Weather conditions determine attenuation and speed of sound: Environmental limitations for monitoring and analyzing bat echolocation

Goerlitz, Holger R.

doi:10.1002/ece3.4088

Cited by 52 publications

(48 citation statements)

References 61 publications

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“…On all nights, the SM4Bat detectors were programed with the following settings: gain = 12 dB, sampling rate = 256 kHz, minimum duration = 1.5 ms, minimum trigger frequency = 16 kHz, trigger level = 12 dB, trigger window = 3 s, maximum length = 5 s. This resulted in 744 detector-hours-408 in 2015 and 240 at ground level and 96 at 50 m in 2016. While the detection distance from the microphones will vary depending on bat source levels and their orientation to the microphone [58], microphone sensitivity, and environmental conditions (temperature and relative humidity) [59], we can safely assume that we were only detecting bats < 50 m above the rice. For example, the SMM-U1 microphone theoretically can detect a 40 kHz-calling bat with a 94 dB SPL source level at around 20 m when it is flying on-axis with the microphone [60].…”

Section: Acoustic Samplingmentioning

confidence: 99%

Local-Scale Bat Guild Activity Differs with Rice Growth Stage at Ground Level in the Philippines

et al. 2019

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High-flying insectivorous bats, as wide-ranging generalist insectivores, are valuable consumers of high-altitude migrating pests of rice in Southeast Asia. Here, we documented the behavior of relatively low-flying bats over irrigated rice to elucidate their potential role as predators of rice-associated pest insects in the Philippines. Specifically, we tested the local-scale effects of rice stage, particularly seedling and late vegetative stages, and time of night on acoustic activity of bats foraging near ground level within three functional guilds (based on foraging distance from background clutter). We also monitored bat activity from two 50 m-high towers to assess the vertical extent of relatively low-flying guilds, as well as document high-flying bat guild presence and temporal behavior. At ground level, the most active guild biased their activity and feeding over early growth stage fields, but also foraged at tower level. Activity of the bat guild adept at foraging closest to vegetation did not vary with time of night or rice stage and was absent from tower recordings. High-flying bats were predictably rare at rice level, but exhibited high foraging intensity at 50 m. Given the well-documented, sequential arrival of insect guilds with growth stage, these data suggest that at ground level edge-space bats may be important consumers of detritivores (e.g., mosquitoes). Moreover, our data suggest that just as habitat heterogeneity enhances the services of arthropod predators, these management practices also enhance bat activity and, presumably, their contribution to pest suppression.

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Section: Acoustic Samplingmentioning

confidence: 99%

Local-Scale Bat Guild Activity Differs with Rice Growth Stage at Ground Level in the Philippines

et al. 2019

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“…Thus, detection distance could be calculated if the environmental conditions are known, in open areas at least (Goerlitz 2018). In both aquatic and aerial surveys, however, physical obstacles such as vegetation will also limit detectability; Patriquin et al (2003), for example, estimated that detection distance in a thinned forest was 12% higher than in an intact forest, and the attenuation of sound reduced the detectability of high frequencies (40 kHz) more than that of low frequencies (25 kHz),making the estimation of detection distance much more complicated (Weller and Zabel 2002).…”

Section: Discussionmentioning

confidence: 99%

Estimating animal density in three dimensions using capture‐frequency data from remote detectors

Soto

Castañeda

Mandrak

et al. 2020

Remote Sens Ecol Conserv

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Remote detectors are being used increasingly often to study aquatic and aerial species, which move significantly differently from terrestrial species. Camera-trapping studies have used frameworks based on animal movement patterns to show that a species' detection frequency, along with movement speed and detector specifications, can be used to estimate absolute population density. This approach, however, has not yet been adapted to cases where movement is threedimensional. Here we adapt one such framework to three-dimensional movement, to characterize the relationship between population density, animal speed, characteristics of a remote sensor's detection zone and detection frequency. The derivation involves defining the detection zone mathematically and calculating the mean area of the profile it presents to approaching individuals. We developed two variants of the model-one assuming random movement of all individuals, and one allowing for different probabilities for each approach direction (e.g. that animals more often swim/fly horizontally than vertically). We used computer simulations to evaluate model performance for a wide range of animal and detector densities. Simulations show that in ideal conditions the method approximates true density well, and that estimates become increasingly accurate using more detectors, or sampling for longer. Moreover the method is robust to violations of assumptions, accuracy is decreased only in extreme cases where all detectors are facing the same way. We provide equations for estimating population density from detection frequency and outline how to estimate the necessary parameters. We discuss how environmental variables and species-specific characteristics affect parameter estimates and how to account for these differences in density estimations. Our method can be applied to common remote detection methods (cameras and acoustic detectors), which are currently being used to study a diversity of species and environments. Therefore, our work may significantly expand the number and diversity of species for which density can be estimated.

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“…A list of data sources and numbers of bats recorded is provided in Table A.1 (Appendix). In spite of these checks, we are aware that "measurement errors" would exist, and cannot be estimated for the different devices and methods used (Adams et al, 2012;Kelly, 2008;Goerlitz, 2018). As they would affect our ability to compare multisource RF data in the same statistical analysis, we used the data only to qualitatively assess patterns that could hint at acoustic divergence.…”

Section: Rf Data From Literature Reviewmentioning

confidence: 99%

“…Among the numerous studies reporting environmentally driven variation in acoustic frequency, atmospheric humidity has received the most attention (Chen et al 2009;Flanders et al 2011;Guillen et al, 2000;Jiang et al 2013Jiang et al , 2010aJiang et al , 2010bSun et al 2013;Xu et al 2008). As per the sensory drive framework (that includes the acoustic adaptation hypothesis: Sun et al, 2013;Wilkins et al, 2013), greater atmospheric humidity is thought to alter Rhinolophus bat frequencies , as it can directly affect signal transmission, sound absorption, and echo reception (Goerlitz, 2018;Snell-Rood, 2012). However, others have disputed the influence of humidity in driving frequency attenuation, showing that acoustic transmission at fine scales remains unaffected despite changes in humidity up to 10% (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…However, others have disputed the influence of humidity in driving frequency attenuation, showing that acoustic transmission at fine scales remains unaffected despite changes in humidity up to 10% (e.g. Armstrong and Kerry, 2011;Goerlitz, 2018). Humidity could also be linked to habitat preferences of bats or insect prey size (Guillen et al, 2000;Jiang et al, 2010b), thus indirectly altering bat frequencies.…”

Section: Introductionmentioning

confidence: 99%

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Environmental influences on acoustic divergence inRhinolophusbats of the Western Ghats-Sri Lanka region

Deshpande

Kelkar

2019

Preprint

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According to the acoustic adaptation hypothesis, environmental and biogeographic factors such as atmospheric humidity can influence divergence of acoustic signals and speciation in high duty-cycle echolocating bats (e.g. Rhinolophus sp.), although this remains disputed. In this study we tested the hypothesis that Resting Frequency (RF) would decrease with increasing humidity along a large latitudinal gradient (6°-21° N), for four Rhinolophus species with different evolutionary histories, in the Western Ghats-Sri Lanka (WGSL) region.We conducted acoustic recordings and compiled published information on RFs of stationary Rhinolophus indorouxi, R. rouxi, R. beddomei, and R. lepidus from 40 roosts in 18 localities of the WGSL. These data comprised of recordings made with different devices and with different settings. Hence, due to the unknown measurement error involved in the recorded RFs, it was not possible to conduct conventional regression analyses to test our hypotheses.Hence, we qualitatively assessed effects of Relative Humidity (RH) and other environmental variables by interpreting only the sign, but not the magnitude of the RF responses (from the slopes of generalized least squares regression models). We also tested how RF and RH varied across biogeographic zones, and with bat body size. RFs of the Miocene-diverged species R.indorouxi and R. rouxi were higher at lower RH, as expected. In contrast, RF of the Pleistocene-diverged species R. beddomei and R. lepidus were higher at higher RH. Elevation and rainfall also emerged as important predictors of RF variation in these species. Bat body 2 size differed in dry and humid regions of the WGSL. RF variation was not consistent across biogeographic zones. The cryptic, phonically differentiated sibling species R. indorouxi and R. rouxi co-occurred only in mid-elevation zones along the Western Ghats escarpment. The variable but significant influences of humidity and correlated factors on RF suggest the importance of environmentally mediated acoustic divergence in different Rhinolophus species in the WGSL. We propose some hypotheses on interacting effects of environmental and phylogenetic factors on acoustic divergence in Rhinolophus bats of the WGSL. These ideas could be further tested with phylogenetic and acoustic studies, as more consistent and comparable data on these species become available in the future.

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Weather conditions determine attenuation and speed of sound: Environmental limitations for monitoring and analyzing bat echolocation

Cited by 52 publications

References 61 publications

Local-Scale Bat Guild Activity Differs with Rice Growth Stage at Ground Level in the Philippines

Local-Scale Bat Guild Activity Differs with Rice Growth Stage at Ground Level in the Philippines

Estimating animal density in three dimensions using capture‐frequency data from remote detectors

Environmental influences on acoustic divergence inRhinolophusbats of the Western Ghats-Sri Lanka region

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