Automated monitoring reveals extreme interindividual variation and plasticity in honeybee foraging activity levels

Honey Bees Can Use Sequence Learning to Predict Rewards from a Prior Unrewarded Visual Stimulus

Learning to anticipate upcoming events can increase fitness by allowing animals to choose the best course of action, and many species can learn sequences of events and anticipate rewards. To date, most studies have focused on sequences over short time scales such as a few seconds. Whereas events separated by a few seconds are easily learned, events separated by longer delays are typically more difficult to learn. Here, we show that honey bees (Apis mellifera) can learn a sequence of two visually distinct food sources alternating in profitability every few minutes. Bees were challenged to learn that the rewarded pattern was the one that was non-rewarded on the prior visit. We show that bees can predict and choose the feeder that will be rewarding upon their next approach more frequently than predicted by chance, and they improve with experience, with 64% correct choices made in the second half of their visit sequence (N = 320 visits by 20 different bees). These results increase our understanding of honey bee visual sequential learning and further demonstrate the flexibility of foragers' learning strategies.

A quantitative Apis mellifera hazard and risk assessment model (AMHRA) illustrated with the insecticide sulfoxaflor: sulfoxaflor environmental science review part VI

In this paper, conceptual models of the exposure pathways outside the hive and the in-hive distribution of pesticide residues brought to the honeybee hive are presented. The conceptual model is based on the natural life history, behavior and diet of individual honeybees (Apis mellifera). Receptor groups of bees with similar diets and potential exposure are defined. From the conceptual model, a quantitative A. mellifera hazard and risk assessment model (AMHRA) is developed and illustrated using sulfoxaflor (SFX) as a case study. The model estimates the exposure of the receptor groups of honeybees within a colony via various routes of exposure. The user selects a deterministic mode to obtain hazard quotients (HQ) or a probabilistic mode to obtain risk quotients (RQ). The model was run in the deterministic mode using the pesticide concentrations in nectar and pollen from a field experiment in which SFX was applied to cotton crops at the highest permitted application rate of 101 g a.i. ha-1. Acute and chronic exposure HQ values were calculated for the adult and larval receptor groups. The results showed that the SFX applied at the highest single application rate following the label directions was not hazardous to honeybees. The probabilistic mode was described but not run.

Weight of evidence assessment from field studies on effects of the insecticide sulfoxaflor on hymenopteran pollinators: sulfoxaflor environmental science review part V

Field studies involve combinations of exposure, natural dynamics, and effects in natural and agricultural environments. To be more realistic, field studies focussed on pollinating insects must consider the details of biology, life history, behavior, and pollination ecology of the test species. While expensive and time-consuming, these tests provide the most realistic information, especially for social insects, but are valuable for solitary bee species as well. They are more realistic than laboratory studies because they determine the combined effects of natural stressors including weather, food availability, parasites, and pathogens with anthropogenic stressors, such as the pesticide treatment itself, within agroecosystem landscapes. Twenty-four field studies conducted with bees to support the registration of sulfoxaflor and published work are included, and a standardized rating system for the quality and relevance of the studies was used. The studies included Apis mellifera L., Bombus terrestris L., and Osmia bicornis L. The results show that, when SFX products are applied at the highest labeled application rate with bees actively foraging or fed in syrup at equivalent rates, the effects are minor and temporary. Sublethal effects included lethargy, disorientation, and reduced body mass at emergence. No new modes of action and no treatment-related effects on brood rearing were found.

Specialism and generalism in social animals in variable environments

An important advantage to sociality is division of labour, which is often associated with specialization of group members, such as the polymorphic subcastes of ant workers. Given this advantage, it is puzzling that many social groups do not show clear specialization. Among ants, workers of closely related species have one, two or even three polymorphisms. The degree of specialism of asocial animals depends on environmental variability because specialists will perform poorly in some conditions. Here, we use a numeric model to consider whether the magnitude and type of environmental variability can help to explain the diversity of specialism in cooperative groups. By finding the optimal distribution of group members along a single dimension of specialization for two tasks, we predict when groups should be composed of specialists, generalists, both of these (trimodal) or moderate specialists. Generalism is predicted more when environments are unstable and when task importance-rather than demand-varies but depends on the likelihood that the group can complete all tasks in the range of experienced conditions. The benefit of sociality is strongest in invariable environments and there is selection for redundancy in the workforce, which may explain the widely observed inactivity in social insects.This article is part of the theme issue 'Division of labour as key driver of social evolution'.

Sexually differentiated decision-making involves faster recruitment in the early stages for the Tibetan antelopes Pantholops hodgsonii

Group living is widespread across diverse taxa, and the mechanisms underlying collective decision-making in contexts of variable role division are critical for understanding the dynamics of group stability. While studies on collective behavior in small animals such as fish and insects are well-established, similar research on large wild animals remains challenging due to the limited availability of sufficient and systematic field data. Here, we aimed to explore the collective decision-making pattern and its sexual difference for the dimorphic Tibetan antelopes Pantholops hodgsonii (chiru) in Xizang Autonomous Region, China, by analyzing individual leadership distribution, as well as the joining process, considering factors such as calving stages and joining ranks. The distinct correlations of decision participants' ratio with group size and decision duration underscore the trade-off between accuracy and speed in decision-making. Male antelopes display a more democratic decision-making pattern, while females exhibit more prompt responses after calving at an early stage. This study uncovers a partially shared decision-making strategy among Tibetan antelopes, suggesting flexible self-organization in group decision processes aligned with animal life cycle progression.

Integrating computer vision and molecular neurobiology to bridge the gap between behavior and the brain

The past decade of social insect research has seen rapid development in automated behavioral tracking and molecular profiling of the nervous system, two distinct but complementary lines of inquiry into phenotypic variation across individuals, colonies, populations, and species. These experimental strategies have developed largely in parallel, as automated tracking generates a continuous stream of behavioral data, while, in contrast, 'omics-based profiling provides a single 'snapshot' of the brain. Better integration of these approaches applied to studying variation in social behavior will reveal the underlying genetic and neurobiological mechanisms that shape the evolution and diversification of social life. In this review, we discuss relevant advances in both fields and propose new strategies to better elucidate the molecular and behavioral innovations that generate social life.

Autonomous tracking of honey bee behaviors over long-term periods with cooperating robots

Digital and mechatronic methods, paired with artificial intelligence and machine learning, are transformative technologies in behavioral science and biology. The central element of the most important pollinator species-honey bees-is the colony's queen. Because honey bee self-regulation is complex and studying queens in their natural colony context is difficult, the behavioral strategies of these organisms have not been widely studied. We created an autonomous robotic observation and behavioral analysis system aimed at continuous observation of the queen and her interactions with worker bees and comb cells, generating behavioral datasets of exceptional length and quality. Key behavioral metrics of the queen and her social embedding within the colony were gathered using our robotic system. Data were collected continuously for 24 hours a day over a period of 30 days, demonstrating our system's capability to extract key behavioral metrics at microscopic, mesoscopic, and macroscopic system levels. Additionally, interactions among the queen, worker bees, and brood were observed and quantified. Long-term continuous observations performed by the robot yielded large amounts of high-definition video data that are beyond the observation capabilities of humans or stationary cameras. Our robotic system can enable a deeper understanding of the innermost mechanisms of honey bees' swarm-intelligent self-regulation. Moreover, it offers the possibility to study other social insect colonies, biocoenoses, and ecosystems in an automated manner. Social insects are keystone species in all terrestrial ecosystems; thus, developing a better understanding of their behaviors will be invaluable for the protection and even the restoration of our fragile ecosystems globally.

Collective decision-making and spatial patterns in orientation of an endemic ungulate on the Tibetan Plateau

Group living animals form striking aggregation patterns and display synchronization, polarization, and collective intelligence. Though many collective behavioral studies have been conducted on small animals like insects and fish, research on large animals is still rare due to the limited availability of field collective data. We used drones to record videos and analyzed the decision-making and behavioral spatial patterns in orientation of Kiang (Tibetan wild ass, Equus kiang). Leadership is unevenly distributed among Kiang, with the minority initiating majority behavior-shift decisions. Decisions of individual to join are driven by imitation between group members, and are largely dependent on the number of members who have already joined. Kiang respond to the behavior and position of neighbors through different strategies. They strongly polarize when moving, therefore adopting a linear alignment. When vigilant, orientation deviation increases as they form a tighter group. They remain scattered while feeding and, in that context, adopt a side-by-side alignment. This study reveals partially-shared decision-making among Kiang, whereby copying neighbors provides the wisdom to thrive in harsh conditions. This study also suggests that animals' spatial patterns in orientation depend largely on their behavioral states in achieving synchronization.

Gut microbiota contribute to variations in honey bee foraging intensity

Gut microbiomes are increasingly recognized for mediating diverse biological aspects of their hosts, including complex behavioral phenotypes. Although many studies have reported that experimental disruptions to the gut microbial community result in atypical host behavior, studies that address how gut microbes contribute to adaptive behavioral trait variation are rare. Eusocial insects represent a powerful model to test this, because of their simple gut microbiota and complex division of labor characterized by colony-level variation in behavioral phenotypes. Although previous studies report correlational differences in gut microbial community associated with division of labor, here, we provide evidence that gut microbes play a causal role in defining differences in foraging behavior between European honey bees (Apis mellifera). We found that gut microbial community structure differed between hive-based nurse bees and bees that leave the hive to forage for floral resources. These differences were associated with variation in the abundance of individual microbes, including Bifidobacterium asteroides, Bombilactobacillus mellis, and Lactobacillus melliventris. Manipulations of colony demography and individual foraging experience suggested that differences in gut microbial community composition were associated with task experience. Moreover, single-microbe inoculations with B. asteroides, B. mellis, and L. melliventris caused effects on foraging intensity. These results demonstrate that gut microbes contribute to division of labor in a social insect, and support a role of gut microbes in modulating host behavioral trait variation.

Impact of odorants on perception of sweetness by honey bees

Organic volatiles produced by fruits can result in overestimation of sweetness by humans, but it is unknown if a comparable phenomenon occurs in other species. Honey bees collect nectar of varying sweetness at different flowering plants. Bees discriminate sugar concentration and generally prefer higher concentrations; they encounter floral volatiles as they collect nectar, suggesting that they, like humans, could be susceptible to sweetness enhancement by odorant. In this study, limonene, linalool, geraniol, and 6-methyl-5-hepten-2-ol were tested for their ability to alter behaviors related to perception of sweetness by honey bees. Honey bees were tested in the laboratory using proboscis extension response-based assays and in the field using feeder-based assays. In the laboratory assays, 6-methyl-5-hepten-2-ol and geraniol, but neither linalool nor limonene, significantly increased responses to low concentrations of sucrose compared with no odorant conditions in 15-day and 25-day-old adult worker honey bees, but not in 35-day-old bees. Limonene reduced responding in 15-day-old bees, but not in the older bees. There was no odorant-based difference in performance in field assays comparing geraniol and limonene with a no odorant control. The interaction of the tested plant volatiles with sucrose concentration revealed in laboratory testing is therefore unlikely to be a major determinant of nectar choice by honey bees foraging under natural conditions. Because geraniol is a component of honey bee Nasonov gland pheromone as well as a floral volatile, its impact on responses in the laboratory may reflect conveyance of different information than the other odorants tested.

Spontaneous and information-induced bursting activities in honeybee hives

Social entrainment is important for functioning of beehive organization. By analyzing a dataset of approximately 1000 honeybees (Apis mellifera) tracked in 5 trials, we discovered that honeybees exhibit synchronized activity (bursting behavior) in their locomotion. These bursts occurred spontaneously, potentially as a result of intrinsic bee interactions. The empirical data and simulations demonstrate that physical contact is one of the mechanisms for these bursts. We found that a subset of honeybees within a hive which become active before the peak of each burst, and we refer to these bees as "pioneer bees." Pioneer bees are not selected randomly, but rather, are linked to foraging behavior and waggle dancing, which may help spread external information in the hive. By using transfer entropy, we found that information flows from pioneer bees to non-pioneer bees, which suggest that the bursting behavior is caused by foraging behavior and spreading the information through the hive and promoting integrated group behavior among individuals.

A Data-Driven Simulation of the Trophallactic Network and Intranidal Food Flow Dissemination in Ants

Food sharing can occur in both social and non-social species, but it is crucial in eusocial species, in which only some group members collect food. This food collection and the intranidal (i.e., inside the nest) food distribution through trophallactic (i.e., mouth-to-mouth) exchanges are fundamental in eusocial insects. However, the behavioural rules underlying the regulation and the dynamics of food intake and the resulting networks of exchange are poorly understood. In this study, we provide new insights into the behavioural rules underlying the structure of trophallactic networks and food dissemination dynamics within the colony. We build a simple data-driven model that implements interindividual variability and the division of labour to investigate the processes of food accumulation/dissemination inside the nest, both at the individual and collective levels. We also test the alternative hypotheses (no variability and no division of labour). The division of labour, combined with inter-individual variability, leads to predictions of the food dynamics and exchange networks that run, contrary to the other models. Our results suggest a link between the interindividual heterogeneity of the trophallactic behaviours, the food flow dynamics and the network of trophallactic events. Our results show that a slight level of heterogeneity in the number of trophallactic events is enough to generate the properties of the experimental networks and seems to be crucial for the creation of efficient trophallactic networks. Despite the relative simplicity of the model rules, efficient trophallactic networks may emerge as the networks observed in ants, leading to a better understanding of the evolution of self-organisation in such societies.

Age-based spatial distribution of workers is resilient to worker loss in a subterranean termite

Elaborate task allocation is key to the ecological success of eusocial insects. Termite colonies are known for exhibiting age polyethism, with older instars more likely to depart the reproductive center to access food. However, it remains unknown how termites retain this spatial structure against external disturbances. Here we show that a subterranean termite Coptotermes formosanus Shiraki combines age polyethism and behavioral flexibility to maintain a constant worker proportion at the food area. Since this termite inhabits multiple wood pieces by connecting them through underground tunnels, disastrous colony splitting events can result in the loss of colony members. We simulated this via weekly removal of all individuals at the food area. Our results showed that termites maintained a worker proportion of ~ 20% at the food area regardless of changes in total colony size and demographic composition, where younger workers replaced food acquisition functions to maintain a constant worker proportion at the food area. Food consumption analysis revealed that the per-capita food consumption rate decreased with younger workers, but the colony did not compensate for the deficiency by increasing the proportion of workers at the feeding site. These results suggest that termite colonies prioritize risk management of colony fragmentation while maintaining suitable food acquisition efficiency with the next available workers in the colony, highlighting the importance of task allocation for colony resiliency under fluctuating environments.

Context-dependent influence of threat on honey bee social network dynamics and brain gene expression

Adverse social experience affects social structure by modifying the behavior of individuals, but the relationship between an individual's behavioral state and its response to adversity is poorly understood. We leveraged naturally occurring division of labor in honey bees and studied the biological embedding of environmental threat using laboratory assays and automated behavioral tracking of whole colonies. Guard bees showed low intrinsic levels of sociability compared with foragers and nurse bees, but large increases in sociability following exposure to a threat. Threat experience also modified the expression of caregiving-related genes in a brain region called the mushroom bodies. These results demonstrate that the biological embedding of environmental experience depends on an individual's societal role and, in turn, affects its future sociability.

Bee Tracker-an open-source machine learning-based video analysis software for the assessment of nesting and foraging performance of cavity-nesting solitary bees

The foraging and nesting performance of bees can provide important information on bee health and is of interest for risk and impact assessment of environmental stressors. While radiofrequency identification (RFID) technology is an efficient tool increasingly used for the collection of behavioral data in social bee species such as honeybees, behavioral studies on solitary bees still largely depend on direct observations, which is very time-consuming. Here, we present a novel automated methodological approach of individually and simultaneously tracking and analyzing foraging and nesting behavior of numerous cavity-nesting solitary bees. The approach consists of monitoring nesting units by video recording and automated analysis of videos by machine learning-based software. This Bee Tracker software consists of four trained deep learning networks to detect bees that enter or leave their nest and to recognize individual IDs on the bees' thorax and the IDs of their nests according to their positions in the nesting unit. The software is able to identify each nest of each individual nesting bee, which permits to measure individual-based measures of reproductive success. Moreover, the software quantifies the number of cavities a female enters until it finds its nest as a proxy of nest recognition, and it provides information on the number and duration of foraging trips. By training the software on 8 videos recording 24 nesting females per video, the software achieved a precision of 96% correct measurements of these parameters. The software could be adapted to various experimental setups by training it according to a set of videos. The presented method allows to efficiently collect large amounts of data on cavity-nesting solitary bee species and represents a promising new tool for the monitoring and assessment of behavior and reproductive success under laboratory, semi-field, and field conditions.

Honey bee (Apis mellifera L.) colonies as bioindicators of environmental SARS-CoV-2 occurrence

SARS-CoV-2 is responsible for the COVID-19 pandemic. Airflows sustain the infection spread, and in densely urbanized areas airborne particulate matters (PMs) are deemed to aggravate the viral transmission. Apis mellifera colonies are used as bioindicators as they allow environmental sampling of different nature, PMs included. This experiment demonstrates for the first time the possible use of honey bee colonies in the SARS-CoV-2 monitoring. The trial was conducted in Bologna on 18 March 2021, when the third wave of the Italian pandemic was at its peak and environmental conditions allowed high PM concentrations in the air. Sterile swabs were lined up at the hive entrance to sample the dusty material on the body of returning foragers. All of them resulted positive for the target genes of viral SARS-CoV-2 RNA. Likewise, internal samples were taken, but they resulted in no amplification of the target sequences. This experiment does not support speculations about the role of honey bees or their products in SARS-CoV-2 transmission. However, it indicates a novel use of A. mellifera colonies in the environmental detection of airborne human pathogens, at least in a densely urbanized area, deserving better understanding and possible integration with data from automatic air samplers.

Differential time allocation of foraging workers in the subterranean termite

Background

Foraging in group living animals such as social insects, is collectively performed by individuals. However, our understanding on foraging behavior of subterranean termites is extremely limited, as the process of foraging in the field is mostly concealed. Because of this limitation, foraging behaviors of subterranean termites were indirectly investigated in the laboratory through tunnel geometry analysis and observations on tunneling behaviors. In this study, we tracked subsets of foraging workers from juvenile colonies of Coptotermes formosanus (2-yr-old) to describe general foraging behavioral sequences and to find how foraging workers allocate time between the foraging site (food acquisition or processing) and non-foraging site (food transportation).

Results

Once workers entered into the foraging site, they spent, on average, a significantly longer time at the foraging site than the non-foraging site. Our clustering analysis revealed two different types of foraging workers in the subterranean termite based on the duration of time they spent at the foraging site and their foraging frequency. After entering the foraging site, some workers (cluster 1) immediately initiated masticating wood fragments, which they transferred as food boluses to recipient workers at the foraging site. Conversely, the recipient workers (cluster 2) moved around after entering the foraging site and received food from donating workers.

Conclusions

This study provides evidence of task specialization within foraging cohorts in subterranean termites.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12983-021-00446-5.

Foraging and Drifting Patterns of the Highly Eusocial Neotropical Stingless Bee Melipona fasciculata Assessed by Radio-Frequency Identification Tags

Bees play a key role in ecosystem services as the main pollinators of numerous flowering plants. Studying factors influencing their foraging behavior is relevant not only to understand their biology, but also how populations might respond to changes in their habitat and to the climate. Here, we used radio-frequency identification tags to monitor the foraging behavior of the neotropical stingless bee Melipona fasciculata with special interest in drifting patterns i.e., when a forager drifts into a foreign nest. In addition, we collected meteorological data to study how abiotic factors affect bees’ activity and behavior. Our results show that only 35% of bees never drifted to another hive nearby, and that factors such as temperature, humidity and solar irradiation affected the bees drifting rates and/or foraging activity. Moreover, we tested whether drifting levels would decrease after marking the nest entrances with different patterns. However, contrary to our predictions, there was an increase in the proportion of drifting, which could indicate factors other than orientation mistakes playing a role in this behavior. Overall, our results demonstrate how managed bee populations are affected by both nearby hives and climate factors, offering insights on their biology and potential commercial application as crop pollinators.

Hierarchical networks of food exchange in the black garden ant Lasius niger

In most eusocial insects, the division of labor results in relatively few individuals foraging for the entire colony. Thus, the survival of the colony depends on its efficiency in meeting the nutritional needs of all its members. Here, we characterize the network topology of a eusocial insect to understand the role and centrality of each caste in this network during the process of food dissemination. We constructed trophallaxis networks from 34 food-exchange experiments in black garden ants (Lasius niger). We tested the influence of brood and colony size on (i) global indices at the network level (i.e., efficiency, resilience, centralization, and modularity) and (ii) individual values (i.e., degree, strength, betweenness, and the clustering coefficient). Network resilience, the ratio between global efficiency and centralization, was stable with colony size but increased in the presence of broods, presumably in response to the nutritional needs of larvae. Individual metrics highlighted the major role of foragers in food dissemination. In addition, a hierarchical clustering analysis suggested that some domestics acted as intermediaries between foragers and other domestics. Networks appeared to be hierarchical rather than random or centralized exclusively around foragers. Finally, our results suggested that networks emerging from social insect interactions can improve group performance and thus colony fitness.

Density-dependent individual variation in male attractiveness in a wild field cricket

Social environments modify a male’s ability to attract females and thus affect its fitness. Theory implies that an individual’s fitness should trade-off with its ability to cope with competition. Individuals are expected to solve this trade-off differently: some males should be more attractive at low but others instead at high density. This prediction has rarely been tested in the wild. We used an automated RFID-surveillance system to quantify for each hour of the day, over 30 days (i.e., almost the entire adult lifespan of our model organism), whether a male had attracted a female in its burrow. The data were collected across a range of naturally varying local densities in wild field crickets, Gryllus campestris. We also estimated whether the shape of the relationship between attractiveness and density was under selection. At the population level, attractiveness increased from low to intermediate density, suggesting an Allee effect. Attractiveness subsequently declined at higher densities, for example, because of detrimental effects of increased competition. Opposite to expectations, males that were more attractive under low densities were also more attractive under higher densities. However, the increase in attractiveness with density varied among males, suggesting that Allee effects were individual-specific. Finally, selection was not acting on density-dependent attractiveness but males that lived longer acquired more mating partners. Our study reveals that social environments shape attractiveness in wild male insects, and imply the occurrence of individual-specific Allee effect that may be evolvable.

Forager age and foraging state, but not cumulative foraging activity, affect biogenic amine receptor gene expression in the honeybee mushroom bodies

Foraging behavior is crucial for the development of a honeybee colony. Biogenic amines are key mediators of learning and the transition from in-hive tasks to foraging. Foragers vary considerably in their behavior, but whether and how this behavioral diversity depends on biogenic amines is not yet well understood. For example, forager age, cumulative foraging activity or foraging state may all be linked to biogenic amine signaling. Furthermore, expression levels may fluctuate depending on daytime. We tested if these intrinsic and extrinsic factors are linked to biogenic amine signaling by quantifying the expression of octopamine, dopamine and tyramine receptor genes in the mushroom bodies, important tissues for learning and memory. We found that older foragers had a significantly higher expression of Amdop1, Amdop2, AmoctαR1, and AmoctβR1 compared to younger foragers, whereas Amtar1 showed the opposite pattern. Surprisingly, our measures of cumulative foraging activity were not related to the expression of the same receptor genes in the mushroom bodies. Furthermore, we trained foragers to collect sucrose solution at a specific time of day and tested if the foraging state of time-trained foragers affected receptor gene expression. Bees engaged in foraging had a higher expression of Amdop1 and AmoctβR3/4 than inactive foragers. Finally, the expression of Amdop1, Amdop3, AmoctαR1, and Amtar1 also varied with daytime. Our results show that receptor gene expression in forager mushroom bodies is complex and depends on both intrinsic and extrinsic factors.

Bipartite network analysis of ant-task associations reveals task groups and absence of colonial daily activity

Social insects are one of the best examples of complex self-organized systems exhibiting task allocation. How task allocation is achieved is the most fascinating question in behavioural ecology and complex systems science. However, it is difficult to comprehensively characterize task allocation patterns due to behavioural complexity, such as the individual variation, context dependency and chronological variation. Thus, it is imperative to quantify individual behaviours and integrate them into colony levels. Here, we applied bipartite network analyses to characterize individual-behaviour relationships. We recorded the behaviours of all individuals with verified age in ant colonies and analysed the individual-behaviour relationship at the individual, module and network levels. Bipartite network analysis successfully detected the module structures, illustrating that certain individuals performed a subset of behaviours (i.e. task groups). We confirmed age polyethism by comparing age between modules. Additionally, to test the daily rhythm of the executed tasks, the data were partitioned between daytime and nighttime, and a bipartite network was re-constructed. This analysis supported that there was no daily rhythm in the tasks performed. These findings suggested that bipartite network analyses could untangle complex task allocation patterns and provide insights into understanding the division of labour.

Individual variations lead to universal and cross-species patterns of social behavior

The duration of interaction events in a society is a fundamental measure of its collective nature and potentially reflects variability in individual behavior. Here we performed a high-throughput measurement of trophallaxis and face-to-face event durations experienced by a colony of honeybees over their entire lifetimes. The interaction time distribution is heavy-tailed, as previously reported for human face-to-face interactions. We developed a theory of pair interactions that takes into account individual variability and predicts the scaling behavior for both bee and extant human datasets. The individual variability of worker honeybees was nonzero but less than that of humans, possibly reflecting their greater genetic relatedness. Our work shows how individual differences can lead to universal patterns of behavior that transcend species and specific mechanisms for social interactions.

Honeybee lifespan: the critical role of pre-foraging stage

Assessing the various anthropogenic pressures imposed on honeybees requires characterizing the patterns and drivers of natural mortality. Using automated lifelong individual monitoring devices, we monitored worker bees in different geographical, seasonal and colony contexts creating a broad range of hive conditions. We measured their life-history traits and notably assessed whether lifespan is influenced by pre-foraging flight experience. Our results show that the age at the first flight and onset of foraging are critical factors that determine, to a large extent, lifespan. Most importantly, our results indicate that a large proportion (40%) of the bees die during pre-foraging stage, and for those surviving, the elapsed time and flight experience between the first flight and the onset of foraging is of paramount importance to maximize the number of days spent foraging. Once in the foraging stage, individuals experience a constant mortality risk of 9% and 36% per hour of foraging and per foraging day, respectively. In conclusion, the pre-foraging stage during which bees perform orientation flights is a critical driver of bee lifespan. We believe these data on the natural mortality risks in honeybee workers will help assess the impact of anthropogenic pressures on bees.

Pan Traps for Tracking Honey Bee Activity-Density: A Case Study in Soybeans

To study how honey bees utilize forage resources and guide pollination management plans in crops, a multitude of methods have been developed, but most are time consuming, costly, and require specialized skills. Colored pan traps for monitoring activity-density are a simple, efficient, and cost-effective alternative; however, their usefulness for studying honey bees is not well described. We examined if trap color, location within a field, and the presence of managed colonies affected estimates of honey bee activity-density within soybean fields. Soybeans are visited by pollinators but do not require these visits for seed development. Pan traps, especially those colored blue, captured more honey bees when colonies were present. There were no differences in activity-density based on placement of traps within a field nor with increasing distance from colonies. Throughout the season, activity-density in soybeans was constant but tripled after soybean ceased blooming, suggesting spikes in pan trap captures may indicate periods of forage scarcity. Activity-density did not correlate with the population size of worker bees at a site, but did correlate with number of colonies present. We conclude that pan traps can be useful for assessing honey bee activity, particularly for estimating colony presence and identifying times of forage scarcity.

Measuring ontogenetic shifts in central-place foragers: A case study with honeybees

Measuring time-activity budgets over the complete individual life span is now possible for many animals with the recent advances of life-long individual monitoring devices. Although analyses of changes in the patterns of time-activity budgets have revealed ontogenetic shifts in birds or mammals, no such technique has been applied to date on insects. We tested an automated breakpoint-based procedure to detect, assess and quantify shifts in the temporal pattern of the flight activities in honeybees. We assumed that the learning and foraging stages of honeybees will differ in several respects, to detect the age at onset of foraging (AOF). Using an extensive dataset covering the life-long monitoring of 1,167 individuals, we compared the AOF outputs with the more conventional approaches based on arbitrary thresholds. We further evaluated the robustness of the different methods comparing the foraging time-activity budget allocations between the presumed foragers and confirmed foragers. We revealed a clear-cut learning-foraging ontogenetic shift that differs in duration, frequency and time of occurrence of flights. Although AOF appeared to be highly plastic among bees, the breakpoint-based procedure seems better capable to detect it than arbitrary threshold-based methods that are unable to deal with inter-individual variation. We developed the aof r-package including a broad range of examples with both simulated and empirical datasets to illustrate the simplicity of use of the procedure. This simple procedure is generic enough to be derived from any individual life-long monitoring devices recording the time-activity budgets, and could propose new ecological applications of bio-logging to detect ontogenetic shifts in the behaviour of central-place foragers.

Social inhibition maintains adaptivity and consensus of honeybees foraging in dynamic environments

To effectively forage in natural environments, organisms must adapt to changes in the quality and yield of food sources across multiple timescales. Individuals foraging in groups act based on both their private observations and the opinions of their neighbours. How do these information sources interact in changing environments? We address this problem in the context of honeybee colonies whose inhibitory social interactions promote adaptivity and consensus needed for effective foraging. Individual and social interactions within a mathematical model of collective decisions shape the nutrition yield of a group foraging from feeders with temporally switching quality. Social interactions improve foraging from a single feeder if temporal switching is fast or feeder quality is low. When the colony chooses from multiple feeders, the most beneficial form of social interaction is direct switching, whereby bees flip the opinion of nest-mates foraging at lower-yielding feeders. Model linearization shows that effective social interactions increase the fraction of the colony at the correct feeder (consensus) and the rate at which bees reach that feeder (adaptivity). Our mathematical framework allows us to compare a suite of social inhibition mechanisms, suggesting experimental protocols for revealing effective colony foraging strategies in dynamic environments.

A spatiotemporal analysis of the food dissemination process and the trophallactic network in the ant Lasius niger

Intranidal food dissemination through trophallactic exchanges is a fundamental issue in social insect colonies but its underlying mechanisms are far from being clear. In light of the division of work, network theory and collective food management we develop a framework to investigate the spatiotemporal dynamics of the trophallactic network in starved Lasius niger ant colonies. Thanks to tracking methods we are able to record spatial locations of the trophallactic interactions in the nest. We highlight quantitative differences between the foragers and non-foragers concerning their contributions, their roles (donor/recipient) and their spatial distributions. Moreover, at the intracaste level, we show interindividual differences in all activities and we characterise their nature. In particular, within each caste, all the individuals have the same probability to start their food exchange activity but their probability to exchange differs after their first trophallactic event. Interestingly, despite the highlighted interindividual differences, the trophallactic network does not differ from a random network.

Honey bees as bioindicators of changing global agricultural landscapes

There is a growing need to understand relationships between agricultural intensification and global change. Monitoring solutions, however, often do not include pollinator communities that are of importance to ecosystem integrity. Here, we put forth the honey bee as an economical and broadly available bioindicator that can be used to assess and track changes in the quality of agricultural ecosystems. We detail a variety of simple, low-cost procedures that can be deployed within honey bee hives to gain generalizable information about ecosystem quality at multiple scales, and discuss the potential of the honey bee system in both environmental and ecological bioindication.

A robot made of robots: Emergent transport and control of a smarticle ensemble

Robot locomotion is typically generated by coordinated integration of single-purpose components, like actuators, sensors, body segments, and limbs. We posit that certain future robots could self-propel using systems in which a delineation of components and their interactions is not so clear, becoming robust and flexible entities composed of functional components that are redundant and generic and can interact stochastically. Control of such a collective becomes a challenge because synthesis techniques typically assume known input-output relationships. To discover principles by which such future robots can be built and controlled, we study a model robophysical system: planar ensembles of periodically deforming smart, active particles—smarticles. When enclosed, these individually immotile robots could collectively diffuse via stochastic mechanical interactions. We show experimentally and theoretically that directed drift of such a supersmarticle could be achieved via inactivation of individual smarticles and used this phenomenon to generate endogenous phototaxis. By numerically modeling the relationship between smarticle activity and transport, we elucidated the role of smarticle deactivation on supersmarticle dynamics from little data—a single experimental trial. From this mapping, we demonstrate that the supersmarticle could be exogenously steered anywhere in the plane, expanding supersmarticle capabilities while simultaneously enabling decentralized closed-loop control. We suggest that the smarticle model system may aid discovery of principles by which a class of future “stochastic” robots can rely on collective internal mechanical interactions to perform tasks.

Division of labor in honey bees is associated with transcriptional regulatory plasticity in the brain

Studies in evolutionary and developmental biology show that relationships between transcription factors (TFs) and their target genes can be altered to result in novel regulatory relationships that generate phenotypic plasticity. We hypothesized that context-dependent shifts in the nervous system associated with behavior may also be linked to changes in TF-target relationships over physiological time scales. We tested this hypothesis using honey bee (Apis mellifera) division of labor as a model system by performing bioinformatic analyses of previously published brain transcriptomic profiles together with new RNAi and behavioral experiments. The bioinformatic analyses identified five TFs that exhibited strong signatures of regulatory plasticity as a function of division of labor. RNAi targeting of one of these TFs (broad complex) and a related TF that did not exhibit plasticity (fushi tarazu transcription factor 1) was administered in conjunction with automated analyses of foraging behavior in the field, laboratory assays of aggression and brood care behavior, and endocrine treatments. The results showed that changes in the regulatory relationships of these TFs were associated with behavioral state, social context and endocrine state. These findings provide the first empirical evidence that TF-target relationships in the brain are altered in conjunction with behavior and social context. They also suggest that one mechanism for this plasticity involves pleiotropic TFs high up in regulatory hierarchies producing behavior-specific transcriptional responses by activating different downstream TFs to induce discrete context-dependent transcriptional cascades. These findings provide new insights into the dynamic nature of the transcriptional regulatory architecture underlying behavior in the brain.

Verification of mathematical models of response threshold through statistical characterisation of the foraging activity in ant societies

The concept of response threshold (RT) has been developed to explain task allocation in social insect colonies, wherein individual workers engage in tasks depending on their responsiveness to the task-related stimulus. Moreover, a mathematical model of RT has been proposed to explain data obtained from task allocation experiments; however, its applicability range warrants clarification through adequate quantitative analysis. Hence, we used an automatic measuring system to count passage events between a nest chamber and a foraging arena in five colonies of ants, Camponotus japonicus. The events were measured using radio-frequency identification tags attached to all workers of each colony. Here, we examined the detailed forms of i) labour distribution during foraging among workers in each colony and ii) the persistence of rank-order of foraging among workers. We found that labour distribution was characterized by a generalized gamma-distribution, indicating that only few workers carried out a large part of the workload. The rank-order of foraging activity among workers in each colony was maintained for a month and collapsed within a few months. We compared the obtained data with testable predictions of the RT model. The comparison indicated that proper evaluation of the mathematical model is required based on the obtained data.

Honey bees increase their foraging performance and frequency of pollen trips through experience

Honey bee foragers must supply their colony with a balance of pollen and nectar to sustain optimal colony development. Inter-individual behavioural variability among foragers is observed in terms of activity levels and nectar vs. pollen collection, however the causes of such variation are still open questions. Here we explored the relationship between foraging activity and foraging performance in honey bees (Apis mellifera) by using an automated behaviour monitoring system to record mass on departing the hive, trip duration, presence of pollen on the hind legs and mass upon return to the hive, during the lifelong foraging career of individual bees. In our colonies, only a subset of foragers collected pollen, and no bee exclusively foraged for pollen. A minority of very active bees (19% of the foragers) performed 50% of the colony’s total foraging trips, contributing to both pollen and nectar collection. Foraging performance (amount and rate of food collection) depended on bees’ individual experience (amount of foraging trips completed). We argue that this reveals an important vulnerability for these social bees since environmental stressors that alter the activity and reduce the lifespan of foragers may prevent bees ever achieving maximal performance, thereby seriously compromising the effectiveness of the colony foraging force.

Spare to share? How does interindividual variation in metabolic rate influence food sharing in the honeybee?

A central benefit of group living is the cooperative acquisition and sharing of resources but the costs associated with these processes can set up a potential conflict between individual and group level fitness. Within a honeybee colony, the task of resource acquisition is relegated to the foragers and any interindividual differences in their metabolic rate and the consequent carbohydrate demand may pose a constraint on the amount of resources they can contribute to the colony. We investigated whether the carbohydrate demand of a forager is a function of her metabolic rate and if this impacts the amount of food she shares with the nestmates. Our results show that the sucrose consumption rates of foragers with high metabolic rates did not meet their carbohydrate demand, placing them at an energy deficit while those with lower metabolic rates had an energy surplus. Our food sharing experiments showed a trend but did not detect a significant difference among individuals with different consumption rates in terms of the amount of food they shared with their nestmates. These results suggest that honeybee foragers with different metabolic rates are likely to differ in terms of whether they have an energy surplus or deficit, but more long-term datasets may be required to detect how this may influence food sharing.

Genetic accommodation and the role of ancestral plasticity in the evolution of insect eusociality

For over a century, biologists have proposed a role for phenotypic plasticity in evolution, providing an avenue for adaptation in addition to 'mutation-first' models of evolutionary change. According to the various versions of this idea, the ability of organisms to respond adaptively to their environment through phenotypic plasticity may lead to novel phenotypes that can be screened by natural selection. If these initially environmentally induced phenotypes increase fitness, then genetic accommodation can lead to allele frequency change, influencing the expression of those phenotypes. Despite the long history of 'plasticity-first' models, the importance of genetic accommodation in shaping evolutionary change has remained controversial - it is neither fully embraced nor completely discarded by most evolutionary biologists. We suggest that the lack of acceptance of genetic accommodation in some cases is related to a lack of information on its molecular mechanisms. However, recent reports of epigenetic transgenerational inheritance now provide a plausible mechanism through which genetic accommodation may act, and we review this research here. We also discuss current evidence supporting a role for genetic accommodation in the evolution of eusociality in social insects, which have long been models for studying the influence of the environment on phenotypic variation, and may be particularly good models for testing hypotheses related to genetic accommodation. Finally, we introduce 'eusocial engineering', a method by which novel social phenotypes are first induced by environmental modification and then studied mechanistically to understand how environmentally induced plasticity may lead to heritable changes in social behavior. We believe the time is right to incorporate genetic accommodation into models of the evolution of complex traits, armed with new molecular tools and a better understanding of non-genetic heritable elements.

Collective clog control: Optimizing traffic flow in confined biological and robophysical excavation

Groups of interacting active particles, insects, or humans can form clusters that hinder the goals of the collective; therefore, development of robust strategies for control of such clogs is essential, particularly in confined environments. Our biological and robophysical excavation experiments, supported by computational and theoretical models, reveal that digging performance can be robustly optimized within the constraints of narrow tunnels by individual idleness and retreating. Tools from the study of dense particulate ensembles elucidate how idleness reduces the frequency of flow-stopping clogs and how selective retreating reduces cluster dissolution time for the rare clusters that still occur. Our results point to strategies by which dense active matter and swarms can become task capable without sophisticated sensing, planning, and global control of the collective.

Low-Cost Electronic Tagging System for Bee Monitoring

This paper introduces both a hardware and a software system designed to allow low-cost electronic monitoring of social insects using RFID tags. Data formats for individual insect identification and their associated experiment are proposed to facilitate data sharing from experiments conducted with this system. The antennas’ configuration and their duty cycle ensure a high degree of detection rates. Other advantages and limitations of this system are discussed in detail in the paper.

Flight capacities of yellow-legged hornet (Vespa velutina nigrithorax, Hymenoptera: Vespidae) workers from an invasive population in Europe

The invasive yellow-legged hornet, Vespa velutina nigrithorax Lepeletier, 1836 (Hymenoptera: Vespidae), is native to Southeast Asia. It was first detected in France (in the southwest) in 2005. It has since expanded throughout Europe and has caused significant harm to honeybee populations. We must better characterize the hornet’s flight capacity to understand the species’ success and develop improved control strategies. Here, we carried out a study in which we quantified the flight capacities of V. velutina workers using computerized flight mills. We observed that workers were able to spend around 40% of the daily 7-hour flight tests flying. On average, they flew 10km to 30km during each flight test, although there was a large amount of variation. Workers sampled in early summer had lower flight capacities than workers sampled later in the season. Flight capacity decreased as workers aged. However, in the field, workers probably often die before this decrease becomes significant. During each flight test, workers performed several continuous flight phases of variable length that were separated by rest phases. Based on the length of those continuous flight phases and certain key assumptions, we estimated that V. velutina colony foraging radius is at least 700 m (half that in early summer); however, some workers are able to forage much farther. While these laboratory findings remain to be confirmed by field studies, our results can nonetheless help inform V. velutina biology and control efforts.

Spatial fidelity of workers predicts collective response to disturbance in a social insect

Individuals in social insect colonies cooperate to perform collective work. While colonies often respond to changing environmental conditions by flexibly reallocating workers to different tasks, the factors determining which workers switch and why are not well understood. Here, we use an automated tracking system to continuously monitor nest behavior and foraging activity of uniquely identified workers from entire bumble bee (Bombus impatiens) colonies foraging in a natural outdoor environment. We show that most foraging is performed by a small number of workers and that the intensity and distribution of foraging is actively regulated at the colony level in response to forager removal. By analyzing worker nest behavior before and after forager removal, we show that spatial fidelity of workers within the nest generates uneven interaction with relevant localized information sources, and predicts which workers initiate foraging after disturbance. Our results highlight the importance of spatial fidelity for structuring information flow and regulating collective behavior in social insect colonies.

Individual crop loads provide local control for collective food intake in ant colonies

Nutritional regulation by ants emerges from a distributed process: food is collected by a small fraction of workers, stored within the crops of individuals, and spread via local ant-to-ant interactions. The precise individual-level underpinnings of this collective regulation have remained unclear mainly due to difficulties in measuring food within ants' crops. Here we image fluorescent liquid food in individually tagged Camponotus sanctus ants and track the real-time food flow from foragers to their gradually satiating colonies. We show how the feedback between colony satiation level and food inflow is mediated by individual crop loads; specifically, the crop loads of recipient ants control food flow rates, while those of foragers regulate the frequency of foraging-trips. Interestingly, these effects do not rise from pure physical limitations of crop capacity. Our findings suggest that the emergence of food intake regulation does not require individual foragers to assess the global state of the colony.

Electronic p-Chip-Based System for Identification of Glass Slides and Tissue Cassettes in Histopathology Laboratories

Background:

The tagging system is based on a small, electronic, wireless, laser-light-activated microtransponder named “p-Chip.” The p-Chip is a silicon integrated circuit, the size of which is 600 μm × 600 μm × 100 μm. Each p-Chip contains a unique identification code stored within its electronic memory that can be retrieved with a custom reader. These features allow the p-Chip to be used as an unobtrusive and scarcely noticeable ID tag on glass slides and tissue cassettes.

Methods:

The system is comprised of p-Chip-tagged sample carriers, a dedicated benchtop p-Chip ID reader that can accommodate both objects, and an additional reader (the Wand), with an adapter for reading IDs of glass slides stored vertically in drawers. On slides, p-Chips are attached with adhesive to the center of the short edge, and on cassettes – embedded directly into the plastic. ID readout is performed by bringing the reader to the proximity of the chip. Standard histopathology laboratory protocols were used for testing.

Results:

Very good ID reading efficiency was observed for both glass slides and cassettes. When processed slides are stored in vertical filing drawers, p-Chips remain readable without the need to remove them from the storage location, thereby improving the speed of searches in collections. On the cassettes, the ID continues to be readable through a thin layer of paraffin. Both slides and tissue cassettes can be read with the same reader, reducing the need for redundant equipment.

Conclusions:

The p-Chip is stable to all chemical challenges commonly used in the histopathology laboratory, tolerates temperature extremes, and remains durable in long-term storage. The technology is compatible with laboratory information management systems software systems. The p-Chip system is very well suited for identification of glass slides and cassettes in the histopathology laboratory.

Comparative Flight Activities and Pathogen Load of Two Stocks of Honey Bees Reared in Gamma-Irradiated Combs

Gamma irradiation is known to inactivate various pathogens that negatively affect honey bee health. Bee pathogens, such as Deformed wing virus (DWV) and Nosema spp., have a deleterious impact on foraging activities and bee survival, and have been detected in combs. In this study, we assessed the effects of gamma irradiation on the flight activities, pathogen load, and survival of two honey bee stocks that were reared in irradiated and non-irradiated combs. Overall, bee genotype influenced the average number of daily flights, the total number of foraging flights, and total flight duration, in which the Russian honey bees outperformed the Italian honey bees. Exposing combs to gamma irradiation only affected the age at first flight, with worker bees that were reared in non-irradiated combs foraging prematurely compared to those reared in irradiated combs. Precocious foraging may be associated with the higher levels of DWV in bees reared in non-irradiated combs and also with the lower amount of pollen stores in colonies that used non-irradiated combs. These data suggest that gamma irradiation of combs can help minimize the negative impact of DWV in honey bees. Since colonies with irradiated combs stored more pollen than those with non-irradiated combs, crop pollination efficiency may be further improved when mite-resistant stocks are used, since they performed more flights and had longer flight durations.

Deep evolutionary conservation of autism-related genes

E. O. Wilson proposed in Sociobiology that similarities between human and animal societies reflect common mechanistic and evolutionary roots. When introduced in 1975, this controversial hypothesis was beyond science's ability to test. We used genomic analyses to determine whether superficial behavioral similarities in humans and the highly social honey bee reflect common molecular mechanisms. Here, we report that gene expression signatures for individual bees unresponsive to various salient social stimuli are significantly enriched for autism spectrum disorder-related genes. These signatures occur in the mushroom bodies, a high-level integration center of the insect brain. Furthermore, our finding of enrichment was unique to autism spectrum disorders; brain gene expression signatures from other honey bee behaviors do not show this enrichment, nor do datasets from other human behavioral and health conditions. These results demonstrate deep conservation for genes associated with a human social pathology and individual differences in insect social behavior, thus providing an example of how comparative genomics can be used to test sociobiological theory.

Task allocation and site fidelity jointly influence foraging regulation in honeybee colonies

Variation in behaviour among group members often impacts collective outcomes. Individuals may vary both in the task that they perform and in the persistence with which they perform each task. Although both the distribution of individuals among tasks and differences among individuals in behavioural persistence can each impact collective behaviour, we do not know if and how they jointly affect collective outcomes. Here, we use a detailed computational model to examine the joint impact of colony-level distribution among tasks and behavioural persistence of individuals, specifically their fidelity to particular resource sites, on the collective trade-off between exploring for new resources and exploiting familiar ones. We developed an agent-based model of foraging honeybees, parametrized by data from five colonies, in which we simulated scouts, who search the environment for new resources, and individuals who are recruited by the scouts to the newly found resources, i.e. recruits. We varied the persistence of returning to a particular food source of both scouts and recruits and found that, for each value of persistence, there is a different optimal ratio of scouts to recruits that maximizes resource collection by the colony. Furthermore, changes to the persistence of scouts induced opposite effects from changes to the persistence of recruits on the collective foraging of the colony. The proportion of scouts that resulted in the most resources collected by the colony decreased as the persistence of recruits increased. However, this optimal proportion of scouts increased as the persistence of scouts increased. Thus, behavioural persistence and task participation can interact to impact a colony's collective behaviour in orthogonal directions. Our work provides new insights and generates new hypotheses into how variations in behaviour at both the individual and colony levels jointly impact the trade-off between exploring for new resources and exploiting familiar ones.