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/S000632071930896102317nas a2200217 4500008004100000022001300041245011300054210006900167260001600236300001400252490000800266520167100274100001401945700001601959700001701975700001701992700001902009700001402028700001602042856004102058 2019 eng d a0003347200aPerformance of Doppler shift compensation in bats varies with species rather than with environmental clutter0 aPerformance of Doppler shift compensation in bats varies with sp cJan-12-2019 a109 - 1200 v1583 a

The performance of vocal motor control is crucial for vocal communication; however, its evolution and ecological drivers are largely unknown. Doppler shift compensation (DSC), which has been found only in bats, represents an excellent model for studying the mechanisms and evolution of vocal control. We tested whether species that are more dependent on DSC for pulse–echo separation have a more precise DSC and whether changes in environmental clutter would result in adjustments in DSC performance. We recorded the echolocation and flight behaviour of the greater horseshoe bat, Rhinolophus ferrumequinum, and the great leaf-nosed bat, Hipposideros armiger, flying through a corridor and a window in turn. The DSC precision in H. armiger was significantly lower than that of R. ferrumequinum; the offset between the reference frequency and resting frequency, however, was not significantly different between the two species. We also studied the DSC of H. armiger flying through windows of different sizes. Their flight speed decreased significantly with reduced window size. However, DSC precision and the offset did not vary significantly with window size. Our results suggest that DSC is more precise in rhinolophids, which have a higher demand for pulse–echo separation by DSC, than in hipposiderids. Changes in environmental clutter do not necessarily result in adjustments of DSC performance. Functional importance associated with high-performance vocal control may be critical in shaping the precision of vocal control in the course of evolution. Instead, habitat clutter encountered by vocalizing animals may not play an important role.

1 aZhang, Yu1 aLin, Aiqing1 aDing, Jianan1 aYang, Xinyao1 aJiang, Tinglei1 aLiu, Ying1 aFeng, Jiang uhttps://bio.acousti.ca/ja/node/5788401703nas 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/ja/node/5757601931nas a2200181 4500008004100000022001400041245009000055210006900145260001600214300001600230490000800246520137800254100001701632700001601649700001501665700001801680856005101698 2017 eng d a0001-496600aHorseshoe bats and Old World leaf-nosed bats have two discrete types of pinna motions0 aHorseshoe bats and Old World leafnosed bats have two discrete ty cJan-05-2017 a3011 - 30170 v1413 a

Horseshoe bats (Rhinolophidae) and the related Old World leaf-nosed bats (Hipposideridae) both show conspicuous pinna motions as part of their biosonar behaviors. In the current work, the kinematics of these motions in one species from each family (Rhinolophus ferrumequinum and Hipposideros armiger) has been analyzed quantitatively using three-dimensional tracking of landmarks placed on the pinna. The pinna motions that were observed in both species fell into two categories: In “rigid rotations” motions the geometry of the pinna was preserved and only its orientation in space was altered. In “open–close motions” the geometry of the pinna was changed which was evident in a change of the distances between the landmark points. A linear discriminant analysis showed that motions from both categories could be separated without any overlap in the analyzed data set. Hence, bats from both species have two separate types of pinna motions with apparently no transitions between them. The deformations associated with open–close pinna motions in Hipposideros armiger were found to be substantially larger compared to the wavelength associated with the largest pulse energy than in Rhinolophus ferrumequinum (137% vs 99%). The role of the two different motions in the biosonar behaviors of the animals remains to be determined.

1 aYin, Xiaoyan1 aQiu, Peiwen1 aYang, Lili1 aMüller, Rolf uhttp://asa.scitation.org/doi/10.1121/1.4982042