Echolocating bats have turned night into day. More than a thousand species of bats occupy all imaginable food niches: from mosquito-hunters to nectar-lickers to so-called trawling bats. Scientists from the Ludwig Maximilian University of Munich and the Max Planck Institute for Ornithology in Seewiesen have now discovered how echolocation could enable those bats to find their prey even on turbulent water surfaces.
When bats hunt close to foliage or the like, they need to find the prey echo amidst a multitude of echoes reflected off the background - the needle in the haystack. However, the Water Bat and the Pond Bat don’t, although they hunt very close to water bodies – after all, nomen est omen. Holger Goerlitz, Head of the Acoustical and Functional Ecology research group at the Max Planck Institute for Ornithology, explains the advantage of hunting above water: „A smooth water surface also acoustically acts like a mirror: at the same angle as the sound hits the surface, it is also reflected, in our case mainly away from the bat. A floating insect, on the other hand, reflects sound directly back to the bat: a single conspicuous prey echo against silence.” But what if the water surface is not as smooth as a mirror? After all, bats do hunt in wind and rain or over flowing waters.
For years, Prof. Lutz Wiegrebe from the Biocenter of the Ludwig Maximilian University has been studying the fundamentals of auditory object recognition with the help of a bat species from the American tropics, the Pale Spear-Nosed Bat (Phyllostomus discolor). He was curious as to whether echolocating bats can perceive the three-dimensional structure of water waves and thus distinguish them from prey. In fact, this ability is widespread among aquatic predators like leeches, spiders, or amphibians, but in the case of bats, this spatial structure would have to be perceived with the sense of hearing – quite the challenge. Like all mammals, bats have only two ears. Any information about where the sound that arrives at the eardrum originally came from must be calculated by comparing the incoming signals at left and right ear. "When a sound comes from the left, it arrives at the left ear both earlier and louder than at the right ear.” says Leonie Baier, first author of the study. “And when a noise comes from the front, it sounds a little bit different than coming from the back - this is because of our outer ears." She goes on to explain that bats also calculate distance: "The more time elapses between sending the call and receiving the echo, the farther away the target is."
Getting to the bottom of the perception of spatial structure, Baier trained the Spear-Nosed Bats to distinguish a smooth surface from a rippled surface - in the dark, i.e. only with the help of echolocation. The animals were much better at detecting structured surfaces when those had a high spatial frequency, i. e. many ripples closely together. The bats could even perceive such ripples of only 1-2 mm height. When the spatial frequency was very low, i.e. with only a few widespread waves, the bats could not tell the difference between the smooth and rippled surfaces; not even when the ripples were 32 mm high. Comparing this to natural patterns, the scientists interpret their results in such a way that gentle background waves caused by wind are virtually invisible to the bats, while the waves of bobbing prey catch the bats’ eye - or rather their ear.
"Comparing the sensitivity of echolocation for spatial frequencies with that of human vision produces astonishing parallels," says Lutz Wiegrebe. But the anatomy of eye and ear are fundamentally different, so the researchers went on in search of the mechanism behind the bats’ performance. They simulated the neuronal activity found in the bat’s auditory nerve and showed that the echoes actually contain a lot of information to distinguish structured surfaces from one another. Holger Goerlitz summarizes: "We were able to show that inherent physical properties of surface structures provide stimuli to the auditory system as they are also used by the visual system to process spatial information. A beautiful example of convergent evolution. "
Read the original publication in iScience here.