Contrary to the popular belief and saying that a person can be “as blind as a bat,” bats themselves are not actually blind. Indeed, as nocturnal hunters, their eyes adapt to low-light conditions better than human eyes do. To supplement their good bat vision, most of the perky-eared, flying critters use echolocation to enhance their hunting skills and to help them employ evasive maneuvers while in the air — for example, to avoid researchers’ nets. Bats that avoid nets present a problem to researchers who sample the animals, as do bats that do not echolocate — that is, fruit bats of the family Pteropodidae. Fruit bats therefore cannot be detected by ultrasound bat detectors. Thus, traditional bat sampling methods pose a challenge to obtaining accurate bat counts. An NIR photograph of a lesser short-nosed fruit bat (Cynopterus brachyotis) passing through an oil palm plantation. Courtesy of Ellena Yusti. An international team led by researchers from the University of Göttingen developed a method of detecting, counting, and identifying bats, called bat point counts. The researchers combined three modern sensing technologies — thermal, ultrasonic, and NIR — to produce a novel method that captures snapshots of all the bats flying around within a certain range. This noninvasive technique allows scientists to better understand bat behavior in response to certain environmental cues, thus enabling better conservation efforts. “Photographing flying bats at night, in the wild, is one of the most challenging types of photography,” said Kevin Darras, a postdoctoral researcher at the University of Göttingen and Westlake University, and first author of the paper detailing the work. “Their flight is fast and mostly unpredictable, and we had to use near-infrared light to avoid disturbing them. It was really no easy feat, so we were very happy to get usable data.” The researchers’ sampling rig combined a thermal scope to detect flying bats and their flight patterns, an ultrasound recorder to identify echolocating calls, and an NIR camera and LED illuminator for photographing bat morphology. The team evaluated the flight pattern information, echolocation call recordings, and NIR photographs to determine a process workflow for integrating heterogeneous data types. The team’s findings allowed classification of both echolocating and nonecholocating bats, assigning 84% of the detections within a specific guild or nesting area. The bats were further categorized based on visible morphological features and echolocation calls. The work is challenging preconceived notions about certain bat populations. For example, previous studies suggested that fruit-eating bats were the predominant bat species at oil palm plantations, because this species was frequently caught in researchers’ nets at these sites. Researchers using the bat point count method, however, found that fruit bats are actually rare at oil palm plantations — making up just 7% of bat point count detections — and that insect-eating bats actually predominate. “This suggests that fruit-eating bats have a short commute through plantations and are easily caught with nets,” Darras said. “However, insect-eating bats can easily fly around nets in these open plantations. Our new technique shows that insect-eating bats are actually much more common than previously thought in oil palm and might play a significant role in suppressing insect pests.” According to Darras, this work, which cataloged a substantial number of images, is key to understanding bats of all kinds and abilities, as well as their behaviors in their natural environments. “We hope that these vivid pictures can be used for increasing conservation awareness and that our method will spur new research about [bats’] behavior and role in the ecosystem,” he said. No nets, no stress — so no bats went batty during this noninvasive analysis.