Emergent dynamics of laboratory insect swarms

Phase Coexistence in Insect Swarms

Animal aggregations are visually striking, and as such are popular examples of collective behavior in the natural world. Quantitatively demonstrating the collective nature of such groups, however, remains surprisingly difficult. Inspired by thermodynamics, we applied topological data analysis to laboratory insect swarms and found evidence for emergent, material-like states. We show that the swarms consist of a core "condensed" phase surrounded by a dilute "vapor" phase. These two phases coexist in equilibrium, and maintain their distinct macroscopic properties even though individual insects pass freely between them. We further define a pressure and chemical potential to describe these phases, extending theories of active matter to aggregations of macroscopic animals and laying the groundwork for a thermodynamic description of collective animal groups.

Stable swarming using adaptive long-range interactions

Sensory mechanisms in biology, from cells to humans, have the property of adaptivity, whereby the response produced by the sensor is adapted to the overall amplitude of the signal, reducing the sensitivity in the presence of strong stimulus, while increasing it when it is weak. This property is inherently energy consuming and a manifestation of the nonequilibrium nature of living organisms. We explore here how adaptivity affects the effective forces that organisms feel due to others in the context of a uniform swarm, in both two and three dimensions. The interactions between the individuals are taken to be attractive and long-range and of power-law form. We find that the effects of adaptivity inside the swarm are dramatic, where the effective forces decrease (or remain constant) with increasing swarm density. Linear stability analysis demonstrates how this property prevents collapse (Jeans instability), when the forces are adaptive. Adaptivity therefore endows swarms with a natural mechanism for self-stabilization.

Are midge swarms bound together by an effective velocity-dependent gravity?

Midge swarms are a canonical example of collective animal behaviour where local interactions do not clearly play a major role and yet the animals display group-level cohesion. The midges appear somewhat paradoxically to be tightly bound to the swarm whilst at the same time weakly coupled inside it. The microscopic origins of this behaviour have remained elusive. Models based on Newtonian gravity do, however, agree well with experimental observations of laboratory swarms. They are biologically plausible since gravitational interactions have similitude with long-range acoustic and visual interactions, and they correctly predict that individual attraction to the swarm centre increases linearly with distance from the swarm centre. Here we show that the observed kinematics implies that this attraction also increases with an individual's flight speed. We find clear evidence for such an attractive force in experimental data.

Quantitative analysis of harmonic convergence in mosquito auditory interactions

This article analyses the hearing and behaviour of mosquitoes in the context of inter-individual acoustic interactions. The acoustic interactions of tethered live pairs of Aedes aegypti mosquitoes, from same and opposite sex mosquitoes of the species, are recorded on independent and unique audio channels, together with the response of tethered individual mosquitoes to playbacks of pre-recorded flight tones of lone or paired individuals. A time-dependent representation of each mosquito's non-stationary wing beat frequency signature is constructed, based on Hilbert spectral analysis. A range of algorithmic tools is developed to automatically analyse these data, and used to perform a robust quantitative identification of the ‘harmonic convergence’ phenomenon. The results suggest that harmonic convergence is an active phenomenon, which does not occur by chance. It occurs for live pairs, as well as for lone individuals responding to playback recordings, whether from the same or opposite sex. Male–female behaviour is dominated by frequency convergence at a wider range of harmonic combinations than previously reported, and requires participation from both partners in the duet. New evidence is found to show that male–male interactions are more varied than strict frequency avoidance. Rather, they can be divided into two groups: convergent pairs, typified by tightly bound wing beat frequencies, and divergent pairs, that remain widely spaced in the frequency domain. Overall, the results reveal that mosquito acoustic interaction is a delicate and intricate time-dependent active process that involves both individuals, takes place at many different frequencies, and which merits further enquiry.

Symmetry-breaking phase transitions in highly concentrated semen

New experimental evidence of self-motion of a confined active suspension is presented. Depositing fresh semen sample in an annular shaped microfluidic chip leads to a spontaneous vortex state of the fluid at sufficiently large sperm concentration. The rotation occurs unpredictably clockwise or counterclockwise and is robust and stable. Furthermore, for highly active and concentrated semen, richer dynamics can occur such as self-sustained or damped rotation oscillations. Experimental results obtained with systematic dilution provide a clear evidence of a phase transition towards collective motion associated with local alignment of spermatozoa akin to the Vicsek model. A macroscopic theory based on previously derived self-organized hydrodynamics models is adapted to this context and provides predictions consistent with the observed stationary motion.

Self-organized sorting limits behavioral variability in swarms

Swarming is a phenomenon where collective motion arises from simple local interactions between typically identical individuals. Here, we investigate the effects of variability in behavior among the agents in finite swarms with both alignment and cohesive interactions. We show that swarming is abolished above a critical fraction of non-aligners who do not participate in alignment. In certain regimes, however, swarms above the critical threshold can dynamically reorganize and sort out excess non-aligners to maintain the average fraction close to the critical value. This persists even in swarms with a distribution of alignment interactions, suggesting a simple, robust and efficient mechanism that allows heterogeneously mixed populations to naturally regulate their composition and remain in a collective swarming state or even differentiate among behavioral phenotypes. We show that, for evolving swarms, this self-organized sorting behavior can couple to the evolutionary dynamics leading to new evolutionarily stable equilibrium populations set by the physical swarm parameters.

Swarm dynamics may give rise to Lévy flights

“Continuous-time correlated random walks” are now gaining traction as models of scale-finite animal movement patterns because they overcome inherent shortcomings with the prevailing paradigm - discrete random walk models. Continuous-time correlated random walk models are founded on the classic Langevin equation that is driven by purely additive noise. The Langevin equation is, however, changed fundamentally by the smallest of multiplicative noises. The inclusion of such noises gives rise to Lévy flights, a popular but controversial model of scale-free movement patterns. Multiplicative noises have not featured prominently in the literature on biological Lévy flights, being seen, perhaps, as no more than a mathematical contrivance. Here we show how Langevin equations driven by multiplicative noises and incumbent Lévy flights arise naturally in the modelling of swarms. Model predictions find some support in three-dimensional, time-resolved measurements of the positions of individual insects in laboratory swarms of the midge Chironomus riparius. We hereby provide a new window on Lévy flights as models of movement pattern data, linking patterns to generative processes.

The second will be first: competition on directed networks

Multiple sinks competition is investigated for a walker diffusing on directed complex networks. The asymmetry of the imposed spatial support makes the system non transitive. As a consequence, it is always possible to identify a suitable location for the second absorbing sink that screens at most the flux of agents directed against the first trap, whose position has been preliminarily assigned. The degree of mutual competition between pairs of nodes is analytically quantified through apt indicators that build on the topological characteristics of the hosting graph. Moreover, the positioning of the second trap can be chosen so as to minimize, at the same time, the probability of being in turn shaded by a thirdly added trap. Supervised placing of absorbing traps on a asymmetric disordered and complex graph is hence possible, as follows a robust optimization protocol. This latter is here discussed and successfully tested against synthetic data.

Simulating Flying Insects Using Dynamics and Data-Driven Noise Modeling to Generate Diverse Collective Behaviors

We present a biologically plausible dynamics model to simulate swarms of flying insects. Our formulation, which is based on biological conclusions and experimental observations, is designed to simulate large insect swarms of varying densities. We use a force-based model that captures different interactions between the insects and the environment and computes collision-free trajectories for each individual insect. Furthermore, we model the noise as a constructive force at the collective level and present a technique to generate noise-induced insect movements in a large swarm that are similar to those observed in real-world trajectories. We use a data-driven formulation that is based on pre-recorded insect trajectories. We also present a novel evaluation metric and a statistical validation approach that takes into account various characteristics of insect motions. In practice, the combination of Curl noise function with our dynamics model is used to generate realistic swarm simulations and emergent behaviors. We highlight its performance for simulating large flying swarms of midges, fruit fly, locusts and moths and demonstrate many collective behaviors, including aggregation, migration, phase transition, and escape responses.

Lipid nanocapsules for behavioural testing in aquatic toxicology: Time-response of Eurytemora affinis to environmental concentrations of PAHs and PCB

The increasing interest for behavioural investigations in aquatic toxicology has heightened the need for developing tools that allow realistic exposure conditions and provide robust quantitative data. Calanoid copepods dominate the zooplankton community in marine and brackish environments. These small organisms have emerged as attractive models because of the sensitivity of their behaviour to important environmental parameters and the significance of self-induced motion in their ecology. Estuarine copepods are particularly relevant in this context because of their incessant exposure to high levels of pollution. We used lipid nanocapsules to deliver sub-lethal concentrations of PAHs (pyrene, phenanthrene and fluoranthene) and PCB 153 into the digestive track of males and females Eurytemora affinis. This novel approach enabled us to achieve both contact and trophic exposure without using phytoplankton, and to expose copepods to small hydrophobic molecules without using organic solvent. We reconstructed the motion of many copepods swimming simultaneously by means of three-dimensional particle tracking velocimetry. We quantified the combined effects of contact and trophic toxicity by comparing the kinematic and diffusive properties of their motion immediately and after 3h and 24h of exposure. Despite the lack of toxicity of their excipients, both empty and loaded capsules increased swimming activity and velocity immediately after exposure. Laser microscopy imaging shows adhesion of nanocapsules on the exoskeleton of the animals, suggesting contact toxicity. The behavioural response resembles an escape reaction allowing copepods to escape stressful conditions. The contact toxicity of empty capsules and pollutants appeared to be additive and nanocapsules loaded with PCB caused the greatest effects. We observed a progressive accumulation of capsules in the digestive track of the animals after 3h and 24h of exposure, which suggests an increasing contribution of systemic toxicity. Nanocapsules filled with PAHs caused a smaller response compared to empty capsules, which we attribute to the narcotic properties of these toxicants. The sharp decrease in velocity after 24h of exposure to capsules loaded with PCB suggests physiological incapacitation following systemic toxicity. Clear differences are visible between genders in their response to empty and loaded capsules, for all exposure durations. Females appear to be less sensitive than males, suggesting different tolerance to stress conditions. Our results confirm the feasibility of using lipid nanocapsules to identify pollutant-induced behavioural alteration in the plankton. They also add new insights into the contact and systemic toxicity of common pollutants. We expect that our results will assist and evoke further research to develop suitable nanocarrier systems for behavioural testing.

Characterization of intermittency in zooplankton behaviour in turbulence

We consider Lagrangian velocity differences of zooplankters swimming in still water and in turbulence. Using cumulants, we quantify the intermittency properties of their motion recorded using three-dimensional particle tracking velocimetry. Copepods swimming in still water display an intermittent behaviour characterized by a high probability of small velocity increments, and by stretched exponential tails. Low values arise from their steady cruising behaviour while heavy tails result from frequent relocation jumps. In turbulence, we show that at short time scales, the intermittency signature of active copepods clearly differs from that of the underlying flow, and reflects the frequent relocation jumps displayed by these small animals. Despite these differences, we show that copepods swimming in still and turbulent flow belong to the same intermittency class that can be modelled by a log-stable model with non-analytical cumulant generating function. Intermittency in swimming behaviour and relocation jumps may enable copepods to display oriented, collective motion under strong hydrodynamic conditions and thus, may contribute to the formation of zooplankton patches in energetic environments.

Intrinsic fluctuations and driven response of insect swarms

Animals of all sizes form groups, as acting together can convey advantages over acting alone; thus, collective animal behavior has been identified as a promising template for designing engineered systems. However, models and observations have focused predominantly on characterizing the overall group morphology, and often focus on highly ordered groups such as bird flocks. We instead study a disorganized aggregation (an insect mating swarm), and compare its natural fluctuations with the group-level response to an external stimulus. We quantify the swarm's frequency-dependent linear response and its spectrum of intrinsic fluctuations, and show that the ratio of these two quantities has a simple scaling with frequency. Our results provide a new way of comparing models of collective behavior with experimental data.

Estimating Orientation of Flying Fruit Flies

The recently growing interest in studying flight behaviours of fruit flies, Drosophila melanogaster, has highlighted the need for developing tools that acquire quantitative motion data. Despite recent advance of video tracking systems, acquiring a flying fly’s orientation remains a challenge for these tools. In this paper, we present a novel method for estimating individual flying fly’s orientation using image cues. Thanks to the line reconstruction algorithm in computer vision field, this work can thereby focus on the practical detail of implementation and evaluation of the orientation estimation algorithm. The orientation estimation algorithm can be incorporated into tracking algorithms. We rigorously evaluated the effectiveness and accuracy of the proposed algorithm by running experiments both on simulation data and on real-world data. This work complements methods for studying the fruit fly’s flight behaviours in a three-dimensional environment.

Intermittent Lagrangian velocities and accelerations in three-dimensional porous medium flow

Intermittency of Lagrangian velocity and acceleration is a key to understanding transport in complex systems ranging from fluid turbulence to flow in porous media. High-resolution optical particle tracking in a three-dimensional (3D) porous medium provides detailed 3D information on Lagrangian velocities and accelerations. We find sharp transitions close to pore throats, and low flow variability in the pore bodies, which gives rise to stretched exponential Lagrangian velocity and acceleration distributions characterized by a sharp peak at low velocity, superlinear evolution of particle dispersion, and double-peak behavior in the propagators. The velocity distribution is quantified in terms of pore geometry and flow connectivity, which forms the basis for a continuous-time random-walk model that sheds light on the observed Lagrangian flow and transport behaviors.

A Novel Method for Tracking Individuals of Fruit Fly Swarms Flying in a Laboratory Flight Arena

The growing interest in studying social behaviours of swarming fruit flies, Drosophila melanogaster, has heightened the need for developing tools that provide quantitative motion data. To achieve such a goal, multi-camera three-dimensional tracking technology is the key experimental gateway. We have developed a novel tracking system for tracking hundreds of fruit flies flying in a confined cubic flight arena. In addition to the proposed tracking algorithm, this work offers additional contributions in three aspects: body detection, orientation estimation, and data validation. To demonstrate the opportunities that the proposed system offers for generating high-throughput quantitative motion data, we conducted experiments on five experimental configurations. We also performed quantitative analysis on the kinematics and the spatial structure and the motion patterns of fruit fly swarms. We found that there exists an asymptotic distance between fruit flies in swarms as the population density increases. Further, we discovered the evidence for repulsive response when the distance between fruit flies approached the asymptotic distance. Overall, the proposed tracking system presents a powerful method for studying flight behaviours of fruit flies in a three-dimensional environment.

Finite-size scaling as a way to probe near-criticality in natural swarms

Collective behavior in biological systems is often accompanied by strong correlations. The question has therefore arisen of whether correlation is amplified by the vicinity to some critical point in the parameters space. Biological systems, though, are typically quite far from the thermodynamic limit, so that the value of the control parameter at which correlation and susceptibility peak depend on size. Hence, a system would need to readjust its control parameter according to its size in order to be maximally correlated. This readjustment, though, has never been observed experimentally. By gathering three-dimensional data on swarms of midges in the field we find that swarms tune their control parameter and size so as to maintain a scaling behavior of the correlation function. As a consequence, correlation length and susceptibility scale with the system's size and swarms exhibit a near-maximal degree of correlation at all sizes.

Determining asymptotically large population sizes in insect swarms

Social animals commonly form aggregates that exhibit emergent collective behaviour, with group dynamics that are distinct from the behaviour of individuals. Simple models can qualitatively reproduce such behaviour, but only with large numbers of individuals. But how rapidly do the collective properties of animal aggregations in nature emerge with group size? Here, we study swarms of Chironomus riparius midges and measure how their statistical properties change as a function of the number of participating individuals. Once the swarms contain order 10 individuals, we find that all statistics saturate and the swarms enter an asymptotic regime. The influence of environmental cues on the swarm morphology decays on a similar scale. Our results provide a strong constraint on how rapidly swarm models must produce collective states. But our findings support the feasibility of using swarms as a design template for multi-agent systems, because self-organized states are possible even with few agents.

Male motion coordination in anopheline mating swarms

The Anopheles gambiae species complex comprises the primary vectors of malaria in much of sub-Saharan Africa. Most of the mating in these species occurs in swarms composed almost entirely of males. Intermittent, organized patterns in such swarms have been observed, but a detailed description of male-male interactions has not previously been available. We identify frequent, time-varying interactions characterized by periods of parallel flight in data from 8 swarms of Anopheles gambiae and 3 swarms of Anopheles coluzzii filmed in 2010 and 2011 in the village of Donéguébogou, Mali. We use the cross correlation of flight direction to quantify these interactions and to induce interaction graphs, which show that males form synchronized subgroups whose size and membership change rapidly. A swarming model with damped springs between each male and the swarm centroid shows good agreement with the correlation data, provided that local interactions represented by damping of relative velocity between males are included.

Consequences of animal interactions on their dynamics: emergence of home ranges and territoriality

Animal spacing has important implications for population abundance, species demography and the environment. Mechanisms underlying spatial segregation have their roots in the characteristics of the animals, their mutual interaction and their response, collective as well as individual, to environmental variables. This review describes how the combination of these factors shapes the patterns we observe and presents a practical, usable framework for the analysis of movement data in confined spaces. The basis of the framework is the theory of interacting random walks and the mathematical description of out-of-equilibrium systems. Although our focus is on modelling and interpreting animal home ranges and territories in vertebrates, we believe further studies on invertebrates may also help to answer questions and resolve unanswered puzzles that are still inaccessible to experimental investigation in vertebrate species.

Collective behaviour without collective order in wild swarms of midges

Collective behaviour is a widespread phenomenon in biology, cutting through a huge span of scales, from cell colonies up to bird flocks and fish schools. The most prominent trait of collective behaviour is the emergence of global order: individuals synchronize their states, giving the stunning impression that the group behaves as one. In many biological systems, though, it is unclear whether global order is present. A paradigmatic case is that of insect swarms, whose erratic movements seem to suggest that group formation is a mere epiphenomenon of the independent interaction of each individual with an external landmark. In these cases, whether or not the group behaves truly collectively is debated. Here, we experimentally study swarms of midges in the field and measure how much the change of direction of one midge affects that of other individuals. We discover that, despite the lack of collective order, swarms display very strong correlations, totally incompatible with models of non-interacting particles. We find that correlation increases sharply with the swarm's density, indicating that the interaction between midges is based on a metric perception mechanism. By means of numerical simulations we demonstrate that such growing correlation is typical of a system close to an ordering transition. Our findings suggest that correlation, rather than order, is the true hallmark of collective behaviour in biological systems.

Our perception of collective behaviour in biological systems is closely associated to the emergence of order on a group scale. For example, birds within a flock align their directions of motion, giving the stunning impression that the group is just one organism. Large swarms of midges, mosquitoes and flies, however, look quite chaotic and do not exhibit any group ordering. It is therefore unclear whether these systems are true instances of collective behaviour. Here we perform the three dimensional tracking of large swarms of midges in the field and find that swarms display strong collective behaviour despite the absence of collective order. In fact, we discover that the capability of swarms to collectively respond to perturbations is surprisingly large, comparable to that of highly ordered groups of vertebrates.

Searching for effective forces in laboratory insect swarms

Collective animal behaviour is often modeled by systems of agents that interact via effective social forces, including short-range repulsion and long-range attraction. We search for evidence of such effective forces by studying laboratory swarms of the flying midge Chironomus riparius. Using multi-camera stereoimaging and particle-tracking techniques, we record three-dimensional trajectories for all the individuals in the swarm. Acceleration measurements show a clear short-range repulsion, which we confirm by considering the spatial statistics of the midges, but no conclusive long-range interactions. Measurements of the mean free path of the insects also suggest that individuals are on average very weakly coupled, but that they are also tightly bound to the swarm itself. Our results therefore suggest that some attractive interaction maintains cohesion of the swarms, but that this interaction is not as simple as an attraction to nearest neighbours.

Evidence of a robust universality class in the critical behavior of self-propelled agents: metric versus topological interactions

The nature of the interactions among self-propelled agents (SPA), i.e., topological versus metric or a combination of both types, is a relevant open question in the field of self-organization phenomena. We studied the critical behavior of a Vicsek-like system of SPA given by a group of agents moving at constant speed and interacting among themselves under the action of a topological rule: each agent aligns itself with the average direction of its seven nearest neighbors, independent of the distance, under the influence of some noise. Based on both stationary and dynamic measurements, we provide strong evidence that both types of interactions are manifestations of the same phenomenon, which defines a robust universality class. Also, the cluster size distribution evaluated at the critical point shows a power-law behavior, and the exponent corresponding to the topological model is in excellent agreement with that of the metric one, further reinforcing our claim. Furthermore, we found that with topological interactions the average distance of influence between agents undergoes large fluctuations that diverge at the critical noise, thus providing clues about a mechanism that could be implemented by the agents to change their moving strategy.