Roosting ecology drives the evolution of diverse bat landing maneuvers.

Bats and birds are the only living vertebrates capable of powered flight. However, bats differ from birds in that their flight required the evolution of ascending landing maneuvers that achieve their iconic head-under-heels roosting posture. We examined the evolution of landing flight in bats and tested its association with the physical properties of roosts. Bats performed four maneuvers, each correlated with patterns of peak impact force, impulse, and roosting ecology, a critical aspect of bat biology. Our findings indicate that the common ancestor of bats performed simple, four-limbed landings, similar to extant gliding mammals, and that rotationally complex landings enhancing control over impact forces coevolved multiple times with shifts to stiff, horizontal roosts. These results suggest landing biomechanics is central to bat biology: it was critical to flight adaptation in the past, mediates roost use in the present, and may affect bats' ability to respond to deforestation in the future.

Application of a novel deep learning-based 3D videography workflow to bat flight.

Studying the detailed biomechanics of flying animals requires accurate three-dimensional coordinates for key anatomical landmarks. Traditionally, this relies on manually digitizing animal videos, a labor-intensive task that scales poorly with increasing framerates and numbers of cameras. Here, we present a workflow that combines deep learning-powered automatic digitization with filtering and correction of mislabeled points using quality metrics from deep learning and 3D reconstruction. We tested our workflow using a particularly challenging scenario: bat flight. First, we documented four bats flying steadily in a 2 m3 wind tunnel test section. Wing kinematic parameters resulting from manually digitizing bats with markers applied to anatomical landmarks were not significantly different from those resulting from applying our workflow to the same bats without markers for five out of six parameters. Second, we compared coordinates from manual digitization against those yielded via our workflow for bats flying freely in a 344 m3 enclosure. Average distance between coordinates from our workflow and those from manual digitization was less than a millimeter larger than the average human-to-human coordinate distance. The improved efficiency of our workflow has the potential to increase the scalability of studies on animal flight biomechanics.