Missing something? Importance of measurement criteria of acoustic parameters in the analysis of bats recordings (original) (raw)
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Do you hear what I hear? Implications of detector selection for acoustic monitoring of bats
The probability of detecting the echolocation calls of bats is affected by the strength of the signal as well as the directionality and frequency response of the acoustic detectors. Regardless of the research question, it is important to quantify variation in recording system performance and its impacts on bat detection results. The purpose of this study was to compare the detection of echolocation calls among five commonly used bat detectors: AnaBat SD2 (Titley Scientific), Avisoft UltraSoundGate 116 CM16/CMPA (Avisoft Bioacoustics), Batcorder 2·0 (ecoObs), Batlogger (Elekon AG) and Song Meter SM2BAT (Wildlife Acoustics).We used playback of synthetic calls to optimize detection settings for each system. We then played synthetic signals at four frequencies (25, 55, 85 and 115 kHz) at 5-m intervals (5–40 m) and three angles (0°, 45°, 90°) from the detectors. Finally, we recorded free-flying bats (Lasiurus cinereus), comparing the number of calls detected by each detector. Detection was most affected by the frequency dominating the signal and the distance from the source. The effect of angle was less apparent. In the synthetic signal experiment, Avisoft and Batlogger outperformed other detectors, while Batcorder and Song Meter performed similarly. Batlogger performed better than the other detectors at angles off-centre (45° and 90°). AnaBat detected the fewest signals and none at 85 kHz or 115 kHz. Avisoft detected the most signals. In the free-flying bat experiment, Batlogger recorded 93% of calls relative to Avisoft, while AnaBat, Batcorder and Song Meter recorded 40–50% of the calls detected by Avisoft. Numerous factors contribute to variation in data sets from acoustic monitoring; our results demonstrate that choice of detector plays a role in this variation. Differences among detectors make it difficult to compare data sets obtained with different systems. Therefore, the choice of detector should be taken into account in designing studies and considering bat activity levels among studies using different detectors.
Acta Chiropterologica, 1999
Since 1978 we have used ultrasound detectors for field studies of European bat species and large scale mapping and monitoring in Denmark and Sweden. The method has revolutionized the field studies of bats with great possibilities and advantages. Most of the 31-32 European bat species can be identified with bat detectors, but in practical work a few species pairs may have to be lumped, e.g., Myotis mystacinus/brandtii. The species are not equally easy to find and identify, and some may need considerable time to be identified. No single variable of bat sound can be used to separate all species, and identification is often based on a number of characters in combination. Both acoustic and visual clues are of importance. Analyses of recorded sounds are valuable but do not stand alone; it is important to gain as much information as possible on the spot from the total situation in the field. We use ultrasound detectors equipped with heterodyne and time expansion systems in combination. Thi...
The Influence of Habitat Structure on the Ability to Detect Ultrasound Using bat Detectors
Wildlife Society Bulletin
Variation in sound transmission has received considerable attention, especially in studies of animals such as birds, frogs, insects, and whales, in which sound is an important mode of communication (e.g., Wiley and Richards 1982, Römer and Lewald 1992, Penna and Solís 1998, Mercado and Frazer 1999). This research has focused primarily on longrange communication because it plays an important role in mate attraction and establishment and defense of territories. Differences in habitat structure can influence transmission of the relatively low frequencies of sound used by birds and frogs (Morton 1975, Cosens and Falls 1984, Appleby and Redpath 1997, Penna and Solís 1998). Habitat differences may also influence the transmission of ultrasound produced by bats. Indeed, Parsons (1996) found that 40-kHz signals were easier to detect at ground level in the open than in forested "bush." However, no other studies have investigated the influence of habitat structure on sound transmission by bats, likely because of the logistical difficulties associated with generating and detecting ultrasound in the field. Variation in sound transmission also is less likely to be important to echolocating bats than to other animals because of the short range at which echolocation works (Altringham 1996). Habitat-associated differences in sound transmission are important to researchers eavesdropping on echolocating bats, however, and deserve further attention. With recent advances in technology, many researchers now employ ultrasonic detectors to study habitat use by bats (e.g., Humes et al. 1999, Kalcounis et al. 1999, Law et al. 1999). Detectors receive the ultrasonic echolocation calls of bats and convert them into audible or digital signals. Some assume it is more difficult to detect bats in areas with dense vegetation than in open habitats (e.g., Humes et al. 1999, Law et al. 1999), but most studies make the unstated assumption that bats are equally detectable in all habitats (e.g.
The effect of call libraries and acoustic filters on the identification of bat echolocation
Ecology and Evolution, 2014
Quantitative methods for species identification are commonly used in acoustic surveys for animals. While various identification models have been studied extensively, there has been little study of methods for selecting calls prior to modeling or methods for validating results after modeling. We obtained two call libraries with a combined 1556 pulse sequences from 11 North American bat species. We used four acoustic filters to automatically select and quantify bat calls from the combined library. For each filter, we trained a species identification model (a quadratic discriminant function analysis) and compared the classification ability of the models. In a separate analysis, we trained a classification model using just one call library. We then compared a conventional model assessment that used the training library against an alternative approach that used the second library. We found that filters differed in the share of known pulse sequences that were selected (68 to 96%), the share of non-bat noises that were excluded (37 to 100%), their measurement of various pulse parameters, and their overall correct classification rate (41% to 85%). Although the top two filters did not differ significantly in overall correct classification rate (85% and 83%), rates differed significantly for some bat species. In our assessment of call libraries, overall correct classification rates were significantly lower (15% to 23% lower) when tested on the second call library instead of the training library. Well-designed filters obviated the need for subjective and time-consuming manual selection of pulses. Accordingly, researchers should carefully design and test filters and include adequate descriptions in publications. Our results also indicate that it may not be possible to extend inferences about model accuracy beyond the training library. If so, the accuracy of acoustic-only surveys may be lower than commonly reported, which could affect ecological understanding or management decisions based on acoustic surveys.
Journal of Mammalogy, 2001
We compared 2 bat detecting systems that use condenser microphones, 1 that performed computer analysis (Anabat6) of the output of a zero-crossing period meter (Anabat system) and the other that performed computer analysis (Canary 1.2) of the output of slowed-down (ϭ time-expanded) recordings (Racal system). The 2 systems provided significantly different pictures of both numbers and characteristics (highest frequency, lowest frequency, and duration) of echolocation calls, whether recorded from free-flying bats in the field or from a stationary bat in the laboratory. Although the AnabatII detector was slightly more sensitive than the QMC S200 detector, the Racal system detected more echolocation calls than the Anabat system; the 19-dB difference in sensitivity was associated with a zero-crossing period meter in the Anabat system. Results suggest 2 recommendations. First, that analysis using zero-crossing period meters should not be used to describe echolocation behavior or calls of bats. Second, that studies of activity and use of habitat based on analysis using zero-crossing period meters should involve calibration against more sensitive bat-detecting systems.
Echolocating bats are regularly studied to investigate auditory-guided behaviors and as important bioindicators. Bioacoustic monitoring methods based on echolocation calls are increasingly used for risk assessment and to ultimately inform conservation strategies for bats. As echolocation calls transmit through the air at the speed of sound, they undergo changes due to atmospheric and geometric attenuation. Both the speed of sound and atmospheric attenuation, however, are variable and determined by weather conditions, particularly temperature and relative humidity. Changing weather conditions thus cause variation in analyzed call parameters, limiting our ability to detect, and correctly analyze bat calls. Here, I use real-world weather data to exemplify the effect of varying weather conditions on the acoustic properties of air. I then present atmospheric attenuation and speed of sound for the global range of weather conditions and bat call frequencies to show their relative effects. Atmospheric attenuation is a nonlinear function of call frequency, temperature, relative humidity, and atmospheric pressure. While atmospheric attenuation is strongly positively correlated with call frequency, it is also significantly influenced by temperature and relative humidity in a complex nonlinear fashion. Variable weather conditions thus result in variable and unknown effects on the recorded call, affecting estimates of call frequency and intensity, particularly for high frequencies. Weather-induced variation in speed of sound reaches up to about ±3%, but is generally much smaller and only relevant for acoustic localization methods of bats. The frequency-and weather-dependent variation in atmospheric attenuation has a threefold effect on bioacoustic monitoring of bats: It limits our capability (1) to monitor bats equally across time, space, and species, (2) to correctly measure frequency parameters of bat echolocation calls, particularly for high frequencies, and (3) to correctly identify bat species in species-rich assemblies or for sympatric species with similar call designs. K E Y W O R D S
Effects of recording media on echolocation data from broadband bat detectors
2001
Bat detectors are an important tool for ecological studies of bats. However, the quality and quantity of data may be affected by the recording devices used to record the output from the detector. We compared recordings of bat activity from audiocassette recorders and computers. Numbers of calls/hour, passes/hour, identifiable passes/hour, and feeding buzzes/hour were similar (all P's > 0.1) between recording devices. All call characteristics, except for the minimum frequency and characteristic frequency, differed (P < 0.05) between tapes and computers. Species identification with discriminate function analysis was less reliable with tape data than with computer data, particularly when the model built with computer-recorded reference calls was tested with tape-recorded calls. Therefore, we suggest when tape recorders are used for field recording that they also are used to record reference calls.
A Portable Chamber for Bat Field Recordings.
Instituto Mexicano de Acústica, Asociación Mexicana de Ingenieros en Radiodifusion. Puebla México. pp. 22-33., 2011
Bats are plague controllers and effective pollinators for many plant species, and thus, an important link for the ecosystem balance. They have evolved a sophisticated system to analyse reflections from their own emitted sounds to perceive their environment; ability known as echolocation. These signals are therefore useful to classify and determine abundance and distribution of species. However, recording ultrasound is challenging since real time and frequency monitoring is not usually available. Moreover, ultrasound signals for echolocation are highly variable since they depend on environmental conditions, biotic factors, and the bat´s task. Acoustic identification of species from their echolocation signals relies on having a reliable database of signals to compare. This paper describes a portable chamber that provides controlled and reproducible conditions for bat echolocation recordings. Conventional field recordings and recordings using the chamber for verspertilionid bats (Lasiurus xanthinus and Parastrellus hesperus hesperus) and Phyllostomid bats (Leptonycteris yerbabuenae) are presented to highlight the advantages of using this chamber.