer of the survey location (Field type: numeric)</li><li><b>chm_100m</b>: Average canopy height within 100m buffer from survey location (Field type: numeric)</li><li><b>shape_100m</b>: Forest shape within 100m buffer of survey location (Field type: numeric)</li><li><b>TRI_100m</b>: Topographic ruggedness within 100m buffer of survey location (Field type: numeric)</li></ul></li></ol><p><b>Date range: </b>2011-04-01 to 2012-06-30</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Mammalia <br> -  -  -  -  Chiroptera <br> -  -  -  -  -  [CF_CROB] <br> -  -  -  -  -  [CF_H140] <br> -  -  -  -  -  [FMQCF1] <br> -  -  -  -  -  [FMQCF2] <br> -  -  -  -  -  [FMQCF3] <br> -  -  -  -  -  [FMQCF4] <br> -  -  -  -  -  [FMQCF5] <br> -  -  -  -  -  [FMQCF6] <br> -  -  -  -  -  [QCF] <br> -  -  -  -  -  [FM] <br> -  -  -  -  -  Rhinolophidae <br> -  -  -  -  -  -  <i>Rhinolophus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus acuminatus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus affinis</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus borneensis</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus creaghi</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus luctus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus philippinensis</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus sedulus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus trifoliatus</i> <br> -  -  -  -  -  Hipposideridae <br> -  -  -  -  -  -  <i>Hipposideros</i> <br> -  -  -  -  -  -  -  <i>Hipposideros ater</i> <br> -  -  -  -  -  -  -  <i>Hipposideros cervinus</i> <br> -  -  -  -  -  -  -  <i>Hipposideros diadema</i> <br> -  -  -  -  -  -  -  <i>Hipposideros galeritus</i> <br> -  -  -  -  -  -  -  <i>Hipposideros ridleyi</i> <br></div><p></p>
Data from: Tillage and herbicide reduction mitigate the gap between conventional and organic farming effects on foraging activity of insectivorous bats
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Functional diversity and trait filtering of insectivorous bats on forest islands created by an Amazonian mega dam
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Data from: Insectivorous birds and bats outperform ants in the top-down regulation of arthropods across strata of a Japanese temperate forest
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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
Shade coffee has shown great promise in providing crucial habitats for biodiversity outside formal protected areas. Insectivorous bats have been understudied in coffee, although they may provide pest control services. We investigated the influence of local and landscape-level features of coffee farms on aerial insectivorous bats in Chikmagalur district in the Western Ghats biodiversity hotspot, India. Bats were monitored in 20 farm sites using ultrasound detectors, and the response of bat species richness and activity to changes in tree density, proportion of built-up area in the neighborhood, and distance of farm from forest areas quantified. We examined if models built to explain the species richness and activity could also predict them in nine additional sites. We detected nine phonic types/species in the study area. The quantified predictors had no effect on assemblage-level species richness and activity of bats. Responses of edge-space and cluttered-space forager guilds mirrored those of the overall assemblage, but some species vulnerable to forest conversion like *Rhinolophus beddomei* were detected rarely. Best models explained up to 20% and 15% variation in assemblage-level species richness and activity respectively, and were poor predictors of both response variables. We conclude that coffee farms in our study area offer an important commuting space for insectivorous bats across a gradient of shade management. Further research should include species-specific responses to management decisions for at-risk species and quantification of ecosystem services like natural pest control to inform biodiversity conservation initiatives in the Western Ghats coffee landscapes.
Data from: Beyond size – morphological predictors of bite force in a diverse insectivorous bat assemblage from Malaysia
1. Bite force is used to investigate feeding performance in a variety of vertebrates. In all taxa studied, bite force is strongly correlated with body and head size. Studies of bite force in bats have largely centred on neotropical species with a particular focus on species that maximize dietary differences. Little is known about the bite force of bats from the Old World tropics, nor of variation in bite force within diverse assemblages of obligate insectivores. Moreover, factors other than size are poorly known but may be important in driving interspecific differences in bite force, and thereby diet. 2. Here, we examine the correlation between morphological variation and bite force of 35 species of insectivorous bats from a single palaeotropical assemblage. We confirmed the overall relationship between size and bite force across species, but found that bite force is predicted more strongly by head length than body mass or forearm length. 3. From the combined action of jaw muscles and muscle-bone mechanisms, bats generate a mechanical advantage that creates pressure during biting. We calculated the size-independent mechanical advantage for each of five mandible lever systems (three delineated by the temporalis muscle and two delineated by the masseter muscle) operating through three function points (molar, canine, and incisor). Size-independent mechanical advantage of the suprazygomatic portion of the temporalis muscle at the molar function point was the only significant predictor of size-independent maximum bite force across all species. 4. Within families, the size-independent mechanical advantage of the superficial portion of the masseter muscle plays a significant role in predicting size-independent maximum bite force in both the Rhinolophidae and Vespertilionidae. For the family Hipposideridae, however, size-independent mechanical advantage showed no role in predicting size-independent maximum bite force, suggesting that size really matters in predicting the maximum bite force capacity for this family.
Data from: Molecular diet analysis finds an insectivorous desert bat community dominated by resource sharing despite diverse echolocation and foraging strategies
Interspecific differences in traits can alter the relative niche use of species within the same environment. Bats provide an excellent model to study niche use because they have a wide variety of behavioural, acoustic and morphological traits that may lead to multi-species, functional groups. Predatory bats have been classified by their foraging location (edge, clutter, open space), ability to aerial hawk and/or substrate glean prey and echolocation call design and flexibility, all of which may dictate their diet. For example, high frequency, broadband calls do not travel far but offer high object resolution while high intensity, low frequency calls travel further but provide lower resolution. Because these behaviours can be flexible four behavioural categories have been proposed: (1) gleaning, (2) behaviourally flexible (gleaning and hawking), (3) clutter tolerant hawking, and (4) open space hawking. Recent studies of diet in bats use molecular tools to identify prey but mainly focus on one or two species in isolation and few studies provide evidence for substantial differences in prey use despite the many behavioural, acoustic and morphological differences. Here we analyse the diet of 17 sympatric species in the Chihuahuan desert and test the hypothesis that peak echolocation frequency and behavioural categories are linked to differences in diet. We find no significant correlation between dietary richness and echolocation frequency (though it spanned close to 100kHz across species). However, our data suggest that behaviourally flexible bats that use gleaning and aerial hawking have the broadest diets and are the most differentiated from clutter-tolerant aerial hawking species.
Data from: Resource availability and roosting ecology shape reproductive phenology of rain forest insectivorous bats
Bats in temperate and subtropical regions typically synchronize birth of a single young with peaks in resource availability driven by local climate patterns. In tropical rain forest, insects are available throughout the year, potentially allowing departures from seasonal monoestry. However, reproductive energy budgets may be constrained by the cost of commuting to foraging grounds from distant roosts. To test these hypotheses, we simultaneously tracked female reproductive activity of 11 insectivorous bat species, insect biomass, and local weather variables for 20 months in a Malaysian rain forest. Five species roost in forest structures and hence have low commuting costs, whereas six species depend on caves, which are limited in the landscape, and are presumed to incur higher commuting costs to foraging sites. Monthly insect biomass was positively correlated with monthly rainfall, and there was a significant relationship between insect biomass and lactation in cave-roosting but not forest-roosting species. Cave-roosting species were seasonally monoestrus, with parturition confined to a two-month period, whereas in forest-roosting species, pregnancy and lactation were recorded throughout the year. Our results suggest that the energetic costs of commuting from roosts to foraging grounds shape annual reproductive patterns in tropical rain forest insectivorous bats. Ongoing changes in forest landscapes are likely to increase these costs for cave-roosting bats, further restricting reproductive opportunities. Climate change is projected to influence the timing of rainfall events in many tropical habitats, which may disrupt relationships between rainfall, insect biomass, and bat reproductive timing, further compromising reproductive success.
List of agricultural pests and disease vectors detected in the diet of insectivorous bats in northern Madagascar
<p>This table is part of the PhD thesis of Carme Tuneu-Corral, entitled '<strong>Bats and rice: promoting Integrated Pest Management to enhance biodiversity conservation</strong>'. It is the <span>Table A4.3</span> of the supplementary material of the Chapter 5 '<em>Beyond borders: evaluating the role of protected areas in promoting bat-mediated pest suppression in rural areas of northern Madagascar</em>', and shows the list of agricultural pests (known and potential) and disease vectors detected in the diet of insectivorous bats, BOLD ID percentage (similarity), and information on the type of crops attacked or disease transmitted by them in Madagascar and/or continental Africa.</p> <p>Methodology:</p> <p><span>To evaluate whether bats were consuming agricultural pests or disease vectors, we only considered prey identified to species level. Using published scientific literature, we classified each arthropod species in one of the following categories: ‘non-pest prey’, ‘known human-disease vector’ (species confirmed as human-disease vector in Madagascar), ‘known livestock-disease vector’ (species confirmed as livestock-disease vector in Madagascar), ‘potential human-disease vector’ (species not confirmed as human-disease vector in Madagascar, but considered as such in continental Africa), ‘potential livestock-disease vector’ (species not confirmed as livestock-disease vector in Madagascar, but considered as such in continental Africa), ‘known agricultural pest’ (species confirmed as agricultural pest in Madagascar), ‘potential agricultural pest’ (species not confirmed as agricultural pest in Madagascar, but considered as such in continental Africa).</span></p> <p> </p>
Figure 2 in Diurnal activity of a trawling insectivorous bat species, Myotis horsfieldii, in Gunung Mulu National Park, Malaysian Borneo
Figure 2. Feeding buzz of Myotis horsfieldii, observed at Site 13 in the Gunung Mulu National Park, recorded between 11.00 and 11.30am on 17 July 2020.
Figure 3 in Diurnal activity of a trawling insectivorous bat species, Myotis horsfieldii, in Gunung Mulu National Park, Malaysian Borneo
Figure 3. The microhabitats where the diurnal bats were observed in Gunung Mulu National Park: (A) – river with high canopy cover in the forest interior (Site 1), (B) – pool with high canopy shade (Site 6), (C) – river with low canopy cover at the forest edge (Site 9), (D) – river with low canopy shade in fragmented forest (Site 12).
Figure 1 in Diurnal activity of a trawling insectivorous bat species, Myotis horsfieldii, in Gunung Mulu National Park, Malaysian Borneo
Figure 1. Records of daylight activity of Horsfield's bat (Myotis horsfieldii) in Gunung Mulu National Park, in Malaysian Borneo. The circles denote visual records, the triangles denote acoustic records, and the squares denote records by both visual and acoustic inspection.
Urban tolerance data for African insectivorous bats
<p>With increasing urbanization, particularly in developing countries, it is important to understand how local biota will respond to such landscape changes. Bats comprise one of the most diverse groups of mammals in urban areas, and many species are threatened by habitat destruction and land use change. Yet, in Africa, the response of bats to urban areas is relatively understudied. Therefore, we collated data on urban presence, phylogenetic relationship, and ecological traits of 54 insectivorous bats in Africa from available literature to test if their response to urbanization was phylogenetically and/or ecologically driven. Ancestral state reconstruction of urban tolerance, defined by functional group and presence observed in urban areas, suggests that ancestral African bat species could adapt to urban landscapes, and significant phylogenetic signal for urban tolerance indicates that this ability is evolutionarily conserved and mediated by pre‐adaptations. Specifically, traits of high wing loading and aspect ratio, and flexible roosting strategies, enable occupancy of urban areas. Therefore, our results identify the traits that predict which bat species will likely occur in urban areas, and which vulnerable bat clades conservation efforts should focus on to reduce loss of both functional and phylogenetic diversity in Africa. We, additionally, highlight several gaps in research that should be investigated in future studies to provide better monitoring of the impact urbanization will have on African bats.</p>
FIG. 4 in Species richness, functional diversity and assemblage structure of insectivorous bats along an elevational gradient in tropical West Africa
FIG. 4. Mean pairwise distances (MPD) of multivariate traits (A and B), forearm length (C and D), greatest skull length (E and F), narrowest breadth of skull (G and H), ear length (I and J) and tail length (K and L) of insectivorous bat assemblages along the Mount Nimba elevational gradient. Observed MPD for each elevation is represented by the blue dots. A blue line of best fit is shown for significant relationships between observed MPD and elevation. The red dots indicate the expected MPD as calculated by 999 randomized community shuffles for figures on the left, and trait shuffles for figures on the right. A red line of best fit is shown for significant relationships between expected MPD and elevation. Instances where observed MPD differs significantly from the expected MPD are indicated by black rings
FIG. 2 in Species richness, functional diversity and assemblage structure of insectivorous bats along an elevational gradient in tropical West Africa
FIG. 2. Quadratic linear regression of species richness of assemblages versus elevation (P = 0.008; species richness = 34.32 - 7.893*elevation + 0.4881*elevation2)
FIG. 5 in Species richness, functional diversity and assemblage structure of insectivorous bats along an elevational gradient in tropical West Africa
FIG. 5. Mean nearest taxon distances (MNTD) of multivariate traits (A and B), forearm length (C and D), greatest skull length (E and F), narrowest breadth of skull (G and H), ear length (I and J) and tail length (K and L) of insectivorous bats along the Mount Nimba elevational gradient. Observed MNTD for each elevation is represented by the green dots. A green line of best fit is shown for significant relationships between observed MNTD and elevation. The red dots indicate the expected MNTD as calculated by 999 randomized community shuffles for figures on the left, and trait shuffles for figures on the right. A red line of best fit is shown for significant relationships between expected MNTD and elevation. Instances where observed MNTD differs significantly from the expected MNTD are indicated by black rings
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OpenNeuro
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