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

Foraging dynamics in social insect colonies: Mechanisms of backward bifurcations and impacts of stochasticity

This investigation presents a two-dimensional collective foraging model alongside its stochastic counterpart, simplifying the previous more complex three-dimensional framework utilized to examine foraging behaviors within social insect colonies. We first conduct a thorough examination of the global dynamics of the deterministic model. The results show that the two-dimensional model exhibits equilibrium dynamics, with the possibility of coexistence between non-foraging and foraging equilibrium states. This finding highlights the parallelism between the two-dimensional model and the traditional three-dimensional framework. Following this, an extensive exploration into the long-term collective foraging dynamics within a stochastic environment is conducted, elucidating the interplay between stochasticity and the transitions across distinct stable foraging states. Additionally, the investigation assesses the risk of foraging cessation across varying initial worker populations, subsequently delineating foraging termination warning thresholds. The findings illuminate the multifaceted influence of environmental stochasticity on the collective foraging dynamics observed in harvester ant colonies. Grasping these dynamics furnishes valuable understanding of ecological resilience and the adaptive strategies deployed by collective entities in navigating environmental fluctuations.

The evolution of division of labour: preconditions and evolutionary feedback

Division of Labour (DoL) among group members reflects the pinnacle of social complexity. The synergistic effects created by task specialization and the sharing of duties benefitting the group raise the efficiency of the acquisition, use, management and defence of resources by a fundamental step above the potential of individual agents. At the same time, it may stabilize societies because of the involved interdependence among collaborators. Here, I review the conditions associated with the emergence of DoL, which include the existence of (i) sizeable groups with enduring membership; (ii) individual specialization improving the efficiency of task performance; and (iii) low conflict of interest among group members owing to correlated payoffs. This results in (iv) a combination of intra-individual consistency with inter-individual variance in carrying out different tasks, which creates (v) some degree of mutual interdependence among group members. DoL typically evolves 'bottom-up' without external regulatory forces, but the latter may gain importance at a later stage of the evolution of social complexity. Owing to the involved feedback processes, cause and effect are often difficult to disentangle in the evolutionary trajectory towards structured societies with well-developed DoL among their members. Nevertheless, the emergence of task specialization and DoL may entail a one-way street towards social complexity, with retrogression getting increasingly difficult the more individual agents depend on each other at progressing stages of social evolution.This article is part of the theme issue 'Division of labour as key driver of social evolution'.

Foraging behavior and work patterns of Bombus terrestris (Hymenoptera: Apidae) in response to tomato greenhouse microclimate

Bumblebees play a significant role as pollinators for many wild plants and cultivated crops, owing to their elongated proboscis, resilience to diverse weather conditions, robustly furred bodies, and their unique capacity for buzz-pollination. To better understand the effect of greenhouse microclimates on bumblebee foraging behavior and working modes, a long-term record of foraging activity for each Bombus terrestris L. (Hymenoptera: Apidae) forager was monitored by the Radio-frequency identification system. The pattern of task performance, including constant housing, foraging, and day-off rotation, was examined under the microclimate. In addition, the correlation between foraging activity of bumblebees and temperature, relative humidity, illumination in the greenhouse, and pollen viability of tomato plants was further analyzed. Our findings revealed that B. terrestris can respond to microclimatic factors and plant resources while also exhibiting a suitable working pattern within the colony. Day-off rotation was observed as a strategy employed by foragers to prolong their survival time. This division of labor and task rotation may serve as strategies for the survival and development of the colony. Our research may contribute to fully understanding how microclimate and plants influence pollinator behavior within greenhouses, thereby optimizing the pollination management of bumblebees on greenhouse crops.

Colony size buffers interactions between neonicotinoid exposure and cold stress in bumblebees

Social bees are critical for supporting biodiversity, ecosystem function and crop yields globally. Colony size is a key ecological trait predicted to drive sensitivity to environmental stressors and may be especially important for species with annual cycles of sociality, such as bumblebees. However, there is limited empirical evidence assessing the effect of colony size on sensitivity to environmental stressors or the mechanisms underlying these effects. Here, we examine the relationship between colony size and sensitivity to environmental stressors in bumblebees. We exposed colonies at different developmental stages briefly (2 days) to a common neonicotinoid (imidacloprid) and cold stress, while quantifying behaviour of individuals. Combined imidacloprid and cold exposure had stronger effects on both thermoregulatory behaviour and long-term colony growth in small colonies. We find that imidacloprid's effects on behaviour are mediated by body temperature and spatial location within the nest, suggesting that social thermoregulation provides a buffering effect in large colonies. Finally, we demonstrate qualitatively similar effects in size-manipulated microcolonies, suggesting that group size per se, rather than colony age, drives these patterns. Our results provide evidence that colony size is critical in driving sensitivity to stressors and may help elucidate mechanisms underlying the complex and context-specific impacts of pesticide exposure.

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.

Automated monitoring of honey bees with barcodes and artificial intelligence reveals two distinct social networks from a single affiliative behavior

Barcode-based tracking of individuals is revolutionizing animal behavior studies, but further progress hinges on whether in addition to determining an individual's location, specific behaviors can be identified and monitored. We achieve this goal using information from the barcodes to identify tightly bounded image regions that potentially show the behavior of interest. These image regions are then analyzed with convolutional neural networks to verify that the behavior occurred. When applied to a challenging test case, detecting social liquid transfer (trophallaxis) in the honey bee hive, this approach yielded a 67% higher sensitivity and an 11% lower error rate than the best detector for honey bee trophallaxis so far. We were furthermore able to automatically detect whether a bee donates or receives liquid, which previously required manual observations. By applying our trophallaxis detector to recordings from three honey bee colonies and performing simulations, we discovered that liquid exchanges among bees generate two distinct social networks with different transmission capabilities. Finally, we demonstrate that our approach generalizes to detecting other specific behaviors. We envision that its broad application will enable automatic, high-resolution behavioral studies that address a broad range of previously intractable questions in evolutionary biology, ethology, neuroscience, and molecular biology.

Scaling of ant colony interaction networks

In social insect colonies, individuals are physically independent but functionally integrated by interaction networks which provide a foundation for communication and drive the emergence of collective behaviors, including nest architecture, division of labor, and potentially also the social regulation of metabolic rates. To investigate the relationship between interactions, metabolism, and colony size, we varied group size for harvester ant colonies (Pogonomyrmex californicus) and assessed their communication networks based on direct antennal contacts and compared these results with proximity networks and a random movement simulation. We found support for the hypothesis of social regulation; individuals did not interact with each other randomly but exhibited restraint. Connectivity scaled hypometrically with colony size, per-capita interaction rate was scale-invariant, and smaller colonies exhibited higher measures of closeness centrality and edge density, correlating with higher per-capita metabolic rates. Although the immediate energetic cost for two ants to interact is insignificant, the downstream effects of receiving and integrating social information can have metabolic consequences. Our results indicate that individuals in larger colonies are relatively more insulated from each other, a factor that may reduce or filter noisy stimuli and contribute to the hypometric scaling of their metabolic rates, and perhaps more generally, the evolution of larger colony sizes.

Olfactory sensitivity differentiates morphologically distinct worker castes in Camponotus floridanus

BACKGROUND

Camponotus floridanus ant colonies are comprised of a single reproductive queen and thousands of sterile female offspring that consist of two morphologically distinct castes: smaller minors and larger majors. Minors perform most of the tasks within the colony, including brood care and food collection, whereas majors have fewer clear roles and have been hypothesized to act as a specialized solider caste associated with colony defense. The allocation of workers to these different tasks depends, in part, on the detection and processing of local information including pheromones and other chemical blends such as cuticular hydrocarbons. However, the role peripheral olfactory sensitivity plays in establishing and maintaining morphologically distinct worker castes and their associated behaviors remains largely unexplored.

RESULTS

We examined the electrophysiological responses to general odorants, cuticular extracts, and a trail pheromone in adult minor and major C. floridanus workers, revealing that the repertoire of social behaviors is positively correlated with olfactory sensitivity. Minors in particular display primarily excitatory responses to olfactory stimuli, whereas major workers primarily manifest suppressed, sub-solvent responses. The notable exception to this paradigm is that both minors and majors display robust, dose-dependent excitatory responses to conspecific, non-nestmate cuticular extracts. Moreover, while both minors and majors actively aggress non-nestmate foes, the larger and physiologically distinct majors display significantly enhanced capabilities to rapidly subdue and kill their adversaries.

CONCLUSIONS

Our studies reveal the behavioral repertoire of minors and majors aligns with profound shifts in peripheral olfactory sensitivity and odor coding. The data reported here support the hypothesis that minors are multipotential workers with broad excitatory sensitivity, and majors are dedicated soldiers with a highly specialized olfactory system for distinguishing non-nestmate foes. Overall, we conclude that C. floridanus majors do indeed represent a physiologically and behaviorally specialized soldier caste in which caste-specific olfactory sensitivity plays an important role in task allocation and the regulation of social behavior in ant colonies.

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.

From dyads to collectives: a review of honeybee signalling

The societies of honeybees (Apis spp.) are microcosms of divided labour where the fitness interests of individuals are so closely aligned that, in some contexts, the colony behaves as an entity in itself. Self-organization at this extraordinary level requires sophisticated communication networks, so it is not surprising that the celebrated waggle dance, by which bees share information about locations outside the hive, evolved here. Yet bees within the colony respond to several other lesser-known signalling systems, including the tremble dance, the stop signal and the shaking signal, whose roles in coordinating worker behaviour are not yet fully understood. Here, we firstly bring together the large but disparate historical body of work that has investigated the “meaning” of such signals for individual bees, before going on to discuss how network-based approaches can show how such signals function as a complex system to control the collective foraging effort of these remarkable social insect societies.

When being flexible matters: Ecological underpinnings for the evolution of collective flexibility and task allocation

A central problem in evolutionary biology is explaining variation in the organization of task allocation across collective systems. Why do human cells irreversibly adopt a task during development (e.g., kidney vs. liver cell), while sponge cells switch between different cell types? And why have only some ant species evolved specialized castes of workers for particular tasks? Although it seems reasonable to suppose that such differences reflect, at least partially, the different ecological pressures that systems face, there is no general understanding of how a system’s dynamic environment shapes its task allocation. To this end, we develop a general mathematical framework that reveals how simple ecological considerations could potentially explain cross-system variation in task allocation—including in flexibility, specialization, and (in)activity.

Task allocation is a central feature of collective organization. Living collective systems, such as multicellular organisms or social insect colonies, have evolved diverse ways to allocate individuals to different tasks, ranging from rigid, inflexible task allocation that is not adjusted to changing circumstances to more fluid, flexible task allocation that is rapidly adjusted to the external environment. While the mechanisms underlying task allocation have been intensely studied, it remains poorly understood whether differences in the flexibility of task allocation can be viewed as adaptive responses to different ecological contexts—for example, different degrees of temporal variability. Motivated by this question, we develop an analytically tractable mathematical framework to explore the evolution of task allocation in dynamic environments. We find that collective flexibility is not necessarily always adaptive, and fails to evolve in environments that change too slowly (relative to how long tasks can be left unattended) or too quickly (relative to how rapidly task allocation can be adjusted). We further employ the framework to investigate how environmental variability impacts the internal organization of task allocation, which allows us to propose adaptive explanations for some puzzling empirical observations, such as seemingly unnecessary task switching under constant environmental conditions, apparent task specialization without efficiency benefits, and high levels of individual inactivity. Altogether, this work provides a general framework for probing the evolved diversity of task allocation strategies in nature and reinforces the idea that considering a system’s ecology is crucial to explaining its collective organization.

Long-term tracking and quantification of individual behavior in bumble bee colonies

Social insects are ecologically dominant and provide vital ecosystem services. It is critical to understand collective responses of social insects such as bees to ecological perturbations. However, studying behavior of individual insects across entire colonies and across timescales relevant for colony performance (i.e., days or weeks) remains a central challenge. Here, we describe an approach for long-term monitoring of individuals within multiple bumble bee (Bombus spp.) colonies that combines the complementary strengths of multiple existing methods. Specifically, we combine (a) automated monitoring, (b) fiducial tag tracking, and (c) pose estimation to quantify behavior across multiple colonies over a 48 h period. Finally, we demonstrate the benefits of this approach by quantifying an important but subtle behavior (antennal activity) in bumble bee colonies, and how this behavior is impacted by a common environmental stressor (a neonicotinoid pesticide).

Behavioural variation among workers promotes feed-forward loops in a simulated insect colony

Coordinated responses in eusocial insect colonies arise from worker interaction networks that enable collective processing of ecologically relevant information. Previous studies have detected a structural motif in these networks known as the feed-forward loop, which functions to process information in other biological regulatory networks (e.g. transcriptional networks). However, the processes that generate feed-forward loops among workers and the consequences for information flow within the colony remain largely unexplored. We constructed an agent-based model to investigate how individual variation in activity and movement shaped the production of feed-forward loops in a simulated insect colony. We hypothesized that individual variation along these axes would generate feed-forward loops by driving variation in interaction frequency among workers. We found that among-individual variation in activity drove over-representation of feed-forward loops in the interaction networks by determining the directionality of interactions. However, despite previous work linking feed-forward loops with efficient information transfer, activity variation did not promote faster or more efficient information flow, thus providing no support for the hypothesis that feed-forward loops reflect selection for enhanced collective functioning. Conversely, individual variation in movement trajectory, despite playing no role in generating feed-forward loops, promoted fast and efficient information flow by linking together otherwise unconnected regions of the nest.

Social associations in common carp (Cyprinus carpio): Insights from induced feeding aggregations for targeted management strategies

Heterogeneity in social interactions can have important consequences for the spread of information and diseases and consequently conservation and invasive species management. Common carp (Cyprinus carpio) are a highly social, ubiquitous, and invasive freshwater fish. Management strategies targeting foraging carp may be ideal because laboratory studies have suggested that carp can learn, have individual personalities, a unique diet, and often form large social groups. To examine social feeding behaviors of wild carp, we injected 344 carp with passive integrated transponder (PIT) tags and continuously monitored their feeding behaviors at multiple sites in a natural lake in Minnesota, USA. The high-resolution, spatio-temporal data were analyzed using a Gaussian mixture model (GMM). Based on these associations, we analyzed group size, feeding bout duration, and the heterogeneity and connectivity of carp social networks at foraging sites. Wild carp responded quickly to bait, forming aggregations most active from dusk to dawn. During the 2020 baiting period (20 days), 133 unique carp were detected 616,593 times. There was some evidence that feeding at multiple sites was constrained by basin geography, but not distance alone. GMM results suggested that feeding bouts were short, with frequent turnover of small groups. Individual foraging behavior was highly heterogeneous with Gini coefficients of 0.79 in 2020 and 0.66 in 2019. "Superfeeders"-those contributing to 80% of total cumulative detections (top 18% and top 29% of foragers in 2020 and 2019 respectively)-were more likely to be detected earlier at feeding stations, had larger body sizes, and had higher network measures of degree, weighted degree, and betweenness than non-superfeeders. Overall, our results indicate that wild carp foraging is social, easily induced by bait, dominated by large-bodied individuals, and potentially predictable, which suggests social behaviors could be leveraged in management of carp, one of the world's most recognizable and invasive fish.

Decoding alarm signal propagation of seed-harvester ants using automated movement tracking and supervised machine learning

Alarm signal propagation through ant colonies provides an empirically tractable context for analysing information flow through a natural system, with useful insights for network dynamics in other social animals. Here, we develop a methodological approach to track alarm spread within a group of harvester ants, Pogonomyrmex californicus. We initially alarmed three ants and tracked subsequent signal transmission through the colony. Because there was no actual standing threat, the false alarm allowed us to assess amplification and adaptive damping of the collective alarm response. We trained a random forest regression model to quantify alarm behaviour of individual workers from multiple movement features. Our approach translates subjective categorical alarm scores into a reliable, continuous variable. We combined these assessments with automatically tracked proximity data to construct an alarm propagation network. This method enables analyses of spatio-temporal patterns in alarm signal propagation in a group of ants and provides an opportunity to integrate individual and collective alarm response. Using this system, alarm propagation can be manipulated and assessed to ask and answer a wide range of questions related to information and misinformation flow in social networks.

Movement, Encounter Rate, and Collective Behavior in Ant Colonies

Spatial patterns of movement regulate many aspects of social insect behavior, because how workers move around, and how many are there, determines how often they meet and interact. Interactions are usually olfactory; for example, in ants, by means of antennal contact in which one worker assesses the cuticular hydrocarbons of another. Encounter rates may be a simple outcome of local density: a worker experiences more encounters, the more other workers there are around it. This means that encounter rate can be used as a cue for overall density even though no individual can assess global density. Encounter rate as a cue for local density regulates many aspects of social insect behavior, including collective search, task allocation, nest choice, and traffic flow. As colonies grow older and larger, encounter rates change, which leads to changes in task allocation. Nest size affects local density and movement patterns, which influences encounter rate, so that nest size and connectivity influence colony behavior. However, encounter rate is not a simple function of local density when individuals change their movement in response to encounters, thus influencing further encounter rates. Natural selection on the regulation of collective behavior can draw on variation within and among colonies in the relation of movement patterns, encounter rate, and response to encounters.

Independent variations in genome-wide expression, alternative splicing, and DNA methylation in brain tissues among castes of the buff-tailed bumblebee, Bombus terrestris

Caste differentiation in social hymenopterans is an intriguing example of phenotypic plasticity. However, the co-ordination among gene regulatory factors to mediate caste differentiation remains inconclusive. In this study, we determined the role of gene regulation and related epigenetic processes in pre-imaginal caste differentiation in the primitively eusocial bumblebee Bombus terrestris. By combining RNA-Seq data from Illumina and PacBio and accurately quantifying methylation at whole-genomic base pair resolution, we found that queens, workers, and drones mainly differentiate in gene expression but not in alternative splicing and DNA methylation. Gynes are the most distinct with the lowest global level of whole-genomic methylation and with the largest number of caste-specific transcripts and alternative splicing events. By contrast, workers exhibit few uniquely expressed or alternatively spliced genes. Moreover, several genes involved in hormone and neurotransmitter metabolism are related to caste differentiation, whereas several neuropeptides are linked with sex differentiation. Despite little genome-wide association among differential gene expression, splicing, and differential DNA methylation, the overlapped gene ontology (GO) terms point to nutrition-related activity. Therefore, variations in gene regulation correlate with the behavioral differences among castes and highlight the specialization of toolkit genes in bumblebee gynes at the beginning of the adult stage.

Response thresholds alone cannot explain empirical patterns of division of labor in social insects

The effects of heterogeneity in group composition remain a major hurdle to our understanding of collective behavior across disciplines. In social insects, division of labor (DOL) is an emergent, colony-level trait thought to depend on colony composition. Theoretically, behavioral response threshold models have most commonly been employed to investigate the impact of heterogeneity on DOL. However, empirical studies that systematically test their predictions are lacking because they require control over colony composition and the ability to monitor individual behavior in groups, both of which are challenging. Here, we employ automated behavioral tracking in 120 colonies of the clonal raider ant with unparalleled control over genetic, morphological, and demographic composition. We find that each of these sources of variation in colony composition generates a distinct pattern of behavioral organization, ranging from the amplification to the dampening of inherent behavioral differences in heterogeneous colonies. Furthermore, larvae modulate interactions between adults, exacerbating the apparent complexity. Models based on threshold variation alone only partially recapitulate these empirical patterns. However, by incorporating the potential for variability in task efficiency among adults and task demand among larvae, we account for all the observed phenomena. Our findings highlight the significance of previously overlooked parameters pertaining to both larvae and workers, allow the formulation of theoretical predictions for increasing colony complexity, and suggest new avenues of empirical study.

This study uses automated tracking of clonal raider ants and mathematical modeling to reveal how previously overlooked traits of larvae and workers might shape social organization in heterogeneous ant colonies. By incorporating the potential for variability in task efficiency among adults and task demand among larvae, the authors were able to account for all empirically observed phenomena.

Leadership - not followership - determines performance in ant teams

Economic theory predicts that organisations achieve higher levels of productivity when tasks are divided among different subsets of workers. This prediction is based upon the expectation that individuals should perform best when they specialise upon a few tasks. However, in colonies of social insects evidence for a causal link between division of labour and performance is equivocal. To address this issue, we performed a targeted worker removal experiment to disrupt the normal allocation of workers to a cooperative team task - tandem running. During a tandem run a knowledgeable leader communicates the location of a new nest to a follower by physically guiding her there. The targeted removal of prominent leaders significantly reduced tandem performance, whereas removal of prominent followers had no effect. Furthermore, analyses of the experience of both participants in each tandem run revealed that tandem performance was influenced primarily by how consistently the leader acted as a leader when the need arose, but not by the consistency of the follower. Our study shows that performance in ant teams depends largely on whether or not a key role is filled by an experienced individual, and suggests that in animal teams, not all roles are equally important.

Individual Ants Do Not Show Activity-Rest Rhythms in Nest Conditions

Circadian rhythms, which respond to the day-night cycle on the earth, arise from the endogenous timekeeping system within organisms, called the "biological clock." For accurate circadian rhythms, daily fluctuations in light and temperature are considered one of the important time cues. In social insects, both abiotic and biotic factors (i.e., social interactions) play a significant role in activity-rest rhythm regulation. However, it is challenging to monitor individual activity-rest rhythms in a colony because of the large group size and small body size. Therefore, it is unclear whether individuals in a colony exhibit activity-rest rhythms and how social interactions regulate their activity-rest rhythms in the colony. This study developed an image-based tracking system using 2D barcodes for Diacamma cf. indicum from Japan (a monomorphic ant) and measured the locomotor activities of all colony members under laboratory colony conditions. We also investigated the effect of broods on activity-rest rhythms by removing all broods under colony conditions. Activity-rest rhythms appeared only in isolated ants, not under colony conditions. In addition, workers showed arrhythmic activities after brood removal. These results suggested that a mixture of social interactions, and not light and temperature, induces the loss of activity-rest rhythms. These results contribute to the knowledge of a diverse pattern of circadian activity rhythms in social insects.

Ant behavioral maturation is mediated by a stochastic transition between two fundamental states

The remarkable ecological success of social insects is often attributed to their advanced division of labor, which is closely associated with temporal polyethism in which workers transition between different tasks as they age. Young nurses are typically found deep within the nest where they tend to the queen and the brood, whereas older foragers are found near the entrance and outside the nest.^1-3 However, the individual-level maturation dynamics remain poorly understood because following individuals over relevant timescales is difficult; hence, previous experimental studies used same-age cohort designs.^4-15 To address this, we used an automated tracking system to follow >500 individuals over >100 days and constructed networks of physical contacts to provide a continuous measure of worker social maturity. These analyses revealed that most workers occupied one of two steady states, namely a low-maturity nurse state and a high-maturity forager state, with the remaining workers rapidly transitioning between these states. There was considerable variation in the age at transition, and, surprisingly, the transition probability was age independent. This suggests that the transition is largely stochastic rather than a hard-wired age-dependent physiological change. Despite the variation in timing, the transition dynamics were highly stereotyped. Transitioning workers moved from the nurse to the forager state according to an S-shaped trajectory, and only began foraging after completing the transition. Stochastic switching, which occurs in many other biological systems, may provide ant colonies with robustness to extrinsic perturbations by allowing the colony to decouple its division of labor from its demography.

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.

Body Size and Behavioural Plasticity Interact to Influence the Performance of Free-Foraging Bumble Bee Colonies

Specialisation and plasticity are important for many forms of collective behaviour, but the interplay between these factors is little understood. In insect societies, workers are often developmentally primed to specialise in different tasks, sometimes with morphological or physiological adaptations, facilitating a division of labour. Workers may also plastically switch between tasks or vary their effort. The degree to which developmentally primed specialisation limits plasticity is not clear and has not been systematically tested in ecologically relevant contexts. We addressed this question in 20 free-foraging bumble bee (Bombus terrestris) colonies by continually manipulating colonies to contain either a typically diverse, or a reduced ("homogeneous"), worker body size distribution while keeping the same mean body size, over two trials. Pooling both trials, diverse colonies produced a larger comb mass, an index of colony performance. The link between body size and task was further corroborated by the finding that foragers were larger than nurses even in homogeneous colonies with a very narrow body size range. However, the overall effect of size diversity stemmed mostly from one trial. In the other trial, homogeneous and diverse colonies showed comparable performance. By comparing behavioural profiles based on several thousand observations of individuals, we found evidence that workers in homogeneous colonies in this trial rescued colony performance by plastically increasing behavioural specialisation and/or individual effort, compared to same-sized individuals in diverse colonies. Our results are consistent with a benefit to colonies of large and small specialists under certain conditions, but also suggest that plasticity or effort can compensate for reduced (size-related) specialisation. Thus, we suggest that an intricate interplay between specialisation and plasticity is functionally adaptive in bumble bee colonies.

Group size increases inequality in cooperative behaviour

In cooperatively breeding species where rearing effort is shared among multiple group members, increases in group size typically reduce average per capita contributions to offspring care by all group members (load-lightening) but it is not known how changes in group size affect the distribution of workload among group members. The socioeconomic collective action theory suggests that, in larger groups, the incentives for free riding are stronger, leading to greater inequalities in work division among group members. Here, we use the Gini index to measure inequality at the group level in the contributions of helpers to three different cooperative behaviours (babysitting, pup-provisioning and raised guarding) in groups of varying size in wild Kalahari meerkats (Suricata suricatta). In larger groups, inequality in helpers' contributions to cooperative activities and the frequency of free riding both increased. Elevated levels of inequality were generated partly as a result of increased differences in contributions to cooperative activities between helpers in different sex and age categories in larger groups. After controlling for the positive effect of group size on total provisioning, increasing levels of inequality in contributions were associated with reductions in total pup-provisioning conducted by the group. Reductions in total pup-provisioning were, in turn, associated with reductions in the growth and survival of pups (but pup growth and survival were not directly affected by inequality in provisioning). Our results support the prediction of collective action theory described above and show how the Gini index can be used to investigate the distribution of cooperative behaviour within the group.

Social networks predict the life and death of honey bees

In complex societies, individuals' roles are reflected by interactions with other conspecifics. Honey bees (Apis mellifera) generally change tasks as they age, but developmental trajectories of individuals can vary drastically due to physiological and environmental factors. We introduce a succinct descriptor of an individual's social network that can be obtained without interfering with the colony. This 'network age' accurately predicts task allocation, survival, activity patterns, and future behavior. We analyze developmental trajectories of multiple cohorts of individuals in a natural setting and identify distinct developmental pathways and critical life changes. Our findings suggest a high stability in task allocation on an individual level. We show that our method is versatile and can extract different properties from social networks, opening up a broad range of future studies. Our approach highlights the relationship of social interactions and individual traits, and provides a scalable technique for understanding how complex social systems function.

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.

Modular structure within groups causes information loss but can improve decision accuracy

Many animal groups exhibit signatures of persistent internal modular structure, whereby individuals consistently interact with certain groupmates more than others. In such groups, information relevant to a collective decision may spread unevenly through the group, but how this impacts the quality of the resulting decision is not well understood. Here, we explicitly model modularity within animal groups and examine how it affects the amount of information represented in collective decisions, as well as the accuracy of those decisions. We find that modular structure necessarily causes a loss of information, effectively silencing the input from a fraction of the group. However, the effect of this information loss on collective accuracy depends on the informational environment in which the decision is made. In simple environments, the information loss is detrimental to collective accuracy. By contrast, in complex environments, modularity tends to improve accuracy. This is because small group sizes typically maximize collective accuracy in such environments, and modular structure allows a large group to behave like a smaller group (in terms of its decision-making). These results suggest that in naturalistic environments containing correlated information, large animal groups may be able to exploit modular structure to improve decision accuracy while retaining other benefits of large group size.

This article is part of the theme issue ‘Liquid brains, solid brains: How distributed cognitive architectures process information’.

Kinematic flexibility allows bumblebees to increase energetic efficiency when carrying heavy loads

Foraging bees fly with heavy loads of nectar and pollen, incurring energetic costs that are typically assumed to depend on load size. Insects can produce more force by increasing stroke amplitude and/or flapping frequency, but the kinematic response of a given species is thought to be consistent. We examined bumblebees (Bombus impatiens) carrying both light and heavy loads and found that stroke amplitude increased in proportion to load size, but did not predict metabolic rate. Rather, metabolic rate was strongly tied to frequency, which was determined not by load size but by the bee's average loading state and loading history, with heavily loaded bees displaying smaller changes in frequency and smaller increases in metabolic rate to support additional loading. This implies that bees can increase force production through alternative mechanisms; yet, they often choose the energetically costly option of elevating frequency, suggesting associated performance benefits that merit further investigation.

A place for everything and everything in its place: spatial organization of individuals on nests of the primitively eusocial wasp Ropalidia marginata

Non-random space use is common among animals across taxa and habitats. Social insects often use space non-randomly, outside as well as inside their nests. While such non-random space use outside the nest may improve foraging efficiency, inside the nest, it is often associated with the efficient division of labour. Non-random space use by adults on their nests has been hypothesized to result from dyadic dominance interactions, non-random distribution of tasks, differential activity levels, workers avoiding their queens or prophylactic avoidance of disease spread. These hypotheses are generally derived from species in which the tasks of the workers are themselves non-randomly distributed on the nest. Here, we study the primitively eusocial wasp Ropalidia marginata, in which tasks are not distributed non-randomly, and show that 62.4% ± 16.2% of the adults nevertheless use space on their nest non-randomly. In this species, we find that non-random space use may help optimizing nutritional exchange between individuals while prophylactically minimizing disease spread among nest-mates. We did not find evidence for the roles of dominance interactions, activity levels or location of larvae in non-random space use. Spatial organization appears to be a mechanism of minimizing the costs and maximizing the benefits of social life.

Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour

Built structures, such as animal nests or buildings that humans occupy, serve two overarching purposes: shelter and a space where individuals interact. The former has dominated much of the discussion in the literature. But, as the study of collective behaviour expands, it is time to elucidate the role of the built environment in shaping collective outcomes. Collective behaviour in social animals emerges from interactions, and collective cognition in humans emerges from communication and coordination. These collective actions have vast economic implications in human societies and critical fitness consequences in animal systems. Despite the obvious influence of space on interactions, because spatial proximity is necessary for an interaction to occur, spatial constraints are rarely considered in studies of collective behaviour or collective cognition. An interdisciplinary exchange between behavioural ecologists, evolutionary biologists, cognitive scientists, social scientists, architects and engineers can facilitate a productive exchange of ideas, methods and theory that could lead us to uncover unifying principles and novel research approaches and questions in studies of animal and human collective behaviour. This article, along with those in this theme issue aims to formalize and catalyse this interdisciplinary exchange.This article is part of the theme issue 'Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour'.

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.

Neuronal Plasticity in the Mushroom-Body Calyx of Bumble Bee Workers During Early Adult Development

Division of labor among workers is a key feature of social insects and frequently characterized by an age-related transition between tasks, which is accompanied by considerable structural changes in higher brain centers. Bumble bees (Bombus terrestris), in contrast, exhibit a size-related rather than an age-related task allocation, and thus workers may already start foraging at two days of age. We ask how this early behavioral maturation and distinct size variation are represented at the neuronal level and focused our analysis on the mushroom bodies (MBs), brain centers associated with sensory integration, learning and memory. To test for structural neuronal changes related to age, light exposure, and body size, whole-mount brains of age-marked workers were dissected for synapsin immunolabeling. MB calyx volumes, densities, and absolute numbers of olfactory and visual projection neuron (PN) boutons were determined by confocal laser scanning microscopy and three-dimensional image analyses. Dark-reared bumble bee workers showed an early age-related volume increase in olfactory and visual calyx subcompartments together with a decrease in PN-bouton density during the first three days of adult life. A 12:12  h light-dark cycle did not affect structural organization of the MB calyces compared to dark-reared individuals. MB calyx volumes and bouton numbers positively correlated with body size, whereas bouton density was lower in larger workers. We conclude that, in comparison to the closely related honey bees, neuronal maturation in bumble bees is completed at a much earlier stage, suggesting a strong correlation between neuronal maturation time and lifestyle in both species.

Integral feedback control is at the core of task allocation and resilience of insect societies

Homeostatic self-regulation is a fundamental aspect of open dissipative systems. Integral feedback has been found to be important for homeostatic control on both the cellular and molecular levels of biological organization and in engineered systems. Analyzing the task allocation mechanisms of three insect societies, we identified a model of integral control residing at colony level. We characterized a general functional core mechanism, called the "common stomach," where a crucial shared substance for colony function self-regulates its own quantity via reallocating the colony's workforce, which collects and uses this substance. The central component in a redundant feedback network is the saturation level of this substance in the colony. An interaction network of positive and negative feedback loops ensures the homeostatic state of this substance and the workforce involved in processing this substance. Extensive sensitivity and stability analyses of the core model revealed that the system is very resilient against perturbations and compensates for specific types of stress that real colonies face in their ecosystems. The core regulation system is highly scalable, and due to its buffer function, it can filter noise and find a new equilibrium quickly after environmental (supply) or colony-state (demand) changes. The common stomach regulation system is an example of convergent evolution among the three different societies, and we predict that similar integral control regulation mechanisms have evolved frequently within natural complex systems.

Neonicotinoid exposure disrupts bumblebee nest behavior, social networks, and thermoregulation

Neonicotinoid pesticides can negatively affect bee colonies, but the behavioral mechanisms by which these compounds impair colony growth remain unclear. Here, we investigate imidacloprid’s effects on bumblebee worker behavior within the nest, using an automated, robotic platform for continuous, multicolony monitoring of uniquely identified workers. We find that exposure to field-realistic levels of imidacloprid impairs nursing and alters social and spatial dynamics within nests, but that these effects vary substantially with time of day. In the field, imidacloprid impairs colony thermoregulation, including the construction of an insulating wax canopy. Our results show that neonicotinoids induce widespread disruption of within-nest worker behavior that may contribute to impaired growth, highlighting the potential of automated techniques for characterizing the multifaceted, dynamic impacts of stressors on behavior in bee colonies.

Fitness benefits and emergent division of labour at the onset of group living

The initial fitness benefits of group-living are considered the greatest hurdle to the evolution of sociality¹, and theory predicts that they need to arise at very small group sizes². Such benefits are thought to emerge partly from scaling effects that increase efficiency as group size increases^3–5. In social insects and other taxa, they have been proposed to stem from division of labor (DOL)^5–8, which is characterized by between-individual variability and within-individual consistency (specialization) in task performance. At the onset of sociality, however, groups were likely small and composed of similar individuals with potentially redundant rather than complementary function¹. Theory suggests that DOL can emerge even in relatively small, simple groups^9,10. However, empirical data on the effects of group size on DOL and fitness remain equivocal⁶. Here, we use long-term automated behavioral tracking in clonal ant colonies, combined with mathematical modeling, to show that increases in social-group size can generate DOL among extremely similar workers, in groups as small as six individuals. These early effects on behavior were associated with large increases in homeostasis—the maintenance of stable conditions in the colony¹¹— and per capita fitness. Our model suggests that increases in homeostasis are primarily driven by increases in group size itself, and, to a smaller extent, by higher DOL. Overall, our results indicate that DOL, increased homeostasis, and higher fitness can naturally emerge in small, homogeneous social groups, and that scaling effects associated with increasing group size can thus promote social cohesion at incipient stages of group-living.