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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