02632nas a2200289 4500008004100000245011000041210006900151520174700220653001501967653002501982653002502007653000902032653001702041653002502058653001002083653001802093653001702111653002102128653002402149653001902173100001502192700001402207700001802221700001402239700002202253856006702275 2019 eng d00aAutomatic standardized processing and identification of tropical bat calls using deep learning approaches0 aAutomatic standardized processing and identification of tropical3 a

Consistent and comparable metrics to automatically monitor biodiversity across the landscape remain a gold-standard for biodiversity research, yet such approaches have frequently been limited to a very small selection of species for which visual approaches (e.g., camera traps) make continuous monitoring possible. Acoustic-based methods have been widely applied in the monitoring of bats and some other taxa across extended spatial scales, but are have yet to be applied to diverse tropical communities.

In this study, we developed a software program “Waveman” and prepared a reference library using over 880 audio-files from 36 Asian bat species. The software incorporated a novel network “BatNet” and a re-checking strategy (ReChk) to maximize accuracy. In Waveman, BatNet outperforms three other published networks: CNNFULL, VggNet and ResNet_v2, with over 90% overall accuracy and 0.94 AUC on the ROC plot. The classification accuracy rates for all 36 species are at least 86% when analysed in combination. Moreover, our library preparation and ReChk greatly improved the sensitivity and reduced the false positive rate, when tested with 15 species for which more detailed and situationally diverse records were available. Finally, BatNet was successfully used to identify Hipposideros larvatus and Rhinolophus siamensis from three different environments. We hope this pipeline is useful tool to process bioacoustic data accurately, effectively and automatically, therefore allowing for greater standardization and comparability for researchers to understand bat activities across space and time and therefore provide a consistent tool for monitoring biodiversity for management and conservation.

10aAlgorithms10aAutomated monitoring10aAutomatic processing10abats10abioacoustics10aBiodiversity metrics10aCalls10aDeep learning10aecholocation10amachine learning10aMonitoring protocol10aNeural network1 aChen, Xing1 aZhao, Jun1 aChen, Yan-hua1 aZhou, Wei1 aHughes, Alice, C. uhttps://linkinghub.elsevier.com/retrieve/pii/S000632071930896102337nas a2200217 4500008004100000245008600041210006900127520164500196653002401841653000901865653002201874653002701896653002001923653001801943100001701961700001601978700002101994700002102015700002102036856006202057 2019 eng d00aDoes bat response to traffic noise support the misleading cue hypothesis?Abstract0 aDoes bat response to traffic noise support the misleading cue hy3 a

The world has become a noisier place due to the increase in urbanization. Noise is generally considered an impediment, altering an animal’s behavior through masking or distraction. But noise can also provide useful information about the environment. For animals that rely on natural environmental noise as an indicator of favorable foraging conditions, increasing levels of anthropogenic noise might mislead informed decision-making. Bats use rain noise, a natural environmental cue, to delay their emergence from the roost, presumably to avoid sensory and metabolic costs associated with foraging in heavy rain. Here we tested the “misleading cue hypothesis,” asking whether traffic noise is mistaken for rain noise by bats. Given the acoustic similarity between rain noise and traffic noise, we predicted that bats would confuse the two. We conducted a playback experiment using rain, traffic, and ambient noise at natural roosts of common big-eared bats (Micronycteris microtis, Phyllostomidae) and recorded bat emergence behavior. In contrast to their response to rain noise, the bats did not delay roost emergence in response to traffic noise. Thus, we found that bats were able to discriminate between traffic noise and rain noise and were not misled by similarity in acoustic parameters in the two noise types, when emerging from their roost. Emerging bats did show more exploration flights during traffic noise than during rain noise, but not during ambient noise, suggesting that they perceive traffic noise as a novel acoustic cue. Our data provide new insights into perception of traffic noise by bats.

10aanthropogenic noise10abats10aevolutionary trap10aMicronycteris microtis10amisleading cues10aTraffic noise1 aGeipel, Inga1 aAmin, Bawan1 aPage, Rachel, A.1 aHalfwerk, Wouter1 aCandolin, Ulrika uhttps://academic.oup.com/beheco/article/30/6/1775/557481101564nas a2200193 4500008004100000245005200041210005200093520101400145653001901159653000901178653001701187653002301204653002301227653001301250100001401263700001301277700001401290856006601304 2019 eng d00aSensory gaze stabilization in echolocating bats0 aSensory gaze stabilization in echolocating bats3 a

Sensing from a moving platform is challenging for both man-made machines and animals. Animals' heads jitter during movement, so if the sensors they carry are not stabilized, any spatial estimation might be biased. Flying animals, like bats, seriously suffer from this problem because flapping flight induces rapid changes in acceleration which moves the body up and down. For echolocating bats, the problem is crucial. Because they emit a sound to sense the world, an unstable head means sound energy pointed in the wrong direction. It is unknown how bats mitigate this problem. By tracking the head and body of flying fruit bats, we show that they stabilize their heads, accurately maintaining a fixed acoustic-gaze relative to a target. Bats can solve the stabilization task even in complete darkness using only echo-based information. Moreover, the bats point their echolocation beam below the target and not towards it, a strategy that should result in better estimations of target elevation.

10aactive sensing10abats10aecholocation10agaze stabilization10asensory perception10atracking1 aEitan, O.1 aKosa, G.1 aYovel, Y. uhttps://royalsocietypublishing.org/doi/10.1098/rspb.2019.149601703nas a2200241 4500008004100000245008100041210006900122520100600191653000901197653002301206653002501229653002001254653002201274100001801296700001501314700001401329700001101343700001801354700001601372700001601388700001601404856004101420 2019 eng d00aVocal Development of Horsfield's Leaf-Nosed Bat Pups (Hipposideros larvatus)0 aVocal Development of Horsfields LeafNosed Bat Pups Hipposideros 3 a

Bats are an appealing animal for investigating the biological basis and evolution of speech-related traits in wild mammal systems. We investigated vocal development in Horsfield's leaf-nosed bat pups, Hipposideros larvatus. We found that newborn bats emit many types of isolation calls, including downward frequency modulation (DFM), arched frequency modulation (AFM), upward frequency modulation (UFM), and others. The gradual decrease of Euclidean distance measurements revealed that pup isolation calls (DFM, AFM, UFM) gradually change into adult social calls. Furthermore, one of the isolation call types (UFM type) encoded an individual signature. By contrast, we report that early echolocation calls and isolation calls develop in parallel. As pups develop, early echolocation calls gradually mature and transform into adult-like echolocation calls. The interval and duration of echolocation calls decreases, while the peak frequency and bandwidth of frequency modulation increases.

10abats10aecholocation calls10aindividual signature10aisolation calls10avocal development1 aChi, Tingting1 aLIU, Muxun1 aTan, Xiao1 aLi, Yu1 aXiao, Yanhong1 aSun, Keping1 aJin, Longru1 aFeng, Jiang uhttps://bio.acousti.ca/sv/node/5757602274nas a2200241 4500008004100000022001400041245009400055210006900149260001600218300001500234520143200249653000901681653002001690653001301710653002101723653001001744653000901754100001701763700002401780700002101804700002101825856018601846 2019 eng d a0022-094900aNoise as an informational cue for decision-making: the sound of rain delays bat emergence0 aNoise as an informational cue for decisionmaking the sound of ra cSep-01-2020 ajeb.1920053 a

Background noise can have strong negative consequences on animals, reducing individual fitness by masking communication signals, impeding prey detection and increasing predation risk. While the negative impacts of noise across taxa have been well documented, the use of noise as an informational cue, providing animals with reliable information on environmental conditions has been less well studied. In the tropical rainforest, downpours can be intense and frequent. Strong rainfall may impede efficient orientation and foraging for bats that need echolocation to both navigate and detect prey, and can result in higher flight costs due to increased metabolic rates. Using playback experiments at natural roosts we tested whether two bat species, differing in their hunting strategies and foraging habitats, use rain noise as a cue to delay emergence from their roosts. We found that both species significantly delayed their emergence time during rain noise playbacks compared to silence and ambient noise controls. We conclude that bats can use background noise, here the acoustic component of rainfall, as a reliable informational cue to make informed decisions, here about whether to initiate foraging trips or remain in the shelter of their roosts. Our findings suggest that environmental background noise can sometimes be beneficial to animals, in particular in situations where other sensory cues may be absent.

10abats10adecision-making10aforaging10ainformation cues10aNoise10arain1 aGeipel, Inga1 aSmeekes, Marcus, J.1 aHalfwerk, Wouter1 aPage, Rachel, A. uhttp://jeb.biologists.org/lookup/doi/10.1242/jeb.192005https://syndication.highwire.org/content/doi/10.1242/jeb.192005https://syndication.highwire.org/content/doi/10.1242/jeb.19200502507nas a2200253 4500008004100000022001400041245012300055210006900178260001600247520173100263653002701994653000902021653001002030653001702040653002102057100001902078700001502097700001602112700001202128700001702140700001602157700002402173856005602197 2019 eng d a1435-944800aBats increase vocal amplitude and decrease vocal complexity to mitigate noise interference during social communication0 aBats increase vocal amplitude and decrease vocal complexity to m cOct-01-20193 a

Natural background noises are common in the acoustic environments in which most organisms have evolved. Therefore, the vocalization and sound perception systems of vocal animals are inherently equipped to overcome natural background noise. Human-generated noises, however, pose new challenges that can hamper audiovocal communication. The mechanisms animals use to cope with anthropogenic noise disturbances have been extensively explored in a variety of taxa. Bats emit echolocation pulses primarily to orient, locate and navigate, while social calls are used to communicate with conspecifics. Previous studies have shown that bats alter echolocation pulse parameters in response to background noise interference. In contrast to high-frequency echolocation pulses, relatively low-frequency components within bat social calls overlap broadly with ambient noise frequencies. However, how bats structure their social calls in the presence of anthropogenic noise is not known. Here, we hypothesized that bats leverage vocal plasticity to facilitate vocal exchanges within a noisy environment. To test this hypothesis, we subjected the Asian particolored bat, Vespertilio sinensis, to prerecorded traffic noise. We observed a significant decrease in vocal complexity (i.e., an increased frequency of monosyllabic calls) in response to traffic noise. However, an increase in the duration and frequency of social calls, as have been observed in other species, was not evident. This suggests that signal simplification may increase communication efficacy in noisy environments. Moreover, V. sinensis also increased call amplitude in response to increased traffic noise, consistent with the predictions of the Lombard effect.

10aacoustic communication10abats10aNoise10aSocial calls10avocal plasticity1 aJiang, Tinglei1 aGuo, Xiong1 aLin, Aiqing1 aWu, Hui1 aSun, Congnan1 aFeng, Jiang1 aKanwal, Jagmeet, S. uhttp://link.springer.com/10.1007/s10071-018-01235-0