Post provided by Chloe Robinson

Bat Conservation International (BCI), founded in 1982, aims to conserve bats and their habitats through a combination of education, conservation, and research. Bats worldwide contribute towards controlling pests, create rich fertilizer for landowners, and pollinate fruit and flowers. BCI introduced International Bat Appreciation Day to increase awareness about bats and what they do for our environment.

In this post, associate editor Chloe Robinson will be summarising the various MEE published methods for bat monitoring and how technological developments have allowed us to further look and listen into the lives of these incredible creatures.

Bat facts

Worldwide, there are more than 1,400 species of bat, ranging from the tiny bumblebee bat (<2 grams) to the golden-crowned flying fox (5ft wingspan). Bats are diverse, and have a wide variety of morphological features, feeding strategies, roosting behaviours and functions they perform in the environment.

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BCI has identified that 21 bat species are critically endangered, 83 endangered, 109 vulnerable and 242 bat species are data-deficient. Globally, bats are divided into 2 groups: the microbats and the megabats. Microbats are mostly small bats which primarily use echolocation (i.e. emit sonar calls and listen to the echoes to locate insect prey) to navigate and feed. Megabats mostly consist of bats which feed on fruit/nectar/pollen and do not conventionally echolocate.

Human activities such as deforestation, mining, and irresponsible tourism have caused a substantial decrease in the bats’ population. Bats have often been understudied and misunderstood animals. They are often perceived as disease spreaders, which has been especially exacerbated due to the current pandemic and general misconception that bats transmit SARS-CoV-2 to humans directly. In reality, provide critical ecological services as insect consumers, pollinators, and seed dispersers.

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Introducing Acoustics

In order to conserve populations of bat around the world, scientists have developed a suite of methods to enable us to collect data on bats and their ecology. Methods required for monitoring microbats and megabats differ, due to the large differences in their ecology. One of the oldest methods used is mist-netting, where nets are strung up high in known bat flight corridors and bats are subsequently caught and analysed for information such as species, sex, wingspan and DNA background. Albeit useful for obtaining physical information on bats, mist-netting is known to cause stress to bats, bias towards particular species and can alter the long-term behaviour of bats.

One alternative way to monitor the presence and behaviour of echolocating bat species is to record the species-specific ultrasonic calls they emit. Since the 1950’s, the field of acoustic monitoring has advanced dramatically, to the point where even community groups can collect bat acoustic data through smartphone devices.

Generally, there are two different acoustic bat survey methods: the transect walk (i.e. walking a set route with a device) and the stationary measurement (i.e. securing an acoustic device to a tree). The latter is often favoured due to the ability to detect bat species across longer timeframes, as was identified in an MEE paper by Stahlschmidt & Brühl in 2012. Different acoustic devices can have different rates of bat detection, as identified in an MEE study by Adams et al. in 2012, therefore choice of detector should be taken into account in designing studies and considering bat activity levels. Another important consideration is how many nights to conduct acoustic surveys in order to acoustically capture all of the bat species in an area. Skalak et al. determined in their 2012 MEE paper that multiple survey nights at multiple sampling locations enable detection of higher levels of species richness and that continuous sampling throughout the night was important for detecting more species.

Identifying bat species via acoustics

One of the long-standing challenges of acoustic research is the ability to accurately identify bat species. The earlier days of acoustic monitoring consisted of identifying bats by the unique series of slaps and clicks, however, now auto-identification software and apps are more commonplace. In their 2016 MEE paper, Zamora-Gutierrez & co-authors created automatic species identification tools for 59 Mexican bat species from 4685 search‐phase calls. As with this paper, most identification algorithms are created using call libraries and machine learning approaches, however misidentification is still possible. One way to overcome this was described in a MEE paper by Barré et al. in 2019, where removing data above the 50% false positive tolerance (FPT) helps ensure accuracy and robustness of species ID.

Eyes in the sky: visual bat monitoring

Acoustic devices are effective at capturing bat data; however their application is more powerful when combined with visual recorders such as thermal imaging technology. A MEE paper by Fu et al. in 2018, demonstrated the application of a specialised unmanned aerial vehicle (UAV; the ‘Chirocopter’) to collect visual and acoustic data on Brazilian free‐tailed bat (Tadarida brasiliensis) in New Mexico. Monitoring microbats during active seasons is relatively easy, however it is often difficult to obtain hibernation data without physically visiting overwintering hibernacula, such as caves. Hibernacula studies are often highly discouraged due to the disturbance to the bats and potential to transfer infective propagules of the devastating white-nose syndrome disease. A method to overcome these limitations was proposed in a MEE paper by Hayman et al. in 2017, whereby thermal‐imaging cameras were used to observe little brown bats (Myotis lucifugus) and Indiana bats (M. sodalis) in two caves over multiple winters. Using this technique, they detect increases in arousals during midwinter in both species and clear signals of daily arousal periodicity in white-nose syndrome infected Indiana bats.

Hands-on data collection

Despite the advancement of relatively non-invasive methods, it is still necessary to use hands-on methods for obtaining physiological data, for answering questions on bat immunity, virology and dietary profiles. This was highlighted in a MEE study by Clerc et al. in 2016, where they developed a field‐ready micro‐adipose biopsy method for sampling adipose tissue of silver-haired bats. Using this method, they were able to interpret fatty acid signatures and described the potential for this method to characterize the origins of migrating individuals. Following on from this study, in 2019, Irving et al. published a study in MEE, developed optimal procedures for anaesthetizing, necropsy methods and cell/tissue extraction for black flying foxes (Pteropus Alecto). Their method enabled them to obtain high‐quality RNA, DNA and protein samples from tissues along with viable cells for various molecular and immunological studies.

Megabats, due to their larger size, are often monitored using tracking devices attached to their backs or around their necks as collars. In 2014, Mara et al. published a study in MEE, reviewing the last 50 years of bat tracking. They found that there has been little development in attachment methods since the first tracking studies and they subsequently proposed future studies build upon previous knowledge to find the best attachment method, size and shape for their study species to effectively improve tracking.

Summary

Overall, methods for monitoring bats continue to be developed, particularly as technology for acoustic, imaging and GPS devices becomes more advanced. It is vital to employ robust, repeatable and minimally-invasive bat monitoring techniques to maximise information gain whilst considering the welfare and long-term implications on our much-needed and much-appreciated bat species.

To read all of the Methods in Ecology & Evolution bat papers featured in this post, please click the corresponding links below:

Stahlschmidt & Brühl (2012) ‘Bats as bioindicators – the need of a standardized method for acoustic bat activity surveys’

Adams et al. (2012) ‘Do you hear what I hear? Implications of detector selection for acoustic monitoring of bats’

Skalak et al. (2012) ‘Sampling period, size and duration influence measures of bat species richness from acoustic surveys’

Zamora-Gutierrez et al. (2016) ‘Acoustic identification of Mexican bats based on taxonomic and ecological constraints on call design’

Barré et al. (2019) ‘Accounting for automated identification errors in acoustic surveys’

Fu et al. (2018) ‘The Chirocopter: A UAV for recording sound and video of bats at altitude’

Hayman et al. (2017) ‘Long‐term video surveillance and automated analyses reveal arousal patterns in groups of hibernating bats’

Clerc et al. (2016) ‘Minimally invasive collection of adipose tissue facilitates the study of eco‐physiology in small‐bodied mammals’

Irving et al. (2019) ‘Optimizing dissection, sample collection and cell isolation protocols for frugivorous bats’

Mara et al. (2014) ‘50 years of bat tracking: device attachment and future directions’