4 Discussion
Our survey’s findings indicate that Komul has a wide variety of bat species, with a potential distribution of 24 bat species. The Classifier Libraries in Kaleidoscope Pro are built on verified recordings of bat calls. Multiple distinct Species Classifiers can be found in Classifier Libraries: Bat call recordings are compared to a database of known species classifiers to determine the species. There haven’t been any prior bat surveys in Komul, and there is a dearth of acoustic data on bats in Xinjiang, China as well. Because the European bat database in Kaleidoscope Pro contains the vast majority of the known bats in Xinjiang, it was used for machine species identification of bats (Huang et al., 2007; Jiang, 2015; Zhang, 2021).
24 species of bats have been identified (Table 1), including 8 species recorded in Xinjiang, except B. leucomelas、 E. gobiensis、 M. blythii、 M. nipalensis and M. petax (Huang et al., 2007; Jiang, 2015; Zhang, 2021). The European bat database lacks acoustic data for these five species, so they have not been identified, but they may exist in Komul. Although M. brandtii and P. auritus are not distributed in Xinjiang, they are distributed in Gansu and Inner Mongolia (Jiang, 2015), and Komul borders Gansu and Inner Mongolia, and bats have strong flight ability, so their distribution is also very possible. 2780 unidentified recordings also indicate that above five species are likely distributed in Komul. Our results implied that the bat species diversity in Xinjiang possibly underestimated (Jiang, 2015) and it needs further investigation.
The Cicadellidae, Carabidae, Pyralidae, and Pieridae are some examples of the insects that the Vespertilionidae family of bats primarily consumes (Liang & Yang, 1985). A variety of crops, including grapes, Hami melons, jujube, and other crops, are grown in Komul, a famous hometown of melons and fruits in China. It is also a sizable area for raising other livestock, such as camels, sheep, and cattle. It has a large grazing area and is watered by the snow-melting-water from the Tianshan Mountains. Additionally, this leads to an abundance and diversity of mosquito species. The 24 bat species that were surveyed (Table 2) therefore fit the local natural context.
The area of Komul with the least number of bats is BLK (Table 2). The species variety of bats in local environments was mostly influenced by habitat types, according to previous studies, which revealed that the species richness pattern of bats declined with increasing latitude (Willig & Selcer, 1989). Since altitude gradients represent significant environmental changes over comparatively small geographic distances, they are especially helpful for examining patterns of biodiversity and their potential structural mechanisms (Korner, 2007). The species diversity of bats decreases with increasing height, Low altitudes are generally distributed in a rich manner (Cisneros et al., 2014; Martins et al., 2015). The distribution of bats is significantly impacted negatively by the low temperature environment in the high altitude area and the relatively isolated habitat type it has produced. The high altitude region also has a dearth of caves and other habitats, which further limits the ability of bats to survive there. But even though it’s higher than YZQ, the variety of bats in YW is comparable (Table 2). It might be as a result of the river’s lack of ice and the abundance of water resources in YW. The abundance of species is firstly influenced by water resources, and until elevation, the abundance of species does not further diminish. Second, YW has a good local habitat and is surrounded by mountains, both of which are key factors in determining the species richness of an area.
Among all the identified echolocation acoustic files, Pipistrellus kuhlii and P. nathusii had the most, with 1037 and 1338 respectively. Barbastella barbastellus has only one bat (Table 3), which indicates that the number of bats in Komul city varies greatly, which can also be seen from its protection level (Table 2). The value of P-value can judge its existence in Komul City (Britzke et al., 2002).
However, there are several issues with the bat detector. The identification accuracy of bat sound waves collected with bat detectors depends on a number of factors. For instance: Background noise and clutter can obfuscate the contour of a bat call that has been recorded. The simultaneous calling of several bats of the same species or similar species can lead to incorrect identification. The degree of identification accuracy can be significantly influenced by the distance between the bat and the microphone: This is so because call shape is what allows for identification. Depending on the distance or other amplitude changes, the call shape that is recorded may differ from the call that the bat actually makes; This may occur if the bat call’s various frequency components are produced at various amplitudes. False positive and false negative identifications are to be anticipated. Bats use echolocation to navigate and hunt, thus they can adjust their sounds in the moment to suit their needs (such as catching insects or avoiding collisions) (Schnitzler et al., 2003; Lin et al., 2014). Additionally, different bat species have extremely diverse call repertoires (Mac Aodha et al., 2018), and it can be challenging to distinguish some of a species’ calls from those of other bat species.
The P-Value of the 24 bat species varies greatly, with some being 0 and some reaching 1 (Table 3). These differences indicate the possibility of these bats existing in Komul City. All analysis tools must use a maximum-likelihood estimator approach rather than relying solely on a single sequence to identify the species present at the site because species identifications are never 100% accurate. P-values from the post-hoc maximum-likelihood estimator will be utilized to choose the acceptance levels for the identification decision (Britzke et al., 2002). The P-value is not perfect, despite being arguably the strongest statistical instrument we have at our disposal. A large P-value does not imply absence. Simply put, it indicates that there is insufficient statistical proof of presence. Furthermore, a low P-value does not prove the presence of something; it merely indicates that the data cannot support the null hypothesis of absence. A low P-value could indicate that a different hypothesis is more likely. Perhaps that is presence. However, it’s also possible that the classification error matrix didn’t fit the data well.
Despite being a thorough examination of Komul’s bat population, this study had a number of limitations that should be considered when analyzing the findings. First of all, our survey did not do secondary confirmation using morphological and genetic methods. Instead, we employed biological recorders to capture the echo sound waves of bats and software to identify bat species. Second, only the echo acoustic waves produced when bats were moving were collected for this investigation since the acoustic properties of bats vary depending on the state of locomotion (Schnitzler et al., 2003; Lin et al., 2014). Although bat acoustics vary depending on the species, it is possible that some bat species are not widespread. We can further identify the species of bats by monitoring them in various locomotor phases, capturing their echo acoustic waves, assessing their physical traits, and using fog net capture to recreate bat circumstances in the wild through an indoor environment.
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