Ka S. Lim

Radar Tracking and Motion-Sensitive Cameras on Flowers Reveal the Development of Pollinator Multi-Destination Routes over Large Spatial Scales

Automated tracking of bumblebees and computer simulations reveal how bees locate a series of flowers and optimize their routes to visit them all.

So Near and Yet So Far: Harmonic Radar Reveals Reduced Homing Ability of Nosema Infected Honeybees

Pathogens may gain a fitness advantage through manipulation of the behaviour of their hosts. Likewise, host behavioural changes can be a defence mechanism, counteracting the impact of pathogens on host fitness. We apply harmonic radar technology to characterize the impact of an emerging pathogen - Nosema ceranae (Microsporidia) - on honeybee (Apis mellifera) flight and orientation performance in the field. Honeybees are the most important commercial pollinators. Emerging diseases have been proposed to play a prominent role in colony decline, partly through sub-lethal behavioural manipulation of their hosts. We found that homing success was significantly reduced in diseased (65.8%) versus healthy foragers (92.5%). Although lost bees had significantly reduced continuous flight times and prolonged resting times, other flight characteristics and navigational abilities showed no significant difference between infected and non-infected bees. Our results suggest that infected bees express normal flight characteristics but are constrained in their homing ability, potentially compromising the colony by reducing its resource inputs, but also counteracting the intra-colony spread of infection. We provide the first high-resolution analysis of sub-lethal effects of an emerging disease on insect flight behaviour. The potential causes and the implications for both host and parasite are discussed.

Mass seasonal bioflows of high-flying insect migrants

Mass movement of “invisibles” We know a lot about vertebrate migrations globally. However, the majority of animals that live on this planet are invertebrates, and we know very little about their movements. Hu et al. monitored the migration of large and small insects over the southern United Kingdom for a decade. They found that more than a trillion insects move across this region annually. The movement of such a large biomass has considerable impacts on the ecosystems between which the insects migrate. Science, this issue p. 1584 Long-term measurements above the United Kingdom reveal that trillions of insects migrate above our heads annually. Migrating animals have an impact on ecosystems directly via influxes of predators, prey, and competitors and indirectly by vectoring nutrients, energy, and pathogens. Although linkages between vertebrate movements and ecosystem processes have been established, the effects of mass insect “bioflows” have not been described. We quantified biomass flux over the southern United Kingdom for high-flying (>150 meters) insects and show that ~3.5 trillion insects (3200 tons of biomass) migrate above the region annually. These flows are not randomly directed in insects larger than 10 milligrams, which exploit seasonally beneficial tailwinds. Large seasonal differences in the southward versus northward transfer of biomass occur in some years, although flows were balanced over the 10-year period. Our long-term study reveals a major transport process with implications for ecosystem services, processes, and biogeochemistry.

The Ontogeny of Bumblebee Flight Trajectories: From Naive Explorers to Experienced Foragers

Understanding strategies used by animals to explore their landscape is essential to predict how they exploit patchy resources, and consequently how they are likely to respond to changes in resource distribution. Social bees provide a good model for this and, whilst there are published descriptions of their behaviour on initial learning flights close to the colony, it is still unclear how bees find floral resources over hundreds of metres and how these flights become directed foraging trips. We investigated the spatial ecology of exploration by radar tracking bumblebees, and comparing the flight trajectories of bees with differing experience. The bees left the colony within a day or two of eclosion and flew in complex loops of ever-increasing size around the colony, exhibiting Lévy-flight characteristics constituting an optimal searching strategy. This mathematical pattern can be used to predict how animals exploring individually might exploit a patchy landscape. The bees’ groundspeed, maximum displacement from the nest and total distance travelled on a trip increased significantly with experience. More experienced bees flew direct paths, predominantly flying upwind on their outward trips although forage was available in all directions. The flights differed from those of naïve honeybees: they occurred at an earlier age, showed more complex looping, and resulted in earlier returns of pollen to the colony. In summary bumblebees learn to find home and food rapidly, though phases of orientation, learning and searching were not easily separable, suggesting some multi-tasking.

Detection of flow direction in high-flying insect and songbird migrants

Goal-oriented migrants travelling through the sea or air must cope with the effect of cross-flows during their journeys if they are to reach their destination. In order to counteract flow-induced drift from their preferred course, migrants must detect the mean flow direction, and integrate this information with output from their internal compass, to compensate for the deflection. Animals can potentially sense flow direction by two nonexclusive mechanisms: either indirectly, by visually assessing the effect of the current on their movement direction relative to the ground; or directly, via intrinsic properties of the current. Here, we report the first evidence that nocturnal compass-guided insect migrants use a turbulence-mediated mechanism for directly assessing the wind direction hundreds of metres above the ground. By comparison, we find that nocturnally-migrating songbirds do not use turbulence to detect the flow; instead they rely on visual assessment of wind-induced drift to indirectly infer the flow direction.

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 Darwin1

Image Processing in Polarimetric SAR Images Using a Hybrid Entropy Decomposition and Maximum Likelihood (EDML)

This paper presents a hybrid entropy decomposition and maximum likelihood (EDML) for synthetic aperture radar (SAR) image analysis and classification with the application of land use management. Entropy decomposition is an effective technique to obtain valuable decomposed parameters for image interpretation with analysis of the underlying scattering mechanisms. However, the main disadvantage of entropy decomposition is that the decision boundaries of the analysis plane are arbitrary. To overcome this problem, maximum likelihood technique is taken into consideration to help to determine the decision boundaries based upon Gaussian probability model. Hence, the hybrid EDML is developed to provide alternative way to improve the classification accuracy. The objective of this paper is to assess the use of polarimetric data for the image analysis and classification of land use management. It is illustrated using a well-known polarimetric AIRSAR data of San Francisco. In this paper, EDML technique is shown to have a superior result compared to other techniques.

Genomewide transcriptional signatures of migratory flight activity in a globally invasive insect pest.

Migration is a key life history strategy for many animals and requires a suite of behavioural, morphological and physiological adaptations which together form the ‘migratory syndrome’. Genetic variation has been demonstrated for many traits that make up this syndrome, but the underlying genes involved remain elusive. Recent studies investigating migration‐associated genes have focussed on sampling migratory and nonmigratory populations from different geographic locations but have seldom explored phenotypic variation in a migratory trait. Here, we use a novel combination of tethered flight and next‐generation sequencing to determine transcriptomic differences associated with flight activity in a globally invasive moth pest, the cotton bollworm Helicoverpa armigera. By developing a state‐of‐the‐art phenotyping platform, we show that field‐collected H. armigera display continuous variation in flight performance with individuals capable of flying up to 40 km during a single night. Comparative transcriptomics of flight phenotypes drove a gene expression analysis to reveal a suite of expressed candidate genes which are clearly related to physiological adaptations required for long‐distance flight. These include genes important to the mobilization of lipids as flight fuel, the development of flight muscle structure and the regulation of hormones that influence migratory physiology. We conclude that the ability to express this complex set of pathways underlines the remarkable flexibility of facultative insect migrants to respond to deteriorating conditions in the form of migratory flight and, more broadly, the results provide novel insights into the fundamental transcriptional changes required for migration in insects and other taxa.

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.

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.