Behavioral flexibility promotes collective consistency in a social insect

Regulation of division of labor in insects: a colony-level perspective

Studies of division of labor have focused mainly on individual workers performing tasks. Here I propose a shift in perspective: colonies perform tasks, and task performance should be evaluated at the colony level. I then review studies from the recent literature from this perspective, on topics including evaluating task performance; specialization and efficiency; flexibility and task performance; response threshold models; and variation in behavior arising from diverse sensory experiences and learning. The use of specialized workers is only one of a variety of strategies that colonies may follow in performing tasks. The ability of colonies to produce consistent responses and to compensate for changes in the labor pool supports the idea of a task allocation system that precedes specialization. The colony-level perspective raises new questions about how tasks are done and the strategies used to improve colony task performance.

Determinants of hyena participation in risky collective action

Collective action problems arise when cooperating individuals suffer costs of cooperation, while the benefits of cooperation are received by both cooperators and defectors. We address this problem using data from spotted hyenas fighting with lions. Lions are much larger and kill many hyenas, so these fights require cooperative mobbing by hyenas for them to succeed. We identify factors that predict when hyena groups engage in cooperative fights with lions, which individuals choose to participate and how the benefits of victory are distributed among cooperators and non-cooperators. We find that cooperative mobbing is better predicted by lower costs (no male lions, more hyenas) than higher benefits (need for food). Individual participation is facilitated by social factors, both over the long term (close kin, social bond strength) and the short term (greeting interactions prior to cooperation). Finally, we find some direct benefits of participation: after cooperation, participants were more likely to feed at contested carcasses than non-participants. Overall, these results are consistent with the hypothesis that, when animals face dangerous cooperative dilemmas, selection favours flexible strategies that are sensitive to dynamic factors emerging over multiple time scales.

Synchrony to a beat predicts synchrony with other minds

Synchrony has been used to describe simple beat entrainment as well as correlated mental processes between people, leading some to question whether the term conflates distinct phenomena. Here we ask whether simple synchrony (beat entrainment) predicts more complex attentional synchrony, consistent with a common mechanism. While eye-tracked, participants listened to regularly spaced tones and indicated changes in volume. Across multiple sessions, we found a reliable individual difference: some people entrained their attention more than others, as reflected in beat-matched pupil dilations that predicted performance. In a second study, eye-tracked participants completed the beat task and then listened to a storyteller, who had been previously recorded while eye-tracked. An individual's tendency to entrain to a beat predicted how strongly their pupils synchronized with those of the storyteller, a corollary of shared attention. The tendency to synchronize is a stable individual difference that predicts attentional synchrony across contexts and complexity.

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.

Extracting individual characteristics from population data reveals a negative social effect during honeybee defence

Honeybees protect their colony against vertebrates by mass stinging and they coordinate their actions during this crucial event thanks to an alarm pheromone carried directly on the stinger, which is therefore released upon stinging. The pheromone then recruits nearby bees so that more and more bees participate in the defence. However, a quantitative understanding of how an individual bee adapts its stinging response during the course of an attack is still a challenge: Typically, only the group behaviour is effectively measurable in experiment; Further, linking the observed group behaviour with individual responses requires a probabilistic model enumerating a combinatorial number of possible group contexts during the defence; Finally, extracting the individual characteristics from group observations requires novel methods for parameter inference.

We first experimentally observed the behaviour of groups of bees confronted with a fake predator inside an arena and quantified their defensive reaction by counting the number of stingers embedded in the dummy at the end of a trial. We propose a biologically plausible model of this phenomenon, which transparently links the choice of each individual bee to sting or not, to its group context at the time of the decision. Then, we propose an efficient method for inferring the parameters of the model from the experimental data. Finally, we use this methodology to investigate the effect of group size on stinging initiation and alarm pheromone recruitment.

Our findings shed light on how the social context influences stinging behaviour, by quantifying how the alarm pheromone concentration level affects the decision of each bee to sting or not in a given group size. We show that recruitment is curbed as group size grows, thus suggesting that the presence of nestmates is integrated as a negative cue by individual bees. Moreover, the unique integration of exact and statistical methods provides a quantitative characterisation of uncertainty associated to each of the inferred parameters.

In this paper, our interdisciplinary team has significantly improved the understanding of how honeybees coordinate their actions during defence. Our first step was to measure the output behaviour of groups of bees under controlled experimental conditions. We then developed a model and methodology that allow us to quantify how the responsiveness to the alarm pheromone evolves during a defensive event, for a given group size. We show that recruitment becomes less effective as group size increases, thus revealing the existence of a negative social effect that acts on top of alarm pheromone communication. Our contribution is thus two-fold: on the computational side, we provide new tools to extract individual characteristics from population data, which is a challenging issue in the study of collective behaviour. On the biological side, we provide evidence that bees weight in their social context when making the decision to sting. We hypothesize that this may be an important mechanism to prevent recruitment from spinning out of control, ultimately preserving the colony from workforce depletion.

The emergence of a collective sensory response threshold in ant colonies

SignificanceIn this study, we ask how ant colonies integrate information about the external environment with internal state parameters to produce adaptive, system-level responses. First, we show that colonies collectively evacuate the nest when the ground temperature becomes too warm. The threshold temperature for this response is a function of colony size, with larger colonies evacuating the nest at higher temperatures. The underlying dynamics can thus be interpreted as a decision-making process that takes both temperature (external environment) and colony size (internal state) into account. Using mathematical modeling, we show that these dynamics can emerge from a balance between local excitatory and global inhibitory forces acting between the ants. Our findings in ants parallel other complex biological systems like neural circuits.

Glyphosate impairs collective thermoregulation in bumblebees

Insects are facing a multitude of anthropogenic stressors, and the recent decline in their biodiversity is threatening ecosystems and economies across the globe. We investigated the impact of glyphosate, the most commonly used herbicide worldwide, on bumblebees. Bumblebee colonies maintain their brood at high temperatures via active thermogenesis, a prerequisite for colony growth and reproduction. Using a within-colony comparative approach to examine the effects of long-term glyphosate exposure on both individual and collective thermoregulation, we found that whereas effects are weak at the level of the individual, the collective ability to maintain the necessary high brood temperatures is decreased by more than 25% during periods of resource limitation. For pollinators in our heavily stressed ecosystems, glyphosate exposure carries hidden costs that have so far been largely overlooked.

Recent approaches to study the neural bases of complex insect behavior

Recent advances in biocompatible materials, miniaturized instrumentation, advanced computational algorithms, and genetic tools have enabled the development of novel methods and approaches to quantify the behavior of individuals or groups of animals. In conjunction with technologies that allow simultaneous monitoring of neural responses, quantitative studies of complex behaviors can reveal tighter links between the external sensory cues in the vicinity of the organism and neural responses they elicit, and how internal neural representations finally get mapped onto the behavior generated. In this review, we examine a few approaches that are beginning to be widely exploited for understanding neural-behavioral response transformations.

Bumblebee resilience to climate change, through plastic and adaptive responses

Bumblebees are ubiquitous, cold-adapted eusocial bees found worldwide from subarctic to tropical regions of the world. They are key pollinators in most temperate and boreal ecosystems, and both wild and managed populations are significant contributors to agricultural pollination services. Despite their broad ecological niche at the genus level, bumblebee species are threatened by climate change, particularly by rising average temperatures, intensifying seasonality and the increasing frequency of extreme weather events. While some temperature extremes may be offset at the individual or colony level through temperature regulation, most bumblebees are expected to exhibit specific plastic responses, selection in various key traits, and/or range contractions under even the mildest climate change. In this review, we provide an in-depth and up-to-date review on the various ways by which bumblebees overcome the threats associated with current and future global change. We use examples relevant to the fields of bumblebee physiology, morphology, behaviour, phenology, and dispersal to illustrate and discuss the contours of this new theoretical framework. Furthermore, we speculate on the extent to which adaptive responses to climate change may be influenced by bumblebees' capacity to disperse and track suitable climate conditions. Closing the knowledge gap and improving our understanding of bumblebees' adaptability or avoidance behaviour to different climatic circumstances will be necessary to improve current species climate response models. These models are essential to make correct predictions of species vulnerability in the face of future climate change and human-induced environmental changes to unfold appropriate future conservation strategies.

A model of resource partitioning between foraging bees based on learning

Central place foraging pollinators tend to develop multi-destination routes (traplines) to exploit patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in detail, how populations of foragers use resources in a common area is an open question, difficult to address experimentally. We explored conditions for the emergence of resource partitioning among traplining bees using agent-based models built from experimental data of bumblebees foraging on artificial flowers. In the models, bees learn to develop routes as a consequence of feedback loops that change their probabilities of moving between flowers. While a positive reinforcement of movements leading to rewarding flowers is sufficient for the emergence of resource partitioning when flowers are evenly distributed, the addition of a negative reinforcement of movements leading to unrewarding flowers is necessary when flowers are patchily distributed. In environments with more complex spatial structures, the negative experiences of individual bees on flowers favour spatial segregation and efficient collective foraging. Our study fills a major gap in modelling pollinator behaviour and constitutes a unique tool to guide future experimental programs.

Collective ventilation in honeybee nests

European honey bees ( Apis mellifera) live in large congested nest cavities with a single opening that limits passive ventilation. When the local air temperature exceeds a threshold, the nests are actively ventilated by bees fanning their wings at the nest entrance. Here, we show that colonies with relatively large nest entrances use an emergent ventilation strategy where fanning bees self-organize to form groups, separating regions of continuous inflow and outflow. The observed spatio-temporal patterns correlate the air velocity and air temperature along the entrances to the distribution of fanning bees. A mathematical model that couples these variables to known fanning behaviour of individuals recapitulates their collective dynamics. Additionally, the model makes predictions about the temporal stability of the fanning group as a function of the temperature difference between the environment and the nest. Consistent with these predictions, we observe that the fanning groups drift, cling to the entrance boundaries, break-up and reform as the ambient temperature varies over a period of days. Overall, our study shows how honeybees use flow-mediated communication to self-organize into a steady state in fluctuating environments.

Within-individual behavioural variability and division of labour in social insects

Division of labour, whereby individuals divide the workload in a group, is a recurrent property of social living. The current conceptual framework for division of labour in social insects is provided by the response-threshold model. This model posits that the differences between individuals (i.e. between-individual variability) in responsiveness to task-associated stimuli is a key feature for task specialisation. The consistency of individual behaviours (i.e. within-individual variability) in task performance represents an additional but little-considered component driving robust patterns of division of labour. On the one hand, the presence of workers with a high level of within-individual variability presumably allows colonies to rapidly adapt to external fluctuations. On the other hand, a reduced degree of within-individual variability promotes a stricter specialisation in task performance, thereby limiting the costs of task switching. The ideal balance between flexibility and canalisation probably varies depending on the developmental stage of the colony to satisfy its changing needs. Here, I introduce the main sources of within-individual variability in behaviours in social insects and I review neural correlates accompanying the changes in behavioural flexibility. I propose the hypothesis that the positive scaling between group size and the intensity of task specialisation, a relationship consistently reported both within and between taxa, may rely on reduced within-individual variability via self-organised processes linked to the quality of brood care. Overall, I emphasise the need for a more comprehensive characterisation of the response dynamics of individuals to better understand the mechanisms shaping division of labour in social insects.