Global information sampling in the honey bee

Social Learning versus Individual Learning in the Division of Labour

Division of labour, or the differentiation of the individuals in a collective across tasks, is a fundamental aspect of social organisations, such as social insect colonies. It allows for efficient resource use and improves the chances of survival for the entire collective. The emergence of large inactive groups of individuals in insect colonies sometimes referred to as laziness, has been a puzzling and hotly debated division-of-labour phenomenon in recent years that is counter to the intuitive notion of effectiveness. It has previously been shown that inactivity can be explained as a by-product of social learning without the need to invoke an adaptive function. While highlighting an interesting and important possibility, this explanation is limited because it is not yet clear whether the relevant aspects of colony life are governed by social learning. In this paper, we explore the two fundamental types of behavioural adaptation that can lead to a division of labour, individual learning and social learning. We find that inactivity can just as well emerge from individual learning alone. We compare the behavioural dynamics in various environmental settings under the social and individual learning assumptions, respectively. We present individual-based simulations backed up by analytic theory, focusing on adaptive dynamics for the social paradigm and cross-learning for the individual paradigm. We find that individual learning can induce the same behavioural patterns previously observed for social learning. This is important for the study of the collective behaviour of social insects because individual learning is a firmly established paradigm of behaviour learning in their colonies. Beyond the study of inactivity, in particular, the insight that both modes of learning can lead to the same patterns of behaviour opens new pathways to approach the study of emergent patterns of collective behaviour from a more generalised perspective.

Two simple movement mechanisms for spatial division of labour in social insects

Many animal species divide space into a patchwork of home ranges, yet there is little consensus on the mechanisms individuals use to maintain fidelity to particular locations. Theory suggests that animal movement could be based upon simple behavioural rules that use local information such as olfactory deposits, or global strategies, such as long-range biases toward landmarks. However, empirical studies have rarely attempted to distinguish between these mechanisms. Here, we perform individual tracking experiments on four species of social insects, and find that colonies consist of different groups of workers that inhabit separate but partially-overlapping spatial zones. Our trajectory analysis and simulations suggest that worker movement is consistent with two local mechanisms: one in which workers increase movement diffusivity outside their primary zone, and another in which workers modulate turning behaviour when approaching zone boundaries. Parallels with other organisms suggest that local mechanisms might represent a universal method for spatial partitioning in animal populations.

Identification of the cuticle protein AccCPR2 gene in Apis cerana cerana and its response to environmental stress

Cuticular proteins (CPs) are known to play important roles in insect development and defence responses. The loss of CP genes can lead to changes in insect morphology and sensitivity to the external environment. In this study, we identified the AccCPR2 gene, which belongs to the CPR family (including the R&R consensus motif) of CPs, and explored its function in the response of Apis cerana cerana to adverse external stresses. Our results demonstrated that AccCPR2 was highly expressed in the late pupal stage and epidermis, and the expression of AccCPR2 may be induced or inhibited under different stressors. RNA interference experiments showed that knockdown of AccCPR2 reduced the activity of antioxidant enzymes, led to the accumulation of oxidative damage and suppressed the expression of several antioxidant genes. In addition, knockdown of AccCPR2 also reduced the pesticide resistance of A. cerana cerana. The overexpression of AccCPR2 in a prokaryotic system further confirmed its role in resistance to various stresses. In summary, AccCPR2 may play pivotal roles in the normal development and environmental stress response of A. cerana cerana. This study also enriched the theoretical knowledge of the resistance biology of bees.

Behavioral variation across the days and lives of honey bees

In honey bee colonies, workers generally change tasks with age (from brood care, to nest work, to foraging). While these trends are well established, our understanding of how individuals distribute tasks during a day, and how individuals differ in their lifetime behavioral trajectories, is limited. Here, we use automated tracking to obtain long-term data on 4,100+ bees tracked continuously at 3 Hz, across an entire summer, and use behavioral metrics to compare behavior at different timescales. Considering single days, we describe how bees differ in space use, detection, and movement. Analyzing the behavior exhibited across their entire lives, we find consistent inter-individual differences in the movement characteristics of individuals. Bees also differ in how quickly they transition through behavioral space to ultimately become foragers, with fast-transitioning bees living the shortest lives. Our analysis framework provides a quantitative approach to describe individual behavioral variation within a colony from single days to entire lifetimes.

Markerless tracking of an entire honey bee colony

From cells in tissue, to bird flocks, to human crowds, living systems display a stunning variety of collective behaviors. Yet quantifying such phenomena first requires tracking a significant fraction of the group members in natural conditions, a substantial and ongoing challenge. We present a comprehensive, computational method for tracking an entire colony of the honey bee Apis mellifera using high-resolution video on a natural honeycomb background. We adapt a convolutional neural network (CNN) segmentation architecture to automatically identify bee and brood cell positions, body orientations and within-cell states. We achieve high accuracy (~10% body width error in position, ~10° error in orientation, and true positive rate > 90%) and demonstrate months-long monitoring of sociometric colony fluctuations. These fluctuations include ~24 h cycles in the counted detections, negative correlation between bee and brood, and nightly enhancement of bees inside comb cells. We combine detected positions with visual features of organism-centered images to track individuals over time and through challenging occluding events, recovering ~79% of bee trajectories from five observation hives over 5 min timespans. The trajectories reveal important individual behaviors, including waggle dances and crawling inside comb cells. Our results provide opportunities for the quantitative study of collective bee behavior and for advancing tracking techniques of crowded systems.

Task syndromes: linking personality and task allocation in social animal groups

Studies of eusocial insects have extensively investigated two components of task allocation: how individuals distribute themselves among different tasks in a colony and how the distribution of labor changes to meet fluctuating task demand. While discrete age- and morphologically-based task allocation systems explain much of the social order in these colonies, the basis for task allocation in non-eusocial organisms and within eusocial castes remains unknown. Building from recent advances in the study of among-individual variation in behavior (i.e., animal personalities), we explore a potential mechanism by which individuality in behaviors unrelated to tasks can guide the developmental trajectories that lead to task specialization. We refer to the task-based behavioral syndrome that results from the correlation between the antecedent behavioral tendencies and task participation as a task syndrome. In this review, we present a framework that integrates concepts from a long history of task allocation research in eusocial organisms with recent findings from animal personality research to elucidate how task syndromes and resulting task allocation might manifest in animal groups. By drawing upon an extensive and diverse literature to evaluate the hypothesized framework, this review identifies future areas for study at the intersection of social behavior and animal personality.

Coping with the cold and fighting the heat: thermal homeostasis of a superorganism, the honeybee colony

The worldwide distribution of honeybees and their fast propagation to new areas rests on their ability to keep up optimal ‘tropical conditions’ in their brood nest both in the cold and in the heat. Honeybee colonies behave like ‘superorganisms’ where individuals work together to promote reproduction of the colony. Social cooperation has developed strongly in thermal homeostasis, which guarantees a fast and constant development of the brood. We here report on the cooperation of individuals in reaction to environmental variation to achieve thermal constancy of 34–36 °C. The measurement of body temperature together with bee density and in-hive microclimate showed that behaviours for hive heating or cooling are strongly interlaced and differ in their start values. When environmental temperature changes, heat production is adjusted both by regulation of bee density due to migration activity and by the degree of endothermy. Overheating of the brood is prevented by cooling with water droplets and increased fanning, which start already at moderate temperatures where heat production and bee density are still at an increased level. This interlaced change and onset of different thermoregulatory behaviours guarantees a graded adaptation of individual behaviour to stabilise the temperature of the brood.

Extensive Vibrational Characterisation and Long-Term Monitoring of Honeybee Dorso-Ventral Abdominal Vibration signals

A very common honeybee signal is the dorso-ventral abdominal vibration (DVAV) signal, widely accepted as a modulatory signal meaning: “prepare for greater activity”. In this study, using ultra-sensitive accelerometer technology embedded in the honeycomb, we visually confirm the one-to-one relationship between a DVAV signal being produced and the resulting accelerometer waveform, allowing the measurement of DVAV signals without relying on any visual inspection. We then demonstrate a novel method for the continuous in-situ non-invasive automated monitoring of this honeybee signal, not previously known to induce any vibration into the honeycomb, and most often inaudible to human hearing. We monitored a total of three hives in the UK and France, showing that the signal is very common, highly repeatable and occurs more frequently at night, exhibiting a distinct decrease in instances and increase in amplitude towards mid-afternoon. We also show an unprecedented increase in the cumulative amplitude of DVAV signals occurring in the hours preceding and following a primary swarm. We conclude that DVAV signals may have additional functions beyond solely being a foraging activation signal, and that the amplitude of the signal might be indicative of the switching of its purpose.

The cues of colony size: how honey bees sense that their colony is large enough to begin to invest in reproduction

As organisms develop, they first invest resources in survival and growth, but after reaching a certain condition they start to also invest in reproduction. Likewise, superorganisms, such as honey bee colonies, first invest in survival and growth, and later commit resources to reproduction once the number of workers in the colony surpasses a reproductive threshold. The first form of reproductive investment for a honey bee colony is the building of beeswax comb made of special large cells used for rearing males (drones). How do the workers sense that their colony is large enough to start building this 'drone comb'? To address this question, we experimentally increased three possible cues of colony size - worker density, volatile pheromone concentration and nest temperature - and looked for effects on the bees' comb construction. Only the colonies that experienced increased worker density were stimulated to build a higher proportion of drone comb. We then monitored and quantified potential cues in small and large colonies, to determine which cues change with colony size. We found that workers in large colonies, relative to small ones, have increased contact rates, spend more time active and experience less variable worker density. Whereas unicellular and multicellular organisms use mainly chemical cues to sense their sizes, our results suggest that at least one superorganism, a honey bee colony, uses physical cues to sense its size and thus its developmental state.

Who Are the "Lazy" Ants? The Function of Inactivity in Social Insects and a Possible Role of Constraint: Inactive Ants Are Corpulent and May Be Young and/or Selfish

Social insect colonies are commonly thought of as highly organized and efficient complex systems, yet high levels of worker inactivity are common. Although consistently inactive workers have been documented across many species, very little is known about the potential function or costs associated with this behavior. Here we ask what distinguishes these "lazy" individuals from their nestmates. We obtained a large set of behavioral and morphological data about individuals, and tested for consistency with the following evolutionary hypotheses: that inactivity results from constraint caused by worker (a) immaturity or (b) senescence; that (c) inactive workers are reproducing; that inactive workers perform a cryptic task such as (d) acting as communication hubs or (e) food stores; and that (f) inactive workers represent the "slow-paced" end of inter-worker variation in "pace-of-life." We show that inactive workers walk more slowly, have small spatial fidelity zones near the nest center, are more corpulent, are isolated in colony interaction networks, have the smallest behavioral repertoires, and are more likely to have oocytes than other workers. These results are consistent with the hypotheses that inactive workers are immature and/or storing food for the colony; they suggest that workers are not inactive as a consequence of senescence, and that they are not acting as communication hubs. The hypotheses listed above are not mutually exclusive, and likely form a "syndrome" of behaviors common to inactive social insect workers. Their simultaneous contribution to inactivity may explain the difficulty in finding a simple answer to this deceptively simple question.

Costs of task allocation with local feedback: Effects of colony size and extra workers in social insects and other multi-agent systems

Adaptive collective systems are common in biology and beyond. Typically, such systems require a task allocation algorithm: a mechanism or rule-set by which individuals select particular roles. Here we study the performance of such task allocation mechanisms measured in terms of the time for individuals to allocate to tasks. We ask: (1) Is task allocation fundamentally difficult, and thus costly? (2) Does the performance of task allocation mechanisms depend on the number of individuals? And (3) what other parameters may affect their efficiency? We use techniques from distributed computing theory to develop a model of a social insect colony, where workers have to be allocated to a set of tasks; however, our model is generalizable to other systems. We show, first, that the ability of workers to quickly assess demand for work in tasks they are not currently engaged in crucially affects whether task allocation is quickly achieved or not. This indicates that in social insect tasks such as thermoregulation, where temperature may provide a global and near instantaneous stimulus to measure the need for cooling, for example, it should be easy to match the number of workers to the need for work. In other tasks, such as nest repair, it may be impossible for workers not directly at the work site to know that this task needs more workers. We argue that this affects whether task allocation mechanisms are under strong selection. Second, we show that colony size does not affect task allocation performance under our assumptions. This implies that when effects of colony size are found, they are not inherent in the process of task allocation itself, but due to processes not modeled here, such as higher variation in task demand for smaller colonies, benefits of specialized workers, or constant overhead costs. Third, we show that the ratio of the number of available workers to the workload crucially affects performance. Thus, workers in excess of those needed to complete all tasks improve task allocation performance. This provides a potential explanation for the phenomenon that social insect colonies commonly contain inactive workers: these may be a 'surplus' set of workers that improves colony function by speeding up optimal allocation of workers to tasks. Overall our study shows how limitations at the individual level can affect group level outcomes, and suggests new hypotheses that can be explored empirically.

Intrinsic worker mortality depends on behavioral caste and the queens' presence in a social insect

According to the classic life history theory, selection for longevity depends on age-dependant extrinsic mortality and fecundity. In social insects, the common life history trade-off between fecundity and longevity appears to be reversed, as the most fecund individual, the queen, often exceeds workers in lifespan several fold. But does fecundity directly affect intrinsic mortality also in social insect workers? And what is the effect of task on worker mortality? Here, we studied how social environment and behavioral caste affect intrinsic mortality of ant workers. We compared worker survival between queenless and queenright Temnothorax longispinosus nests and demonstrate that workers survive longer under the queens' absence. Temnothorax ant workers fight over reproduction when the queen is absent and dominant workers lay eggs. Worker fertility might therefore increase lifespan, possibly due to a positive physiological link between fecundity and longevity, or better care for fertile workers. In social insects, division of labor among workers is age-dependant with young workers caring for the brood and old ones going out to forage. We therefore expected nurses to survive longer than foragers, which is what we found. Surprisingly, inactive inside workers showed a lower survival than nurses but comparable to that of foragers. The reduced longevity of inactive workers could be due to them being older than the nurses, or due to a positive effect of activity on lifespan. Overall, our study points to behavioral caste-dependent intrinsic mortality rates and a positive association between fertility and longevity not only in queens but also in ant workers.

Task switching is associated with temporal delays in Temnothorax rugatulus ants

The major evolutionary transitions often result in reorganization of biological systems, and a component of such reorganization is that individuals within the system specialize on performing certain tasks, resulting in a division of labor. Although the traditional benefit of division of labor is thought to be a gain in work efficiency, one alternative benefit of specialization is avoiding temporal delays associated with switching tasks. While models have demonstrated that costs of task switching can drive the evolution of division of labor, little empirical support exists for this hypothesis. We tested whether there were task-switching costs in Temnothorax rugatulus. We recorded the behavior of every individual in 44 colonies and used this dataset to identify each instance where an individual performed a task, spent time in the interval (i.e., inactive, wandering inside, and self-grooming), and then performed a task again. We compared the interval time where an individual switched task type between that first and second bout of work to instances where an individual performed the same type of work in both bouts. In certain cases, we find that the interval time was significantly shorter if individuals repeated the same task. We find this time cost for switching to a new behavior in all active worker groups, that is, independently of worker specialization. These results suggest that task-switching costs may select for behavioral specialization.

Sting, Carry and Stock: How Corpse Availability Can Regulate De-Centralized Task Allocation in a Ponerine Ant Colony

We develop a model to produce plausible patterns of task partitioning in the ponerine ant Ectatomma ruidum based on the availability of living prey and prey corpses. The model is based on the organizational capabilities of a “common stomach” through which the colony utilizes the availability of a natural (food) substance as a major communication channel to regulate the income and expenditure of the very same substance. This communication channel has also a central role in regulating task partitioning of collective hunting behavior in a supply&demand-driven manner. Our model shows that task partitioning of the collective hunting behavior in E. ruidum can be explained by regulation due to a common stomach system. The saturation of the common stomach provides accessible information to individual ants so that they can adjust their hunting behavior accordingly by engaging in or by abandoning from stinging or transporting tasks. The common stomach is able to establish and to keep stabilized an effective mix of workforce to exploit the prey population and to transport food into the nest. This system is also able to react to external perturbations in a de-centralized homeostatic way, such as to changes in the prey density or to accumulation of food in the nest. In case of stable conditions the system develops towards an equilibrium concerning colony size and prey density. Our model shows that organization of work through a common stomach system can allow Ectatomma ruidum to collectively forage for food in a robust, reactive and reliable way. The model is compared to previously published models that followed a different modeling approach. Based on our model analysis we also suggest a series of experiments for which our model gives plausible predictions. These predictions are used to formulate a set of testable hypotheses that should be investigated empirically in future experimentation.

Worker personality and its association with spatially structured division of labor

Division of labor is a defining characteristic of social insects and fundamental to their ecological success. Many of the numerous tasks essential for the survival of the colony must be performed at a specific location. Consequently, spatial organization is an integral aspect of division of labor. The mechanisms organizing the spatial distribution of workers, separating inside and outside workers without central control, is an essential, but so far neglected aspect of division of labor. In this study, we investigate the behavioral mechanisms governing the spatial distribution of individual workers and its physiological underpinning in the ant Myrmica rubra. By investigating worker personalities we uncover position-associated behavioral syndromes. This context-independent and temporally stable set of correlated behaviors (positive association between movements and attraction towards light) could promote the basic separation between inside (brood tenders) and outside workers (foragers). These position-associated behavior syndromes are coupled with a high probability to perform tasks, located at the defined position, and a characteristic cuticular hydrocarbon profile. We discuss the potentially physiological causes for the observed behavioral syndromes and highlight how the study of animal personalities can provide new insights for the study of division of labor and self-organized processes in general.

Ants in a labyrinth: a statistical mechanics approach to the division of labour

Division of labour (DoL) is a fundamental organisational principle in human societies, within virtual and robotic swarms and at all levels of biological organisation. DoL reaches a pinnacle in the insect societies where the most widely used model is based on variation in response thresholds among individuals, and the assumption that individuals and stimuli are well-mixed. Here, we present a spatially explicit model of DoL. Our model is inspired by Pierre de Gennes' 'Ant in a Labyrinth' which laid the foundations of an entire new field in statistical mechanics. We demonstrate the emergence, even in a simplified one-dimensional model, of a spatial patterning of individuals and a right-skewed activity distribution, both of which are characteristics of division of labour in animal societies. We then show using a two-dimensional model that the work done by an individual within an activity bout is a sigmoidal function of its response threshold. Furthermore, there is an inverse relationship between the overall stimulus level and the skewness of the activity distribution. Therefore, the difference in the amount of work done by two individuals with different thresholds increases as the overall stimulus level decreases. Indeed, spatial fluctuations of task stimuli are minimised at these low stimulus levels. Hence, the more unequally labour is divided amongst individuals, the greater the ability of the colony to maintain homeostasis. Finally, we show that the non-random spatial distribution of individuals within biological and social systems could be caused by indirect (stigmergic) interactions, rather than direct agent-to-agent interactions. Our model links the principle of DoL with principles in the statistical mechanics and provides testable hypotheses for future experiments.

Spatial effects, sampling errors, and task specialization in the honey bee

Task allocation patterns should depend on the spatial distribution of work within the nest, variation in task demand, and the movement patterns of workers, however, relatively little research has focused on these topics. This study uses a spatially explicit agent based model to determine whether such factors alone can generate biases in task performance at the individual level in the honey bees, Apis mellifera. Specialization (bias in task performance) is shown to result from strong sampling error due to localized task demand, relatively slow moving workers relative to nest size, and strong spatial variation in task demand. To date, specialization has been primarily interpreted with the response threshold concept, which is focused on intrinsic (typically genotypic) differences between workers. Response threshold variation and sampling error due to spatial effects are not mutually exclusive, however, and this study suggests that both contribute to patterns of task bias at the individual level. While spatial effects are strong enough to explain some documented cases of specialization; they are relatively short term and not explanatory for long term cases of specialization. In general, this study suggests that the spatial layout of tasks and fluctuations in their demand must be explicitly controlled for in studies focused on identifying genotypic specialists.

A self-organizing model for task allocation via frequent task quitting and random walks in the honeybee

Social insect colonies are able to quickly redistribute their thousands of workers between tasks that vary strongly in space and time. How individuals collectively track spatial variability is particularly puzzling because bees have access only to local information. This work presents and tests a model showing how honeybees solve their fundamental within-nest spatial task-allocation problem. The algorithm, which is self-organizing and derived from empirical studies, couples two processes with opposing effects. Frequent task quitting, followed by patrols, during which bees are insensitive to task stimuli, serves to randomize individual location throughout the nest without reference to variation in task demand, while a foraging-for-work-like mechanism provides the opposing force of localizing individuals to areas of high task demand. This simple model is shown to generate sophisticated patterns of task allocation. It allocates bees to tasks in proportion to their demand, independent of their spatial distribution in the nest, and also reallocates labor in response to temporal changes in task demand. Finally, the model shows that task-allocation patterns at the colony level do not reflect colonies allocating particular individuals to tasks. In contrast, they reflect a dynamic equilibrium of workers switching between tasks and locations in the nest.

Division of labor in honeybees: form, function, and proximate mechanisms

Honeybees exhibit two patterns of organization of work. In the spring and summer, division of labor is used to maximize growth rate and resource accumulation, while during the winter, worker survivorship through the poor season is paramount, and bees become generalists. This work proposes new organismal and proximate level conceptual models for these phenomena. The first half of the paper presents a push–pull model for temporal polyethism. Members of the nursing caste are proposed to be pushed from their caste by the development of workers behind them in the temporal caste sequence, while middle-aged bees are pulled from their caste via interactions with the caste ahead of them. The model is, hence, an amalgamation of previous models, in particular, the social inhibition and foraging for work models. The second half of the paper presents a model for the proximate basis of temporal polyethism. Temporal castes exhibit specialized physiology and switch caste when it is adaptive at the colony level. The model proposes that caste-specific physiology is dependent on mutually reinforcing positive feedback mechanisms that lock a bee into a particular behavioral phase. Releasing mechanisms that relate colony level information are then hypothesized to disrupt particular components of the priming mechanisms to trigger endocrinological cascades that lead to the next temporal caste. Priming and releasing mechanisms for the nursing caste are mapped out that are consistent with current experimental results. Less information-rich, but plausible, mechanisms for the middle-aged and foraging castes are also presented.

Pattern formation on the combs of honeybees: increasing fitness by coupling self-organization with templates

Biological patterns are often constructed via a combination of mechanisms including self-organization, templates and recipes. Our understanding of self-organization is becoming increasingly clear, yet how multiple mechanisms work together and what selective advantage they confer over simpler mechanisms is poorly understood. Honeybee (Apis mellifera) combs exhibit a pattern of brood at the bottom, pollen in a band next to it and honey at the top. This study constructs an agent-based model, derived from experimental studies, to determine both how self-organization interacts with two templates and to elucidate a selective basis for the use of multiple mechanisms. The vertical pattern of honey and brood is shown to be dependent on a gravity-based template, while the pollen band is shown to form via the interaction of a queen-based template and self-organization. The study suggests that the selective basis for this complex mechanism may be that colonies have higher growth rates when multiple mechanisms are used as opposed to self-organization alone. As self-organization is used in many contexts in which the addition of supplemental mechanisms could be advantageous, this result may be of general significance to many biological systems.