81 resultados para echolocation


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Linkage of echolocation call production with contraction of flight muscles has been suggested to reduce the energetic cost of flight with echolocation, such that the overall cost is approximately equal to that of flight alone. However, the pattern of call production with limb movement in terrestrially agile bats has never been investigated. We used synchronised high-speed video and audio recordings to determine patterns of association between echolocation call production and limb motion by Mystacina tuberculata Gray 1843 as individuals walked and flew, respectively. Results showed that there was no apparent linkage between call production and limb motion when bats walked. When in flight, two calls were produced per wingbeat, late in the downstroke and early in the upstroke. When bats walked, calls were produced at a higher rate, but at a slightly lower intensity, compared with bats in flight. These results suggest that M. tuberculata do not attempt to reduce the cost of terrestrial locomotion and call production through biomechanical linkage. They also suggest that the pattern of linkage seen when bats are in flight is not universal and that energetic savings cannot necessarily be explained by contraction of muscles associated with the downstroke alone.

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Calls from 14 species of bat were classified to genus and species using discriminant function analysis (DFA), support vector machines (SVM) and ensembles of neural networks (ENN). Both SVMs and ENNs outperformed DFA for every species while ENNs (mean identification rate – 97%) consistently outperformed SVMs (mean identification rate – 87%). Correct classification rates produced by the ENNs varied from 91% to 100%; calls from six species were correctly identified with 100% accuracy. Calls from the five species of Myotis, a genus whose species are considered difficult to distinguish acoustically, had correct identification rates that varied from 91 – 100%. Five parameters were most important for classifying calls correctly while seven others contributed little to classification performance.

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Automated remote ultrasound detectors allow large amounts of data on bat presence and activity to be collected. Processing of such data involves identifying bat species from their echolocation calls. Automated species identification has the potential to provide more consistent, predictable, and potentially higher levels of accuracy than identification by humans. In contrast, identification by humans permits flexibility and intelligence in identification, as well as the incorporation of features and patterns that may be difficult to quantify. We compared humans with artificial neural networks (ANNs) in their ability to classify short recordings of bat echolocation calls of variable signal to noise ratios; these sequences are typical of those obtained from remote automated recording systems that are often used in large-scale ecological studies. We presented 45 recordings (1–4 calls) produced by known species of bats to ANNs and to 26 human participants with 1 month to 23 years of experience in acoustic identification of bats. Humans correctly classified 86% of recordings to genus and 56% to species; ANNs correctly identified 92% and 62%, respectively. There was no significant difference between the performance of ANNs and that of humans, but ANNs performed better than about 75% of humans. There was little relationship between the experience of the human participants and their classification rate. However, humans with <1 year of experience performed worse than others. Currently, identification of bat echolocation calls by humans is suitable for ecological research, after careful consideration of biases. However, improvements to ANNs and the data that they are trained on may in future increase their performance to beyond those demonstrated by humans.

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We studied the wing morphology, echolocation calls, diet and emergence time of the black-bearded tomb bat (Taphozous melanopogon) from May to October 2006 in Guangxi Province, southwest China. Taphozous melanopogon has wings with high aspect ratio, high loading and pointed wing-tip shape-characteristics associated with fast flight in open space. This species usually produces low-intensity, low frequency, and frequency-modulated (FM) calls usually containing up to four harmonics, with most energy in the second (or sometimes third) harmonic. The diet of this species consists mostly of Lepidoptera and Hemiptera. Timing of evening emergence is correlated with the time of sunset. This is the first study to describe the flight and echolocation behavior of this species in China, and opens the way for future studies of its biology.

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We studied the wing morphology, echolocation calls, foraging behaviour and flight speed of Tylonycteris pachypus and Tylonycteris robustula in Longzhou County, South China during the summer (June–August) of 2005. The wingspan, wing loading and aspect ratio of the two species were relatively low, and those of T. pachypus were lower compared with T. robustula. The echolocation calls of T. pachypus and T. robustula consist of a broadband frequency modulated (FM) sweep followed by a short narrowband FM sweep. The dominant frequency of calls of T. pachypus was 65.1 kHz, whereas that of T. robustula was 57.7 kHz. The call frequencies (including highest frequency of the call, lowest frequency of the call and frequency of the call that contained most energy) of T. pachypus were higher than those of T. robustula, and the pulse duration of the former was longer than that of the latter. The inter-pulse interval and bandwidth of the calls were not significantly different between the two species. Tylonycteris pachypus foraged in more complex environments than T. robustula, although the two species were both netted in edge habitats (around trees or houses), along pathways and in the tops of trees. Tylonycteris pachypus flew slower (straight level flight speed, 4.3 m s−1) than T. robustula (straight level flight speed, 4.8 m s−1). We discuss the relationship between wing morphology, echolocation calls, foraging behaviour and flight speed, and demonstrate resource partitioning between these two species in terms of morphological and behavioural factors.

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We describe the echolocation calls, flight morphology and diet of the endemic Chinese bat Myotis pequinius Thomas, 1908. Orientation calls are broadband, and reach low terminal frequencies. Diet comprised 80% beetles by volume. Wing shape and call design suggest that the bats fly in cluttered habitats, and the possession of moderately long ears and the dietary composition imply they forage at least sometimes by gleaning. Myotis pequinius resembles a larger Oriental version of the western Palaearctic species M. nattereri. Phylogenetic analysis based on sequences of the cytochrome b gene of mitochondrial DNA (1,140 base pairs) from a range of Palaearctic Myotis species confirmed that M. pequinius is close to the nattereri group, and is a sister-species to the eastern Palaearctic M. bombinus. One bat sequenced from China could not be identified from available species descriptions. It was smaller than M. pequinius, and also differed from it in sequence divergence by 6.7%, suggesting the existence of additional, cryptic taxonomic diversity in this group. Our phylogenetic analysis also supports the recognition of M. schaubi as a species distinct from M. nattereri in Transcaucasia and south-western Asia. Myotis nattereri tschuliensis is more closely related to M. schaubi than to M. nattereri, and is best considered either as a subspecies of M. schaubi, or possibly as a distinct species.

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The intermediate leaf-nosed bat (Hipposideros larvatus) is a medium-sized bat distributed throughout the Indo-Malay region. In north-east India, bats identified as H. larvatus captured at a single cave emitted echolocation calls with a bimodal distribution of peak frequencies, around either 85 kHz or 98 kHz. Individuals echolocating at 85 kHz had larger ears and longer forearms than those echolocating at 98 kHz, although no differences were detected in either wing morphology or diet, suggesting limited resource partitioning. A comparison of mitochondrial control region haplotypes of the two phonic types with individuals sampled from across the Indo-Malay range supports the hypothesis that, in India, two cryptic species are present. The Indian 98-kHz phonic bats formed a monophyletic clade with bats from all other regional populations sampled, to the exclusion of the Indian 85-kHz bats. In India, the two forms showed 12–13% sequence divergence and we propose that the name Hipposideros khasiana for bats of the 85-kHz phonic type. Bats of the 98-kHz phonic type formed a monophyletic group with bats from Myanmar, and corresponded to Hipposideros grandis, which is suggested to be a species distinct from Hipposideros larvatus. Differences in echolocation call frequency among populations did not reflect phylogenetic relationships, indicating that call frequency is a poor indicator of evolutionary history. Instead, divergence in call frequency probably occurs in allopatry, possibly augmented by character displacement on secondary contact to facilitate intraspecific communication.

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Aerial hawking bats use intense echolocation calls to search for insect prey. Their calls have evolved into the most intense airborne animal vocalisations. Yet our knowledge about call intensities in the field is restricted to a small number of species. We describe a novel stereo videogrammetry method used to study flight and echolocation behaviour, and to measure call source levels of the aerial hawking bat Eptesicus bottae (Vespertilionidae). Bats flew close to their predicted minimum power speed. Source level increased with call duration; the loudest call of E. bottae was at 133 dB peSPL. The calculated maximum detection distance for large flying objects (e.g. large prey, conspecifics) was up to 21 m. The corresponding maximum echo delay is almost exactly the duration of one wing beat in E. bottae and this also is its preferred pulse interval. These results, obtained by using videogrammetry to track bats in the field, corroborate earlier findings from other species from acoustic tracking methods.

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Echolocation calls of 119 bats belonging to 12 species in three families from Antillean islands of Puerto Rico, Dominica, and St. Vincent were recorded by using time-expansion methods. Spectrograms of calls and descriptive statistics of five temporal and frequency variables measured from calls are presented. The echolocation calls of many of these species, particularly those in the family Phyllostomidae, have not been described previously. The wing morphology of each taxon is described and related to the structure of its echolocation calls and its foraging ecology. Of slow aerial-hawking insectivores, the Mormoopidae and Natalidae Mormoops blainvillii, Pteronotus davyi davyi, P. quadridens fuliginosus, and Natalus stramineus stramineus can forage with great manoeuvrability in background-cluttered space (close to vegetation), and are able to hover. Pteronotus parnellii portoricensis is able to fly and echolocate in highly-cluttered space (dense vegetation). Among frugivores, nectarivores and omnivores in the family Phyllostomidae, Brachyphylla cavernarum intermedia is adapted to foraging in the edges of vegetation in background-cluttered space, while Erophylla bombifrons bombifrons, Glossophaga longirostris rostrata, Artibeus jamaicensis jamaicensis, A. jamaicensis schwartzi and Stenoderma rufum darioi are adapted to foraging under canopies in highly-cluttered space and do not have speed or efficiency in commuting flight. In contrast, Monophyllus plethodon luciae, Sturnira lilium angeli and S. lilium paulsoni are adapted to fly in highly-cluttered space, but can also fly fast and efficiently in open areas.

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Many species of bat use ultrasonic frequency modulated (FM) pulses to measure the distance to objects by timing the emission and reception of each pulse. Echolocation is mainly used in flight. Since the flight speed of bats often exceeds 1% of the speed of sound, Doppler effects will lead to compression of the time between emission and reception as well as an elevation of the echo frequencies, resulting in a distortion of the perceived range. This paper describes the consequences of these Doppler effects on the ranging performance of bats using different pulse designs. The consequences of Doppler effects on ranging performance described in this paper assume bats to have a very accurate ranging resolution, which is feasible with a filterbank receiver. By modeling two receiver types, it was first established that the effects of Doppler compression are virtually independent of the receiver type. Then, used a cross-correlation model was used to investigate the effect of flight speed on Doppler tolerance and range–Doppler coupling separately. This paper further shows how pulse duration, bandwidth, function type, and harmonics influence Doppler tolerance and range–Doppler coupling. The influence of each signal parameter is illustrated using calls of several bat species. It is argued that range–Doppler coupling is a significant source of error in bat echolocation, and various strategies bats could employ to deal with this problem, including the use of range rate information are discussed.

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Time-expanded and heterodyned echolocation calls of the New Zealand long-tailed Chalinolobus tuberculatus and lesser short-tailed bat Mystacina tuberculata were recorded and digitally analysed. Temporal and spectral parameters were measured from time-expanded calls and power spectra generated for both time-expanded and heterodyned calls. Artificial neural networks were trained to classify the calls of both species using temporal and spectral parameters and power spectra as input data. Networks were then tested using data not previously seen. Calls could be unambiguously identified using parameters and power spectra from time-expanded calls. A neural network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 40 kHz (the frequency with the most energy of the fundamental of C. tuberculatus call), could identify 99% and 84% of calls of C. tuberculatus and M. tuberculata, respectively. A second network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 27 kHz (the frequency with the most energy of the fundamental of M. tuberculata call), could identify 34% and 100% of calls of C. tuberculatus and M. tuberculata, respectively. This study represents the first use of neural networks for the identification of bats from their echolocation calls. It is also the first study to use power spectra of time-expanded and heterodyned calls for identification of chiropteran species. The ability of neural networks to identify bats from their echolocation calls is discussed, as is the ecology of both species in relation to the design of their echolocation calls.

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Using a broad‐band recording system (150 Hz‐100 kHz) the echolocation calls of the lesser short‐tailed bat (Mystacina tuberculata) were recorded under three very different situations: free‐flying, flying within a flight cage, and on release from the hand. Calls of bats landing and feeding on a platform in Wellington Zoo were also recorded. Both the lowest frequency and frequency of peak amplitude of calls were significantly affected by the situation under which calls were recorded. Although the calls of free‐flying bats are different from those produced by bats foraging on the ground, it is unlikely that M. tuberculata uses echolocation to locate prey on the ground. No significant differences could be found between the calls emitted by male and female bats, and no consistent relationships were obvious between temporal and spectral call characteristics. There was some evidence to suggest that individual bats could be identified by their echolocation calls.

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The echolocation calls of long-tailed bats (Chalinolobus tuberculatus) were recorded in the Eglinton Valley, Fjordland, New Zealand, and digitized for analysis with the signal-processing software. Univariate and multivariate analyses of measure features facilitated a quantitative classification of the calls. Cluster analysis was used to categorize calls into two groups equating to search and terminal buzz calls described qualitatively for other species. When moving from search to terminal phases, the calls decrease in bandwidth, maximum and minimum frequency of call, and duration. Search calls begin with a steep-downward FM sweep followed by a short, less-modulated component. Buzz calls are FM sweeps. Although not found quantitatively, a broad pre-buzz group of calls also was identified. Ambiguity analysis of calls from the three groups shows that search-phrase calls are well suited to resolving the velocity of targets, and hence, identifying moving targets in a stationary clutter. Pre-buzz and buzz calls are better suited to resolving range, a feature that may aid the bats in capture of evasive prey after it has been identified.

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This paper describes the search-phase echolocation calls of lesser short-tailed bats (Mystacina tuberculata) and long-tailed bats (Chalinolobus tuberculatus). Calls were recorded from all three subspecies of short-tailed bat and seven populations of long-tailed bat, three in Northland, two in the central North Island, and two in the lower South Island. The calls were recorded in the field and digitised, then three spectral components and one temporal component of the calls were measured. Calls of the lesser short-tailed bat could be loosely classified into subspecies by means of multivariate discriminant function analysis. Similarly, long-tailed bat calls showed regional variation, and discriminant function analysis was able to fit calls to regional groups with a high rate of success. The significance of the results presented is discussed in terms of the conservation of New Zealand bats and the unique ecology of the lesser short-tailed bat.