A Sublethal Concentration of Sulfoxaflor Has Minimal Impact on Buff-Tailed Bumblebee (Bombus terrestris) Locomotor Behaviour under Aversive Conditioning.

Pesticide exposure has been cited as a key threat to insect pollinators. Notably, a diverse range of potential sublethal effects have been reported in bee species, with a particular focus on effects due to exposure to neonicotinoid insecticides. Here, a purpose-built thermal-visual arena was used in a series of pilot experiments to assess the potential impact of approximate sublethal concentrations of the next generation sulfoximine insecticide sulfoxaflor (5 and 50 ppb) and the neonicotinoid insecticides thiacloprid (500 ppb) and thiamethoxam (10 ppb), on the walking trajectory, navigation and learning abilities of the buff-tailed bumblebee (Bombus terrestris audax) when subjected to an aversive conditioning task. The results suggest that only thiamethoxam prevents forager bees from improving in key training parameters (speed and distanced travelled) within the thermal visual arena. Power law analyses further revealed that a speed-curvature power law, previously reported as being present in the walking trajectories of bumblebees, is potentially disrupted under thiamethoxam (10 ppb) exposure, but not under sulfoxaflor or thiacloprid exposure. The pilot assay described provides a novel tool with which to identify subtle sublethal pesticide impacts, and their potential causes, on forager bees, that current ecotoxicological tests are not designed to assess.

Harmonic radar tracking reveals that honeybee drones navigate between multiple aerial leks.

Male honeybees (drones) are thought to congregate in large numbers in particular "drone congregation areas" to mate. We used harmonic radar to record the flight paths of individual drones and found that drones favored certain locations within the landscape which were stable over two years. Drones often visit multiple potential lekking sites within a single flight and take shared flight paths between them. Flights between such sites are relatively straight and begin as early as the drone's second flight, indicating familiarity with the sites acquired during initial learning flights. Arriving at congregation areas, drones display convoluted, looping flight patterns. We found a correlation between a drone's distance from the center of each area and its acceleration toward the center, a signature of collective behavior leading to congregation in these areas. Our study reveals the behavior of individual drones as they navigate between and within multiple aerial leks.

An equation of state for insect swarms.

Collective behaviour in flocks, crowds, and swarms occurs throughout the biological world. Animal groups are generally assumed to be evolutionarily adapted to robustly achieve particular functions, so there is widespread interest in exploiting collective behaviour for bio-inspired engineering. However, this requires understanding the precise properties and function of groups, which remains a challenge. Here, we demonstrate that collective groups can be described in a thermodynamic framework. We define an appropriate set of state variables and extract an equation of state for laboratory midge swarms. We then drive swarms through "thermodynamic" cycles via external stimuli, and show that our equation of state holds throughout. Our findings demonstrate a new way of precisely quantifying the nature of collective groups and provide a cornerstone for potential future engineering design.

Environmental perturbations induce correlations in midge swarms.

Although collectively behaving animal groups often show large-scale order (such as in bird flocks), they need not always (such as in insect swarms). It has been suggested that the signature of collective behaviour in disordered groups is a residual long-range correlation. However, results in the literature have reported contradictory results as to the presence of long-range correlation in insect swarms, with swarms in the wild displaying correlation but those in a controlled laboratory environment not. We resolve these apparently incompatible results by showing that the external perturbations generically induce the emergence of correlations. We apply a range of different external stimuli to laboratory swarms of the non-biting midge Chironomus riparius, and show that in all cases correlations appear when perturbations are introduced. We confirm the generic nature of these results by showing that they can be reproduced in a stochastic model of swarms. Given that swarms in the wild will always have to contend with environmental stimuli, our results thus harmonize previous findings. These findings emphasize that collective behaviour cannot be understood in isolation without considering its environmental context, and that new research is needed to disentangle the distinct roles of intrinsic dynamics and external stimuli.

Mechanical spectroscopy of insect swarms.

Social animals routinely form groups, which are thought to display emergent, collective behavior. This hypothesis suggests that animal groups should have properties at the group scale that are not directly linked to the individuals, much as bulk materials have properties distinct from those of their constituent atoms. Materials are often probed by measuring their response to controlled perturbations, but these experiments are difficult to conduct on animal groups, particularly in the wild. Here, we show that laboratory midge swarms have emergent continuum mechanical properties, displaying a collective viscoelastic response to applied oscillatory visual stimuli that allows us to extract storage and loss moduli for the swarm. We find that the swarms strongly damp perturbations, both viscously and inertially. Thus, unlike bird flocks, which appear to use collective behavior to promote lossless information flow through the group, our results suggest that midge swarms use it to stabilize themselves against environmental perturbations.

Continuous Radar Tracking Illustrates the Development of Multi-destination Routes of Bumblebees.

Animals that visit multiple foraging sites face a problem, analogous to the Travelling Salesman Problem, of finding an efficient route. We explored bumblebees' route development on an array of five artificial flowers in which minimising travel distances between individual feeders conflicted with minimising overall distance. No previous study of bee spatial navigation has been able to follow animals' movement during learning; we tracked bumblebee foragers continuously, using harmonic radar, and examined the process of route formation in detail for a small number of selected individuals. On our array, bees did not settle on visit sequences that gave the shortest overall path, but prioritised movements to nearby feeders. Nonetheless, flight distance and duration reduced with experience. This increased efficiency was attributable mainly to experienced bees reducing exploration beyond the feeder array and flights becoming straighter with experience, rather than improvements in the sequence of feeder visits. Flight paths of all legs of a flight stabilised at similar rates, whereas the first few feeder visits became fixed early while bees continued to experiment with the order of later visits. Stabilising early sections of a route and prioritising travel between nearby destinations may reduce the search space, allowing rapid adoption of efficient routes.

Characterizing Indeterminate Renal Masses with Molecular Imaging: the Role of 99mTc-MIBI SPECT/CT.

PURPOSE OF REVIEW: The majority of enhancing renal masses cannot be characterized through imaging as malignant or benign; however, such characterization could save patients from unnecessary surgery and/or biopsy and associated morbidity. Herein, we review the recent literature on the emerging use of 99mTc-MIBI SPECT/CT in preoperative differentiation of enhancing renal masses. RECENT FINDINGS: Recent reports have shown that 99mTc-MIBI SPECT/CT imaging can differentiate mitochondrial-rich, benign, or indolent renal masses from renal cell carcinoma. These studies demonstrate good correlation between a positive 99mTc-MIBI SPECT/CT scan and a pathologically proven diagnosis of renal oncocytoma and hybrid oncocytic/chromophobe tumor. In addition, there is excellent correlation between a negative scan and a diagnosis of clear cell subtype of renal cell carcinoma. Preoperative 99mTc-MIBI SPECT/CT offers a non-invasive method for differentiating renal lesions with low aggressiveness from other RCCs, in particular, clear cell renal cell carcinoma.

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.

Optimal search patterns in honeybee orientation flights are robust against emerging infectious diseases.

Lévy flights are scale-free (fractal) search patterns found in a wide range of animals. They can be an advantageous strategy promoting high encounter rates with rare cues that may indicate prey items, mating partners or navigational landmarks. The robustness of this behavioural strategy to ubiquitous threats to animal performance, such as pathogens, remains poorly understood. Using honeybees radar-tracked during their orientation flights in a novel landscape, we assess for the first time how two emerging infectious diseases (Nosema sp. and the Varroa-associated Deformed wing virus (DWV)) affect bees' behavioural performance and search strategy. Nosema infection, unlike DWV, affected the spatial scale of orientation flights, causing significantly shorter and more compact flights. However, in stark contrast to disease-dependent temporal fractals, we find the same prevalence of optimal Lévy flight characteristics (µ ≈ 2) in both healthy and infected bees. We discuss the ecological and evolutionary implications of these surprising insights, arguing that Lévy search patterns are an emergent property of fundamental characteristics of neuronal and sensory components of the decision-making process, making them robust against diverse physiological effects of pathogen infection and possibly other stressors.

Life-Long Radar Tracking of Bumblebees.

Insect pollinators such as bumblebees play a vital role in many ecosystems, so it is important to understand their foraging movements on a landscape scale. We used harmonic radar to record the natural foraging behaviour of Bombus terrestris audax workers over their entire foraging career. Every flight ever made outside the nest by four foragers was recorded. Our data reveal where the bees flew and how their behaviour changed with experience, at an unprecedented level of detail. We identified how each bee's flights fit into two categories-which we named exploration and exploitation flights-examining the differences between the two types of flight and how their occurrence changed over the course of the bees' foraging careers. Exploitation of learned resources takes place during efficient, straight trips, usually to a single foraging location, and is seldom combined with exploration of other areas. Exploration of the landscape typically occurs in the first few flights made by each bee, but our data show that further exploration flights can be made throughout the bee's foraging career. Bees showed striking levels of variation in how they explored their environment, their fidelity to particular patches, ratio of exploration to exploitation, duration and frequency of their foraging bouts. One bee developed a straight route to a forage patch within four flights and followed this route exclusively for six days before abandoning it entirely for a closer location; this second location had not been visited since her first exploratory flight nine days prior. Another bee made only rare exploitation flights and continued to explore widely throughout its life; two other bees showed more frequent switches between exploration and exploitation. Our data shed light on the way bumblebees balance exploration of the environment with exploitation of resources and reveal extreme levels of variation between individuals.

Lévy patterns in seabirds are multifaceted describing both spatial and temporal patterning.

BACKGROUND: The flight patterns of albatrosses and shearwaters have become a touchstone for much of Lévy flight research, spawning an extensive field of enquiry. There is now compelling evidence that the flight patterns of these seabirds would have been appreciated by Paul Lévy, the mathematician after whom Lévy flights are named. Here we show that Lévy patterns (here taken to mean spatial or temporal patterns characterized by distributions with power-law tails) are, in fact, multifaceted in shearwaters being evident in both spatial and temporal patterns of activity. RESULTS: We tested for Lévy patterns in the at-sea behaviours of two species of shearwater breeding in the North Atlantic Ocean (Calonectris borealis) and the Mediterranean sea (C. diomedea) during their incubating and chick-provisioning periods. We found that distributions of flight durations, on/in water durations and inter-dive time-intervals have power-law tails and so bear the hallmarks of Lévy patterns. CONCLUSIONS: The occurrence of these statistical laws is remarkable given that bird behaviours are strongly shaped by an individual's motivational state and by complex environmental interactions. Our observations could take Lévy patterns as models of animal behaviour to a new level by going beyond the characterisation of spatial movements to characterise how different behaviours are interwoven throughout daily animal life.

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.

Airborne Quercus pollen in SW Spain: Identifying favourable conditions for atmospheric transport and potential source areas.

The pollen grains of Quercus spp. (oak trees) are allergenic. This study investigates airborne Quercus pollen in SW Spain with the aim identifying favourable conditions for atmospheric transport and potential sources areas. Two types of Quercus distribution maps were produced. Airborne Quercus pollen concentrations were measured at three sites located in the Extremadura region (SW Spain) for 3 consecutive years. The seasonal occurrence of Quercus pollen in the air was investigated, as well as days with pollen concentrations ≥80Pm(-3). The distance that Quercus pollen can be transported in appreciable numbers was calculated using clusters of back trajectories representing the air mass movement above the source areas (oak woodlands), and by using a state-of-the-art dispersion model. The two main potential sources of Quercus airborne pollen captured in SW Spain are Q. ilex subsp. ballota and Q. suber. The minimum distances between aerobiological stations and Quercus woodlands have been estimated as: 40km (Plasencia), 66km (Don Benito), 62km (Zafra) from the context of this study. Daily mean Quercus pollen concentration can exceed 1,700Pm(-3), levels reached not less than 24 days in a single year. High Quercus pollen concentration were mostly associated with moderate wind speed events (6-10ms(-1)), whereas that a high wind speed (16-20ms(-1)) seems to be associated with low concentrations.

Pelagic seabird flight patterns are consistent with a reliance on olfactory maps for oceanic navigation.

Homing studies have provided tantalizing evidence that the remarkable ability of shearwaters (Procellariiformes) to pinpoint their breeding colony after crossing vast expanses of featureless open ocean can be attributed to their assembling cognitive maps of wind-borne odours but crucially, it has not been tested whether olfactory cues are actually used as a system for navigation. Obtaining statistically important samples of wild birds for use in experimental approaches is, however, impossible because of invasive sensory manipulation. Using an innovative non-invasive approach, we provide strong evidence that shearwaters rely on olfactory cues for oceanic navigation. We tested for compliance with olfactory-cued navigation in the flight patterns of 210 shearwaters of three species (Cory's shearwaters, Calonectris borealis, North Atlantic Ocean, Scopoli's shearwaters, C. diomedea Mediterranean Sea, and Cape Verde shearwaters, C. edwardsii, Central Atlantic Ocean) tagged with high-resolution GPS loggers during both incubation and chick rearing.We found that most (69%) birds displayed exponentially truncated scale-free(Lévy-flight like) displacements, which we show are consistent with olfactory-cued navigation in the presence of atmospheric turbulence. Our analysis provides the strongest evidence yet for cognitive odour map navigation in wild birds. Thus, we may reconcile two highly disputed questions in movement ecology, by mechanistically connecting Lévy displacements and olfactory navigation. Our approach can be applied to any species which can be tracked at sufficient spatial resolution, using a GPS logger.

Evidence for a pervasive 'idling-mode' activity template in flying and pedestrian insects.

Understanding the complex movement patterns of animals in natural environments is a key objective of 'movement ecology'. Complexity results from behavioural responses to external stimuli but can also arise spontaneously in their absence. Drawing on theoretical arguments about decision-making circuitry, we predict that the spontaneous patterns will be scale-free and universal, being independent of taxon and mode of locomotion. To test this hypothesis, we examined the activity patterns of the European honeybee, and multiple species of noctuid moth, tethered to flight mills and exposed to minimal external cues. We also reanalysed pre-existing data for Drosophila flies walking in featureless environments. Across these species, we found evidence of common scale-invariant properties in their movement patterns; pause and movement durations were typically power law distributed over a range of scales and characterized by exponents close to 3/2. Our analyses are suggestive of the presence of a pervasive scale-invariant template for locomotion which, when acted on by environmental cues, produces the movements with characteristic scales observed in nature. Our results indicate that scale-finite complexity as embodied, for instance, in correlated random walk models, may be the result of environmental cues overriding innate behaviour, and that scale-free movements may be intrinsic and not limited to 'blind' foragers as previously thought.

Hierarchical random walks in trace fossils and the origin of optimal search behavior.

Efficient searching is crucial for timely location of food and other resources. Recent studies show that diverse living animals use a theoretically optimal scale-free random search for sparse resources known as a Lévy walk, but little is known of the origins and evolution of foraging behavior and the search strategies of extinct organisms. Here, using simulations of self-avoiding trace fossil trails, we show that randomly introduced strophotaxis (U-turns)--initiated by obstructions such as self-trail avoidance or innate cueing--leads to random looping patterns with clustering across increasing scales that is consistent with the presence of Lévy walks. This predicts that optimal Lévy searches may emerge from simple behaviors observed in fossil trails. We then analyzed fossilized trails of benthic marine organisms by using a novel path analysis technique and find the first evidence, to our knowledge, of Lévy-like search strategies in extinct animals. Our results show that simple search behaviors of extinct animals in heterogeneous environments give rise to hierarchically nested Brownian walk clusters that converge to optimal Lévy patterns. Primary productivity collapse and large-scale food scarcity characterizing mass extinctions evident in the fossil record may have triggered adaptation of optimal Lévy-like searches. The findings suggest that Lévy-like behavior has been used by foragers since at least the Eocene but may have a more ancient origin, which might explain recent widespread observations of such patterns among modern taxa.

Scaling laws of ambush predator 'waiting' behaviour are tuned to a common ecology.

The decisions animals make about how long to wait between activities can determine the success of diverse behaviours such as foraging, group formation or risk avoidance. Remarkably, for diverse animal species, including humans, spontaneous patterns of waiting times show random 'burstiness' that appears scale-invariant across a broad set of scales. However, a general theory linking this phenomenon across the animal kingdom currently lacks an ecological basis. Here, we demonstrate from tracking the activities of 15 sympatric predator species (cephalopods, sharks, skates and teleosts) under natural and controlled conditions that bursty waiting times are an intrinsic spontaneous behaviour well approximated by heavy-tailed (power-law) models over data ranges up to four orders of magnitude. Scaling exponents quantifying ratios of frequent short to rare very long waits are species-specific, being determined by traits such as foraging mode (active versus ambush predation), body size and prey preference. A stochastic-deterministic decision model reproduced the empirical waiting time scaling and species-specific exponents, indicating that apparently complex scaling can emerge from simple decisions. Results indicate temporal power-law scaling is a behavioural 'rule of thumb' that is tuned to species' ecological traits, implying a common pattern may have naturally evolved that optimizes move-wait decisions in less predictable natural environments.

Unravelling the mechanisms of trapline foraging in bees.

Trapline foraging (repeated sequential visits to a series of feeding locations) is a taxonomically widespread but poorly understood behavior. Investigating these routing strategies in the field is particularly difficult, as it requires extensive tracking of animal movements to retrace their complete foraging history. In a recent study, we used harmonic radar and motion-triggered video cameras to track bumblebees foraging between artificial flowers in a large open field. We describe how all bees gradually developed a near optimal trapline to link all flowers and have identified a simple learning heuristic capable of replicating this optimisation behavior. Our results provide new perspectives to clarify the sequence of decisions made by pollinating insects during trapline foraging, and explore how spatial memory is organized in their small brains.   "I have always regretted that I did not mark the bees by attaching bits of cotton wool or eiderdown to them with rubber, because this would have made it much easier to follow their paths." Charles Darwin(1.)

A simple iterative model accurately captures complex trapline formation by bumblebees across spatial scales and flower arrangements.

Pollinating bees develop foraging circuits (traplines) to visit multiple flowers in a manner that minimizes overall travel distance, a task analogous to the travelling salesman problem. We report on an in-depth exploration of an iterative improvement heuristic model of bumblebee traplining previously found to accurately replicate the establishment of stable routes by bees between flowers distributed over several hectares. The critical test for a model is its predictive power for empirical data for which the model has not been specifically developed, and here the model is shown to be consistent with observations from different research groups made at several spatial scales and using multiple configurations of flowers. We refine the model to account for the spatial search strategy of bees exploring their environment, and test several previously unexplored predictions. We find that the model predicts accurately 1) the increasing propensity of bees to optimize their foraging routes with increasing spatial scale; 2) that bees cannot establish stable optimal traplines for all spatial configurations of rewarding flowers; 3) the observed trade-off between travel distance and prioritization of high-reward sites (with a slight modification of the model); 4) the temporal pattern with which bees acquire approximate solutions to travelling salesman-like problems over several dozen foraging bouts; 5) the instability of visitation schedules in some spatial configurations of flowers; 6) the observation that in some flower arrays, bees' visitation schedules are highly individually different; 7) the searching behaviour that leads to efficient location of flowers and routes between them. Our model constitutes a robust theoretical platform to generate novel hypotheses and refine our understanding about how small-brained insects develop a representation of space and use it to navigate in complex and dynamic environments.

Radar tracking and motion-sensitive cameras on flowers reveal the development of pollinator multi-destination routes over large spatial scales.

Central place foragers, such as pollinating bees, typically develop circuits (traplines) to visit multiple foraging sites in a manner that minimizes overall travel distance. Despite being taxonomically widespread, these routing behaviours remain poorly understood due to the difficulty of tracking the foraging history of animals in the wild. Here we examine how bumblebees (Bombus terrestris) develop and optimise traplines over large spatial scales by setting up an array of five artificial flowers arranged in a regular pentagon (50 m side length) and fitted with motion-sensitive video cameras to determine the sequence of visitation. Stable traplines that linked together all the flowers in an optimal sequence were typically established after a bee made 26 foraging bouts, during which time only about 20 of the 120 possible routes were tried. Radar tracking of selected flights revealed a dramatic decrease by 80% (ca. 1500 m) of the total travel distance between the first and the last foraging bout. When a flower was removed and replaced by a more distant one, bees engaged in localised search flights, a strategy that can facilitate the discovery of a new flower and its integration into a novel optimal trapline. Based on these observations, we developed and tested an iterative improvement heuristic to capture how bees could learn and refine their routes each time a shorter route is found. Our findings suggest that complex dynamic routing problems can be solved by small-brained animals using simple learning heuristics, without the need for a cognitive map.