Biology subjects

Sponberg, S.

Publications and source records attributed to Sponberg, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Flight muscle allocation diverges between two moth families with distinct flight strategies

An animal's musculature must support its specific biomechanical needs, so muscle morphology and volume allocation may adapt when locomotor strategies diversify. We examined muscle size and morphology in two sister families of bombycoid moths, wild silkmoths (Saturniidae) and hawkmoths (Sphingidae), that have diverged in wingbeat frequency, wing morphology, and behavior. Although both families rely on the same muscles to power and steer flight, they may distribute muscle volume differently to prioritize distinct functions. We hypothesized that flight power muscle proportions are larger in hawkmoths and increase with wingbeat frequency, helping meet inertial power demands of high-frequency maneuverable flight. We also hypothesized that some individual muscles diverge in proportional volume and area to support distinct wing control strategies. To test our hypotheses, we took CT scans of twenty bombycoid species and quantified volumes and geometries of six flight muscle pairs. As expected, flight power muscle proportions positively correlate with wingbeat frequency and are generally greater in hawkmoths. Two of three steering muscles diverge substantially in relative volume and area between families. Most muscles exhibit greater length in silkmoths and greater cross-sectional area in hawkmoths. Finally, the dorsal oblique(DO) muscle diverges exceptionally in size and morphology, being highly developed in hawkmoths and smaller or absent in silkmoths. This unexpected difference supports the DO having an underappreciated role in flight control, possibly via shaping indirect strain propagation in the elastic thorax. We show that muscle volume distribution parallels bombycoids' divergent flight strategies, demonstrating how muscle allocation can adapt for specialized functional goals.

evolutionary biology↗

bioRxiv2026

The physiological dynamic clamp allows insect flight muscle to transition between two actuation modes in virtual reality

In most muscles, contraction is initiated by neural activation. Some groups of insects break this rule, flapping at frequencies far exceeding the neural drive to their flight muscles. These insects muscles (termed asynchronous) produce force in response to stretch, enabling flight at faster frequencies than would be possible through the slow calcium-dependent processes associated with neural activation. The first flapping insects lacked stretch-activated physiology, which then evolved on top of neural activation dynamics before likely being reduced again in some groups including moths. Stretch and neural activation can co-exist, but it remains unclear if stretch-activation alone is sufficient to generate asynchronous flapping in insect flight muscle. Building on prior closed-loop muscle physiology platforms, we develop a new way to perform a gain-of-function muscle physiology experiment called the physiological dynamic clamp. Inspired by dynamic clamp experiments in neuroscience, we couple isolated intact flight muscle from a hawkmoth, Manduca sexta, to simulated stretch-activation in virtual reality. Tuning virtual reality parameters allows us to manipulate the degree of stretch-activation in silico while retaining all other physiological properties of the muscle. With artificially enhanced stretch activation, we find that hawkmoth muscle can support stretch-activated work at typical wingbeat frequencies. When simultaneously stimulated at wingbeat frequency, interference between stretch and neural activation results in variable work production. However, this interference disappears when the two activation timescales are close to each other resulting in entrainment to the neural drive. Matching time scales suggests an evolutionary path for smoothly transitioning to stretch-activated, asynchronous flight and back again.

physiology↗

bioRxiv2026

Superposition eyes of diurnal and nocturnal hawkmoths are imperfect spheres and lack acute zones.

Superposition compound eyes improve sensitivity by pooling light from multiple facets and are widespread among nocturnal insects, including moths and beetles. Optical theory predicts that superposition eyes must be nearly spherical to form coherent images and therefore lack highly pronounced acute zones with high spatial resolution. To examine this, we imaged eyes of six hawkmoths (Sphingidae) spanning diurnal and nocturnal activity with high-resolution microcomputed tomography. Our automated pipeline created detailed eye maps quantifying morphological parameters. We measured local eye curvature (radial distance), interommatidial angle ({Delta}{varphi}), facet size and crystalline cone skewness (tilt of cone axes relative to the local surface normal). All species show more curvature in the dorso-ventral plane with flattening in the antero-posterior plane. However, their eyes still retain near-spherical curvature globally, with diurnal species showing greater distortion. For facet parameters, spatial acuity is generally highest (lowest {Delta}{varphi}) near the eye center and decreases gradually toward the periphery. However, overall variation in spatial acuity is low and these eyes lack distinct acute zones. Facet size gradually changes from center to periphery, increasing in some species and decreasing in the others. Cone skewness is present in all six species (0{degrees}-10{degrees}), but in two diurnal species of hummingbird hawkmoths it increases markedly in the posterior region (15{degrees}-30{degrees}) possibly compensating for regional eye flatness. This paper provides foundational data of ommatidial and eye shape measurements and advances our assumptions about how superposition eyes function.

animal behavior and cognition↗

bioRxiv2025

Supra-resonant wingbeats in insects

Powering small-scale flapping flight is challenging, yet insects sustain exceptionally fast wingbeats with ease. Since insects act as tiny biomechanical resonators, tuning their wingbeat frequency to the resonant frequency of their springy thorax and wings could make them more efficient fliers. But operating at resonance poses control problems and potentially constrains wingbeat frequencies within and across species. Resonance may be particularly limiting for the many orders of insects that power flight with specialized muscles that activate in response to mechanical stretch. Here, we test whether insects operate at their resonant frequency. First, we extensively characterize bumblebees and find that they surprisingly flap well above their resonant frequency via interactions between stretch-activation and mechanical resonance. Modeling and robophysical experiments then show that resonance is actually a lower bound for rapid wingbeats in most insects because muscles only pull, not push. Supra-resonance emerges as a general principle of high-frequency flight across five orders of insects from moths to flies.

zoology↗

bioRxiv2024

Neuron synchronization analyzed through spatial-temporal attention

Across diverse organisms, the temporal dynamics of spiking responses between neurons, the neural synchrony, is crucial for encoding different stimuli. Neural synchrony is especially important in the insect antennal (olfactory) lobe (AL). Previous studies on synchronization, however, rely on pair-wise synchronization metrics including the cross-correlogram and cos-similarity between kernelized spikes train. These pair-wise analyses overlook an important aspect of synchronization which is the interaction at the population neuron level. There are also limited modeling techniques that incorporate the synchronization between neurons in modeling population spike trains. Inspired by recent advancements in machine learning, we leverage a modern attention mechanism to learn a generative normalizing flow that captures neuron population synchronization. Our method not only reveals the spiking mechanism of neurons in the AL region but also produces semi-interpretable attention weights that characterize neuron interactions over time. These automatically learned attention weights allow us to elucidate the known principles of neuron synchronization and further shed light on the functional roles of different cell types (the local interneurons (LNs), and projection neurons (PNs)) in the dynamic neural network in the AL. By varying the balance of excitation and inhibition in this neural circuit, our method further uncovers the pattern between the strength of synchronization and the ratio of an odorant in the mixture. Author SummaryThe olfactory system can accurately compute the mixture of volatile compounds emitted from distant sources, enabling the foraging species to exhibit fast and effective decisions. However, altering ratios of one of the compounds in the mixture could be perceived as a different odor. Leveraging the current understanding of neural synchronization on sensory neural regions of insects, we construct a spatial-temporal attention normalizing flow, which partially replicates the AL regions functionality by learning the spiking mechanics of neurons. Beyond providing insights of the spiking mechanism of neurons in the AL region, our method also produces semi-interpretable attention weights that characterize neuron interaction over time. These automatically learned attention weights allow us to dissect out the principles of neuron synchronization and interaction mechanisms between projection neurons (PNs) and local neurons (LNs). Utilizing our accurate model of these AL functionality, we show evidence that the behavioral relevant compounds are closely clustered together while varying the intensities of one of the behavioral compounds in the mixture could attenuate the synchronization

neuroscience↗

bioRxiv2024

Body size and light environment modulate flight speed and saccadic behavior in free flying Drosophila melanogaster

For flying insects, visual control relies on acquiring adequate light, but many circumstances limit this, such as dim environments, high image speeds, or eyes of modest light gathering power. To determine these effects on vinegar flies, we limited light by either placing them in dim conditions, or generating individuals with developmentally smaller eyes, then examined activity levels and three-dimensional flight paths. When simulating dawn and dusk light periods, walking flies increase activity, reflecting their crepuscular nature, and this is stronger for flies with larger eyes. When light switches abruptly, similar to many lab settings, activity associated with crepuscular periods diminishes, as does activity associated with greater facet size. During free flight, we find flight speed decreases similarly in both dim light and small eye conditions, but excess light induces smaller individuals to restore their flight speed. Through a machine learning approach, we confirmed that two features, translational speed and saccade distance, are sufficient to classify treatment groups by light niche, size, and age. Together, these imply that flight changes in smaller individuals result from visual deficits, rather than other elements of body structure.

animal behavior and cognition↗

bioRxiv2024

Temporal resolution of spike coding in feedforward networks with signal convergence and divergence

Convergent and divergent structures in the networks that make up biological brains are found across many species and brain regions at various spatial scales. Neurons in these networks fire action potentials, or "spikes", whose precise timing is becoming increasingly appreciated as large sources of information about both sensory input and motor output. While previous theories on coding in convergent and divergent networks have largely neglected the role of precise spike timing, our model and analyses place this aspect at the forefront. For a suite of stimuli with different timescales, we demonstrate that structural bottlenecks- small groups of neurons post-synaptic to network convergence - have a stronger preference for spike timing codes than expansion layers created by structural divergence. Additionally, we found that a simple network model based on convergence and divergence ratios of a hawkmoth (Manduca sexta) nervous system can reproduce the relative contribution of spike timing information in its motor output, providing testable predictions on optimal temporal resolutions of spike coding across the moth sensory-motor pathway at both the single-neuron and population levels. Our simulations and analyses suggest a relationship between the level of convergent/divergent structure present in a feedforward network and the loss of stimulus information encoded by its population spike trains as their temporal resolution decreases, which could be tested experimentally across diverse neural systems in future studies. We further show that this relationship can be generalized across different spike-generating models and measures of coding capacity, implying a potentially fundamental link between network structure and coding strategy using spikes. Author summaryWithin the complex anatomy of the brain, there are certain structures that appear more often than expected. One example of this is when large populations of neurons connect to much smaller populations, and vice versa. We refer to these structural patterns as network convergence and divergence; they are observed in systems like the cerebellum, insect olfactory networks, visuomotor pathways, and the early visual system of mammals. Despite the ubiquity of this connectivity pattern, we are only beginning to understand its functional implications from a computational point of view. Here, we construct and analyze mathematical models of spiking neural networks to understand how convergent and divergent structure shapes the way that information is represented in each part of the network, as a function of the temporal resolution of population spiking activity. We then developed a simple feedforward network model of the visuomotor pathway of a moth, with similar convergent/divergent network structure, and reproduce a similar proportion of spike timing to spike count information as observed experimentally. Our results form predictions about spike coding in populations previously unobserved in experiment.

neuroscience↗

bioRxiv2024

Body oscillations reduce the aerodynamic power requirement of wild silkmoth flight

Insects show diverse flight kinematics and morphologies reflecting their evolutionary histories and ecological adaptations. Many silkmoths utilizing low wingbeat frequencies and large wings to fly display body oscillations: Their bodies pitch and bob periodically - synchronized with their wing flapping cycle. Similar oscillations in butterflies augment weight support and thrust and reduce flight power requirements. However, how the instantaneous body and wing kinematics interact for these beneficial aerodynamic and power consequences is not well understood. We hypothesized that the body oscillations affect aerodynamic power requirements by influencing the wing rotation relative to the airflow. Using three-dimensional forward flight video recordings of four silkmoth species and a quasi-steady blade-element aerodynamic method, we found that the body pitch angle and the wing sweep angle maintain a narrow range of phase differences to enhance the angle of attack variation between each half-stroke due to enhanced wing rotation relative to the airflow. This redirects the aerodynamic force to increase upward and forward force during downstroke and upstroke respectively thus lowering the overall drag without compromising weight support and forward thrust. A reduction in energy expenditure is beneficial because adult silkmoths do not feed and rely on limited energy budgets.

biophysics↗

bioRxiv2024

Moth resonant mechanics are tuned to wingbeat frequency and energetic demands.

An insects wingbeat frequency is a critical determinant of its flight performance and varies by multiple orders of magnitude across Insecta. Despite potential energetic and kine-matic benefits for an insect that matches its wingbeat frequency to its resonant frequency, recent work has shown that moths may operate off of their resonant peak. We hypothesized that across species, wingbeat frequency scales with resonance frequency to maintain favorable energetics, but with an offset in species that use frequency modulation as a means of flight control. The moth superfamily Bombycoidea is ideal for testing this hypothesis because their wingbeat frequencies vary across species by an order of magnitude, despite similar morphology and actuation. We used materials testing, high-speed videography, and a "spring-wing" model of resonant aerodynamics to determine how components of an insects flight apparatus (thoracic properties, wing inertia, muscle strain, and aerodynamics) vary with wingbeat frequency. We find that the resonant frequency of a moth correlates with wingbeat frequency, but resonance curve shape (described by the Weis-Fogh number) and peak location vary within the clade in a way that corresponds to frequency-dependent biomechanical demands. Our results demonstrate that a suite of adaptations in muscle, exoskeleton and wing drive variation in resonant mechanics, reflecting potential constraints on matching wingbeat and resonant frequencies.

physiology↗

bioRxiv2023

Context dependent multisensory integration: Mechanosensation depends on luminance for robust performance

Multisensory, goal-directed behaviors are ubiquitous and essential in animals across taxa. Individual sensory modalities may be significantly tuned by environmental context, and yet they must continue to combine and produce multisensory behaviors. This necessitates either behavioral robustness or goal-relevant adaptation in sensorimotor systems. In the case of hover-feeding hawkmoths of the species Manduca sexta, proboscis mechanosensation and vision are known to combine linearly in tracking of moving flowers. This tracking behavior is affected by light-levels, and visual compensation is necessary for robust flower-tracking. Whether the mechanosensory response also adjusts to light-level, in order to produce linear combination across luminance contexts, is not known. We applied control theoretic analyses to study integration of mechanosensory and visual information in flower tracking hawkmoths in the context of high luminance. This was performed using a two-part robotic flower system. Under the conditions of high luminance, we verified the linear combination of mechanosensory and visual systems, and the complementary modulation of these systems. We show that both systems tune their frequency response with changing environmental light level,while keeping their combined error low at relevant frequencies. Thus, the animal adapts to changing conditions, across modalities, even when only one of the modalities (vision) is directly affected. This cross-talk between sensorimotor systems is constrained, and possibly driven, by performance requirements.

neuroscience↗

bioRxiv2023

Flight power muscles have a coordinated, causal role in controlling hawkmoth pitch turns

Flying insects solve a daunting control problem of generating a patterned and precise motor program to stay airborne and generate agile maneuvers. In this motor program consisting of every action potential controlling wing musculature, each muscle encodes significant information about movement in precise spike timing down to the millisecond scale. While individual muscles share information about movement, we do not yet know if they have separable effects on an animals motion, or if muscles functionally interact such that the effects of any muscles timing depends heavily on the state of the entire musculature. To answer these questions, we performed spike-resolution electromyography and precise stimulation of individual spikes in the hawkmoth Manduca sexta during tethered flapping. We specifically explored how the flight power muscles themselves may contribute to pitch control which is necessary to stabilize flight. Combining correlational study of visually-induced turns with causal manipulation of spike timing, we discovered likely coordination patterns for pitch turns, investigated if these correlational patterns can individually drive pitch control, and studied whether the precise spike timing of indirect power muscles can lead to pitch maneuvers. We observed significant timing change of the main downstroke muscles, the dorsolongitudinal muscles (DLMs), associated with whether a moth was pitching up or down. Causally inducing this timing change in the DLMs with electrical stimulation produced a consistent, mechanically relevant feature in pitch torque, establishing that indirect power muscles in Manduca have a control role in pitch. Because changes were evoked in unconstrained flapping in only the DLMs, however, these pitch torque features left large unexplained variation. We find this unexplained variation indicates significant functional overlap in pitch control such that precise timing of one power muscle does not produce a precise turn, demonstrating the importance of coordination across the entire motor program for flight. Summary StatementWe investigate how individual muscles contribute to flight by manipulating muscle timing in behaving hawkmoths. We find precise timing of single muscles does not produce precise turns, highlighting the importance of coordination across the entire motor program.

neuroscience↗

bioRxiv2023

Cross-subject Mapping of Neural Activity with Restricted Boltzmann Machines

Subject-to-subject variability is a common challenge in generalizing neural data models across subjects. While many methods exist that map one subject to another, it remains challenging to combine many subjects in a computationally efficient manner, especially with features that are highly non-linear such as when considering populations of spiking neurons or motor units. Our objective is to transfer data from one or more target subjects to the data space of one or more source subject(s) such that the neural decoder of the source subject can directly decode the target data when the source(s) is not available during test time. We propose to use the Gaussian-Bernoulli Restricted Boltzmann Machine (RBM); once trained over the entire set of subjects, the RBM allows the mapping of target features on source feature spaces using Gibbs sampling. We also consider a novel computationally efficient training technique for RBMs based on the minimization of the Fisher divergence, which allows the gradients of the RBM to be computed in closed form, in contrast to the more traditional contrastive divergence. We apply our methods to decode turning behaviors from a comprehensive spike-resolved motor program - neuromuscular recordings of spike trains from the ten muscles that control wing motion in an agile flying Manduca sexta. The dataset consists of the comprehensive motor program recorded from nine subjects driven by six discrete visual stimuli. The evaluations show that the target features can be decoded using the source classifier with an accuracy of up to 95% when mapped using an RBM trained by Fisher divergence. Significant StatementIn this study, we address the variability of neural data across subjects, which is a significant obstacle in developing models that can generalize across subjects. Our objective is to create a task-specific representation of the target subject signal in the feature space of the source subject. Our proposed RBM architectures achieve highly flexible and accurate cross-subject mapping with few assumptions. Our Fisher RBM improved the previous state of the art method by 300%. Our methods show promise in generalizing features of complex neural datasets across individuals, tuning neural interfaces to subject-specific features, and leveraging data across multiple subjects when experiments are limited in time or completeness.

neuroscience↗

bioRxiv2022

Structural damping renders the insect exoskeleton mechanically insensitive to non-sinusoidal deformations

Muscles act through elastic and dissipative elements to mediate movement, but these elements can introduce dissipation and filtering which are important for energetics and control. The high power requirements of flapping flight can be reduced by the insects exoskeleton, which acts as a structurally damped spring under purely sinusoidal deformation. However, this purely sinusoidal dynamic regime does not encompass the asymmetric wing strokes of many insects or non-periodic deformations induced by external perturbations. As such, it remains unknown whether a structural damping model applies broadly and what implications it has for control. We used a vibration testing system to measure the mechanical properties of isolated Manduca sexta thoraces under symmetric, asymmetric, and band-limited white noise deformations. We measured a thoracic stiffness of 2980 Nm-1 at 25 Hz and physiological peak-to-peak amplitude of 0.92 mm. Power savings and dissipation were indistinguishable between symmetric and asymmetric conditions, demonstrating that no additional energy is required to deform the thorax non-sinusoidally. Under white noise conditions, stiffness and damping were invariant with frequency, which is consistent with a structural damping model and suggests the thorax has no frequency-dependent filtering properties. A simple flat frequency response function fits our measured frequency response. This work demonstrates the potential of structurally damped materials to simplify motor control by eliminating any velocity-dependent filtering that viscoelastic elements usually impose between muscle and appendage.

biophysics↗

bioRxiv2021

An information theoretic method to resolve millisecond-scale spike timing precision in a comprehensive motor program

Sensory inputs in nervous systems are often encoded at the millisecond scale in a temporally precise code. There is now a growing appreciation for the prevalence of precise timing encoding in motor systems. Animals from moths to birds control motor outputs using precise spike timing, but we largely do not know at what scale timing matters in these circuits due to the difficulty of recording a complete set of spike-resolved motor signals and relatively few methods for assessing spike timing precision. We introduce a method to estimate spike timing precision in motor circuits using continuous MI estimation at increasing levels of added uniform noise. This method can assess spike timing precision at fine scales for encoding rich motor output variation. We demonstrate the advantages of this approach compared to a previously established discrete information theoretic method of assessing spike timing precision. We use this method to analyze a data set of simultaneous turning (yaw) torque output and EMG recordings from the 10 primary muscles of Manduca sexta as tethered moths visually tracked a robotic flower moving with a 1 Hz sinusoidal trajectory. We know that all 10 muscles in this motor program encode the majority of information about yaw torque in spike timings, but we do not know whether individual muscles receive information encoded at different levels of precision. Using the continuous MI method, we demonstrate that the scale of temporal precision in all motor units in this insect flight circuit is at the sub-millisecond or millisecond-scale, with variation in precision scale present between muscle types. This method can be applied broadly to estimate spike timing precision in sensory and motor circuits in both invertebrates and vertebrates.

neuroscience↗

bioRxiv2021

Consistent coordination patterns provide near perfect behavior decoding in a comprehensive motor program for insect flight

Patterns of motor activity can be used to decode behavior state. Precise spike timing encoding is present in many motor systems, but is not frequently utilized to decode behavior or to examine how coordination is achieved across many motor units. Testing whether the same coordinated sets of muscles control different movements is difficult without a complete motor representation at the level of the currency of control - action potentials. Here, we demonstrate nearly perfect decoding of six hawk moth flight behaviors elicited in response to wide-field drifting visual stimuli about the flight axes - pitch, roll, and yaw - using a comprehensive, spike-resolved motor program and a simple linear decoding pipeline. A complex decoding scheme is not necessary, even if the functional patterns of control are nonlinear. We show that muscle covariation present in one pair of visual stimulus conditions can be used to decode behavior in a different pair of visual stimulus conditions, indicating the presence of conserved muscle coordination patterns at the level of motor neuronal timings in functionally distinct behaviors. We also demonstrate that as few as half the muscles can be used to retain decoding performance, linking coordination to redundancy in encoding, if not function, across the entire moth flight motor program.

neuroscience↗

bioRxiv2021

Adaptive shifts underlie the divergence in wing morphology in bombycoid moths

The evolution of flapping flight is linked to the prolific success of insects. Across Insecta, wing morphology diversified, strongly impacting aerodynamic performance. In the presence of ecological opportunity, discrete adaptive shifts and early bursts are two processes hypothesized to give rise to exceptional morphological diversification. Here, we use the sister-families Sphingidae and Saturniidae to answer how the evolution of aerodynamically important traits is linked to clade divergence and through what process(es) these traits evolve. Many agile Sphingidae evolved hover-feeding behaviors, while adult Saturniidae lack functional mouth parts and rely on a fixed energy budget as adults. We find that Sphingidae underwent an adaptive shift in wing morphology coincident with life history and behavior divergence, evolving small high aspect-ratio wings advantageous for power reduction that can be moved at high frequencies, beneficial for flight control. In contrast, Saturniidae, which do not feed as adults, evolved large wings and morphology which surprisingly does not reduce aerodynamic power, but could contribute to their erratic flight behavior, aiding in predator avoidance. We suggest that after the evolution of flapping flight, diversification of wing morphology can be potentiated by adaptative shifts, shaping the diversity of wing morphology across insects.

evolutionary biology↗

bioRxiv2020

Hawkmoths use wingstroke-to-wingstroke frequency modulation for aerial recovery to vortex ring perturbations

Centimeter-scale fliers that combine wings with springy elements must contend with the high power requirements and mechanical constraints of flapping wing flight. Insects utilize elastic energy exchange to reduce the inertial costs of flapping wing flight and potentially match wingbeat frequencies to a mechanical resonance. Flying at resonance may be energetically favorable under steady conditions, but it is difficult to modulate the frequency of a resonant system. Evidence suggests that insects utilize frequency modulation over long time scales to adjust aerodynamic forces, but it remains an open question the extent to which insects can modulate frequency on the wingstroke-to-wingstroke timescale. If wingbeat frequencies deviate from resonance, the musculature must work against the elastic flight system, thereby potentially increasing energetic costs. To assess how insects address the simultaneous needs for power and control, we tested the capacity for wingstroke-to-wingstroke wingbeat frequency modulation by perturbing free hovering Manduca sexta with vortex rings while recording high-speed video at 2000 fps. Because hawkmoth flight muscles are synchronous, there is at least the potential for the nervous system to modulate frequency on each wingstroke. We observed {+/-} 16% wingbeat frequency modulation in just a few wing strokes. Via instantaneous phase analysis of wing kinematics, we found that over 85% of perturbation responses required active changes in motor input frequency. Unlike their robotic counterparts that explicitly abdicate frequency modulation in favor of energy efficiency, we find that wingstroke-to-wingstroke frequency modulation is an underappreciated control strategies that complements other strategies for maneuverability and stability in insect flight.

biophysics↗

bioRxiv2020

Wing shape evolution in bombycoid moths reveals two distinct strategies for maneuverable flight

Across insects, wing shape and size have undergone dramatic divergence even in closely related sister groups, but we do not yet know morphology changes in tandem with kinematics to support body weight within available aerodynamic power and how the specific force production patterns are linked to changes in behavior. Hawkmoths and wild silkmoths are two such diverse sister families with divergent wing morphology. Using 3d kinematics and quasi-steady aerodynamic modeling, we compare the aerodynamics and the contributions of wing shape, size, and kinematics in 10 moth species. We find that wing movement also diverges between the clades and underlies two distinct strategies for flight. Hawkmoths use wing kinematics, especially high frequencies, to enhance force, but wing morphologies that reduces power. Silkmoths use wing morphology to enhance force, and high amplitude wingstrokes to reduce power. Both strategies converge on similar aerodynamic power and can support similar body mass ranges, but their within-wingstroke force profiles are quite different and linked to the hovering flight of hawkmoths and the bobbing flight of silkmoths. These two groups of moths each fly more like other, distantly related insects than they do each other, demonstrating the convergence and diversity of flapping flight evolution.

physiology↗