Person:

Combes, Stacey A.

The development of flapping-wing micro air vehicles (MAVs) demands a systematic exploration of the available design space to identify ways in which the unsteady mechanisms governing flapping-wing flight can best be utilized for producing optimal thrust or maneuverability. Mimicking the wing kinematics of biological flight requires examining the potential effects of wing morphology on flight performance, as wings may be specially adapted for flapping flight. For example, insect wings passively deform during flight, leading to instantaneous and potentially unpredictable changes in aerodynamic behavior. Previous studies have postulated various explanations for insect wing complexity, but there lacks a systematic approach for experimentally examining the functional significance of components of wing morphology, and for determining whether or not natural design principles can or should be used for MAVs. In this work, a novel fabrication process to create centimeter-scale wings of great complexity is introduced; via this process, a wing can be fabricated with a large range of desired mechanical and geometric characteristics. We demonstrate the versatility of the process through the creation of planar, insect-like wings with biomimetic venation patterns that approximate the mechanical properties of their natural counterparts under static loads. This process will provide a platform for studies investigating the effects of wing morphology on flight dynamics, which may lead to the design of highly maneuverable and efficient MAVs and insight into the functional morphology of natural wings.

Environmental turbulence is ubiquitous in natural habitats, but its effect on flying animals remains unknown because most flight studies are performed in still air or artificially smooth flow. Here we show that variability in external airflow limits maximum flight speed in wild orchid bees by causing severe instabilities. Bees flying in front of an outdoor, turbulent air jet become increasingly unstable about their roll axis as airspeed and flow variability increase. Bees extend their hindlegs ventrally at higher speeds, improving roll stability but also increasing body drag and associated power requirements by 30%. Despite the energetic cost, we observed this stability-enhancing behavior in 10 euglossine species from 3 different genera, spanning an order of magnitude in body size. A field experiment in which we altered the level of turbulence demonstrates that flight instability and maximum flight speed are directly related to flow variability. The effect of environmental turbulence on flight stability is thus an important and previously unrecognized determinant of flight performance.

Airflow conditions close to the Earth’s surface are often complex, posing challenges to flight stability and control for volant taxa. Relatively little is known about how well flying animals can contend with complex, adverse air flows, or about the flight-control mechanisms employed by animals to mitigate wind disturbances. Several recent studies have examined flight in the unsteady von Kármán vortex streets that form behind cylinders, generating flow disturbances that are predictable in space and time; these structures are relatively rare in nature, as they occur only in the immediate, downstream vicinity of an object. In contrast, freestream turbulence is characterized by rapid, unpredictable flow disturbances across a wide range of spatial and temporal scales, and is nearly ubiquitous in natural habitats. Hummingbirds are ideal organisms for studying the influence of freestream turbulence on flight, as they forage in a variety of aerial conditions and are powerful flyers. We filmed ruby-throated hummingbirds (A. colubris) maintaining position at a feeder in laminar and strongly turbulent (intensity ~15%) airflow environments within a wind tunnel, and compared their mean head, body, tail and wing kinematics, as well as variability in these parameters. Hummingbirds exhibited remarkably stable head position and orientation in both smooth and turbulent flow while maintaining position at the feeder. However, the hummingbird’s body was less stable in turbulent flow and appeared to be most sensitive to disturbances along the mediolateral axis, displaying large lateral accelerations, translations, and rolling motions during flight. The hummingbirds mitigated these disturbances by increasing mean wing stroke amplitude and stroke plane angle, and by varying these parameters asymmetrically between the wings, and from one stroke to the next. They also actively varied the orientation and fan angle of the tail, maintaining a larger mean fan angle when flying in turbulent flow; this may improve their passive stability, but likely incurs an energetic cost due to increased drag. Overall, we observed many of the same kinematic changes noted previously for hummingbirds flying in a von Kármán vortex street, but we also observed kinematic changes associated with high force production, similar to those seen during load-lifting or high-speed flight. These findings suggest that flight may be particularly costly in fully mixed, freestream turbulence, the flow condition that hummingbirds are likely to encounter most frequently in natural habitats.

Aerial predation is a highly complex, three-dimensional flight behavior that affects the individual fitness and population dynamics of both predator and prey. Most studies of predation adopt either an ecological approach in which capture or survival rates are quantified, or a biomechanical approach in which the physical interaction is studied in detail. In the present study, we show that combining these two approaches provides insight into the interaction between hunting dragonflies (Libellula cyanea) and their prey (Drosophila melanogaster) that neither type of study can provide on its own. We performed >2500 predation trials on nine dragonflies housed in an outdoor artificial habitat to identify sources of variability in capture success, and analyzed simultaneous predator–prey flight kinematics from 50 high-speed videos. The ecological approach revealed that capture success is affected by light intensity in some individuals but that prey density explains most of the variability in success rate. The biomechanical approach revealed that fruit flies rarely respond to approaching dragonflies with evasive maneuvers, and are rarely successful when they do. However, flies perform random turns during flight, whose characteristics differ between individuals, and these routine, erratic turns are responsible for more failed predation attempts than evasive maneuvers. By combining the two approaches, we were able to determine that the flies pursued by dragonflies when prey density is low fly more erratically, and that dragonflies are less successful at capturing them. This highlights the importance of considering the behavior of both participants, as well as their biomechanics and ecology, in developing a more integrative understanding of organismal interactions.

A fundamental challenge common to studies of animal movement, behavior, and ecology is the collection of high-quality datasets on spatial positions of animals as they change through space and time. Recent innovations in tracking technology have allowed researchers to collect large and highly accurate datasets on animal spatiotemporal position while vastly decreasing the time and cost of collecting such data. One technique that is of particular relevance to the study of behavioral ecology involves tracking visual tags that can be uniquely identified in separate images or movie frames. These tags can be located within images that are visually complex, making them particularly well suited for longitudinal studies of animal behavior and movement in naturalistic environments. While several software packages have been developed that use computer vision to identify visual tags, these software packages are either (a) not optimized for identification of single tags, which is generally of the most interest for biologists, or (b) suffer from licensing issues, and therefore their use in the study of animal behavior has been limited. Here, we present BEEtag, an open-source, image-based tracking system in Matlab that allows for unique identification of individual animals or anatomical markers. The primary advantages of this system are that it (a) independently identifies animals or marked points in each frame of a video, limiting error propagation, (b) performs well in images with complex backgrounds, and (c) is low-cost. To validate the use of this tracking system in animal behavior, we mark and track individual bumblebees (Bombus impatiens) and recover individual patterns of space use and activity within the nest. Finally, we discuss the advantages and limitations of this software package and its application to the study of animal movement, behavior, and ecology.