The long-distance flight behavior of Drosophila supports an agent-based model for wind-assisted dispersal in insects

Monitoring of the nAChRsα6 G275A spinetoram resistance allele in Drosophila melanogaster populations from New York vineyards

BACKGROUND

Spinosyns are a group of naturally occurring and semi-synthetic insecticides with widespread utility in agriculture, including organic production systems. One example is spinetoram (Delegate), which is the only registered insecticide in New York State (for control of Drosophila melanogaster in vineyards) to which vinegar flies have not yet evolved high levels of resistance. However, low levels of resistance have been found in vineyard populations of D. melanogaster, and a highly resistant strain was obtained after only five selections (in the laboratory). We identified the nAChR α6 mutation (G275A) responsible for the resistance and developed a rapid, high-throughput assay for resistance.

RESULTS

Surveys of collections made in 2023 show low levels of the resistance allele in four populations. A correlation was observed between vineyard use of spinetoram and frequency of the resistance allele, but not between county-wide use of spinosyns and frequency of the resistance allele.

CONCLUSIONS

One of the sites we monitored was previously surveyed in 2019 and the frequency of the resistance allele detected in 2023 had increased. Implications of these findings to resistance management of D. melanogaster are discussed. © 2024 Society of Chemical Industry.

A neural circuit architecture for rapid learning in goal-directed navigation

Anchoring goals to spatial representations enables flexible navigation but is challenging in novel environments when both representations must be acquired simultaneously. We propose a framework for how Drosophila uses internal representations of head direction (HD) to build goal representations upon selective thermal reinforcement. We show that flies use stochastically generated fixations and directed saccades to express heading preferences in an operant visual learning paradigm and that HD neurons are required to modify these preferences based on reinforcement. We used a symmetric visual setting to expose how flies' HD and goal representations co-evolve and how the reliability of these interacting representations impacts behavior. Finally, we describe how rapid learning of new goal headings may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in circuit architecture. Such evolutionarily structured architectures, which enable rapidly adaptive behavior driven by internal representations, may be relevant across species.

Inhibitory control of locomotor statistics in walking Drosophila

In order to forage for food, many animals regulate not only specific limb movements but the statistics of locomotor behavior over time, for example switching between long-range dispersal behaviors and more localized search depending on the availability of resources. How pre-motor circuits regulate such locomotor statistics is not clear. Here we took advantage of the robust changes in locomotor statistics evoked by attractive odors in walking Drosophila to investigate their neural control. We began by analyzing the statistics of ground speed and angular velocity during three well-defined motor regimes: baseline walking, upwind running during odor, and search behavior following odor offset. We find that during search behavior, flies adopt higher angular velocities and slower ground speeds, and tend to turn for longer periods of time in one direction. We further find that flies spontaneously adopt periods of different mean ground speed, and that these changes in state influence the length of odor-evoked runs. We next developed a simple physiologically-inspired computational model of locomotor control that can recapitulate these statistical features of fly locomotion. Our model suggests that contralateral inhibition plays a key role both in regulating the difference between baseline and search behavior, and in modulating the response to odor with ground speed. As the fly connectome predicts decussating inhibitory neurons in the lateral accessory lobe (LAL), a pre-motor structure, we generated genetic tools to target these neurons and test their role in behavior. Consistent with our model, we found that activation of neurons labeled in one line increased curvature. In a second line labeling distinct neurons, activation and inactivation strongly and reciprocally regulated ground speed and altered the length of the odor-evoked run. Additional targeted light activation experiments argue that these effects arise from the brain rather than from neurons in the ventral nerve cord, while sparse activation experiments argue that speed control in the second line arises from both LAL neurons and a population of neurons in the dorsal superior medial protocerebrum (SMP). Together, our work develops a biologically plausible computational architecture that captures the statistical features of fly locomotion across behavioral states and identifies potential neural substrates of these computations.

Bumblebees compensate for the adverse effects of sidewind during visually guided landings

Flying animals often encounter winds during visually guided landings. However, how winds affect their flight control strategy during landing is unknown. Here, we investigated how sidewind affects the landing performance and sensorimotor control of foraging bumblebees (Bombus terrestris). We trained bumblebees to forage in a wind tunnel, and used high-speed stereoscopic videography to record 19,421 landing maneuvers in six sidewind speeds (0 to 3.4 m s-1), which correspond to winds encountered in nature. Bumblebees landed less often in higher windspeeds, but the landing durations from free flight were not increased by wind. By testing how bumblebees adjusted their landing control to compensate for adverse effects of sidewind on landing, we showed that the landing strategy in sidewind resembled that in still air, but with important adaptations. Bumblebees landing in a sidewind tended to drift downwind, which they controlled for by performing more hover maneuvers. Surprisingly, the increased hover prevalence did not increase the duration of free-flight landing maneuvers, as these bumblebees flew faster towards the landing platform outside the hover phases. Hence, by alternating these two flight modes along their flight path, free-flying bumblebees negated the adverse effects of high windspeeds on landing duration. Using control theory, we hypothesize that bumblebees achieve this by integrating a combination of direct aerodynamic feedback and a wind-mediated mechanosensory feedback control, with their vision-based sensorimotor control loop. The revealed landing strategy may be commonly used by insects landing in windy conditions, and may inspire the development of landing control strategies onboard autonomously flying robots.

Fantastic beasts and how to study them: rethinking experimental animal behavior

Humans have been trying to understand animal behavior at least since recorded history. Recent rapid development of new technologies has allowed us to make significant progress in understanding the physiological and molecular mechanisms underlying behavior, a key goal of neuroethology. However, there is a tradeoff when studying animal behavior and its underlying biological mechanisms: common behavior protocols in the laboratory are designed to be replicable and controlled, but they often fail to encompass the variability and breadth of natural behavior. This Commentary proposes a framework of 10 key questions that aim to guide researchers in incorporating a rich natural context into their experimental design or in choosing a new animal study system. The 10 questions cover overarching experimental considerations that can provide a template for interspecies comparisons, enable us to develop studies in new model organisms and unlock new experiments in our quest to understand behavior.

Wind Gates Search States in Free Flight

For any organism tracking a chemical cue to its source, the motion of its surrounding fluid provides crucial information for success. For both swimming and flying animals engaged in olfaction driven search, turning into the direction of oncoming wind or water current is often a critical first step 1, 2 . However, in nature, wind and water currents may not always provide a reliable directional cue 3, 4, 5 . It is unclear how organisms adjust their search strategies accordingly due to the challenges of separately controlling flow and chemical encounters. Here, we use the genetic toolkit of Drosophila melanogaster , a model organism for olfaction 6 , to develop an optogenetic paradigm to deliver temporally precise "virtual" olfactory experiences in free-flying animals while independently manipulating the wind conditions. We show that in free flight, Drosophila melanogaster adopt distinct search routines that are gated by whether they are flying in laminar wind or in still air. We first confirm that in laminar wind flies turn upwind, and further, we show that they achieve this using a rapid turn. In still air, flies adopt remarkably stereotyped "sink and circle" search state characterized by ∼60°turns at 3-4 Hz, biased in a consistent direction. In both laminar wind and still air, immediately after odor onset, flies decelerate and often perform a rapid turn. Both maneuvers are consistent with predictions from recent control theoretic analyses for how insects may estimate properties of wind while in flight 7, 8 . We suggest that flies may use their deceleration and "anemometric" turn as active sensing maneuvers to rapidly gauge properties of their wind environment before initiating a proximal or upwind search routine.

Drosophila flight: How flies control casts and surges

In the absence of directional cues, most foraging animals explore space by turning and zigzagging in search of sensory information. Recent progress in the identification of the neural correlates of turns in flies offers exciting new perspectives on the evolution of neural circuits controlling fundamental aspects of orientation responses.

Descending control and regulation of spontaneous flight turns in Drosophila

The clumped distribution of resources in the world has influenced the pattern of foraging behavior since the origins of locomotion, selecting for a common search motif in which straight movements through resource-poor regions alternate with zig-zag exploration in resource-rich domains. For example, during local search, flying flies spontaneously execute rapid flight turns, called body saccades, but suppress these maneuvers during long-distance dispersal or when surging upstream toward an attractive odor. Here, we describe the key cellular components of a neural network in flies that generate spontaneous turns as well as a specialized pair of neurons that inhibits the network and suppresses turning. Using 2-photon imaging, optogenetic activation, and genetic ablation, we show that only four descending neurons appear sufficient to generate the descending commands to execute flight saccades. The network is organized into two functional units-one for right turns and one for left-with each unit consisting of an excitatory (DNae014) and an inhibitory (DNb01) neuron that project to the flight motor neuropil within the ventral nerve cord. Using resources from recently published connectomes of the fly, we identified a pair of large, distinct interneurons (VES041) that form inhibitory connections to all four saccade command neurons and created specific genetic driver lines for this cell. As predicted by its connectivity, activation of VES041 strongly suppresses saccades, suggesting that it promotes straight flight to regulate the transition between local search and long-distance dispersal. These results thus identify the key elements of a network that may play a crucial role in foraging ecology.

Neuronal calcium spikes enable vector inversion in the Drosophila brain

A typical neuron signals to downstream cells when it is depolarized and firing sodium spikes. Some neurons, however, also fire calcium spikes when hyperpolarized. The function of such bidirectional signaling remains unclear in most circuits. Here we show how a neuron class that participates in vector computation in the fly central complex employs hyperpolarization-elicited calcium spikes to invert two-dimensional mathematical vectors. When cells switch from firing sodium to calcium spikes, this leads to a ~180° realignment between the vector encoded in the neuronal population and the fly's internal heading signal, thus inverting the vector. We show that the calcium spikes rely on the T-type calcium channel Ca-α1T, and argue, via analytical and experimental approaches, that these spikes enable vector computations in portions of angular space that would otherwise be inaccessible. These results reveal a seamless interaction between molecular, cellular and circuit properties for implementing vector math in the brain.

Descending control and regulation of spontaneous flight turns in Drosophila

The clumped distribution of resources in the world has influenced the pattern of foraging behavior since the origins of life, selecting for a common locomotor search motif in which straight movements through resource-poor regions alternate with zig -zag exploration in resource-rich domains. For example, flies execute rapid changes in flight heading called body saccades during local search, but suppress these turns during long-distance dispersal or when surging upwind after encountering an attractive odor plume. Here, we describe the key cellular components of a neural network in flies that generates spontaneous turns as well as a specialized neuron that inhibits the network to promote straight flight. Using 2-photon imaging, optogenetic activation, and genetic ablation, we show that only four descending neurons appear sufficient to generate the descending commands to execute flight saccades. The network is organized into two functional couplets-one for right turns and one for left-with each couplet consisting of an excitatory (DNae014) and inhibitory (DNb01) neuron that project to the flight motor neuropil within the ventral nerve cord. Using resources from recently published connectomes of the fly brain, we identified a large, unique interneuron (VES041) that forms inhibitory connections to all four saccade command neurons and created specific genetic driver lines for this cell. As suggested by its connectivity, activation of VES041 strongly suppresses saccades, suggesting that it regulates the transition between local search and long-distance dispersal. These results thus identify the critical elements of a network that not only structures the locomotor behavior of flies, but may also play a crucial role in their natural foraging ecology.

An Agent-Based Model of Biting Midge Dynamics to Understand Bluetongue Outbreaks

Bluetongue (BT) is a well-known vector-borne disease that infects ruminants such as sheep, cattle, and deer with high mortality rates. Recent outbreaks in Europe highlight the importance of understanding vector-host dynamics and potential courses of action to mitigate the damage that can be done by BT. We present an agent-based model, entitled 'MidgePy', that focuses on the movement of individual Culicoides spp. biting midges and their interactions with ruminants to understand their role as vectors in BT outbreaks, especially in regions that do not regularly experience outbreaks. The results of our sensitivity analysis suggest that midge survival rate has a significant impact on the probability of a BTV outbreak as well as its severity. Using midge flight activity as a proxy for temperature, we found that an increase in environmental temperature corresponded with an increased probability of outbreak after identifying parameter regions where outbreaks are more likely to occur. This suggests that future methods to control BT spread could combine large-scale vaccination programs with biting midge population control measures such as the use of pesticides. Spatial heterogeneity in the environment is also explored to give insight on optimal farm layouts to reduce the potential for BT outbreaks.

Biogeography and evolution of social parasitism in Australian Myrmecia bulldog ants revealed by phylogenomics

Studying the historical biogeography and life history transitions from eusocial colony life to social parasitism contributes to our understanding of the evolutionary mechanisms generating biodiversity in eusocial insects. The ants in the genus Myrmecia are a well-suited system for testing evolutionary hypotheses about how their species diversity was assembled through time because the genus is endemic to Australia with the single exception of the species M. apicalis inhabiting the Pacific Island of New Caledonia, and because at least one social parasite species exists in the genus. However, the evolutionary mechanisms underlying the disjunct biogeographic distribution of M. apicalis and the life history transition(s) to social parasitism remain unexplored. To study the biogeographic origin of the isolated, oceanic species M. apicalis and to reveal the origin and evolution of social parasitism in the genus, we reconstructed a comprehensive phylogeny of the ant subfamily Myrmeciinae. We utilized Ultra Conserved Elements (UCEs) as molecular markers to generate a comprehensive molecular genetic dataset consisting of 2,287 loci per taxon on average for 66 out of the 93 known Myrmecia species as well as for the sister lineage Nothomyrmecia macrops and selected outgroups. Our time-calibrated phylogeny inferred that: (i) stem Myrmeciinae originated during the Paleocene ∼58 Ma ago; (ii) the current disjunct biogeographic distribution of M. apicalis was driven by long-distance dispersal from Australia to New Caledonia during the Miocene ∼14 Ma ago; (iii) the single social parasite species, M. inquilina, evolved directly from one of the two known host species, M. nigriceps, in sympatry via the intraspecific route of social parasite evolution; and (iv) 5 of the 9 previously established taxonomic species groups are non-monophyletic. We suggest minor changes to reconcile the molecular phylogenetic results with the taxonomic classification. Our study enhances our understanding of the evolution and biogeography of Australian bulldog ants, contributes to our knowledge about the evolution of social parasitism in ants, and provides a solid phylogenetic foundation for future inquiries into the biology, taxonomy, and classification of Myrmeciinae.

Near-surface wind variability over spatiotemporal scales relevant to plume tracking insects

Odor plume tracking is important for many organisms, and flying insects have served as popular model systems for studying this behavior both in field and laboratory settings. The shape and statistics of the airborne odor plumes that insects follow are largely governed by the wind that advects them. Prior atmospheric studies have investigated aspects of microscale wind patterns with an emphasis on characterizing pollution dispersion, enhancing weather prediction models, and for assessing wind energy potential. Here, we aim to characterize microscale wind dynamics through the lens of short-term ecological functions by focusing on spatial and temporal scales most relevant to insects actively searching for odor sources. We collected and compared near-surface wind data across three distinct environments (sage steppe, forest, and urban) in Northern Nevada. Our findings show that near-surface wind direction variability decreases with increasing wind speeds and increases in environments with greater surface complexity. Across environments, there is a strong correlation between the variability in the wind speed (i.e., turbulence intensity) and wind direction (i.e., standard deviation in wind direction). In some environments, the standard deviation in the wind direction varied as much as 15°-75° on time scales of 1-10 min. We draw insight between our findings and previous plume tracking experiments to provide a general intuition for future field research and guidance for wind tunnel design. Our analysis suggests a hypothesis that there may be an ideal range of wind speeds and environment complexity in which insects will be most successful when tracking odor plumes over long distances.

The genetic basis of adaptation to copper pollution in Drosophila melanogaster

Introduction: Heavy metal pollutants can have long lasting negative impacts on ecosystem health and can shape the evolution of species. The persistent and ubiquitous nature of heavy metal pollution provides an opportunity to characterize the genetic mechanisms that contribute to metal resistance in natural populations. Methods: We examined variation in resistance to copper, a common heavy metal contaminant, using wild collections of the model organism Drosophila melanogaster. Flies were collected from multiple sites that varied in copper contamination risk. We characterized phenotypic variation in copper resistance within and among populations using bulked segregant analysis to identify regions of the genome that contribute to copper resistance. Results and Discussion: Copper resistance varied among wild populations with a clear correspondence between resistance level and historical exposure to copper. We identified 288 SNPs distributed across the genome associated with copper resistance. Many SNPs had population-specific effects, but some had consistent effects on copper resistance in all populations. Significant SNPs map to several novel candidate genes involved in refolding disrupted proteins, energy production, and mitochondrial function. We also identified one SNP with consistent effects on copper resistance in all populations near CG11825, a gene involved in copper homeostasis and copper resistance. We compared the genetic signatures of copper resistance in the wild-derived populations to genetic control of copper resistance in the Drosophila Synthetic Population Resource (DSPR) and the Drosophila Genetic Reference Panel (DGRP), two copper-naïve laboratory populations. In addition to CG11825, which was identified as a candidate gene in the wild-derived populations and previously in the DSPR, there was modest overlap of copper-associated SNPs between the wild-derived populations and laboratory populations. Thirty-one SNPs associated with copper resistance in wild-derived populations fell within regions of the genome that were associated with copper resistance in the DSPR in a prior study. Collectively, our results demonstrate that the genetic control of copper resistance is highly polygenic, and that several loci can be clearly linked to genes involved in heavy metal toxicity response. The mixture of parallel and population-specific SNPs points to a complex interplay between genetic background and the selection regime that modifies the effects of genetic variation on copper resistance.

Dehydrated Drosophila melanogaster track a water plume in tethered flight

Perception of sensory stimuli can be modulated by changes in internal state to drive contextually appropriate behavior. For example, dehydration is a threat to terrestrial animals, especially to Drosophila melanogaster due to their large surface area to volume ratio, particularly under the energy demands of flight. While hydrated D. melanogaster avoid water cues, while walking, dehydration leads to water-seeking behavior. We show that in tethered flight, hydrated flies ignore a water stimulus, whereas dehydrated flies track a water plume. Antennal occlusions eliminate odor and water plume tracking, whereas inactivation of moist sensing neurons in the antennae disrupts water tracking only upon starvation and dehydration. Elimination of the olfactory coreceptor eradicates odor tracking while leaving water-seeking behavior intact in dehydrated flies. Our results suggest that while similar hygrosensory receptors may be used for walking and in-flight hygrotaxis, the temporal dynamics of modulating the perception of water vary with behavioral state.

Drosophila Free-Flight Odor Tracking is Altered in a Sex-Specific Manner By Preimaginal Sensory Exposure

In insects such as Drosophila melanogaster, flight guidance is based on converging sensory information provided by several modalities, including chemoperception. Drosophila flies are particularly attracted by complex odors constituting volatile molecules from yeast, pheromones and microbe-metabolized food. Based on a recent study revealing that adult male courtship behavior can be affected by early preimaginal exposure to maternally transmitted egg factors, we wondered whether a similar exposure could affect free-flight odor tracking in flies of both sexes. Our main experiment consisted of testing flies differently conditioned during preimaginal development in a wind tunnel. Each fly was presented with a dual choice of food labeled by groups of each sex of D. melanogaster or D. simulans flies. The combined effect of food with the cis-vaccenyl acetate pheromone (cVA), which is involved in aggregation behavior, was also measured. Moreover, we used the headspace method to determine the "odorant" identity of the different labeled foods tested. We also measured the antennal electrophysiological response to cVA in females and males resulting from the different preimaginal conditioning procedures. Our data indicate that flies differentially modulated their flight response (take off, flight duration, food landing and preference) according to sex, conditioning and food choice. Our headspace analysis revealed that many food-derived volatile molecules diverged between sexes and species. Antennal responses to cVA showed clear sex-specific variation for conditioned flies but not for control flies. In summary, our study indicates that preimaginal conditioning can affect Drosophila free flight behavior in a sex-specific manner.

Emergent behaviour and neural dynamics in artificial agents tracking odour plumes

Tracking an odour plume to locate its source under variable wind and plume statistics is a complex task. Flying insects routinely accomplish such tracking, often over long distances, in pursuit of food or mates. Several aspects of this remarkable behaviour and its underlying neural circuitry have been studied experimentally. Here we take a complementary in silico approach to develop an integrated understanding of their behaviour and neural computations. Specifically, we train artificial recurrent neural network agents using deep reinforcement learning to locate the source of simulated odour plumes that mimic features of plumes in a turbulent flow. Interestingly, the agents' emergent behaviours resemble those of flying insects, and the recurrent neural networks learn to compute task-relevant variables with distinct dynamic structures in population activity. Our analyses put forward a testable behavioural hypothesis for tracking plumes in changing wind direction, and we provide key intuitions for memory requirements and neural dynamics in odour plume tracking.

The insect perspective on Z-disc structure and biology

Myofibrils are the intracellular structures formed by actin and myosin filaments. They are paracrystalline contractile cables with unusually well-defined dimensions. The sliding of actin past myosin filaments powers contractions, and the entire system is held in place by a structure called the Z-disc, which anchors the actin filaments. Myosin filaments, in turn, are anchored to another structure called the M-line. Most of the complex architecture of myofibrils can be reduced to studying the Z-disc, and recently, important advances regarding the arrangement and function of Z-discs in insects have been published. On a very small scale, we have detailed protein structure information. At the medium scale, we have cryo-electron microscopy maps, super-resolution microscopy and protein-protein interaction networks, while at the functional scale, phenotypic data are available from precise genetic manipulations. All these data aim to answer how the Z-disc works and how it is assembled. Here, we summarize recent data from insects and explore how it fits into our view of the Z-disc, myofibrils and, ultimately, muscles.

Individual tracking reveals long-distance flight-path control in a nocturnally migrating moth

Each year, trillions of insects make long-range seasonal migrations. These movements are relatively well understood at a population level, but how individual insects achieve them remains elusive. Behavioral responses to conditions en route are little studied, primarily owing to the challenges of tracking individual insects. Using a light aircraft and individual radio tracking, we show that nocturnally migrating death's-head hawkmoths maintain control of their flight trajectories over long distances. The moths did not just fly with favorable tailwinds; during a given night, they also adjusted for head and crosswinds to precisely hold course. This behavior indicates that the moths use a sophisticated internal compass to maintain seasonally beneficial migratory trajectories independent of wind conditions, illuminating how insects traverse long distances to take advantage of seasonal resources.

A neural circuit for wind-guided olfactory navigation

To navigate towards a food source, animals frequently combine odor cues about source identity with wind direction cues about source location. Where and how these two cues are integrated to support navigation is unclear. Here we describe a pathway to the Drosophila fan-shaped body that encodes attractive odor and promotes upwind navigation. We show that neurons throughout this pathway encode odor, but not wind direction. Using connectomics, we identify fan-shaped body local neurons called h∆C that receive input from this odor pathway and a previously described wind pathway. We show that h∆C neurons exhibit odor-gated, wind direction-tuned activity, that sparse activation of h∆C neurons promotes navigation in a reproducible direction, and that h∆C activity is required for persistent upwind orientation during odor. Based on connectome data, we develop a computational model showing how h∆C activity can promote navigation towards a goal such as an upwind odor source. Our results suggest that odor and wind cues are processed by separate pathways and integrated within the fan-shaped body to support goal-directed navigation.

Inversions and parallel evolution

Local adaptation leads to differences between populations within a species. In many systems, similar environmental contrasts occur repeatedly, sometimes driving parallel phenotypic evolution. Understanding the genomic basis of local adaptation and parallel evolution is a major goal of evolutionary genomics. It is now known that by preventing the break-up of favourable combinations of alleles across multiple loci, genetic architectures that reduce recombination, like chromosomal inversions, can make an important contribution to local adaptation. However, little is known about whether inversions also contribute disproportionately to parallel evolution. Our aim here is to highlight this knowledge gap, to showcase existing studies, and to illustrate the differences between genomic architectures with and without inversions using simple models. We predict that by generating stronger effective selection, inversions can sometimes speed up the parallel adaptive process or enable parallel adaptation where it would be impossible otherwise, but this is highly dependent on the spatial setting. We highlight that further empirical work is needed, in particular to cover a broader taxonomic range and to understand the relative importance of inversions compared to genomic regions without inversions.

This article is part of the theme issue ‘Genomic architecture of supergenes: causes and evolutionary consequences’.

Active anemosensing hypothesis: how flying insects could estimate ambient wind direction through sensory integration and active movement

Estimating the direction of ambient fluid flow is a crucial step during chemical plume tracking for flying and swimming animals. How animals accomplish this remains an open area of investigation. Recent calcium imaging with tethered flying Drosophila has shown that flies encode the angular direction of multiple sensory modalities in their central complex: orientation, apparent wind (or airspeed) direction and direction of motion. Here, we describe a general framework for how these three sensory modalities can be integrated over time to provide a continuous estimate of ambient wind direction. After validating our framework using a flying drone, we use simulations to show that ambient wind direction can be most accurately estimated with trajectories characterized by frequent, large magnitude turns. Furthermore, sensory measurements and estimates of their derivatives must be integrated over a period of time that incorporates at least one of these turns. Finally, we discuss approaches that insects might use to simplify the required computations, and present a list of testable predictions. Together, our results suggest that ambient flow estimation may be an important driver underlying the zigzagging manoeuvres characteristic of plume tracking animals’ trajectories.

Endocrine control of glycogen and triacylglycerol breakdown in the fly model

Over the last decade, the combination of genetics, transcriptomic and proteomic approaches yielded substantial insights into the mechanisms behind the synthesis and breakdown of energy stores in the model organisms. The fruit fly Drosophila melanogaster has been particularly useful to unravel genetic regulations of energy metabolism. Despite the considerable evolutionary distance between humans and flies, the energy storage organs, main metabolic pathways, and even their genetic regulations remained relatively conserved. Glycogen and fat are universal energy reserves used in all animal phyla and several of their endocrine regulators, such as the insulin pathway, are highly evolutionarily conserved. Nevertheless, some of the factors inducing catabolism of energy stores have diverged significantly during evolution. Moreover, even within a single insect species, D. melanogaster, there are substantial developmental and context-dependent variances in the regulation of energy stores. These differences include, among others, the endocrine pathways that govern the catabolic events or the predominant fuel which is utilized for the given process. For example, many catabolic regulators that control energy reserves in adulthood seem to be largely dispensable for energy mobilization during development. In this review, we focus on a selection of the most important catabolic regulators from the group of peptide hormones (Adipokinetic hormone, Corazonin), catecholamines (octopamine), steroid hormones (20-hydroxyecdysone), and other factors (extracellular adenosine, regulators of lipase Brummer). We discuss their roles in the mobilization of energy reserves for processes such as development through non-feeding stages, flight or starvation survival. Finally, we conclude with future perspectives on the energy balance research in the fly model.

Mass Trapping Drosophila suzukii, What Would It Take? A Two-Year Field Study on Trap Interference

Simple Summary

Drosophila suzukii is an invasive fruit fly that have became a key pest of soft-skinned fruits during the past decade. Today, the control of this pest relies strongly on broad-spectrum insecticides. Deploying attractive traps to control the pest population (mass trapping) could be part of the management strategy of D. suzukii. The present study analyses whether mass trapping with different attractants could be viable for D. suzukii control and how far traps should be maximally spaced in a grid. Traps in a grid compete for the same insects when they are spaced close enough and their radii of attraction overlap. Since the traps on the corners of a grid have fewer competing traps around than fully surrounded centre traps, the ratio of the catches in the corner traps and the centre traps indicates whether the traps are spaced close enough. By quantifying that trap interference in 4 × 4 trapping grids, it was found in this two-year field study that workable trap densities can be expected to control D. suzukii. From June onwards, synthetic lures in dry traps show equal or better results than the same traps with a reference liquid bait (apple cider vinegar).

Abstract

The invasion of Drosophila suzukii (Matsumura) (Diptera: Drosophilidae) worldwide has disrupted existing or developing integrated pest management (IPM) programs in soft-skinned fruits. Currently, with a reliance on only broad-spectrum insecticides, there is a critical call for alternative control measures. Behavioural control is one of the pillars of IPM, and, in the present study, it is investigated whether mass trapping could be viable for D. suzukii management. By quantifying trap interference in 4 × 4 replicate trapping grids, an estimate of the attraction radius for a certain attractant and context can be obtained. Traps designed for dry trapping (no drowning solution, but a killing agent inside) and synthetic controlled released experimental lures were tested in a two-year field study. Apple cider vinegar (ACV) was included as a reference bait and trials were performed with 5, 10 and 15 m inter-trap spacings at different seasonal timings. Clear trap interference and, hence, overlapping attraction radii were observed both in spring and summer for both the synthetic lures and ACV. In early spring, ACV shows the most potential for mass trapping, however from June onwards, the experimental dry lures show equal or better results than ACV. Based on our findings, workable trap densities are deemed possible, encouraging further development of mass trapping strategies for the control of D. suzukii.

Flying Into the Wind: Insects and Bio-Inspired Micro-Air-Vehicles With a Wing-Stroke Dihedral Steer Passively Into Wind-Gusts

Natural fliers utilize passive and active flight control strategies to cope with windy conditions. This capability makes them incredibly agile and resistant to wind gusts. Here, we study how insects achieve this, by combining Computational Fluid Dynamics (CFD) analyses of flying fruit flies with freely-flying robotic experiments. The CFD analysis shows that flying flies are partly passively stable in side-wind conditions due to their dorsal-ventral wing-beat asymmetry defined as wing-stroke dihedral. Our robotic experiments confirm that this mechanism also stabilizes free-moving flapping robots with similar asymmetric dihedral wing-beats. This shows that both animals and robots with asymmetric wing-beats are dynamically stable in sideways wind gusts. Based on these results, we developed an improved model for the aerodynamic yaw and roll torques caused by the coupling between lateral motion and the stroke dihedral. The yaw coupling passively steers an asymmetric flapping flyer into the direction of a sideways wind gust; in contrast, roll torques are only stabilizing at high air gust velocities, due to non-linear coupling effects. The combined CFD simulations, robot experiments, and stability modeling help explain why the majority of flying insects exhibit wing-beats with positive stroke dihedral and can be used to develop more stable and robust flapping-wing Micro-Air-Vehicles.

A population of descending neurons that regulates the flight motor of Drosophila

Like many insect species, Drosophila melanogaster are capable of maintaining a stable flight trajectory for periods lasting up to several hours^1,2. Because aerodynamic torque is roughly proportional to the fifth power of wing length³, even small asymmetries in wing size require the maintenance of subtle bilateral differences in flapping motion to maintain a stable path. Flies can even fly straight after losing half of a wing, a feat they accomplish via very large, sustained kinematic changes to both the damaged and intact wings⁴. Thus, the neural network responsible for stable flight must be capable of sustaining fine-scaled control over wing motion across a large dynamic range. In this paper, we describe an unusual type of descending neuron (DNg02) that projects directly from visual output regions of the brain to the dorsal flight neuropil of the ventral nerve cord. Unlike many descending neurons, which exist as single bilateral pairs with unique morphology, there is a population of at least 15 DNg02 cell pairs with nearly identical shape. By optogenetically activating different numbers of DNg02 cells, we demonstrate that these neurons regulate wingbeat amplitude over a wide dynamic range via a population code. Using 2-photon functional imaging, we show that DNg02 cells are responsive to visual motion during flight in a manner that would make them well suited to continuously regulate bilateral changes in wing kinematics. Collectively, we have identified a critical set of DNs that provide the sensitivity and dynamic range required for flight control.

Using an activation screen in flying flies, Namiki et al. identify a population of descending neurons that regulates wing amplitude over a large dynamic range. Via functional imaging and activation of different numbers of cells, they show that this population is a core component of the flight circuit, allowing the fly to steer and fly straight.

Building an allocentric travelling direction signal via vector computation

Many behavioural tasks require the manipulation of mathematical vectors, but, outside of computational models1-7, it is not known how brains perform vector operations. Here we show how the Drosophila central complex, a region implicated in goal-directed navigation7-10, performs vector arithmetic. First, we describe a neural signal in the fan-shaped body that explicitly tracks the allocentric travelling angle of a fly, that is, the travelling angle in reference to external cues. Past work has identified neurons in Drosophila8,11-13 and mammals14 that track the heading angle of an animal referenced to external cues (for example, head direction cells), but this new signal illuminates how the sense of space is properly updated when travelling and heading angles differ (for example, when walking sideways). We then characterize a neuronal circuit that performs an egocentric-to-allocentric (that is, body-centred to world-centred) coordinate transformation and vector addition to compute the allocentric travelling direction. This circuit operates by mapping two-dimensional vectors onto sinusoidal patterns of activity across distinct neuronal populations, with the amplitude of the sinusoid representing the length of the vector and its phase representing the angle of the vector. The principles of this circuit may generalize to other brains and to domains beyond navigation where vector operations or reference-frame transformations are required.

Hoverflies use a time-compensated sun compass to orientate during autumn migration

The sun is the most reliable celestial cue for orientation available to daytime migrants. It is widely assumed that diurnal migratory insects use a 'time-compensated sun compass' to adjust for the changing position of the sun throughout the day, as demonstrated in some butterfly species. The mechanisms used by other groups of diurnal insect migrants remain to be elucidated. Migratory species of hoverflies (Diptera: Syrphidae) are one of the most abundant and beneficial groups of diurnal migrants, providing multiple ecosystem services and undergoing directed seasonal movements throughout much of the temperate zone. To identify the hoverfly navigational strategy, a flight simulator was used to measure orientation responses of the hoverflies Scaeva pyrastri and Scaeva selenitica to celestial cues during their autumn migration. Hoverflies oriented southwards when they could see the sun and shifted this orientation westward following a 6 h advance of their circadian clocks. Our results demonstrate the use of a time-compensated sun compass as the primary navigational mechanism, consistent with field observations that hoverfly migration occurs predominately under clear and sunny conditions.

Insect inspired vision-based velocity estimation through spatial pooling of optic flow during linear motion

Insects rely on the perception of image motion, or optic flow, to estimate their velocity relative to nearby objects. This information provides important sensory input for avoiding obstacles. However, certain behaviors, such as estimating the absolute distance to a landing target, accurately measuring absolute distance traveled, and estimating the ambient wind speed require decoupling optic flow into its component parts: absolute ground velocity and distance to nearby objects. Behavioral experiments suggest that insects perform these calculations, but their mechanism for doing so remains unknown. Here we present a novel algorithm that combines the geometry of dynamic forward motion with known features of insect visual processing to provide a hypothesis for how insects mightdirectlyestimate absolute ground velocity from a combination of optic flow and acceleration information. Our robotics-inspired-biology approach reveals three critical requirements. First, absolute ground velocity can only be directly estimated from optic flow during times of active acceleration and deceleration. Second, spatial pooling of optic flow across a receptive field helps to alleviate the effects of noise and/or low resolution visual systems. Third, averaging velocity estimates from multiple receptive fields further helps to reject noise. Our algorithm provides a hypothesis for how insects might estimate absolute velocity from vision during active maneuvers, and also provides a theoretical framework for designing fast analog circuitry for efficient state estimation that can be applied to insect-sized robots.

Body size dependent dispersal influences stability in heterogeneous metacommunities

Body size affects key biological processes across the tree of life, with particular importance for food web dynamics and stability. Traits influencing movement capabilities depend strongly on body size, yet the effects of allometrically-structured dispersal on food web stability are less well understood than other demographic processes. Here we study the stability properties of spatially-arranged model food webs in which larger bodied species occupy higher trophic positions, while species’ body sizes also determine the rates at which they traverse spatial networks of heterogeneous habitat patches. Our analysis shows an apparent stabilizing effect of positive dispersal rate scaling with body size compared to negative scaling relationships or uniform dispersal. However, as the global coupling strength among patches increases, the benefits of positive body size-dispersal scaling disappear. A permutational analysis shows that breaking allometric dispersal hierarchies while preserving dispersal rate distributions rarely alters qualitative aspects of metacommunity stability. Taken together, these results suggest that the oft-predicted stabilizing effects of large mobile predators may, for some dimensions of ecological stability, be attributed to increased patch coupling per se, and not necessarily coupling by top trophic levels in particular.

Correlated decision making across multiple phases of olfactory guided search in Drosophila improves search efficiency

Nearly all motile organisms must search for food, often requiring multiple phases of exploration across heterogeneous environments. The fruit fly, Drosophila, has emerged as an effective model system for studying this behavior, however, little is known about the extent to which experiences at one point in their search might influence decisions in another. To investigate whether prior experiences impact flies' search behavior after landing, I tracked individually labelled fruit flies as they explored three odor emitting but food-barren objects. I found two features of their behavior that are correlated with the distance they travel on foot. First, flies walked larger distances when they approached the odor source, which they were almost twice as likely to do when landing on the patch farthest downwind. Computational fluid dynamics simulations suggest this patch may have had a stronger baseline odor, but only ∼15% higher than the other two. This small increase, together with flies' high olfactory sensitivity, suggests that perhaps their flight trajectory used to approach the patches plays a role. Second, flies also walked larger distances when the time elapsed since their last visit was longer. However, the correlation is subtle and subject to a large degree of variability. Using agent-based models, I show that this small correlation can increase search efficiency by 25-50% across many scenarios. Furthermore, my models provide mechanistic hypotheses explaining the variability through either a noisy or straightforward decision-making process. Surprisingly, these stochastic decision-making algorithms enhance search efficiency in challenging but realistic search scenarios compared to deterministic strategies.